neural network based fuzzy system model
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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Forecasting of Intellectual Capital by Measuring Innovation Using Adaptive Neuro-Fuzzy Inference System
... forecasting system based on ANFIS, which differs from the traditional Artificial Neural Networks (ANN) in that it is not fully connected and not all the weights or nodal parameters are ...The ...
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Adaptive Network Based Fuzzy Inference System Model for Minimizing Handover Failure in Mobile Networks
... Adaptive network based fuzzy inference system is also referred to as Adaptive neuro-fuzzy inference system ...hybrid system which combine fuzzy logic system ...
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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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Computing air demand using the Takagi–Sugeno model for dam outlets
... inference system (ANFIS) was developed using the subtractive clustering technique to study the air demand in low-level outlet ...ANFIS model was employed to calculate vent air discharge in different gate ...
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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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Sugeno Type Fuzzy Inference Model for Stock Price Prediction
... a fuzzy engine model that acts as an expert indicator that can generate buy and sell ...The fuzzy engine model combines the most popular technical indicators with their firing strengths to ...
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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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Testing Of Network Intrusion Detection System
... Network based intrusion detection system use the models of attacks to identify intrusive behavior ability of systems to detect attacks by quality of models which are called ...of ...
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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 ...Expert ...
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Smart Growth Evaluation System based on Fuzzy Theory and Neural Network
... Fig. 4. The scoring of each evaluation indicator Each project is related to a number of indicators. We predict that 20 years later, by the plan one - the government increased the supply of infrastructure and public ...
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Vol 2, No 11 (2014)
... as fuzzy logic control, neural network control, genetic algorithm, and expert system, proved to be ...accurate system mathematical ...schemes. Fuzzy controller conventionally is ...
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ASSOCIATION RULE MINING BASED VIDEO CLASSIFIER WITH LATE ACCEPTANCE HILL CLIMBING APPROACH
... past fuzzy clustering algorithms when identifying systems, a fuzzy clustering neural network (FCNN) is proposed and is applied to conjunction speech recognition ...system. Based ...
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Adaptive and intelligent navigation of autonomous planetary rovers – a survey
... of fuzzy cognitive maps (FCM) for a knowledge-based navigation ...the system becomes able to adapt to changes in the environment and successfully avoid ...learning model, implemented through a ...
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Applying Fuzzy Logic Model for Bending Rigidity Evaluation of Woven Fabrics
... artificial neural network, with corresponding experimental results in terms of absolute error % of prediction ...usually based on certain idealized assumptions, so their success potential is largely ...
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Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation
... estimation model criterion. In addition, models based on single- objective optimization are not able to manage software projects, and the results of this type of estimators are greatly different from one ...
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Neuro fuzzy.ppt
... better results are obtained when we assign three better results are obtained when we assign three membership functions to each input variable. In membership functions to each input variable. In this case, the ANFIS ...
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A Survey on Advanced Segmentation Techniques for Brain MRI Image Segmentation
... k-means, Fuzzy C-Means (FCM) and Improved Mountain Clustering technique for the segmentation of brain ...a system of the optimization algorithm to detect the ventricle region or the eyeball region of the ...
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Artificial Intelligence and its Application as an Integrated Approach
... AI is at the centre of a new enterprise to build computational models of intelligence. The main assumption is that intelligence (human or otherwise) can be represented in terms of symbol structures and symbolic ...
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Comparative Study of Various Neural Network Models for Software Quality Estimation
... Software quality describes the wide range of activities concerned with measurement in Software Engineering. It provides measurement of the software products and the process of software production/development. The ...
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