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59 results for “Fuzzy Neural Network”
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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 abstractData-Driven Forecasting Schemes: Evaluation and ApplicationsJosip Vrbanek Jr, Wilson WangA reliable multi-step predictor is very useful to a wide array of applications to forecast the behavior of dynamic systems. The objective of this paper is to develop a more robust data-driven predictor for time series forecasting. Based on simulation analysis, it is found that multi-step-ahead forecasting schemes based on step inputs perform better than those based on sequential inputs. … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,565 accessesView PDFCite
Research ArticleOpen accessIn the abstractQualitative Ferromagnetic Hysteresis ModelingM. Mordjaoui, M. Chabane, B. Boudjema, R. DairaIn determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. A new qualitative hysteresis model for ferromagnetic core presented, based on the function approximation capabilities of adaptive neuro-fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 7,076 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzy Automata Induction using Construction MethodMo Z. Wen, Wan MinRecurrent neural networks have recently been demonstrated to have the ability to learn simple grammars. In particular, networks using second-order units have been successfully at this task. However, it is often difficult to predict the optimal neural network size to induce an unknown automaton from examples. Instead of just adjusting the weights in a network of fixed topology, we adopt … …Journal of Mathematics and Statistics, Vol. 2, Issue 2 · 30 Jun 2006 · 7,209 accessesView PDFCite
Research ArticleOpen accessIn the abstractANFIS Aided AODV Routing Protocolfor Mobile Ad Hoc NetworksVivek Sharma, Bashir Alam, M. N. DojaCommunication between mobile nodes is the key purpose of Mobile Ad Hoc Networks (MANETs). However, increase in the traffic leads to multiple challenging issues like congestion among nodes, consumption of more bandwidth, high energy requirement and low efficiency output. A powerful solution to these issues of the MANET is to use intelligent routing protocols. The Adaptive Neural Fuzzy Inference System … …Journal of Computer Science, Vol. 13, Issue 10 · 12 Oct 2017 · 7,429 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordNEURAL CASCADED WITH FUZZY SCHEME FOR CONTROL OF A HYDROELECTRIC POWER PLANTA. Selwin Mich Priyadharson, T. Ramesh Kumar, M. S. Saravanan et al.A novel design for flow and level control in a hydroelectric power plant using Programmable Logic Controller (PLC)-Human Machine Interface (HMI) and neural cascaded with fuzzy scheme is proposed. This project will focus on design and development of flow and level controller for small scale hydro generating units by implementing gate control based on PLC-HMI with the proposed scheme. The … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 30 Sep 2014 · 6,527 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPREDICTION OF GLIOMA USING GENETIC OPTIMIZED NEURAL NETWORKS. Karpagam, S. GowriNeural networks are a computational paradigm model of the human brain that has become popular in recent years. We have tried to address the problem of Glioma by creating a more accurate classifier which can act as an expert assistant to medical practitioners. Brain stem gliomas are now recognized as a heterogenous group of tumors. In this study proposed a … …Journal of Computer Science, Vol. 9, Issue 11 · 1 Oct 2013 · 6,693 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordImplementation and Evaluation of Evolutionary Connectionist Approaches to Automated Text SummarizationUday Kulkarni, Rajesh Shardanand PrasadProblem statement: Text summarization takes care of choosing the most significant portions of text and generates coherent summaries that express the main intent of the given document. This study aims to compare the performances of the three text summarization systems developed by the authors with some of the existing Summarization systems available. These three approaches to text summarization are based … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 8,489 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordIntelligent Voice-Based Door Access Control System Using Adaptive-Network-based Fuzzy Inference Systems (ANFIS) for Building SecurityWahyudi, Winda Astuti, Syazilawati MohamedSecure buildings are currently protected from unauthorized access by a variety of devices. Even though there are many kinds of devices to guarantee the system safety such as PIN pads, keys both conventional and electronic, identity cards, cryptographic and dual control procedures, the people voice can also be used. The ability to verify the identity of a speaker by analyzing … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 8,547 accessesView PDFCite