adaptive neural fuzzy systems
Dynamic Modeling and Adaptive Controlling in GPS-Intelligent Buoy (GIB) Systems Based on Neural-Fuzzy Networks
... ii) When the performance in GIB systems is enhanced, one witnesses its interference with other controllers’ performance. Consequently, in the presented study’s system in which there exists a broad multi-variable ...
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Automatic Heart Disease Diagnosis System Based on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) Approaches
... The programming language used for developing the automated heart disease diagnosis system is MATLAB, which is a powerful language for data analysis and visualization. There are many programming languages used in data ...
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Adaptive Neuro-Fuzzy Inference System based control of six DOF robot manipulator
... The flowchart of ANFIS procedure is shown in Figure 4. AN FIS distinguishes itself from normal fuzzy logic systems by the adaptive parameters, i.e., both the premise and consequent parameters are ...
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A Fuzzy-Neural Adaptive Iterative Learning Control for Freeway Traffic Flow Systems
... flow systems of a single lane freeway with random bounded off-ramp traffic volumes is ...An adaptive fuzzy neural network (FNN) controller and an adaptive robust controller are applied ...
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Adaptive Fuzzy Output-Feedback Sliding Mode Control for Switched Uncertain Nonlinear Systems with Input Saturation
... nonlinear systems has attracted much attention [1], ...nonlinear systems, an adaptive fuzzy output-feedback stabilization control method has been already studied in ...The adaptive ...
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Adaptive Neuro-Fuzzy Systems
... of fuzzy systems (Zadeh, 1965; Ruspini et ...specify fuzzy sets to partition all variables and a sufficient number of fuzzy rules to describe the input/output relation of the problem at ...a ...
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Comparison of ANFIS and ANN for Estimation of Thermal Conductivity Coefficients of Construction Materials
... Articial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFISs) have been used in many dierent elds, from predicting material properties to customer ...
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Modelling the formation of Ozone in the air by using Adaptive Neuro-Fuzzy Inference System (ANFIS) (Case study: city of Yazd, Iran)
... A study was conducted in 2013 on modelling and predicting the formation of ozone in the air of Mashhad city using a neural fuzzy network based on inference fuzzy-adaptive systems. It ...
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Hybrid Models Performance Assessment to Predict Flow of Gamasyab River
... algorithms, neural network and fuzzy logic in order to design a nonlinear mapping between the input and output ...a fuzzy systems with a numerical strength of a neural network, the ...
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Navigational Path Analysis of Mobile Robot in Various Environments
... controller fuzzy logic and neural network play vital ...that fuzzy if-then rules are well suited for capturing the imprecise nature of human knowledge and reasoning ...processes. Fuzzy logic ...
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Highly nonlinear control of a solar thermal power plant using soft computing fuzzy tuning techniques
... supply systems. Many of these real world systems exhibit varying degrees of ...Sugeno-type fuzzy incremental controller was tuned using an ANFIS (Adaptive Neural Fuzzy Inference ...
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Optimized Scheduling of Generating Unit for Economic Load Dispatch using Neuro Fuzzy Expert Systems
... received. Neural networks work on training and testing ...a neural network resembling the working of the human based brain architecture with a self organizing memory ...The neural network can work on ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... a fuzzy if–then rule base so that a desired input/output mapping is ...using adaptive networks to fine tune membership functions of a fuzzy rule base has received more attention ...optimizing ...
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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 ...
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Forecasting Fuzzy Delphi and Hybrid intelligent system for ERP Architecture through the Scientific Private Cloud
... Enterprise Resource Planning (ERP) is a standard of a complete set of enterprise management system.It emphasizes integration of the flow of information relating to the major functions of the firm [6]. There are four ...
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Implementing The Speaker Recognition Process In Python Using ‘Thuyg-20-Sre’ Data Set
... classification neural networks are essentially ...of neural network abbreviated as NN, the difficulty can be marked by making use of the feed forward technique in multi-layer division, where a single neuron ...
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Neural fuzzy Inference Based Robust Adaptive Beamforming
... on fuzzy logic theory that is suitable for both point and scattered ...the fuzzy inference- based beamformer relies on the fuzzy description of the DOA estimation, and at high SNR it places more ...
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Predicting the Collapsibility Potential of Unsaturated Soils Using Adaptive Neural Fuzzy Inference System and Particle Swarm Optimization
... a simple indication of the system behavior. There are dierent methods for determining the primary model structure of fuzzy inference system, among which grid partition and Subtractive Clustering Method (SCM) can ...
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Modelling tide prediction using linear model and adaptive neuro fuzzy inference system (ANFIS) in Semarang, Indonesia
... FJ Chang, HC Lain. 2014. Adaptive neuro-fuzzy inference system for the prediction of monthly shoreline changes in northeastern Taiwan. Ocean Engineering. 84: 145-156. GEP Box, GM Jenkins, and GC Reissel. ...
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An adaptive fuzzy regression model for the prediction of dichotomous response variables
... purposes, fuzzy neural network and classical statistical logistic regression models were constructed and the same 17 input data sets were fed into them to predict oral cancer ...The fuzzy ...
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