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34 results for “Radial Basis Function”
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Research ArticleOpen accessIn the keywordsA Heuristic Moving Vehicle Location Prediction Technique Via Optimal Paths Selection with Aid of Genetic Algorithm and Feed Forward Back Propagation Neural NetworkE. Baby Anitha, K. DuraiswamyThe moving object or vehicle location prediction based on their spatial and temporal information is an important task in many applications. Different methods were utilized for performing the vehicle movement detection and prediction process. In such works, there is a lack of analysis in predicting the vehicles location in current as well as in future. Moreover, such methods compute the … …Journal of Computer Science, Vol. 8, Issue 12 · 12 Dec 2012 · 8,888 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImproving the Performance of Machine Learning Based Multi Attribute Face Recognition Algorithm Using Wavelet Based Image Decomposition TechniqueS. Sakthivel, M. RajaramProblem statement: Recognizing a face based attributes is an easy task for a human to perform; it is closely automated and requires little mental effort. A computer, on the other hand, has no innate ability to recognize a face or a facial feature and must be programmed with an algorithm to do so. Generally, to recognize a face, different kinds … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 6,907 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAccurate Wavelet Neural Network for Efficient Controlling of an Active Magnetic Bearing SystemYoussef Harkouss, Souhad Mcheik, Roger AchkarProblem statement: The synthesis of a command by the neural network has an excellent advantage over the classical one such as PID. This study presented a fast and accurate Wavelet Neural Network (WNN) approach for efficient controlling of an Active Magnetic Bearing (AMB) system. Approach: The proposed approach combined neural network with the wavelet theory. Wavelet theory may be exploited … …Journal of Computer Science, Vol. 6, Issue 12 · 9 Nov 2010 · 15,569 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Neural Network Models for Predicting EUR/USD Direction: An Empirical StudyEl Badaoui Mohamed, Raouyane Brahim, El Moumen Samira, Bellafkih MostafaThis paper presents a rigorous comparative analysis of six feedforward neural network models for predicting the directional movement of the EUR/USD currency pair. The evaluated models include the Learning Vector Quantization, Cascade Neural Network, Feedforward Neural Network, Single Layer Perceptron, Multi-Layer Perceptron, and Radial Basis Function network. Utilizing daily historical data from April 2009 to May 2024, each model was … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractRBF Approximation of the Lippmann-Schwinger EquationNadaniela Egidi, Josephin Giacomini, Pierluigi MaponiWe consider the direct scattering problem that consists of the computation of the scattered wave generated by an incident plane wave and an inhomogeneous object defined in terms of the refractive index. From some suitable physical and geometrical hypotheses, this is formulated as a boundary value problem for the Helmholtz equation and, in turn, as the Lippman-Schwinger equation. For the … …Journal of Mathematics and Statistics, Vol. 19, Issue 1 · 6 Nov 2023 · 5,094 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion DetectionOlujimi Daniel Alao, Sheriff Alimi, Shade Oluwakemi Kuyoro et al.NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or rejecting the network packets. In this study,the aim is the implementation of NIDS with improved performance using anensemble of Support Vector Machines (SVMs) and the Gaussian Mixture Model(GMM). Four SVMs with Radial Basis Function (RBF), … …Journal of Computer Science, Vol. 18, Issue 9 · 21 Sep 2022 · 6,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractStudy and Analysis of Prediction Model for Heart Disease Data Using Machine Learning TechniquesB. Santhi, K. RenukaHeart disease is the number one cause of death for all communities of individuals in advanced countries and a major problem for emerging nations too. Doctors’ availability to care for the general population could not catch up with the present demand for healthcare. So, there is a severe need for a support system to assist save individuals. With novel ML … …Journal of Computer Science, Vol. 16, Issue 3 · 26 Mar 2020 · 7,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractA GAUSSIAN MIXTURE MODEL FOR CLASSIFYING THE HUMAN AGE USING DWT AND SAMMON MAPJ. Nithyashri, G. KulanthaivelThe appearance of a human face rigorously changes with respect to age that makes Age Classification as a more challenging task. The algorithms such as, K-Nearest Neighbor (K-NN), Support Vector Machine (SVM), Radial Basis Function (RBF), motivated many Face Researchers to focus their attention in classifying the human age into various age groups. The Classification rate produced by these existing … …Journal of Computer Science, Vol. 10, Issue 11 · 20 Dec 2014 · 7,707 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,968 accessesView PDFCite