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55 articles for “Artificial Neural Networks (ANN)”
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Research ArticleOpen accessIn the abstractA Novel Approach to Classify Noises in Images Using Artificial Neural NetworkT. Santhanam, S. RadhikaProblem statement: Noise identification is predominant in any digital image processing algorithms, which helps in identifying the filters to smooth the image for further processing. Approach: An Artificial Neural Network (ANN) based approach was proposed for noise identification. The suggested technique involved seclusion of the noise samples and extracts their statistical features, which was then applied to a neural network … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,192 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Use of Artificial Neural Networks in Analysis Cationic Trypsinogen Gene and Hepatitis B Surface AntigenLiu Qicai, Zeng Kai, Zhuang Zehao et al.Problem statement: More and more severe hepatitis cases reported in China are infected with HBV and the immune response of HBV will be reduced if mutations occur in the TCR, therefore it is very important to investigate the relation of T-cellular function and clinical effect by studying the function of T-cell receptor. Approach: Artificial Neural Networks (ANN) was applied to … …American Journal of Immunology, Vol. 5, Issue 2 · 30 Apr 2009 · 7,566 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Neural Networks Based Modeling and Control of Continuous Stirred Tank ReactorR. Suja Mani Malar, T. ThyagarajanContinuous Stirred Tank Reactor (CSTR) is one of the common reactors in chemical plant. Problem statement: Developing a model incorporating the nonlinear dynamics of the system warrants lot of computation. An efficient control of the product concentration can be achieved only through accurate model. Approach: In this study, attempts were made to alleviate the above mentioned problem using &#34Artificial Intelligence&#34 … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 1 · 31 Mar 2009 · 8,213 accessesView PDFCite
Research ArticleOpen accessIn the abstractANN Based Prediction of Effect of Reinforcements on Abrasive Wear Loss and Hardness in a Hybrid MMCP. Sathyabalan, V. Selladurai, P. SakthivelProblem statement: The reinforcements added to an alloy lead to variation in properties. The content and size of the reinforcement influences the properties of composites. Very little research has been carried out in hybrid composites. Work on hybrid LM6 aluminium alloy metal matrix composites (MMC) with flyash and SiC has been initiated here. The effect of the four parameters, size … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 1 · 31 Mar 2009 · 7,558 accessesView PDFCite
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 abstractNeural-Based Models of Semiconductor Devices for SPICE SimulatorHanene Ben Hammouda, Mongia Mhiri, Zièd Gafsi, Kamel BesbesThe paper addresses a simple and fast new approach to implement Artificial Neural Networks (ANN) models for the MOS transistor into SPICE. The proposed approach involves two steps, the modeling phase of the device by NN providing its input/output patterns, and the SPICE implementation process of the resulting model. Using the Taylor series expansion, a neural based small-signal model is … …American Journal of Applied Sciences, Vol. 5, Issue 4 · 30 Apr 2008 · 8,582 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 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 abstractAn Analysis of Credit Scoring for Agricultural Loans in ThailandVisit Limsombunchai, Christopher Gan, Minsoo LeeLoan contract performance determines the profitability and stability of the financial institutions and screening the loan applications is a key process in minimizing credit risk. Before making any credit decisions, credit analysis (the assessment of the financial history and financial backgrounds of the borrowers) should be completed as part of the screening process. A good credit risk assessment assists financial … …American Journal of Applied Sciences, Vol. 2, Issue 8 · 31 Aug 2005 · 7,622 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Rainfall-runoff Models to Zard River Catchment'sM. B. Rahnama, G. A. BaraniRainfall-runoff models are nonlinear processes according to the sequential and spatial distribution of the rainfall. So, it is difficult to explain the response of catchments systems with the simple models. In the present work simulation of the rainfall-runoff processes have been carried out by the Artificial Neural Networks (ANN) and the HEC-HMS models. The ANN models of Multi Layer Perceptron … …American Journal of Environmental Sciences, Vol. 1, Issue 1 · 31 Mar 2005 · 6,535 accessesView PDFCite