Search results for: time series forecasting

Authors: Armin Ardekani, Mohammad Akbari

Abstract:

We present a method of generating series solutions to large classes of nonlinear differential equations. The method is well suited to be adapted in mathematical software and unlike the available commercial solvers, we are capable of generating solutions to boundary value ODEs and PDEs. Many of the generated solutions converge to closed form solutions. Our method can also be applied to systems of ODEs or PDEs, providing all the solutions efficiently. As examples, we present results to many difficult differential equations in engineering fields.

Keywords: computational mathematics, differential equations, engineering, series

Procedia PDF Downloads 312

Authors: Chi T. L. Pham, L. Vu, Hoang T. Le, Huong T. T. Le, Quyen T. T. Bui

Abstract:

Burning joss paper and incense during religious and cultural ceremonies is common in Vietnam. This study aims to measure the impact of burning joss paper and incense during Vu Lai festival (full moon of July) in Vietnam. Data of Hanoi air quality in year 2020 was used. Interrupted time series analysis was employed to examine the changes in pattern of various air quality indicators before and after the festival period. The results revealed that burning joss paper and incense led to an immediate increase of 15.94 units in the air quality index on the first day, which gradually rose to 47.4 units by the end of the full moon period. Regarding NO2, PM10, and PM25, there was no significant immediate change at the start of the intervention period (August 29th, 2020). However, significant increases in levels and an upward trend were observed during the intervention time, followed by substantial decreases after the intervention period ended (September 3rd, 2020). This analysis did not find a significant impact on CO, SO2, and O3 due to burning joss paper and incense. These findings provide valuable insights for policymakers and stakeholders involved in managing and enhancing air quality in regions where such practices are prevalent.

Keywords: air pollution, incense, ITSA, joss paper, religious activities

Procedia PDF Downloads 12

Authors: Sharad Singh, Ajay Kumar Sinha

Abstract:

Coupled dampers like viscoelastic-frictional dampers for supplemental damping are a newer technique. In this paper, innovative Visco-frictional damping models have been presented and investigated. This paper attempts to couple frictional and fluid viscous dampers into a single unit of supplemental dampers. Visco-frictional damping model is developed by series and parallel coupling of frictional and fluid viscous dampers using Maxwell and Kelvin-Voigat models. The time analysis has been performed using numerical simulation on an SDOF system with varying fundamental periods, subject to a set of 12 ground motions. The simulation was performed using the direct time integration method. MATLAB programming tool was used to carry out the numerical simulation. The response behavior has been analyzed for the varying time period and added damping. This paper compares the response reduction behavior of the two modes of coupling. This paper highlights the performance efficiency of the suggested damping models. It also presents a mathematical modeling approach to visco-frictional dampers and simultaneously suggests the suitable mode of coupling between the two sub-units.

Keywords: hysteretic damping, Kelvin model, Maxwell model, parallel coupling, series coupling, viscous damping

Procedia PDF Downloads 128

Authors: Mohamed Hassan Abdullahi

Abstract:

Decomposition is used as a synthesis tool in several physical systems. It can also be used for tearing and restructuring, which is large-scale system analysis. On the other hand, the commutativity of series-connected systems has fascinated the interest of researchers, and its advantages have been emphasized in the literature. The presentation looks into the necessary conditions for decomposing any third-order discrete-time linear time-varying system into a commutative pair of first- and second-order systems. Additional requirements are derived in the case of nonzero initial conditions. MATLAB simulations are used to verify the findings. The work is unique and is being published for the first time. It is critical from the standpoints of synthesis and/or design. Because many design techniques in engineering systems rely on tearing and reconstruction, this is the process of putting together simple components to create a finished product. Furthermore, it is demonstrated that regarding sensitivity to initial conditions, some combinations may be better than others. The results of this work can be extended for the decomposition of fourth-order discrete-time linear time-varying systems into lower-order commutative pairs, as two second-order commutative subsystems or one first-order and one third-order commutative subsystems.

Keywords: commutativity, decomposition, discrete time-varying systems, systems

Procedia PDF Downloads 72

Authors: Mesut BALIBEY, Serpil TÜRKYILMAZ

Abstract:

A popular topic in the econometrics and time series area is the cointegrating relationships among the components of a nonstationary time series. Engle and Granger’s least squares method and Johansen’s conditional maximum likelihood method are the most widely-used methods to determine the relationships among variables. Furthermore, a method proposed to test a unit root based on the periodogram ordinates has certain advantages over conventional tests. Periodograms can be calculated without any model specification and the exact distribution under the assumption of a unit root is obtained. For higher order processes the distribution remains the same asymptotically. In this study, in order to indicate advantages over conventional test of periodograms, we are going to examine a possible relationship between tourism and economic growth during the period 1999:01-2010:12 for Turkey by using periodogram method, Johansen’s conditional maximum likelihood method, Engle and Granger’s ordinary least square method.

Keywords: cointegration, economic growth, periodogram ordinate, tourism

Procedia PDF Downloads 242

Authors: A. Fettahoglu

Abstract:

Theory of viscoelasticity is used by many researchers to represent behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain like pavements of bridges can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell elements and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Subsequently, a practical problem, which has an analytical solution given in literature, is used to verify the applicability of viscoelasticity tool embedded in ANSYS. Finally, amount of error in the results of ANSYS is compared with the analytical results to indicate the influence of used method and time step size.

Keywords: generalized Maxwell model, finite element method, prony series, time step size, viscoelasticity

Procedia PDF Downloads 340

Authors: Ming Yi Hsu, Hui Jung Chao

Abstract:

The anxiety and depression adolescents in Taiwan experience can cause suicide attempts and result in unfortunate deaths. An effective method for relieving anxiety and depression is brisk walking; a moderate and low intensity aerobic exercise, which uses large muscle groups rhythmically. The research purpose was to investigate the effects of a 12-week, school-based, brisk-walking program in decreasing anxiety and depression, and in improving self-concept among high school students living in central Taiwan. A quasi-experiment using the time series design (T1 T2 X T3 T4) was conducted. The Beck Youth Inventories 2 (BYI-II) Chinese version was given four times: the first time T1 was in the 4th week prior to intervention, T2 was in the intervention week, T3 was in the 6th week after the start of the intervention period and T4 was in the 12th week post intervention. The baseline phase of the time series constituted T1 and T2. The intervention phase constituted T2, T3, and T4. The amounts of brisk walking were recorded by self-report The Generalized Estimating Equation (GEE) was used to examine the effects of brisk walking on anxiety, depression, and self-concept. The independent t-test was used to compare mean scores on three dependent variables between brisk walking over and less than 90-minutes per week. Findings revealed that levels of anxiety and self-concept had nonsignificant change during the baseline phase, while the level of depression increased significantly. In contrast, the study demonstrated significant decreases in anxiety and depression as well as increases in positive self-concept (p=.001, p<.001, p=.017) during the intervention phase. Furthermore, a subgroup analysis was completed on participants who demonstrated elevated anxiety (23.4%), and depression (29.7%), and below average self-concept (18.6%) at baseline (T2). The subgroup of anxious, depressed, or low self-concept participants who received the brisk-walking intervention demonstrated significant decreases in anxiety and depression, and significant increases in self-concept scores. Participants who engaged in brisk walking over 90 minutes per week reported decreased mean scores on anxiety (t=-2.395, p=.035) and depression (t=-2.142, p=.036) in contrast with those who engaged in brisk-walking time less than 90 minutes per week. Regarding the effects on participants whose anxiety, scores were within the normal range at baseline, there was demonstrated significant decrease in the level of anxiety when they increased their time on brisk walking before each term examination. Overall, the brisk-walking program was effective and feasible to promote adolescents’ mental health by decreasing anxiety and depression as well as elevating self-concept. It also helped adolescents from anxiety before term examinations.

Keywords: adolescents, anxiety, depression, self-concept

Procedia PDF Downloads 161

Authors: Luofu Liu, Fei Xiao Jr., Fei Xiao

Abstract:

Through the analysis technology of gas chromatography-mass spectrometry (GC-MS), the composition and distribution characteristics of aromatic hydrocarbons in the Chepaizi area of the Junggar Basin were analyzed in detail. Based on that, the biological input, maturity of crude oils and sedimentary environment of the corresponding source rocks were determined and the origin types of crude oils were divided. The results show that there are three types of crude oils in the study area including Type I, Type II and Type III oils. The crude oils from the 1st member of the Neogene Shawan Formation are the Type I oils; the crude oils from the 2nd member of the Neogene Shawan Formation are the Type II oils; the crude oils from the Cretaceous Qingshuihe and Jurassic Badaowan Formations are the Type III oils. For the Type I oils, they show a single model in the late retention time of the chromatogram of total aromatic hydrocarbons. The content of triaromatic steroid series is high, and the content of dibenzofuran is low. Maturity parameters related to alkyl naphthalene, methylphenanthrene and alkyl dibenzothiophene all indicate low maturity for the Type I oils. For the Type II oils, they have also a single model in the early retention time of the chromatogram of total aromatic hydrocarbons. The content of naphthalene and phenanthrene series is high, and the content of dibenzofuran is medium. The content of polycyclic aromatic hydrocarbon representing the terrestrial organic matter is high. The aromatic maturity parameters indicate high maturity for the Type II oils. For the Type III oils, they have a bi-model in the chromatogram of total aromatic hydrocarbons. The contents of naphthalene series, phenanthrene series, and dibenzofuran series are high. The aromatic maturity parameters indicate medium maturity for the Type III oils. The correlation results of triaromatic steroid series fingerprint show that the Type I and Type III oils have similar source and are both from the Permian Wuerhe source rocks. Because of the strong biodegradation and mixing from other source, the Type I oils are very different from the Type III oils in aromatic hydrocarbon characteristics. The Type II oils have the typical characteristics of terrestrial organic matter input under oxidative environment, and are the coal oil mainly generated by the mature Jurassic coal measure source rocks. However, the overprinting effect from the low maturity Cretaceous source rocks changed the original distribution characteristics of aromatic hydrocarbons to some degree.

Keywords: oil source, geochemistry, aromatic hydrocarbons, crude oils, chepaizi area, Junggar Basin

Procedia PDF Downloads 327

Authors: Seyedvahid Najafi, Viliam Makis

Abstract:

In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems

Procedia PDF Downloads 94

Authors: Veronika Antoniou, Rene Carraz, Yiorgos Hadjichristou

Abstract:

The Green Urban Lab took the form of public installations that were placed at various locations in four cities in Cyprus. These installations - through which a series of events, activities, workshops and research took place - were the main tools in regenerating a series of urban public spaces in Cyprus. The purpose of this project was to identify issues and opportunities related to public space and to offer guidelines on how design and participatory democracy improvements could strengthen civil society, while raising the quality of the urban public scene. Giant inflatable structures were injected in important urban fragments in order to accommodate series of events. The design and playful installation generated a wide community engagement. The fluid presence of the installations acted as a catalyst for social interaction. They were accessed and viewed effortlessly and surprisingly, creating opportunities to rediscover public spaces.

Keywords: bottom-up initiatives, creativity, public space, social innovation, urban environments

Procedia PDF Downloads 492

Authors: Gurmail Singh

Abstract:

Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

Procedia PDF Downloads 94

Authors: Mark Andrew

Abstract:

Geopolitical tensions are at a thirty-year high, and the pace of technological innovation is driving asymmetry in force capabilities between nation states and between non-state actors. Technology futures are a vital component of defence capability growth, and investments in technology futures need to be informed by accurate and reliable forecasts of the options for ‘systems of systems’ innovation, development, and deployment. This paper describes a method for forecasting technology futures developed through an analysis of four key systems’ development stages, namely: technology domain categorisation, scanning results examining novel systems’ signals and signs, potential system-of systems’ implications in warfare theatres, and political ramifications in terms of funding and development priorities. The method has been applied to several technology domains, including physical systems (e.g., nano weapons, loitering munitions, inflight charging, and hypersonic missiles), biological systems (e.g., molecular virus weaponry, genetic engineering, brain-computer interfaces, and trans-human augmentation), and information systems (e.g., sensor technologies supporting situation awareness, cyber-driven social attacks, and goal-specification challenges to proliferation and alliance testing). Although the current application of the method has been team-centred using paper-based rapid prototyping and iteration, the application of autonomous language models (such as GPT-3) is anticipated as a next-stage operating platform. The importance of forecasting accuracy and reliability is considered a vital element in guiding technology development to afford stronger contingencies as ideological changes are forecast to expand threats to ecology and earth systems, possibly eclipsing the traditional vulnerabilities of nation states. The early results from the method will be subjected to ground truthing using longitudinal investigation.

Keywords: forecasting, technology futures, uncertainty, complexity

Procedia PDF Downloads 83

Authors: Ulrike Dowie, Ralph Grothmann

Abstract:

Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

Procedia PDF Downloads 143

Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

Abstract:

Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

Procedia PDF Downloads 90

Authors: André Rafael Ferreira, Laurentina Vareiro, Raquel Mendes

Abstract:

This study’s main objective is to explore residents’ perceptions of film-induced tourism and the impacts of filmmaking on the development of a destination. Specifically, the research examines resident´s perceptions of the social, economic, and environmental impacts on a Portuguese municipality (Arcos de Valdevez) given its feature in a popular Portuguese television series. Data is collected by means of an Internet survey, in which resident´s perceptions of the impacts of filmmaking are solicited. Residents generally agree that the recording and exhibition of the television series is important to the municipality, and contributes to the increased number of tourists. Given that residents consider that the positive impacts are more significant than the negative impacts, they supported the recording of another television series in the same municipality. Considering that destination managers and tourism development authorities aim to plan for optimal tourism development, and at the same time wish to minimize the negative impacts of this development on the local communities, monitoring residents’ opinions of perceived impacts is a good way of incorporating their reaction into tourism planning and development. The results of this research may provide useful information in this sense.

Keywords: film-induced tourism, residents’ perceptions, tourism development, tourism impacts

Procedia PDF Downloads 423

Authors: Eyal Rosen

Abstract:

This study is aimed to report a possible effect of the presence of dental implants on the development of crown or root fractures in adjacent natural teeth. A series of 26 cases of teeth diagnosed with crown or root fractures following the placement of adjacent dental implants is presented. In addition, a comprehensive systematic review of the literature was performed to detect other studies that evaluated this possible complication. The case series analysis revealed that all crown-fractured teeth were non-endodontically treated teeth (n=18), and all root fractured teeth were endodontically treated teeth (n=8). The time from implant loading to the diagnosis of a fracture in an adjacent tooth was longer than 1 year in 78% of cases. The majority of crown or root fractures occurred in female patients, over 50 years of age, with an average age of 59 in the crown fractures group, and 54 in the root fractures group. Most of the patients received 2 or more implants. Nine (50%) of the teeth with crown fracture were molars, 7 (39%) were mandibular premolars, and 2 (11%) were incisor teeth. The majority of teeth with root fracture were premolar or mandibular molar teeth (6 (75%)). The systematic review of the literature did not reveal additional studies that reported on this possible complication. To the best of the author’s knowledge this case series, although limited in its extent, is the first clinical report of a possible serious complication of implants, associated fractures in adjacent endodontically and non-endodontically treated natural teeth. The most common patient profile found in this series was a woman over 50 years of age, having a fractured premolar tooth, which was diagnosed more than 1 year after reconstruction that was based on multiple adjacent implants. Additional clinical studies are required in order to shed light on this potential serious complication.

Keywords: complications, dental implants, endodontics, fractured teeth

Procedia PDF Downloads 112

Authors: Chien-Chung Yuan, Cunqiang Cai, Wu-Hsun Chung, Shu-Te Sung

Abstract:

A tanker is a critical vessel used to transport or store liquids or gases in bulk in maritime shipping. However, it is more dangerous than other types of vessels. Port State Control (PSC) inspection is an important measure to ensure maritime safety when such vessels traveling between ports. However, the current inspection system lacks a useful tool to observe the inspections for tankers and to identify non-random instances in PSC inspections. This study collects the inspection records in Taiwan’s ports from 2015 to 2018 and utilizes run charts to map the PSC inspections for tankers in terms of deficiencies. Based on these time-series charts, several patterns of deficiencies are identified. The results demonstrate that run charts are a useful tool to observe how the PSC inspections for tankers are performed. Also, the charts can help port administrations to identify abnormal phenomena for further investigation. Furthermore, with valuable information from the analysis, port administrations can take proactive improvement measures to ensure the safety of tanker shipping.

Keywords: port state control, tanker, run chart, deficiency

Procedia PDF Downloads 126

Authors: Ashneel Ajay Singh, Kazumi Sakuramoto, Naoki Suzuki, Kalla Alok, Nath Paras

Abstract:

Bluefin (Thunnus orientalis) tuna is one of the most economically valuable tuna species in the world. In recent years the stock has been observed to decline. It is suspected that the stock-recruitment relationship and population structure is influenced by environmental and climatic variables. This study was aimed at investigating the influence of environmental and climatic conditions on the trajectory of the different life stages of the North Pacific bluefin tuna. Exploratory analysis was performed for the North Pacific sea surface temperature (SST) and Pacific Decadal Oscillation (PDO) on the time series of the bluefin tuna cohorts (age-0, 1, 2,…,9, 10+). General Additive Modeling (GAM) was used to reconstruct the recruitment (R) trajectory. The spatial movement of the SST was also monitored from 1953 to 2012 in the distribution area of the bluefin tuna. Exploratory analysis showed significance influence of the North Pacific Sea Surface temperature (SST) and Pacific Decadal Oscillation (PDO) on the time series of the age-0 group. Other age group (1, 2,…,9, 10+) time series did not exhibit any significant correlations. PDO showed most significant relationship in the months of October to December. Although the stock-recruitment relationship is of biological significance, the recruits (age-0) showed poor correlation with the Spawning Stock Biomass (SSB). Indeed the most significant model incorporated the SSB, SST and PDO. The results show that the stock-recruitment relationship of the North Pacific bluefin tuna is multi-dimensional and cannot be adequately explained by the SSB alone. SST and PDO forcing of the population structure is of significant importance and needs to be accounted for when making harvesting plans for bluefin tuna in the North Pacific.

Keywords: pacific bluefin tuna, Thunnus orientalis, cohorts, recruitment, spawning stock biomass, sea surface temperature, pacific decadal oscillation, general additive model

Procedia PDF Downloads 214

Authors: Jinhoa Lee

Abstract:

The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of carbon dioxide (CO2) emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), CO2 emissions and gross domestic product (GDP) for Egypt using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey-Fuller (ADF) test for stationarity, Johansen maximum likelihood method for co-integration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests some negative impacts of the CO2 emissions and the coal and natural gas use on the GDP. Conversely, a positive long-run causality from the electricity consumption to the GDP is found to be significant in Egypt during the period. In the short-run, some positive unidirectional causalities exist, running from the coal consumption to the GDP, and the CO2 emissions and the natural gas use. Further, the GDP and the electricity use are positively influenced by the consumption of petroleum products and the direct combustion of crude oil. Overall, the results support arguments that there are relationships among environmental quality, energy use, and economic output in both the short term and long term; however, the effects may differ due to the sources of energy, such as in the case of Egypt for the period of 1980-2010.

Keywords: CO2 emissions, Egypt, energy consumption, GDP, time series analysis

Procedia PDF Downloads 586

Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

Abstract:

A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

Procedia PDF Downloads 111

Authors: K. S. Sreejith, C. Shaji

Abstract:

Though both Arabian Sea and its counterpart Bay of Bengal is forced primarily by the semi-annually reversing monsoons, the spatio-temporal variations of surface waters is very strong in the Arabian Sea as compared to the Bay of Bengal. This study focuses on the inter-annual variability of Sea Surface Temperature (SST) in the Arabian Sea by analysing ERSST dataset which covers 152 years of SST (January 1854 to December 2002) based on the ICOADS in situ observations. To capture the dominant SST oscillations and to understand the inter-annual SST variations at various local regions of the Arabian Sea, wavelet analysis was performed on this long time-series SST dataset. This tool is advantageous over other signal analysing tools like Fourier analysis, based on the fact that it unfolds a time-series data (signal) both in frequency and time domain. This technique makes it easier to determine dominant modes of variability and explain how those modes vary in time. The analysis revealed that pentadal SST oscillations predominate at most of the analysed local regions in the Arabian Sea. From the time information of wavelet analysis, it was interpreted that these cold and warm events of large amplitude occurred during the periods 1870-1890, 1890-1910, 1930-1950, 1980-1990 and 1990-2005. SST oscillations with peaks having period of ~ 2-4 years was found to be significant in the central and eastern regions of Arabian Sea. This indicates that the inter-annual SST variation in the Indian Ocean is affected by the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events.

Keywords: Arabian Sea, ICOADS, inter-annual variation, pentadal oscillation, SST, wavelet analysis

Procedia PDF Downloads 257

Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

Abstract:

Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

Procedia PDF Downloads 285

Authors: R. Premasiri, W. A. H. A. Abeygunasekara, S. M. Hewavidana, T. Jananthan, R. M. S. Madawala, K. Vaheeshan

Abstract:

Forecasting the potential for disastrous events such as landslides has become one of the major necessities in the current world. Most of all, the landslides occurred in Sri Lanka are found to be triggered mostly by intense rainfall events. The study area is the landslide near Gerandiella waterfall which is located by the 41st kilometer post on Nuwara Eliya-Gampala main road in Kotmale Division in Sri Lanka. The landslide endangers the entire Kotmale town beneath the slope. Geographic Information System (GIS) platform is very much useful when it comes to the need of emulating the real-world processes. The models are used in a wide array of applications ranging from simple evaluations to the levels of forecast future events. This project investigates the possibility of developing a dynamic model to map the spatial distribution of the slope stability. The model incorporates several theoretical models including the infinite slope model, Green Ampt infiltration model and Perched ground water flow model. A series of rainfall values can be fed to the model as the main input to simulate the dynamics of slope stability. Hydrological model developed using GIS is used to quantify the perched water table height, which is one of the most critical parameters affecting the slope stability. Infinite slope stability model is used to quantify the degree of slope stability in terms of factor of safety. DEM was built with the use of digitized contour data. Stratigraphy was modeled in Surfer using borehole data and resistivity images. Data available from rainfall gauges and piezometers were used in calibrating the model. During the calibration, the parameters were adjusted until a good fit between the simulated ground water levels and the piezometer readings was obtained. This model equipped with the predicted rainfall values can be used to forecast of the slope dynamics of the area of interest. Therefore it can be investigated the slope stability of rainfall induced landslides by adjusting temporal dimensions.

Keywords: factor of safety, geographic information system, hydrological model, slope stability

Procedia PDF Downloads 391

Authors: Riaz A. Agha, Alexander J. Fowler, Seon-Young Lee, Buket Gundogan, Katharine Whitehurst, Harkiran K. Sagoo, Kyung Jin Lee Jeong, Douglas G. Altman, Dennis P. Orgill

Abstract:

Introduction: Case Series are an important and common study type. Currently, no guideline exists for reporting case series and there is evidence of key data being missed from such reports. We propose to develop a reporting guideline for case series using a methodologically robust technique. The first step in this process is a systematic review of literature relevant to the reporting deficiencies of case series. Methods: A systematic review of methodological and reporting quality in surgical case series was performed. The electronic search strategy was developed by an information specialist and included MEDLINE, EMBASE, Cochrane Methods Register, Science Citation index and Conference Proceedings Citation index, from the start of indexing until 5th November 2014. Independent screening, eligibility assessments and data extraction was performed. Included articles were analyzed for five areas of deficiency: failure to use standardized definitions missing or selective data transparency or incomplete reporting whether alternate study designs were considered. Results: The database searching identified 2,205 records. Through the process of screening and eligibility assessments, 92 articles met inclusion criteria. Frequency of methodological and reporting issues identified was a failure to use standardized definitions (57%), missing or selective data (66%), transparency, or incomplete reporting (70%), whether alternate study designs were considered (11%) and other issues (52%). Conclusion: The methodological and reporting quality of surgical case series needs improvement. Our data shows that clear evidence-based guidelines for the conduct and reporting of a case series may be useful to those planning or conducting them.

Keywords: case series, reporting quality, surgery, systematic review

Procedia PDF Downloads 335

Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

Abstract:

The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

Procedia PDF Downloads 475

Authors: Yuzhi Cai

Abstract:

In this paper, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.

Keywords: DJIA, financial returns, predictive distribution, quantile function model

Procedia PDF Downloads 343

Authors: Chien-Wei Hung, Fu-Hau Hsu, Chuan-Sheng Wang, Chia-Hao Lee

Abstract:

Nowadays, the abuse of keyloggers is one of the most widespread approaches to steal sensitive information. In this paper, we propose an On-Screen Prompts Approach to Keyloggers (OSPAK) and its analysis, which is installed in public computers. OSPAK utilizes a canvas to cue users when their keystrokes are going to be logged or ignored by OSPAK. This approach can protect computers against recoding sensitive inputs, which obfuscates keyloggers with letters inserted among users' keystrokes. It adds a canvas below each password field in a webpage and consists of three parts: two background areas, a hit area and a moving foreground object. Letters at different valid time intervals are combined in accordance with their time interval orders, and valid time intervals are interleaved with invalid time intervals. It utilizes animation to visualize valid time intervals and invalid time intervals, which can be integrated in a webpage as a browser extension. We have tested it against a series of known keyloggers and also performed a study with 95 users to evaluate how easily the tool is used. Experimental results made by volunteers show that OSPAK is a simple approach.

Keywords: authentication, computer security, keylogger, privacy, information leakage

Procedia PDF Downloads 90

Authors: Jinhoa Lee

Abstract:

The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of CO2 emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), carbon dioxide (CO2) emissions and gross domestic product (GDP) for Israel using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Phillips–Perron (PP) test for stationarity, Johansen maximum likelihood method for cointegration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests significant positive impacts of coal and natural gas consumptions on GDP in Israel. In the short run, GDP positively affects coal consumption. While there exists a positive unidirectional causality running from coal consumption to consumption of petroleum products and the direct combustion of crude oil, there exists a negative unidirectional causality running from natural gas consumption to consumption of petroleum products and the direct combustion of crude oil in the short run. Overall, the results support arguments that there are relationships among environmental quality, energy use and economic output but the associations can to be differed by the sources of energy in the case of Israel over of period 1980-2010.

Keywords: CO2 emissions, energy consumption, GDP, Israel, time series analysis

Procedia PDF Downloads 621

Authors: Jonardan Koner

Abstract:

The study attempts to find out the impact of infrastructural investment on state economic growth in India. It further tries to determine the magnitude of the impact of infrastructural investment on economic indicator, i.e., per-capita income (PCI) in Indian States. The study uses panel regression technique to measure the impact of infrastructural investment on per-capita income (PCI) in Indian States. Panel regression technique helps incorporate both the cross-section and time-series aspects of the dataset. In order to analyze the difference in impact of the explanatory variables on the explained variables across states, the study uses Fixed Effect Panel Regression Model. The conclusions of the study are that infrastructural investment has a desirable impact on economic development and that the impact is different for different states in India. We analyze time series data (annual frequency) ranging from 1991 to 2010. The study reveals that the infrastructural investment significantly explains the variation of economic indicators.

Keywords: infrastructural investment, multiple regression, panel regression techniques, economic development, fixed effect dummy variable model

Procedia PDF Downloads 345

Authors: Jacky Hau

Abstract:

The prevalence of emerging technologies disrupts various industries as well as consumer behavior. Data collection has been in the fingertip and inherited through enabled Internet-of-things (IOT) devices. Big data analytics (BDA) becomes possible and allows real-time demand network management (DNM) through leagile supply chain. To enhance further on its resilience and predictability, governance is going to be examined to promote supply chain transparency and trust in an efficient manner. Leagility combines lean thinking and agile techniques in supply chain management. It aims at reducing costs and waste, as well as maintaining responsiveness to any volatile consumer demand by means of adjusting the decoupling point where the product flow changes from push to pull. Leagility would only be successful when collaborative planning, forecasting, and replenishment (CPFR) process or alike is in place throughout the supply chain business entities. Governance and procurement of the supply chain, however, is crucial and challenging for the execution of CPFR as every entity has to walk-the-talk generously for the sake of overall benefits of supply chain performance, not to mention the complexity of exercising the polices at both of within across various supply chain business entities on account of organizational behavior and mutual trust. Empirical survey results showed that the effective timespan on demand forecasting had been drastically shortening in the magnitude of months to weeks planning horizon, thus agility shall come first and preferably following by lean approach in a timely manner.

Keywords: governance, leagility, procure-to-pay, source-to-contract

Procedia PDF Downloads 87