Research ArticleOpen accessIn the abstractNeural Network in Modeling Malaysian Oil Palm YieldZuhaimy Ismail, Azme KhamisProblem statement: Forecasting of palm oil yield has become an important element in the management of oil palm industry for proper planning and decision making. The importance of yield forecasting has led us to explore modeling of palm oil yield for Malaysia using the most recent development of Artificial Neural Network (ANN). The main issue in yield forecasting is to … …American Journal of Applied Sciences, Vol. 8, Issue 8 · 19 Jul 2011 · 8,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Resonance Theory Training Parameters: Pretty Good SetsTaisir Mohammad Eldos, Abdulaziz Suleiman AlmazyadProblem statement: ART1 artificial neural networks offer good tools for test clustering, where no expert is needed if the system is well trained. However, having no output reference for the input patterns makes it hard to judge the quality of the training. Moreover, the performance depends to a great extent on a set of training parameters. Designers follow some recommendations … …Journal of Computer Science, Vol. 6, Issue 12 · 6 Nov 2010 · 7,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractAsymptotic Behavior of an Artificial Neural Network Defined on Multipartite Directed GraphN. C. Majee, A. B. RoyProblem statement: Artificial Neural Network (ANN) are simple models to mimic some essential features of the complex central nervous system. ANN models are realistic due to their inherent stochastic nature of neural computation and strong synchronicity. Different ANN models are associated with directed and signed graphs. The present study proceeded by relaxing certain simplifying assumptions in the ANN model. Approach: … …OnLine Journal of Biological Sciences, Vol. 10, Issue 1 · 30 Jun 2010 · 7,479 accessesView PDFCite
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 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 abstractA Cost Estimation Model for Repair Bridges Based on Artificial Neural NetworkMohamed Bouabaz, Mounir HamamiEstimating the total cost of bridges repair and maintenance with high accuracy is an important components, and points to a need for a cost estimation model. This paper focuses on the development of a more accurate estimation model for repair and maintenance of bridges in developing countries using artificial neural networks. Cost and design data for two categories of repair … …American Journal of Applied Sciences, Vol. 5, Issue 4 · 30 Apr 2008 · 7,300 accessesView PDFCite
Research ArticleOpen accessIn the abstractFine 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 · 7,156 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Artificial Neural Network Based Approach for Mortality Structure AnalysisSokolova M. Kursk, Rashad J. Rasras, D. SkopinThe theoretical outcomes and experimental results of applying of Artificial Neural Networks towards mortality structure examination in Russian Federation are presented in the paper. The most influencing classes of diseases are selected by sensitivity analysis. It is proved that Neural Network Models appear to be an adequate tool for mortality structure examination. Some interesting results for males and females total … …American Journal of Applied Sciences, Vol. 3, Issue 2 · 28 Sep 2006 · 7,061 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