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85 results for “Artificial Neural Network (ANN)”
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Research ArticleOpen accessIn the abstractWeighting Spatial Information in GIS for Copper Mining ExplorationFarhad Hosseinali, Ali Asghar AlesheikhExploration of new mines is vitally important for human life. Geospatial Information Systems (GIS) can be effectively used in the gathering, weighting, analyzing and presenting spatial and attribute information to facilitate the mine exploration process. The success of mine exploration largely depends on: the identification of governing factors, the determination of their impacts and the selection of suitable models to … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 8,609 accessesView PDFCite
Research ArticleOpen accessIn the abstractComputation of a Single-phase Shell-Type Transformer Windings Forces Caused by Inrush and Short-circuit CurrentsM. B.B. Sharifian, R. Esmaeilzadeh, M. Farrokhifar et al.This research studies the forces on the windings of transformer due to inrush current. These forces are compared with the corresponding forces due to short-circuit of the windings. Two-dimensional finite element computation of a single-phase shell-type transformer is carried out based on the maximum permissible inrush current value where its amplitude is the same as the rated short-circuit current. To … …Journal of Computer Science, Vol. 4, Issue 1 · 31 Jan 2008 · 7,437 accessesView PDFCite
Research ArticleOpen accessIn the abstractCombustion Analysis of a CI Engine Performance Using Waste Cooking Biodiesel Fuel with an Artificial Neural Network AidGholamhassan NAJAFI, Barat GHOBADIAN, Talal F. YUSAF, Hadi RAHIMIA comprehensive combustion analysis has been conducted to evaluate the performance of a commercial DI engine, water cooled two cylinders, in-line, naturally aspirated, RD270 Ruggerini diesel engine using waste vegetable cooking oil as an alternative fuel. In order to compare the brake power and the torques values of the engine, it has been tested under same operating conditions with diesel … …American Journal of Applied Sciences, Vol. 4, Issue 10 · 31 Oct 2007 · 8,196 accessesView PDFCite
Research ArticleOpen accessIn the abstractANN Based DSPIC Controller for Reactive Power CompensationR.A. Jayabarathi, N.B. DevarajanIn India with a power shortage of about 10% of installed capacity, the transmission and distribution losses are relatively high. One of the reasons for the large loss is the excessive reactive loads on the primary distribution feeder. With the right amount of reactive power compensation, as system load varies, line losses can be considerably reduced. The application of Artificial … …American Journal of Applied Sciences, Vol. 4, Issue 7 · 31 Jul 2007 · 6,852 accessesView PDFCite
Research ArticleOpen accessIn the abstractWavelet and ANN Based Relaying for Power Transformer ProtectionS. Sudha, A. Ebenezer JeyakumarThis paper presents an efficient wavelet and neural network (WNN) based algorithm for distinguishing magnetizing inrush currents from internal fault currents in three phase power transformers. The wavelet transform is applied first to decompose the current signals of the power transformer into a series of detailed wavelet components. The values of the detailed coefficients obtained can accurately discriminate between an … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 6,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Performance of Maximum Likelihood, Spectral Angle Mapper, Neural Network and Decision Tree Classifiers in Hyperspectral Image AnalysisHelmi Zulhaidi Mohd Shafri, Affendi Suhaili, Shattri MansorSeveral classification algorithms for pattern recognition had been tested in the mapping of tropical forest cover using airborne hyperspectral data. Results from the use of Maximum Likelihood (ML), Spectral Angle Mapper (SAM), Artificial Neural Network (ANN) and Decision Tree (DT) classifiers were compared and evaluated. It was found that ML performed the best followed by ANN, DT and SAM with … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 142,423 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting River Flow in the USA: A Comparison between Auto-Regression and Neural Network Non-Parametric ModelsAbdel K.M. Baareh, Alaa F. Sheta, Khaled A. KhnaifesForecasting a time series became one of the most challenging tasks to variety of data sets. The existence of large number of parameters to be estimated and the effect of uncertainty and outliers in the measurements makes the time series modeling too complicated. Recently, Artificial Neural Network (ANN) became quite successful tool to handle time series modeling problem. This paper … …Journal of Computer Science, Vol. 2, Issue 10 · 31 Oct 2006 · 6,968 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Hot Strip Rolling Force Prediction using a Bayesian Trained Artificial Neural Network and Analytical ModelsAbdelkrim Moussaoui, Yacine Selaimia, Hadj A. AbbassiThe authors discuss the combination of an Artificial Neural Network (ANN) with analytical models to improve the performance of the prediction model of finishing rolling force in hot strip rolling mill process. The suggested model was implemented using Bayesian Evidence based training algorithm. It was found that the Bayesian Evidence based approach provided a superior and smoother fit to the … …American Journal of Applied Sciences, Vol. 3, Issue 6 · 30 Jun 2006 · 7,140 accessesView PDFCite
Research ArticleOpen accessIn the abstractConsumer Choice Prediction: Artificial Neural Networks versus Logistic ModelsChristopher Gan, Visit Limsombunchai, Mike Clemes, Amy WengConventional econometric models, such as discriminant analysis and logistic regression have been used to predict consumer choice. However, in recent years, there has been a growing interest in applying artificial neural networks (ANN) to analyse consumer behaviour and to model the consumer decision-making process. The purpose of this paper is to empirically compare the predictive power of the probability neural … …Journal of Social Sciences, Vol. 1, Issue 4 · 31 Dec 2005 · 8,444 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybridization of Neural Learning Algorithms Using Evolutionary and Discrete Gradient ApproachesRanadhir Ghosh, John Yearwood, Moumita Ghosh, Adil BagirovIn this study we investigated a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 6,590 accessesView PDFCite