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149 articles for “Neural Network Classification”
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Research ArticleOpen accessIn the abstractFAULT DETECTION IN SWITCHED RELUCTANCE MOTOR DRIVES USING DISCRETE WAVELET TRANSFORM AND K-MEANS CLUSTERINGV. S. Chandrika, A. Ebenezer JeyakumarThis study presents a novel method of detection of inter turn shorts based on k means clustering technique. In addition to inter turn short detection, the other faults like open, short, phase to phase faults and DC volt-age faults are detected through wavelet transforms and k means clustering. Open and short faults are classified using artificial neural network. All other … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 30 Dec 2013 · 7,990 accessesView PDFCite
Research ArticleOpen accessIn the abstractHALF OF THRESHOLD ALGORITHM: AN ENHANCED LINEAR ADAPTIVE SKIPPING TRAINING ALGORITHM OR MULTILAYER FEEDFORWARD NEURAL NETWORKSManjula Devi Ramasamy, Kuppuswami Subbaraya GounderMultilayer Feed Forward Neural Network (MFNN) has been successfully administered architectures for solving a wide range of supervised pattern recognition tasks. The most problematic task of MFNN is training phase which consumes very long training time on very huge training datasets. An enhanced linear adaptive skipping training algorithm for MFNN called Half of Threshold (HOT) is proposed in this research … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 22 Nov 2013 · 7,020 accessesView PDFCite
Research ArticleOpen accessIn the abstractDETERMINATION OF EPILEPTIC DISORDER WITH DISCRETE WAVELET TRANSFORMS AND NEURAL NETWORK CLASSIFIERS. T. Sadish Kumar, N. KasthuriNowadays Epileptic disorder is a most challenge aspects in brain activation. Electroencephalograph (EEG) is one of the popular procedures to understand the human brain condition. The activation of brain will be changed due to the symptoms of neurological disorder. We have been proposed a procedure to find epilepsy disorder, using discrete wavelet transform and neural network classifier. The EEG classification … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 6,663 accessesView PDFCite
Research ArticleOpen accessIn the abstractRadial Basis Function Network Dependent Exclusive Mutual Interpolation for Missing Value ImputationR. S. Somasundaram, R. NedunchezhianThe success of data mining relies on the purity of the data set. Before performing the data mining, the data has to be cleaned. An unprocessed data set may contain noisy or missing values which is a critical research issue in the pre-processing stage. Imputation methods are being used to solve the missing value problems. In this proposed work, a … …Journal of Computer Science, Vol. 9, Issue 3 · 24 Apr 2013 · 7,008 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Classification Model of Sandals Dhiif’s Product with Back Propagation and Fourier Descriptors MethodWikaria Gazali, Haryono Soeparno, Ngarap Im ManikClassification is a vital process in every industry. While manual classification is inefficient in terms of cost and time, the computerized techniques offer better and faster solution on this matter. Fourier Descriptors is the mathematical formulas to save objects in functions of Fourier series. While back propagation is an Artificial Neural Network (ANN) method to recognize patterns and images through … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 6,375 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Overview of Research Challenges for Classification of Cardiotocogram DataC. Sundar, M. Chitradevi, G. GeetharamaniCardiotocography (CTG) is a simultaneous recording of Fetal Heart Rate (FHR) and Uterine Contractions (UC). The most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. There are several signal processing and computer programming based techniques for interpreting a typical Cardiotocography … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,835 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Ensemble Prediction Algorithms for Detecting Faulty Modules in Object Oriented Systems Using Quality MetricsM. Punithavalli, C. NeelamegamThe high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,438 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Fuzzy Neural Approach for Medical Image RetrievalC. Sriramakrishnan, A. ShanmugamImage retrieval based on a query image is necessary for effective and efficient use the information that is stored in medical image databases. Medical Image Retrieval is difficult as not only the localization and directionality of human visual system is to be considered but also the pathological condition. Image identification and segmentation for feature extraction pose a challenge to image … …Journal of Computer Science, Vol. 8, Issue 11 · 8 Sep 2012 · 6,670 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Improved Approach for Detecting Car in Video using Neural Network ModelS. N. Sivanandam, T. Senthil KumarThe study represents a novel approach taken towards car detection, feature extraction and classification in a video. Though many methods have been proposed to deal with individual features of a vehicle, like edge, license plate, corners, no system has been implemented to combine features. Combination of four unique features, namely, color, shape, number plate and logo gives the application a … …Journal of Computer Science, Vol. 8, Issue 10 · 1 Sep 2012 · 7,157 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnvironmental Modeling for Traffic Noise in Urban AreaFrancis Cirianni, Giovanni LeonardiTraffic noise can be classified among the worst factors in terms of damage to people’s health and well-being. The trend of noise pollution modeling variable from the smart result of classic regressive models in the performance of many assessment models based on mathematical expressions, genetic algorithms and neural networks (of GRNN type, General Regression Neural Network). A methodological approach for … …American Journal of Environmental Sciences, Vol. 8, Issue 4 · 18 Jun 2012 · 7,444 accessesView PDFCite