Search results for: Time series modelling
7381 Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series
Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser
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In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.Keywords: Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16037380 Using Time-Series NDVI to Model Land Cover Change: A Case Study in the Berg River Catchment Area, Western Cape, South Africa
Authors: A. S. Adesuyi, Z. Munch
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This study investigates the use of a time-series of MODIS NDVI data to identify agricultural land cover change on an annual time step (2007 - 2012) and characterize the trend. Following an ISODATA classification of the MODIS imagery to selectively mask areas not agriculture or semi-natural, NDVI signatures were created to identify areas cereals and vineyards with the aid of ancillary, pictometry and field sample data for 2010. The NDVI signature curve and training samples were used to create a decision tree model in WEKA 3.6.9 using decision tree classifier (J48) algorithm; Model 1 including ISODATA classification and Model 2 not. These two models were then used to classify all data for the study area for 2010, producing land cover maps with classification accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2 was subsequently used to create land cover classification and change detection maps for all other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices. Over the years as predicted by the land cover classification. Forty one percent of the catchment comprised of cereals with 35% possibly following a crop rotation system. Vineyards largely remained constant with only one percent conversion to vineyard from other land cover classes.Keywords: Change detection, Land cover, NDVI, time-series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22787379 Studying the Trend of Drought in Fars Province (Iran) using SPI Method
Authors: A. Gandomkar, R. Dehghani
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Drought is natural and climate phenomenon and in fact server as a part of climate in an area and also it has significant environmental, social ,and economic consequences .drought differs from the other natural disasters from this viewpoint that it s a creeping phenomenon meaning that it progresses little and its difficult to determine the time of its onset and termination .most of the drought definitions are on based on precipitation shortage and consequently ,the shortage of water some of the activities related to the water such as agriculture In this research ,drought condition in Fars province was evacuated using SPI method within a 37 year – statistical –period(1974-2010)and maps related to the drought were prepared for each of the statistical period years. According to the results obtained from this research, the years 1974, 1976, 1975, 1982 with SPI (-1.03, 0.39, -1.05, -1.49) respectively, were the doughiest years and 1996,1997,2000 with SPI (2.49, 1.49, 1.46, 1.04) respectively, the most humid within the studying time series and the rest are in more normal conditions in the term of drought.
Keywords: Fars Province, Drought, SPI Method, Time Series
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15747378 Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method
Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage
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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.Keywords: Equivalent circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13377377 Spatial Time Series Models for Rice and Cassava Yields Based On Bayesian Linear Mixed Models
Authors: Panudet Saengseedam, Nanthachai Kantanantha
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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.
Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22387376 A New Framework to Model a Secure E-Commerce System
Authors: A. Youseef, F. Liu
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The existing information system (IS) developments methods are not met the requirements to resolve the security related IS problems and they fail to provide a successful integration of security and systems engineering during all development process stages. Hence, the security should be considered during the whole software development process and identified with the requirements specification. This paper aims to propose an integrated security and IS engineering approach in all software development process stages by using i* language. This proposed framework categorizes into three separate parts: modelling business environment part, modelling information technology system part and modelling IS security part. The results show that considering security IS goals in the whole system development process can have a positive influence on system implementation and better meet business expectations.Keywords: Business Process Modelling (BPM), Information System Security, Software Development Process, Requirement Engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20247375 Fuzzy Inference Based Modelling of Perception Reaction Time of Drivers
Authors: U. Chattaraj, K. Dhusiya, M. Raviteja
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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.Keywords: Driver, fuzzy logic, perception reaction time, premise variable.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10017374 Empowering Student Success: Innovative Modelling Techniques for Enhancing Self-Efficacy in Education
Authors: Aldrin R. Logdat, Marianne Christine Jane B. Capio
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The study aimed to investigate the impact of modelling techniques on the self-efficacy of first year Bachelor of Science Major in Hospitality Management (BSHM) college students at City College of Calapan, Oriental Mindoro. The research utilized a ten-point general self-efficacy scale and collected responses from a sample of 107 students across five BSHM sections. The study found that the majority of students had a moderate level of self-efficacy, with 49.53% of total respondents falling within this category. However, 35.51% of students had high self-efficacy, and 14.95% had low self-efficacy levels. The two-tailed t-test for independent samples indicated a significant difference between the mean post-test scores of the experimental and control groups. Furthermore, Wilcoxon test showed that there were significant differences in the experimental group's self-efficacy before and after treatment, while no such difference was observed in the control group. Thus, the modelling technique proved to be effective in improving the self-efficacy levels of first year BSHM college students. Ultimately, the use of modelling techniques helped to elevate students’ self-efficacy levels into higher categories.
Keywords: Self-efficacy, counselling, modelling techniques, hospitality management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3657373 Analyzing the Impact of Spatio-Temporal Climate Variations on the Rice Crop Calendar in Pakistan
Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad
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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.
Keywords: Landsat NDVI, panel models, temperature, rainfall.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9027372 Modelling of a Multi-Track Railway Level Crossing System Using Timed Petri Net
Authors: Prasun Hajra, Ranjan Dasgupta
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Petri Net being one of the most useful graphical tools for modelling complex asynchronous systems, we have used Petri Net to model multi-track railway level crossing system. The roadway has been augmented with four half-size barriers. For better control, a three stage control mechanism has been introduced to ensure that no road-vehicle is trapped on the level crossing. Timed Petri Net is used to include the temporal nature of the signalling system. Safeness analysis has also been included in the discussion section.
Keywords: Modelling, Timed Petri Net, Railway Level Crossing, Safeness Condition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20987371 A Study on Changing of Energy-Saving Performance of GHP Air Conditioning System with Time-Series Variation
Authors: Ying Xin, Shigeki Kametani
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This paper deals the energy saving performance of GHP (Gas engine heat pump) air conditioning system has improved with time-series variation. There are two types of air conditioning systems, VRF (Variable refrigerant flow) and central cooling and heating system. VRF is classified as EHP (Electric driven heat pump) and GHP. EHP drives the compressor with electric motor. GHP drives the compressor with the gas engine. The electric consumption of GHP is less than one tenth of EHP does.
In this study, the energy consumption data of GHP installed the junior high schools was collected. An annual and monthly energy consumption per rated thermal output power of each apparatus was calculated, and then their energy efficiency was analyzed. From these data, we investigated improvement of the energy saving of the GHP air conditioning system by the change in the generation.
Keywords: Energy-saving, VRF, GHP, EHP, Air Conditioning System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18717370 Database Modelling Using WSML in the Specification of a Banking Application
Authors: Omid Sharifi, Member, ACM, Zeki Bayram, Member, ACM
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We demonstrate through a sample application, Ebanking, that the Web Service Modelling Language Ontology component can be used as a very powerful object-oriented database design language with logic capabilities. Its conceptual syntax allows the definition of class hierarchies, and logic syntax allows the definition of constraints in the database. Relations, which are available for modelling relations of three or more concepts, can be connected to logical expressions, allowing the implicit specification of database content. Using a reasoning tool, logic queries can also be made against the database in simulation mode.Keywords: Semantic web, ontology, E-banking, database, WSML, WSMO, E-R diagram.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19247369 Determination of the Quality of the Machined Surface Using Fuzzy Logic
Authors: Dejan Tanikić, Jelena Đoković, Saša Kalinović, Miodrag Manić, Saša Ranđelović
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This paper deals with measuring and modelling of the quality of the machined surface of the metal machining process. The average surface roughness (Ra) which represents the quality of the machined part was measured during the dry turning of the AISI 4140 steel. A large number of factors with the unknown relations among them influences this parameter, and that is why mathematical modelling is extremely complicated. Different values of cutting speed, feed rate, depth of cut (cutting regime) and workpiece hardness causes different surface roughness values. Modelling with soft computing techniques may be very useful in such cases. This paper presents the usage of the fuzzy logic-based system for determining metal machining process parameter in order to find the proper values of cutting regimes.
Keywords: Metal machining, surface roughness, fuzzy logic, process modelling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6827368 A Model Predictive Control and Time Series Forecasting Framework for Supply Chain Management
Authors: Philip Doganis, Eleni Aggelogiannaki, Haralambos Sarimveis
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Model Predictive Control has been previously applied to supply chain problems with promising results; however hitherto proposed systems possessed no information on future demand. A forecasting methodology will surely promote the efficiency of control actions by providing insight on the future. A complete supply chain management framework that is based on Model Predictive Control (MPC) and Time Series Forecasting will be presented in this paper. The proposed framework will be tested on industrial data in order to assess the efficiency of the method and the impact of forecast accuracy on overall control performance of the supply chain. To this end, forecasting methodologies with different characteristics will be implemented on test data to generate forecasts that will serve as input to the Model Predictive Control module.Keywords: Forecasting, Model predictive control, production planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19637367 Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network
Authors: Jia Xin Low, Keng Wah Choo
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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.Keywords: Convolutional neural network, discrete wavelet transform, deep learning, heart sound classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11357366 Optimizing Approach for Sifting Process to Solve a Common Type of Empirical Mode Decomposition Mode Mixing
Authors: Saad Al-Baddai, Karema Al-Subari, Elmar Lang, Bernd Ludwig
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Empirical mode decomposition (EMD), a new data-driven of time-series decomposition, has the advantage of supposing that a time series is non-linear or non-stationary, as is implicitly achieved in Fourier decomposition. However, the EMD suffers of mode mixing problem in some cases. The aim of this paper is to present a solution for a common type of signals causing of EMD mode mixing problem, in case a signal suffers of an intermittency. By an artificial example, the solution shows superior performance in terms of cope EMD mode mixing problem comparing with the conventional EMD and Ensemble Empirical Mode decomposition (EEMD). Furthermore, the over-sifting problem is also completely avoided; and computation load is reduced roughly six times compared with EEMD, an ensemble number of 50.Keywords: Empirical mode decomposition, mode mixing, sifting process, over-sifting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9797365 Product Feature Modelling for Integrating Product Design and Assembly Process Planning
Authors: Baha Hasan, Jan Wikander
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This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.Keywords: Assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11687364 A 4-Element Corporate Series Feed Millimeter-Wave Microstrip Antenna Array for 5G Applications
Authors: G. Viswanadh Raviteja
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In this paper, a microstrip antenna array is designed for 5G applications. A corporate series feed is considered to operate with a center frequency between 27 to 28 GHz to be able to cover the 5G frequency bands 24.25-27.5 GHz, 26.5-29.5 GHz and 27.5-28.35 GHz. The substrate is taken to be Rogers RT/Duroid 6002. The corporate series 5G antenna array is designed stage by stage by taking into consideration a conventional antenna designed at 28 GHz, thereby constructing the 2X1 antenna array before arriving at the final design structure of 4-element corporate series feed antenna array. The discussions concerning S11 parameter, gain and voltage standing wave ratio (VSWR) for the design structures are considered and all the important findings are tabulated. The proposed antenna array’s S11 parameter was found to be -29.00 dB at a frequency of 27.39 GHz with a good directional gain of 12.12 dB.
Keywords: Corporate series feed, millimeter wave antenna array, 5G applications, millimeter-wave (mm-wave) applications
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6237363 Synthetic Daily Flow Duration Curves for the Çoruh River Basin, Turkey
Authors: Fatih Tosunoğlu, İbrahim Can
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The flow duration curve (FDC) is an informative method that represents the flow regime’s properties for a river basin. Therefore, the FDC is widely used for water resource projects such as hydropower, water supply, irrigation and water quality management. The primary purpose of this study is to obtain synthetic daily flow duration curves for Çoruh Basin, Turkey. For this aim, we firstly developed univariate auto-regressive moving average (ARMA) models for daily flows of 9 stations located in Çoruh basin and then these models were used to generate 100 synthetic flow series each having same size as historical series. Secondly, flow duration curves of each synthetic series were drawn and the flow values exceeded 10, 50 and 95% of the time and 95% confidence limit of these flows were calculated. As a result, flood, mean and low flows potential of Çoruh basin will comprehensively be represented.Keywords: ARMA models, Çoruh basin, flow duration curve, Turkey.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37827362 Analysis on the Relationship between Rating and Economic Growth for the European Union Emergent Economies
Authors: Monica Dudian , Raluca Andreea Popa
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This article analyses the relationship between sovereign credit risk rating and gross domestic product for Central and Eastern European Countries for the period 1996 – 2010. In order to study the metioned relationship, we have used a numerical transformation of the risk qualification, thus: we marked 0 the lowest risk; then, we went on ascending, with a pace of 5, up to the score of 355 corresponding to the maximum risk. The used method of analysis is that of econometric modelling with EViews 7.0. programme. This software allows the analysis of data into a pannel type system, involving a mix of periods of time and series of data for different entities. The main conclusion of the work is the one confirming the negative relationship between the sovereign credit risk and the gross domestic product for the Central European and Eastern countries during the reviewed period.Keywords: credit rating agencies, economic growth, gross domestic product, sovereign credit risk rating.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24237361 Localization of Geospatial Events and Hoax Prediction in the UFO Database
Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi
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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.
Keywords: Time-series clustering, feature extraction, hoax prediction, geospatial events.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8417360 Modelling Peer Group Dieting Behaviour
Authors: M. J. Cunha
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The aim of this paper is to understand how peers can influence adolescent girls- dieting behaviour and their body image. Departing from imitation and social learning theories, we study whether adolescent girls tend to model their peer group dieting behaviours, thus influencing their body image construction. Our study was conducted through an enquiry applied to a cluster sample of 466 adolescent high school girls in Lisbon city public schools. Our main findings point to an association between girls- and peers- dieting behaviours, thus reinforcing the modelling hypothesis.Keywords: Modelling, Diet, Body image, Adolescent girls, Peer group.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17617359 Worm Gearing Design Improvement by Considering Varying Mesh Stiffness
Authors: A. H. Elkholy, A. H. Falah
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A new approach has been developed to estimate the load share and distribution of worm gear drives, and to calculate the instantaneous tooth meshing stiffness. In the approach, the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using the well-established formulae of spur gear loading and stresses. By combining the results obtained for all slices, the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. Based on the slicing method introduced in this study, the instantaneous meshing stiffness and load share are obtained. In comparison with existing methods, this approach has both good analysis accuracy and less computing time.Keywords: Gear, load/stress distribution, worm, wheel, tooth stiffness, contact line.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22137358 A Prediction Method for Large-Size Event Occurrences in the Sandpile Model
Authors: S. Channgam, A. Sae-Tang, T. Termsaithong
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In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions.
Keywords: Bak-Tang-Wiesenfeld sandpile model, avalanches, cross-correlation, prediction method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11637357 High Order Cascade Multibit ΣΔ Modulator for Wide Bandwidth Applications
Authors: S. Zouari, H. Daoud, M. Loulou, P. Loumeau, N. Masmoudi
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A wideband 2-1-1 cascaded ΣΔ modulator with a single-bit quantizer in the two first stages and a 4-bit quantizer in the final stage is developed. To reduce sensitivity of digital-to-analog converter (DAC) nonlinearities in the feedback of the last stage, dynamic element matching (DEM) is introduced. This paper presents two modelling approaches: The first is MATLAB description and the second is VHDL-AMS modelling of the proposed architecture and exposes some high-level-simulation results allowing a behavioural study. The detail of both ideal and non-ideal behaviour modelling are presented. Then, the study of the effect of building blocks nonidealities is presented; especially the influences of nonlinearity, finite operational amplifier gain, amplifier slew rate limitation and capacitor mismatch. A VHDL-AMS description presents a good solution to predict system-s performances and can provide sensitivity curves giving the impact of nonidealities on the system performance.Keywords: behavioural study, DAC nonlinearity, DEM, ΣΔ modulator, VHDL-AMS modelling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 48137356 Forecasting the Fluctuation of Currency Exchange Rate Using Random Forest
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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable on one country's competitiveness, trade and current account, inflation, wages, domestic economic activity and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021 and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables in the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.
Keywords: Exchange rate, Random Forest, time series, Machine Learning, forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6317355 Implementation and Simulation of Half-Bridge Series Resonant Inverter in Zero Voltage Switching
Authors: Buket Turan Azizoğlu
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In switch mode power inverters, small sized inverters can be obtained by increasing the switching frequency. Switching frequency increment causes high driver losses. Also, high dt di and dt dv produced by the switching action creates high Electromagnetic Interference (EMI) and Radio Frequency Interference (RFI). In this paper, a series half bridge series resonant inverter circuit is simulated and evaluated practically to demonstrate the turn-on and turn-off conditions during zero or close to zero voltage switching. Also, the reverse recovery current effects of the body diode of the MOSFETs were investigated by operating above and below resonant frequency.Keywords: Driver losses, Half Bridge series resonant inverter, Zero Voltage Switching
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37537354 Automatic Detection and Spatio-temporal Analysis of Commercial Accumulations Using Digital Yellow Page Data
Authors: Yuki. Akiyama, Hiroaki. Sengoku, Ryosuke. Shibasaki
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In this study, the locations and areas of commercial accumulations were detected by using digital yellow page data. An original buffering method that can accurately create polygons of commercial accumulations is proposed in this paper.; by using this method, distribution of commercial accumulations can be easily created and monitored over a wide area. The locations, areas, and time-series changes of commercial accumulations in the South Kanto region can be monitored by integrating polygons of commercial accumulations with the time-series data of digital yellow page data. The circumstances of commercial accumulations were shown to vary according to areas, that is, highly- urbanized regions such as the city center of Tokyo and prefectural capitals, suburban areas near large cities, and suburban and rural areas.Keywords: Commercial accumulations, Spatio-temporal analysis, Urban monitoring, Yellow page data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12517353 Development of an Automatic Calibration Framework for Hydrologic Modelling Using Approximate Bayesian Computation
Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke
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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.Keywords: Automatic calibration framework, approximate Bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17257352 Object-Oriented Multivariate Proportional-Integral-Derivative Control of Hydraulic Systems
Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral
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This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.
Keywords: Object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1098