neural network-based fuzzy model
The Fuzzy Neural Network Model of Smart Grid Risk Evaluation Based on Bayes
... The total learning process is dividen into two periods:the first period computes from botom to top of the network. With the structure and weight setted, the output neuron can be computed according to the input ...
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Numerical solution of fuzzy differential equations under generalized differentiability by fuzzy neural network
... a fuzzy differential equation by using the strongly generalized differen- tiability ...method based on learning algorithm of fuzzy neural network for the solution of differential ...
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ASSOCIATION RULE MINING BASED VIDEO CLASSIFIER WITH LATE ACCEPTANCE HILL CLIMBING APPROACH
... recognition model based on fuzzy clustering neural ...This model is based on fuzzy system model, taking each HMM state as a fuzzy system, letting continuous ...
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An adaptive fuzzy regression model for the prediction of dichotomous response variables
... combining fuzzy concept with statistical logistic regression. The model was tested on an oral cancer dataset in predicting oral cancer ...proposed model based on the experiment carried ...
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Vol 2, No 11 (2014)
... as fuzzy logic control, neural network control, genetic algorithm, and expert system, proved to be ...schemes. Fuzzy controller conventionally is totally dependent to memberships and rules, ...
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Applying Fuzzy Logic Model for Bending Rigidity Evaluation of Woven Fabrics
... artificial neural network model, ...to model the bending rigidity of plain-woven fabrics using fuzzy ...of fuzzy model to predict bending rigidity based on the ...
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The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models
... Hybrid neural networks – based systems, are based on an architecture which integrates the neural networks and the fuzzy logic based system in the form of parallel ...the ...
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Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller
... propagation neural net with one hidden layer is ...The neural networks are trained using Levenburg- Marquardt ...the neural network Simulink block is generated using “gensim”, as shown in ...
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Auto control of pumping operations in sewerage systems by rule based fuzzy neural networks
... counterpropagation network (CPN), which was pro- posed by Hecht-Nielsen (1987), functions as a self- programming optimal lookup table, providing the mapping between input and output ...and fuzzy arithmetic, ...
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An Image Compression Scheme Based on Fuzzy Neural Network
... Neural network almost is involved in every aspect of image processing, such as image segmentation, image enhancement, image pattern recognition, image restoration and image compression ...of neural ...
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Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange
... artificial neural networks has many considerable advantages; first, neural networks have a high similarity with the human nervous system, and unlike the traditional methods, they are data-driven ...
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A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction
... the neural-based models, 20 simulations are conducted, and the averaged results are collected for comparison ...functional neural network (RBFNN), and an adaptive neuro-fuzzy inference ...
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Comparative study of static and dynamic neural network models for nonlinear time series forecasting
... decades, neural network models have been focused upon by researchers due to their more real performance and on this basis different types of these models have been used in ...dynamic neural ...
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A Hybrid Intelligent Model for Software Cost Estimation
... intelligent model combining a neural network model integrated with fuzzy model (neuro-fuzzy model) has been used to improve the accuracy of estimating software ...
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Development of an Expert System for Message Routing in a Switched Network Environment
... computer network environment (Switched Network) using a Neuro- Fuzzy Expert System (NFES) ...of network traffic condition and imprecise and poor bandwidth management ...System model ...
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A Review Of Clinical Data Prediction Using Different Data Mining Technique And Neuro Fuzzy System
... expectation model depended on a molecule swarm improvement (PSO)- based Fuzzy Hyper-Rectangular Composite Neural Network (PFHRCNN) that incorporates three computational insight devices ...
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Co-Attention Based Neural Network for Source-Dependent Essay Scoring
... Recently, neural network models have been in- troduced into AES, making the development of handcrafted features unnecessary or at least op- ...volutional Neural Network (CNN) model for ...
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Soft Computing Stock Market Price Prediction for the Nigerian Stock Exchange
... state variables and " is the number of control variable.The fuzzy set used for the input stock classifiers were BestBuy (BB), Buy (B), Sell (S) and BestSell (BS) and mapped on a scale of 5-50. Center of ...
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Neuro-Fuzzy Scheduler for the Control of Real Time Spherical Tank Process
... The basic learning rule of adaptive network is back- propagation algorithm where the model parameters are updated by a gradient descent optimization technique. However, due to the slowness and tendency to ...
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FAIR: A Fuzzy ART Network Based Scheme for Retrieving Useful Information from Blogs
... Most of bloggers’ comments are written in text format. Information retrieval (IR) techniques can extract useful knowledge from textual data. That’s also the reason why we employed IR techniques to mine useful knowledge ...
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