fuzzy neural net
Utilizing a new feed-back fuzzy neural network for solving a system of fuzzy equations
... a fuzzy linear system were discussed by Dubois and Prade ...fully fuzzy linear system. Linear and nonlinear fuzzy systems were solved by [3, 1, ...solving fuzzy systems have been ...of ...
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Auto control of pumping operations in sewerage systems by rule based fuzzy neural networks
... In case of flood/flooding in urban areas, the operation strategy for sewerage systems in Taipei City is to set up pumping stations which are the major hydraulic facilities for inner rainwater discharges. Undoubtedly, ...
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I. INTRODUCTION HE fuzzy neural networks (FNN) combine the strength
... unsupervised fuzzy min- max clustering neural network (FMCN) in which clusters are implemented as fuzzy sets using membership function with a hyperbox core that is constructed from a min point and a ...
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Motion learning by robot apprentices : a fuzzy neural approach
... Analytical resolution methods for fuzzy relational equations allow incremental on- line learning in fuzzy neural networks, which is an advantage over classic neural models.. However, the[r] ...
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The effects of using problem knowledge in a neural network for image processing tasks : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Palmerston North, New Zealand
... a fuzzy neural network window filter for the reliable detection of tree crowns in an aerial photograph of a forest plantation consisting solely of Pinus ...
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Comparative Study of Various Neural Network Models for Software Quality Estimation
... of neural network in software quality estimation based on object oriented ...three neural network models namely Ward Neural Network (WNN), General Regression Neural network (GRNN) and ...
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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 data, the ...
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Online Full Text
... AKING the advantage of neural networks in learning from processes, this is an active research topic in the area of fuzzy neural networks (FNNs) [1, 2]. Generally, FNNs can be divided into two types, ...
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A New Approach to the Numerical Solution of Dual Fully Fuzzy Polynomial Equations
... of fuzzy neural networks with fuzzy weights for fuzzy input vector and fuzzy ...the fuzzy neural network, which is also a fuzzy number, is numerically calculated by ...
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Evolutive Neural Net Fuzzy Filtering: Basic Description
... neuro fuzzy filtering (ENFF) properties, which based on back propagation fuzzy neural net, this filter adaptively choose and emit a decision according with the reference signal changes of an ...
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Comparison of Artificial Intelligence Methods on the Example of Tea Classification Based on Signals from E nose Sensors
... Mamdani-type fuzzy system with pa- rameters optimized using a genetic algorithm The most important parameters of these systems are presented in Table ...the fuzzy system are: the type with the number of ...
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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 neural networks and ...
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Solving fully fuzzy linear programming
... Linear programming is concerned with the opti- mization (minimization or maximization) of a lin- ear function while satisfying a set of linear equal- ity and/ or inequality constrains or restrictions. In the real life ...
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3D Firework Reconstruction from a Given Videos
... a neural network structure to analyze the video efficiently, and finally a simple but effective method was proposed for obtaining these parameters from the ...
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Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS
... the fuzzy reasoning process, the fuzzy rules and membership function parameters in the model can be adjusted adaptively, which makes the model have high prediction accuracy, and the algorithm can be ...
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Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange
... 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 network models ...
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Analysis of Advanced Controllers for Temperature Control in a Heat Exchanger
... simple fuzzy controller control signal depends on the measured inputs error and the change in ...of fuzzy set must be converted to a number that can be sent to the process as a control ...
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Memory Capacity of a novel optical neural net architecture
... memory neural nets are useful for pattern recognition and for associating the recognized patterns with corresponding output ...[5] net storing orthogonal codes in the intermediate layer to minimise the ...
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Neural Net Models of Open domain Discourse Coherence
... Here we introduce two classes of neural models for discourse coherence. Our discriminative mod- els induce coherence by treating human generated texts as coherent examples and texts with random sentence ...
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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 in the ...
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