fuzzy neural network approach
Modelling tide prediction using linear model and adaptive neuro fuzzy inference system (ANFIS) in Semarang, Indonesia
... and fuzzy inference system (FIS) where neural network algorithm is used to determine FIS parameter (Chang and Lain, ...Sugeno’s fuzzy model is a sistematic approach in generating ...
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Neural Network Approaches for Software Development Time Estimation: A Review
... Neuro-Fuzzy Approach” (2012) in this paper they explore Neuro-fuzzy techniques to design a suitable model to utilize improved estimation of software effort for NASA software ...of neural ...
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Systemic Approach for Health Risk Assessment of Ambient Air Concentrations of Benzene in Petrochemical Environments: In-tegration of Fuzzy Logic, Artificial Neural Network, and IRIS Toxicity Method
... The output from this last module gives the over- all dose through inhalation for each individual around the site, taking into account both the ex- posure factors and the receptor factors in a quan- titative way, based on ...
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Neural Network Regressions with Fuzzy Clustering
... and fuzzy clustering. Their main idea is to employ a fuzzy clustering for linear or polynomial regression models for data ...Their approach leads to an iterative procedure to formulate linear or ...
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1. Age invariant face recognition using fuzzy local binary pattern and artificial neural network classifier
... Our approach uses Fuzzy Local Binary Pattern for facial features extraction and Neural Network for classification.The flowchart for the developed age invariant face recognition system is as ...
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Implementation of Computational Intelligent Techniques for Diagnosis of Cancer Using Digital Signal Processor
... novel approach to implement Computational (CI) techniques like Fuzzy Logic, Adoptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network for diagnosis of cancer using TMS320C6713 ...
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Title : Detecting air pollution from Ariyalur meteorological data using fuzzy controlled optimized generative deep learning neural network Author (s) : S.Sagayaraj and Dr. N. Vetrivelan
... neighboring approach, support vector machine, regression analysis, decision tree, neural network and so ...called fuzzy controlled optimized generative deep learning neural ...
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Implementation of Evolutionary Computing Techniques for Cancer Diagnosis Using Digital Signal Processor
... logic, Neural Network, Genetic algorithm and adaptive neuro fuzzy inference system approaches have been used earlier in the computerized diagnostic system for cancer ...with Fuzzy logic, ANN ...
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COMPARISON OF FEATURE EXTRACTION AND FUZZY FILTERED NEURAL NETWORK APPROACH FOR HANDWRITTEN CHARACTER RECOGNITION
... dimensional fuzzy filters were applied to the physical data of the images of the handwritten digits, the neural nets showed an output accuracy of 92%, which corresponds to the efficiency stated in ...
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On hybrid intelligence-based control approach with its application to flexible robot system
... the fuzzy-based concepts can be discussed in the area of control systems of smart ...The neural network is used to design the control system of a flexible robot ...artificial neural networks ...
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Comparison of Fuzzy Logic & Hybrid Controller based DTC Technique of Induction Motor
... control approach, the actual and change in torque of motor values are generated in form of vector and data is provided to neural ...the fuzzy interference system for generating the control ...
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Impact of Structural Components of Market on the Markup Level Based on Radial Basis Neural Network and Fuzzy Logic
... the fuzzy approach we examine the impact of the entry to barriers, concentration and efficiency criteria on the Mark up variable and finally we constructed 19 rules for every variable with three low, median ...
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Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation
... of neural network and fuzzy logic, determines the parameters of the fuzzy system using the neural network learning ...the fuzzy system, indicative of uncertainty. ...
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Survey on Intrusion Detection System using Support Vector Machine
... bias. Fuzzy inference model works on three basic components: 1)database 2)knowledge base 3)inference ...dataset. Fuzzy ESVDF approach uses 7 ...and neural network approach and ...
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Hybrid Approach for Classification using Multilevel Fuzzy Min-Max Neural Network
... of fuzzy set and neural network. The various fuzzy min-max neural network (FMM) classification models usage hyperbox structure for pattern ...hybrid approach is developed ...
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Analytical and numerical solution of differential equations with generalized fuzzy derivative
... novel approach based on the fuzzy neural network for finding the numerical solution of the first order fuzzy differential equations under generalized ...order fuzzy differential ...
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Sugeno Type Fuzzy Inference Model for Stock Price Prediction
... nonlinear neural-Fuzzy model to classic linear model and verify the capabilities of Fuzzy-neural networks in this ...study fuzzy rule-based framework for effective control of ...
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Online Full Text
... of neural networks in learning from processes, this is an active research topic in the area of fuzzy neural networks (FNNs) [1, ...adaptive network control approach has grown rapidly in ...
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Adaptive Neuro-Fuzzy Inference System based control of six DOF robot manipulator
... uncertainties. Fuzzy Logic Controller can very well describe the desired system behavior with simple “if-then” relations owing the designer to derive “if-then” rules manually by trial and ...hand, Neural ...
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FLEXIBLE SHARING IN DHT BASED P2P NETWORKS USING METADATA OF RESOURCE
... the fuzzy neural network’s basic principle, and proposes the wind power prediction model based on NWP data and fuzzy neural network ...the fuzzy neural network’s input ...
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