Fuzzy radial basis function
Forecasting Value of Pollutant Index in Surabaya River Using Fuzzy Radial Basis Function Neural Network
... models Fuzzy Radial Basis Function in predicting the value of the pollution index in ...adopts fuzzy theory and application of supervised learning on Radial Basis ...
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EEG-based Mind Driven Type Writer by Fuzzy Radial Basis Function Neural Classifier
... 1 fuzzy radial basis function (RBF)[16] induced perceptron neural network (PNN)[17] and ii) type 2 fuzzy radial basis function (RBF) induced perceptron neural ...
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Radial Basis Function Neural Network Trained by Adaptive Chaotic Particle Swarm Optimization to Control Nonlinear Systems
... the radial basis function neural network (RBFNN) has a more compact structure and consequently, it requires less training time compared with other ANNs and neuro-fuzzy ...the radial ...
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A Neuro-fuzzy approach for user behaviour classification and prediction
... The fuzzy rule-based system (FRBS) receives three input variables, namely, normalized web fre- quency, normalized network frequency and normalized ma- chine frequency, and predicts one output variable named ...
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Prediction of Combine Harvester Performance Using Hybrid Machine Learning Modeling and Response Surface Methodology
... using radial basis function (RBF) and the hybrid machine learning method of adaptive neuro-fuzzy inference system (ANFIS) to predict various variables of the combine harvester for the optimal ...
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Maximum energy capture of variable speed variable pitch wind turbine by using RBF neural network and fuzzy logic control
... The pitch control of variable speed variable pitch angle wind turbine gave the following results by using radial basis function neural networks and fuzzy logic controller they are explain ...
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Dynamic Approach of MPPT for PV device by using Adaptive Control and fuzzy controller
... (ii) radial basis function based neural network used to approximate the non-linear(I-V) curve (iii) Lyapunov based adaptive learning control technique is applied to guarantee the convergence of ...
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Unified Noise Reduction using Adaptive Radial Basis Function
... on radial basis functions ...(complex radial basis function neural network) for low order digital channel equalization with an extra parameter to reduce nonlinear ...of radial ...
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Impact of Structural Components of Market on the Markup Level Based on Radial Basis Neural Network and Fuzzy Logic
... a radial basis function for clustering the industries and the fuzzy logic approach to appraise the impact of concentration intensity, intensity of entry to barrier and economies of scale ...
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Design of Hanman Entropy Network from Radial Basis Function Network
... the fuzzy set theory, we can form 4 fuzzy sets in each cluster corresponding to four ...each fuzzy set is defined by its attribute values and their membership function ...the fuzzy sets ...
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Benchmarking of the Key Sample Machine
... the function with v = ...indicator function of rigid structure is not a good approximator for this data set, which fluctuates swiftly for small values of x and very slowly for large values of ...
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An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks
... of radial basis func- tions (RBFs), and 4) determination of RBF centers and ...first function enables AL-RAN to decide the necessity of data normalization from incoming training data, and if it is ...
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An Application Of Radial Basis Function In Identifying Banana Maturity Level
... 2.6 Regression value of training of ANN with 2 different networks (Momentum Rate 0.3 & 0.7) 11 2.7 Training Function (traingdx & traingda) 12 2.8 System output (solid data) superimposed on one step ...
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C2-Element radial basis function methods for some continuum mechanics problems
... convergence rate caused by differentiation in a conventional scheme, Mai-Duy and Tran-Cong (2001, 2003) proposed an indirect or integral approach. RBFs were used to represent highest order derivatives and such RBF-based ...
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An Approach of Artificial Neural Networks Modeling Based on Fuzzy Regression for Forecasting Purposes
... The fuzzy regression models are suitable models for these ...the function with nonlinear ...a fuzzy nonlinear regression model while it is capable of dealing with both uncertain situations and ...
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Compact integrated radial basis function modelling of particulate suspensions
... integrated radial ba- sis function approximations are developed into compact local form to achieve sparse system matrices and high levels of accuracy ...
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Error bound for radial basis interpolation in terms of a growth function
... In this paper we are interested in local error bounds for the radial basis interpolation in the form going back to [18]. We introduce an error bound where a polynomial growth function explicitly ...
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Training of Radial Basis Function Using Particle Swarm Optimization
... i.e Radial Basis Function by ...radius. Radial Basis Function emerged as a variant of artificial neural networks in late ...a radial activated ...a Radial ...
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A RADIAL BASIS FUNCTION PARTITION OF UNITY METHOD FOR TRANSPORT ON THE SPHERE
... both be kept low which initially researchers incorrectly thought implied that there were limits on using small values of the shape parameter ε. The issue with using small values of ε are that shifts of the radial ...
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Libyan vehicle license plate detection and recognition using radila basis function
... There are many known methods for LP detections such as binary image processing, grey-level processing, colour processing (Anagnostopoulos et al., 2006), (Anagnostopoulos et al., 2008), fuzzy logic, texture ...
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