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37 results for “RBF”
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Research ArticleOpen accessIn the abstractElectrical Load Forecasting Using Artificial Neural Network: The Case Study of the Grid Inter-Connected Network of Benin Electricity Community (CEB)Adekunlé Akim Salami, Ayité Sénah Akoda Ajavon, Koffi A. Dotche, Koffi-Sa BedjaThe low rate of electrification seems challenging in many West African countries and many strategies are underway to improve upon. In this regard, the target of achieving the universal access and services calls for a stable and reliable electrical network. Forecasting of electrical load on a connected grid network is very delicate and requires tremendous task from the utilities (billing … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 2 · 11 Apr 2018 · 9,143 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Sensors for Monitoring Combustion Quality and Flue Gas Emissions in Power Station BoilersNallamilli P G Bhavani, Kesavan Sujatha, Ponmagal RajendranThis research work includes a combination of Fisher’s Linear Discriminant (FLD) analysis by merging Radial Basis Function (RBF) Network and Back Propagation Algorithm (BPA) for monitoring the combustion conditions of a coal fired boiler. The CCD Camera is used to capture the two dimensional flame images. The features such as images, average intensity, area, brightness and orientation etc., of the … …American Journal of Applied Sciences, Vol. 15, Issue 1 · 7 Feb 2018 · 7,552 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
Research ArticleOpen accessIn the abstractAUTHORSHIP CATEGORIZATION IN EMAIL INVESTIGATIONS USING FISHER’S LINEAR DISCRIMINANT METHOD WITH RADIAL BASIS FUNCTIONA. Pandian, Md. Abdul Karim SadiqEmail plays a vital role in faster communication. Lots of mails are sent to common public with falsified information that appears to be a realistic. It is mandatory to trace the origin of the email and the authors/systems responsible for generating such emails. Representative signatures of email are to be generated using lexical and syntactic based methods. The signature of … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 6,686 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vehicle License Plate Detection and Recognition SystemKhalid W. MagladProblem statement: Automatic vehicle license plate detection and recognition is a key technique in most of traffic related applications and is an active research topic in the image processing domain. Different methods, techniques and algorithms have been developed for license plate detection and recognitions. Approach: Due to the varying characteristics of the license plate from country to country like numbering … …Journal of Computer Science, Vol. 8, Issue 3 · 7 Jan 2012 · 9,008 accessesView PDFCite
Research ArticleOpen accessIn the abstractPecan Weevil Recognition Using Support Vector Machine MethodGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: The Pecan weevil was considered as the most dangerous pest of Pecan fruits. The aim of this research is to evaluate Support Vector Machine method (SVM) for identifying Pecan Weevil among other insects. Eventually, this recognition system will serve in a wireless imaging network for monitoring Pecan Weevils. Approach: SVM has been evaluated using two different kernel functions … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 4 · 24 Dec 2011 · 7,926 accessesView PDFCite
Research ArticleOpen accessIn the abstractAccurate 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 abstractPrediction of Double Layer Grids' Maximum Deflection Using Neural NetworksReza Kamyab Moghadas, Kok Keong ChoongEfficient neural networks models are trained to predict the maximum deflection of two-way on two-way grids with variable geometrical parameters (span and height) as well as cross-sectional areas of the element groups. Backpropagation (BP) and Radial Basis Function (RBF) neural networks are employed for the mentioned purpose. The inputs of the neural networks are the length of the spans, L, … …American Journal of Applied Sciences, Vol. 5, Issue 11 · 30 Nov 2008 · 6,488 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Rainfall-runoff Models to Zard River Catchment'sM. B. Rahnama, G. A. BaraniRainfall-runoff models are nonlinear processes according to the sequential and spatial distribution of the rainfall. So, it is difficult to explain the response of catchments systems with the simple models. In the present work simulation of the rainfall-runoff processes have been carried out by the Artificial Neural Networks (ANN) and the HEC-HMS models. The ANN models of Multi Layer Perceptron … …American Journal of Environmental Sciences, Vol. 1, Issue 1 · 31 Mar 2005 · 6,528 accessesView PDFCite