24 results for “Multilayer Perceptron”

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Research ArticleOpen accessIn the abstractPredicting the Severity of Breast Masses with Ensemble of Bayesian ClassifiersAlaa M. ElsayadProblem statement: This study evaluated two different Bayesian classifiers; tree augmented Naive Bayes and Markov blanket estimation networks in order to build an ensemble model for prediction the severity of breast masses. The objective of the proposed algorithm was to help physicians in their decisions to perform a breast biopsy on a suspicious lesion seen in a mammogram image or … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,299 accessesView PDF Cite

Research ArticleOpen accessIn the abstractKnowledge Representation of Ion-Sensitive Field-Effect Transistor Voltage Response for Potassium Ion Concentration Detection in Mixed Potassium/Ammonium Ion SolutionsWan Fazlida Hanim Abdullah, Mohd Alaudin Mohd Ali, Md Shabiul Islam, Masuri OthmanProblem statement: The Ion-Sensitive Field-Effect Transistor (ISFET) is a metal-oxide field-effect transistor-based sensor that reacts to ionic activity at the electrolye/membrane/gate interface. The ionic sensor faces issue of selectivity from interfering ions that contribute to the sensor electrical response in mixed solutions. Approach: We present the training data collection of ISFET voltage response for the purpose of post-processing stage neural … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,816 accessesView PDF Cite

Research ArticleOpen accessIn the abstractOptimal Thyristor Control Series Capacitor Neuro-Controller for Damping OscillationsM. Magaji, M. W. MustafaThis study applies a neural-network-based optimal TCSC controller for damping oscillations. Optimal neural network controller is related to model-reference adaptive control, the network controller is developed based on the recursive "pseudo-linear regression". Problem statement: The optimal NN controller is designed to damp out the low frequency local and inter-area oscillations of the large power system. Approach: Two multilayer-perceptron neural networks … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,281 accessesView PDF Cite

Research ArticleOpen accessIn the abstractVulnerability Assessment of Power System Using Radial Basis Function Neural Network and a New Feature Extraction MethodAhmed M.A. Haidar, Azah Mohamed, Aini HussainVulnerability assessment in power systems is important so as to determine how vulnerable a power system in case of any unforeseen catastrophic events. This paper presents the application of Radial Basis Function Neural Network (RBFNN) for vulnerability assessment of power system incorporating a new proposed feature extraction method named as the Neural Network Weight Extraction (NNWE) for dimensionality reduction of … …American Journal of Applied Sciences, Vol. 5, Issue 6 · 30 Jun 2008 · 7,153 accessesView PDF Cite