Search results for: environmental variables

Authors: M. Lloret-Climent, J. Nescolarde-Selva

Abstract:

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: Attractor, invariant set, orbits, tourist variables.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1706

Authors: Y. Rathiranee, D. M. Semasinghe

Abstract:

This study attempts to identify the factors influencing on women empowerment of rural area in Sri Lanka through micro finance services. Data were collected from one hundred (100) rural women involving self-employment activities through a questionnaire using direct personal interviews. Judgment and Convenience Random sampling technique was used to select the sample size from three Divisional Secretariat divisions of Kandawalai, Poonakari and Karachchi in Kilinochchi District. The factor analysis was performed on fourteen (14) variables for screening and reducing the variables to identify the influencing factors on empowerment. Multiple regression analysis was used to identify the relationship between the three empowerment factors and the impact of micro finance on overall empowerment of rural women. The result of this study summarized the variables into three factors namely decision making, freedom to mobility and family support and which are positively associated with empowerment. In addition to this the value of adjusted R2 is 0.248 indicates that all the variables extracted can be explained 24.8% of the variation in the women empowerment through microfinance. Independent variables of these three factors have positive correlation with women empowerment as well as significant values at 5 percent level.

Keywords: Influencing factors, Micro finance, rural women and women empowerment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3900

Authors: Nazli Akhlaghinia, Ali Rajabzadeh Ghatari

Abstract:

In today's world, with increasing environmental awareness, firms are facing severe pressure from various stakeholders, including the government and customers, to reduce their harmful effects on the environment. Over the past few decades, the increasing effects of global warming, climate change, waste, and air pollution have increased the global attention of experts to the issue of the green supply chain and led them to the optimal solution for greenery. Green supply chain management (GSCM) plays an important role in motivating the sustainability of the organization. With increasing environmental concerns, the main objective of the research is to use system thinking methodology and Vensim software for designing a dynamic system model for green supply chain and observing behaviors. Using this methodology, we look for the effects of a green supply chain structure on the behavioral dynamics of output variables. We try to simulate the complexity of GSCM in a period of 30 months and observe the complexity of behaviors of variables including sustainability, providing green products, and reducing energy consumption, and consequently reducing sample pollution.

Keywords: Supply chain management, green supply chain management, system dynamics, energy consumption.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 813

Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

Abstract:

Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: Cross-validation, decision tree, lagged variables, short-term forecasting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 663

Authors: R. Rajendiran, S. Gayathri devi, B.T. SureshKumar, V. Arul Priya

Abstract:

Plackett-Burman statistical screening of media constituents and operational conditions for extracellular lipase production from isolate Trichoderma viride has been carried out in submerged fermentation. This statistical design is used in the early stages of experimentation to screen out unimportant factors from a large number of possible factors. This design involves screening of up to 'n-1' variables in just 'n' number of experiments. Regression coefficients and t-values were calculated by subjecting the experimental data to statistical analysis using Minitab version 15. The effects of nine process variables were studied in twelve experimental trials. Maximum lipase activity of 7.83 μmol /ml /min was obtained in the 6th trail. Pareto chart illustrates the order of significance of the variables affecting the lipase production. The present study concludes that the most significant variables affecting lipase production were found to be palm oil, yeast extract, K2HPO4, MgSO4 and CaCl2.

Keywords: lipase, submerged fermentation, statistical optimization, Trichoderma viride

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2267

Authors: Akinola Ikudayisi, Josiah Adeyemo

Abstract:

The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: Irrigation, principal component analysis, reference evapotranspiration, Vaalharts.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1018

Authors: Javier Rivas, Olga Gimeno, Maria Carbajo, Teresa Borralho

Abstract:

Potassium monopersulfate has been decomposed in aqueous solution in the presence of Co(II). The effect of the main operating variables has been assessed. Minimum variations in pH exert a considerable influence on the process kinetics. Thus, when no pH adjustment is considered, the actual effect of variables like initial monopersulfate and/or catalyst concentration may be hindered. As expected, temperature enhances the monopersulfate decomposition rate by following the Arrhenius law. The activation energy in the proximity of 85 kJ/mol has been obtained. Amongst the different solids tested in the monopersulfate decomposition, only the perovskite LaTi0.15Cu0.85O3 has shown a significant catalytic activity.

Keywords: Monopersulfate, Oxone®, Sulfate radicals, Watertreatment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1723

Authors: Mosses E. Lufuke

Abstract:

This paper attempted to investigate whether there is Granger-causality running from trade to environment as evidenced in the changing climatic condition and land degradation. Using Tanzania as the reference, VAR-Granger-causality test was employed to rationalize the conundrum of causal-effect relationship between trade and environment. The changing climatic condition, as the proxy of both nitrous oxide emissions (in thousand metric tons of CO₂ equivalent) and land degradation measured by the size of arable land were tested against trade using both exports and imports variables. The result indicated that neither of the trade variables Granger-cause the variability on gas emissions and arable land size. This suggests the possibility that all trade concerns in relation to environment to have been internalized in domestic policies to offset any likely negative consequence.

Keywords: Trade, growth, impact, environment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1151

Authors: Thomas I. Kounitis

Abstract:

The purpose of this paper is to investigate the influence of a number of variables on the conditional mean and conditional variance of credit spread changes. The empirical analysis in this paper is conducted within the context of bivariate GARCH-in- Mean models, using the so-called BEKK parameterization. We show that credit spread changes are determined by interest-rate and equityreturn variables, which is in line with theory as provided by the structural models of default. We also identify the credit spread change volatility as an important determinant of credit spread changes, and provide evidence on the transmission of volatility between the variables under study.

Keywords: Credit spread changes, GARCH-in-Mean models, structural framework, volatility transmission.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1603

Authors: Vijay Kumar Bajpai, Sudhir Kumar Singh

Abstract:

In this study, the performance analyses of the twenty five Coal-Fired Power Plants (CFPPs) used for electricity generation are carried out through various Data Envelopment Analysis (DEA) models. Three efficiency indices are defined and pursued. During the calculation of the operational performance, energy and non-energy variables are used as input, and net electricity produced is used as desired output (Model-1). CO2 emitted to the environment is used as the undesired output (Model-2) in the computation of the pure environmental performance while in Model-3 CO2 emissions is considered as detrimental input in the calculation of operational and environmental performance. Empirical results show that most of the plants are operating in increasing returns to scale region and Mettur plant is efficient one with regards to energy use and environment. The result also indicates that the undesirable output effect is insignificant in the research sample. The present study will provide clues to plant operators towards raising the operational and environmental performance of CFPPs.

Keywords: Coal fired power plants, environmental performance, data envelopment analysis, operational performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2318

Authors: Seyed Ali Mir Heydari, Mohsen Sayadiharikandeh

Abstract:

Static analysis of source code is used for auditing web applications to detect the vulnerabilities. In this paper, we propose a new algorithm to analyze the PHP source code for detecting LFI and RFI potential vulnerabilities. In our approach, we first define some patterns for finding some functions which have potential to be abused because of unhandled user inputs. More precisely, we use regular expression as a fast and simple method to define some patterns for detection of vulnerabilities. As inclusion functions could be also used in a safe way, there could occur many false positives (FP). The first cause of these FP-s could be that the function does not use a usersupplied variable as an argument. So, we extract a list of usersupplied variables to be used for detecting vulnerable lines of code. On the other side, as vulnerability could spread among the variables like by multi-level assignment, we also try to extract the hidden usersupplied variables. We use the resulted list to decrease the false positives of our method. Finally, as there exist some ways to prevent the vulnerability of inclusion functions, we define also some patterns to detect them and decrease our false positives.

Keywords: User-supplied Variables, hidden user-supplied variables, PHP vulnerabilities.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2463

Authors: Syeda Maria Ali Shah, Asif Mansoor, Talat Sharafat Rehmani, Safia Mirza

Abstract:

The stock market of any country acts as a predictor of the economy. The spread of the COVID-19 pandemic has severely impacted the global financial markets. Besides, it has also critically affected the economy of Pakistan. In this study, we consider the role of the Karachi Stock Exchange (KSE) with regard to the Pakistan Stock Exchange and quantify the impact on macroeconomic variables in presence of COVID-19. The suitable macroeconomic variables are used to quantify the impact of COVID-19 by developing the stochastic model. The sufficiency of the computed model is attained by means of available techniques in the literature. The estimated equations are used to forecast the impact of pandemic on macroeconomic variables. The constructed model can help the policymakers take counteractive measures for restricting the influence of viruses on the Karachi Stock Market.

Keywords: COVID-19, Karachi Stock Market, macroeconomic variables, stochastic model, forecasting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 676

Authors: Mae C. Pavilario

Abstract:

This study employs a sequential explanatory mixed method. Quantitatively it investigated the profile of grade VII students. Qualitatively, the prevailing contextual variables that affect their frustration-level were sought based on their perspective and that of their parents and teachers. These students were categorized as frustration-level in reading based on the data on word list of the Philippine Informal Reading Inventory (Phil-IRI). The researcher-made reading factor instrument translated to local dialect (Hiligaynon) was subjected to cross-cultural translation to address content, semantic, technical, criterion, or conceptual equivalence, the open-ended questions, and one unstructured interview was utilized. In the profile of the 26 participants, the 12 males are categorized as grade II and grade III frustration-levels. The prevailing contextual variables are personal-“having no interest in reading”, “being ashamed and fear of having to read in front of others” for extremely high frustration level; social environmental-“having no regular reading schedule at home” for very high frustration level and personal- “having no interest in reading” for high frustration level. Kendall Tau inferential statistical tool was used to test the significant relationship in the prevailing contextual variables that affect frustration-level readers when grouped according to perspective. Result showed that significant relationship exists between students-parents perspectives; however, there is no significant relationship between students’ and teachers’, and parents’ and teachers’ perspectives. The themes in the narratives of the participants on frustration-level readers are existence of speech defects, undesirable attitude, insufficient amount of reading materials, lack of close supervision from parents, and losing time and focus on task. Intervention was designed.

Keywords: Contextual variables, frustration-level readers, perspective, inquiry.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1063

Authors: T. Rashid, T. Kechadi

Abstract:

This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.

Keywords: Daily peak load forecasting, feed forward and feedback multi-context neural network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1805

Authors: Saleh Dabil

Abstract:

The study will search the level of existence of the sweethearting in Saudi Arabia's Supermarkets in Riyadh. Sweethearting occurs when frontline workers give unauthorized free or uncounted goods and services to customer-s conspirators. The store managers and /or security managers were asked about the sweethearting that occurs in the supermarkets. The characteristics of sweethearting in Riyadh stores were investigated. Two independent variables were related to the report of sweethearting. These independent variables are: The effect of store environment on sweethearting and the security techniques and loss prevention electronics techniques used. This study expected to shed the light about the level of sweethearting in Saudi Arabia and the factors behind it. This study will serve as an exploratory study for such phenomenon in Saudi Arabia as well as both descriptive for the characteristics of sweethearting and explanatory study to link between the environmental and security systems factors to sweethearting.

Keywords: supermarket, stealing, sweethearting, theft.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1840

Authors: Daniela Grădinaru, Iuliana Georgescu, Loredana Huţanu (Toma), Mihai-Bogdan Afrăsinei

Abstract:

This article aims to analyze the situation of Romanian companies from an environmental point of view. Environmental issues are addressed very often nowadays, and they reach and affect every domain, including the economical one. Implementing an environmental management system will not only help the companies to comply with laws and regulations, but, above all, will offer them an important competitive advantage.

Keywords: Environmental management system, environmental reporting, environmental expenses, sustainable development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2169

Authors: Tarik Rashid, B. Q. Huang, M-T. Kechadi, B. Gleeson

Abstract:

this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.

Keywords: Daily peak load forecasting, neural networks, recurrent neural networks, auto regressive multi-context neural network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2490

Authors: W. M. Wan Muhamad, E. Sujatmika, M.R. Idris, S.A. Syed Ahmad

Abstract:

A finite element analysis (FEA) computer software HyperWorks is utilized in re-designing an automotive component to reduce its mass. Reduction of components mass contributes towards environmental sustainability by saving world-s valuable metal resources and by reducing carbon emission through improved overall vehicle fuel efficiency. A shape optimization analysis was performed on a rear spindle component. Pre-processing and solving procedures were performed using HyperMesh and RADIOSS respectively. Shape variables were defined using HyperMorph. Then optimization solver OptiStruct was utilized with fatigue life set as a design constraint. Since Stress-Number of Cycle (S-N) theory deals with uni-axial stress, the Signed von Misses stress on the component was used for looking up damage on S-N curve, and Gerber criterion for mean stress corrections. The optimization analysis resulted in mass reduction of 24% of the original mass. The study proved that the adopted approach has high potential use for environmental sustainability.

Keywords: Environmental Sustainability, Shape Optimization, Fatigue, Rear Spindle.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4245

Authors: W. Y. Wan Fairos, W. H. Wan Azaki, L. Mohamad Alias, Y. Bee Wah

Abstract:

Dengue fever has become a major concern for health authorities all over the world particularly in the tropical countries. These countries, in particular are experiencing the most worrying outbreak of dengue fever (DF) and dengue haemorrhagic fever (DHF). The DF and DHF epidemics, thus, have become the main causes of hospital admissions and deaths in Malaysia. This paper, therefore, attempts to examine the environmental factors that may influence the recent dengue outbreak. The aim of this study is twofold, firstly is to establish a statistical model to describe the relationship between the number of dengue cases and a range of explanatory variables and secondly, to identify the lag operator for explanatory variables which affect the dengue incidence the most. The explanatory variables involved include the level of cloud cover, percentage of relative humidity, amount of rainfall, maximum temperature, minimum temperature and wind speed. The Poisson and Negative Binomial regression analyses were used in this study. The results of the analyses on the 915 observations (daily data taken from July 2006 to Dec 2008), reveal that the climatic factors comprising of daily temperature and wind speed were found to significantly influence the incidence of dengue fever after 2 and 3 weeks of their occurrences. The effect of humidity, on the other hand, appears to be significant only after 2 weeks.

Keywords: Dengue Fever, Dengue Hemorrhagic Fever, Negative Binomial Regression model, Poisson Regression model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2763

Authors: Z. Ghobadi, Z. Hamidi- Esfahani, M. H. Azizi

Abstract:

In the present study, the oleaginous fungus Mortierella alpina CBS 754.68 was screened for arachidonic acidproduction using inexpensive agricultural by-products as substrate. Four oilcakes were analysed to choose the best substrate among them. Sunflower oilcake was the most effective substrate for ARA production followed by soybean, colza and olive oilcakes. In the next step, seven variables including substrate particle size, moisture content, time, temperature, yeast extract supply, glucose supply and glutamate supply were surveyed and effective variables for ARA production were determined using a Plackett-Burman screening design. Analysis results showed that time (12 days), substrate particle size (1-1.4 mm) and temperature (20ºC) were the most effective variables for the highest level of ARA production respectively.

Keywords: Arachidonic acid, Mortierella alpine, Solid-statefermentation, Plackett-Burman design

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2185

Authors: V. Vidučić, T. Brešan Ančić, M. Tomelić Ćurlin

Abstract:

Prior to quantifying the variables of the information model for using school terminology in Croatia's region of Dalmatia from 1884 to 2014, the most relevant model variables had to be determined: historical circumstances, standard of living, education system, linguistic situation, and media. The research findings show that there was no significant transfer of the 1884 school terms into 1949 usage; likewise, the 1949 school terms were not widely used in 2014. On the other hand, the research revealed that the meaning of school terms changed over the decades. The quantification of the variables will serve as the groundwork for creating an information model for using school terminology in Dalmatia from 1884 to 2014 and for defining direct growth rates in further research.

Keywords: Education system, historical circumstances, linguistic situation, media, school terminology, standard of living.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1572

Authors: N. Zainol, J. Salihon, R. Abdul-Rahman

Abstract:

Factor analysis was applied to two stages biogas production from banana stem waste allowing a screening of the experimental variables second stage temperature (T), organic loading rates (OLR) and hydraulic retention times (HRT). Biogas production was found to be strongly influenced by all the above experimental variables. Results from factorial analysis have shown that all variables which were HRT, OLR and T have significant effect to biogas production. Increased in HRT and OLR could increased the biogas yield. The performance was tested under the conditions of various T (35oC-60oC), OLR (0.3 g TS/l.d–1.9 gTS/l.d), and HRT (3 d–15 d). Conditions for temperature, OLR and HRT in this study were based on the best range obtained from literature review.

Keywords: Biogas, factor analysis, banana stem waste

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1698

Authors: E. Bárcena-Martín, S. Pérez-Moreno

Abstract:

This paper explores the extent of the gap in poverty rates between immigrant and native households in Spanish regions and assess to what extent regional differences in individual and contextual characteristics can explain the divergences in such a gap. By using multilevel techniques and European Union Survey on Income and Living Conditions, we estimate immigrant households experiments an increase of 76 per cent in the odds of being poor compared with a native one when we control by individual variables. In relation to regional differences in the risk of poverty, regionallevel variables have higher effect in the reduction of these differences than individual variables.

Keywords: Immigration, Multilevel Analysis, Poverty, Spanish Regions

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1847

Authors: Jesús Everardo Olguín Tiznado, Rafael García Martínez, Claudia Camargo Wilson, Juan Andrés López Barreras, Everardo Inzunza González, Javier Ordorica Villalvazo

Abstract:

The response surface methodology (RSM) is a collection of mathematical and statistical techniques useful in the modeling and analysis of problems in which the dependent variable receives the influence of several independent variables, in order to determine which are the conditions under which should operate these variables to optimize a production process. The RSM estimated a regression model of first order, and sets the search direction using the method of maximum / minimum slope up / down MMS U/D. However, this method selects the step size intuitively, which can affect the efficiency of the RSM. This paper assesses how the step size affects the efficiency of this methodology. The numerical examples are carried out through Monte Carlo experiments, evaluating three response variables: efficiency gain function, the optimum distance and the number of iterations. The results in the simulation experiments showed that in response variables efficiency and gain function at the optimum distance were not affected by the step size, while the number of iterations is found that the efficiency if it is affected by the size of the step and function type of test used.

Keywords: RSM, dependent variable, independent variables, efficiency, simulation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1949

Authors: Takayuki Shiina

Abstract:

We consider power system expansion planning under uncertainty. In our approach, integer programming and stochastic programming provide a basic framework. We develop a multistage stochastic programming model in which some of the variables are restricted to integer values. By utilizing the special property of the problem, called block separable recourse, the problem is transformed into a two-stage stochastic program with recourse. The electric power capacity expansion problem is reformulated as the problem with first stage integer variables and continuous second stage variables. The L-shaped algorithm to solve the problem is proposed.

Keywords: electric power capacity expansion problem, integerprogramming, L-shaped method, stochastic programming

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1778

Authors: LI qiu-min, TIAN yi-xiang, ZHANG gao-xun

Abstract:

GMDH algorithm can well describe the internal structure of objects. In the process of modeling, automatic screening of model structure and variables ensure the convergence rate.This paper studied a new GMDH model based on polynomial spline  stimation. The polynomial spline function was used to instead of the transfer function of GMDH to characterize the relationship between the input variables and output variables. It has proved that the algorithm has the optimal convergence rate under some conditions. The empirical results show that the algorithm can well forecast Consumer Price Index (CPI).

Keywords: spline, GMDH, nonparametric, bias, forecast.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2073

Authors: Md. Sharif Imam Ibne Amir, Mohammad Masud Kamal khan, Mohammad Golam Rasul, Raj H Sharma, Fatema Akram

Abstract:

Future flood can be predicted using the probable maximum flood (PMF). PMF is calculated using the historical discharge or rainfall data considering the other climatic parameters remaining stationary. However climate is changing globally and the key climatic variables are temperature, evaporation, rainfall and sea level rise are likely to change. To develop scenarios to a basin or catchment scale these important climatic variables should be considered. Nowadays scenario based on climatic variables is more suitable than PMF. Six scenarios were developed for a large Fitzroy basin and presented in this paper.

Keywords: Climate change, rainfall, potential evaporation, scenario, sea level rise (SLR), sub-catchment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3334

Authors: Peiangpob Monnuanprang

Abstract:

In this paper we study the transformation of Euler equations  1 , u u u Pf t (ρ ∂) + ⋅∇ = − ∇ + ∂ G G G G ∇⋅ = u 0, G where (ux, t) G G is the velocity of a fluid, P(x, t) G is the pressure of a fluid andρ (x, t) G is density. First of all, we rewrite the Euler equations in terms of new unknown functions. Then, we introduce new independent variables and transform it to a new curvilinear coordinate system. We obtain the Euler equations in the new dependent and independent variables. The governing equations into two subsystems, one is hyperbolic and another is elliptic.

Keywords: Euler equations, transformation, hyperbolic, elliptic

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694

Authors: Wataru Nakamura, Tomoaki Hashimoto, Liang-Kuang Chen

Abstract:

This paper provides a state estimation method for automatic control systems of nonlinear vehicle dynamics. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. In general, all the state variables of control systems are not precisedly known, because those variables are observed through output sensors and limited parts of them might be only measurable. Hence, automatic control systems must incorporate some type of state estimation. It is needed to establish a state estimation method for nonlinear vehicle dynamics with restricted measurable state variables. For this purpose, unscented Kalman filter method is applied in this study for estimating the state variables of nonlinear vehicle dynamics. The objective of this paper is to propose a state estimation method using unscented Kalman filter for nonlinear vehicle dynamics. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: State estimation, control systems, observer systems, unscented Kalman filter, nonlinear vehicle dynamics.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 537

Authors: Yung-Chien Sun, O. Grant Clark

Abstract:

In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1346