Research ArticleOpen accessPhrase in the titleIris Recognition Using Discrete Cosine Transform and Artificial Neural NetworksAhmad M. SarhanProblem statement: The study presented an efficient Iris recognition system. Approach: The design used the discrete cosine transform for feature extraction and artificial neural networks for classification. The iris images used in this system were obtained from the CASIA database. Results: A robust system for iris recognition was developed. Conclusion: An iris recognition system that produces very low error rates … …Journal of Computer Science, Vol. 5, Issue 5 · 30 May 2009 · 7,751 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleThe 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 · 7,564 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Arabic Text-To-Speech System Based on Artificial Neural NetworksGhadeer Al-Said, Moussa AbdallahProblem statement: With the rapid advancement in information technology and communications, computer systems increasingly offer the users the opportunity to interact with information through speech. The interest in speech synthesis and in building voices is increasing. Worldwide, speech synthesizers have been developed for many popular languages English, Spanish and French and many researches and developments have been applied to those … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,368 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleArtificial 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 "Artificial Intelligence" … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 1 · 31 Mar 2009 · 8,209 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFunctional Link Artificial Neural Network for Classification Task in Data MiningB. B. Misra, S. DehuriIn solving classification task of data mining, the traditional algorithm such as multi-layer perceptron takes longer time to optimize the weight vectors. At the same time, the complexity of the network increases as the number of layers increases. In this study, we have used Functional Link Artificial Neural Networks (FLANN) for the task of classification. In contrast to multiple layer … …Journal of Computer Science, Vol. 3, Issue 12 · 31 Dec 2007 · 60,797 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFine Needle Aspiration Cytology Evaluation for Classifying Breast Cancer Using Artificial Neural NetworkNor Ashidi Mat Isa, Esugasini Subramaniam, Mohd Yusoff Mashor, Nor Hayati OthmanThirteen cytology of fine needle aspiration image (i.e. cellularity, background information, cohesiveness, significant stromal component, clump thickness, nuclear membrane, bare nuclei, normal nuclei, mitosis, nucleus stain, uniformity of cell, fragility and number of cells in cluster) are evaluated their possibility to be used as input data for artificial neural network in order to classify the breast precancerous cases into four … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 7,152 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleConsumer 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 · 8,441 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEnergy and Carbon Flux Coupling: Multi-ecosystem Comparisons Using Artificial Neural NetworkAssefa M. Melesse, Rodney S. HanleyA multi-ecosystems carbon flux simulation from energy fluxes is presented. A new statistical learning technique based on Artificial Neural Network (ANN) back propagation algorithm and multi-layer perceptron architecture was used in the CO2 simulation. Four input layers (net radiation, soil heat flux, sensible and latent heat flux) were used for training (calibration) and testing (verification) of model outputs. The 15-days … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 7,347 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleHouse Price Prediction: Hedonic Price Model vs. Artificial Neural NetworkVisit Limsombunchai, Christopher Gan, Minsoo LeeThe objective of this study is to empirically compare the predictive power of the hedonic model with an artificial neural network model for house price prediction. A sample of 200 houses in Christchurch, New Zealand is randomly selected from the Harcourt website. Factors including house size, house age, house type, number of bedrooms, number of bathrooms, number of garages, amenities … …American Journal of Applied Sciences, Vol. 1, Issue 3 · 30 Sep 2004 · 9,603 accessesView PDFCite