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9 results for “RBFNN”
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Research ArticleOpen accessEvery word in the titleRBFNN Model for Predicting Nonlinear Response of Uniformly Loaded Paddle CantileverAbdullah H. AbdullahThe Radial basis Function neural network (RBFNN) model has been developed for the prediction of nonlinear response for paddle Cantilever with built-in edges and different sizes, thickness and uniform loads. Learning data was performed by using a nonlinear finite element program, incremental stages of the nonlinear finite element analysis were generated by using 25 schemes of built paddle Cantilevers with … …American Journal of Applied Sciences, Vol. 6, Issue 1 · 31 Jan 2009 · 7,644 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Carbon Steel Pipe Protection Based on Radial Basis Function Neural NetworkSami Abulnoun AjeelProblem statement: The cost due to corrosion Damage have estimated to be 3-4% of their gross national product which significantly Countries problem around the world. Approach: In this study, a novel carbon steel pipe protection based on RBFNN was proposed. The RBFNN used to predict the minimum current density required in impressed current cathodic protection to protect low carbon steel … …American Journal of Applied Sciences, Vol. 7, Issue 2 · 28 Feb 2010 · 7,140 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRule Extraction from Radial Basis Functional Neural Networks by Using Particle Swarm OptimizationM. R. Senapati, I. Vijaya, P. K. DashRadial basis functional neural networks (RBFNN) provide an outstanding possibility for generating rules for solving pattern classification problems. One of the most important factors in RBFNN is finding out the center and spread. This paper examines rules extracted from RBF networks trained by Particle swarm Optimization (PSO). The selection of the RBFNN centers, spreads and the network weights can be … …Journal of Computer Science, Vol. 3, Issue 8 · 31 Aug 2007 · 6,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Hepatitis Disease with Logistic Regression and Artificial Neural NetworksAlaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-DhaifallahHepatitis C refers to the inflammatory state of the liver caused by viruses, bacteria, fungi, and exposure to toxins such as alcohol and self-immunity. The diagnosis requires investigating many laboratory tests and comparing the results to those of the former patients with the same conditions. This study presents the results of our experiments to build a hybrid system that combines … …Journal of Computer Science, Vol. 16, Issue 3 · 27 Mar 2020 · 7,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Speech Recognition System with Hidden Markov Model and Radial Basis Function Neural NetworkJudith Justin, Ila VennilaWe analyze the performance of continuous speech recognition of a speaker independent system using Hidden Markov Model and Artificial Neural Network. Modern speech recognition systems use different combinations of the standard techniques over the basic approach to improve performance accuracy. One such combination which has gained more attention is the hybrid model. Our hybrid system for continuous speech recognition consists … …American Journal of Applied Sciences, Vol. 10, Issue 10 · 5 Sep 2013 · 6,819 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 abstractDirect Model Reference Adaptive Controller Based-On Neural-Fuzzy Techniques for Nonlinear Dynamical SystemsHafizah Husain, Marzuki Khalid, Rubiyah YusofThis paper presents a direct neural-fuzzy-based Model Reference Adaptive Controller (MRAC) for nonlinear dynamical systems with unknown parameters. The two-phase learning is implemented to perform structure identification and parameter estimation for the controller. In the first phase, similarity index-based fuzzy c-means clustering technique extracts the fuzzy rules in the premise part for the neural-fuzzy controller. This technique enables the recruitment … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 6,939 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessIn the abstractRadial Basis Function Neural Networks Towards Electronic Trust QuantificationSmitha Zacaria, Tiny du ToitTrust is a broad term applicable in various contexts. Trust between electronic entities is complex to quantify, particularly in intricate networks. Traditional trust algorithms rely on historical trust values, requiring storage and access to past transaction details. Contextual variations further complicate trust calculation. Challenges in calculating trust include heightened computational complexities, managing information storage, and securing access to extensive datasets … …Journal of Computer Science, Vol. 20, Issue 11 · 26 Sep 2024 · 4,791 accessesView PDFCite