ANFIS and fuzzy
A Comparison Of Type-1 Fuzzy And Type-2 Fuzzy Methods In Anfis Modelling To Analyze FTSE Bursa Malaysia Kuala Lumpur Composite Index
... on fuzzy model. By using the Type-2 Fuzzy in ANFIS in this project, it will successful to modelling the FTSE Bursa Malaysia KLCI stock market than Type-1 Fuzzy in ANFIS in term of ...
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Modelling tide prediction using linear model and adaptive neuro fuzzy inference system (ANFIS) in Semarang, Indonesia
... and fuzzy inference system (FIS) where neural network algorithm is used to determine FIS parameter (Chang and Lain, ...Sugeno’s fuzzy model is a sistematic approach in generating fuzzy ruleusing IF x ...
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Intelligent Optimal Control of a Heat Exchanger Using ANFIS and Interval Type-2 Based Fuzzy Inference System
... type-2 fuzzy sets. A type-2 fuzzy set is characterized by a fuzzy MF, that is, the membership value (or membership grade) for each element of this set is a fuzzy set in [0, 1], unlike a type-1 ...
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Indirect Position Estimation of Switched Reluctance Motor based on Flux Sensing Method
... The proposed method uses the phasor current and flux linkage characteristics of the SRM to predict the position of the rotor without any external sensor makes the drive to be cost effective. The training data and ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... the Fuzzy Adaptive Learning Control/Decision Network (FALCON)-Based Fault Detector (FFD), and the Adaptive-Network-Based Fuzzy Inference System (ANFIS)-Based Fault Detector ...
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A Hybrid AI approach based on Genetic Algorithm and ANFIS for Heart Disease Diagnosis
... and fuzzy inference system (FIS) introduced by Jang. ANFIS is used to model, control and estimate parameters in complex ...and fuzzy-set theory can provide advantages and remove the limitations in ...
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Surge Detection System Using Gaussian Curve Membership Function
... The ANFIS is used to implement the proposed model ...the fuzzy detection system which have 4 inputs with one ...function ANFIS constructs a fuzzy inference system (FIS) whose membership ...
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NEW MODEL TRANSFORMATION USING REQUIREMENT TRACEBILITY FROM REQUIREMENT TO UML BEHAVIORAL DESIGN
... PI, fuzzy, hybrid fuzzy-PI, GA-PI and adaptive neuro-fuzzy inference system (ANFIS) controller based soft switching inverter using transformer, which can generate dc link voltage notches ...
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Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS
... of ANFIS, and its parameters and membership functions are adaptively adjusted according to training ...the fuzzy inference rules are determined, and the optimal ANFIS is ...for ANFIS is ...
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LOAD FREQUENCY CONTROL OF HYBRID POWER SYSTEM USING INTELLIGENT CONTROLLERS
... neuro fuzzy interference system because it deals with nonlinearities and does not require exact numerical modeling of the system ...[8]. ANFIS controller has the potential to give an enhanced execution even ...
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LAYOUT AN INEXPENSIVE ELLIPTICAL POLARIZED PRODUCTIVE INTEGRATED TRANSCEIVER
... regression, ANFIS, Type-1 Fuzzy Model and Type-2 Fuzzy Model were developed to predict compressive strength of ...different fuzzy model on the performance of concrete strength prediction has ...
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Using Fuzzy Logic Methods for Carbon Dioxide Control in Carbonated Beverages
... neuro fuzzy Inference system (ANFIS) [9]. ANFIS can serve as a basis for constructing a set of fuzzy „if-then‟ rules with appropriate membership functions in order to generate the stipulated ...
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“Genetically Tuned Optimization Of Plastic Extrusion Process: A Litreture Review”
... (ANN), fuzzy logic, Adaptive neuro fuzzy inference system (ANFIS), genetic algorithms (GA), non-linear modeling, Application of ANFIS and Application of ANFIS+GA have been ...
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Comparative study of ANN and ANFIS prediction models for thermal error compensation on CNC machine tools
... Neuro Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) techniques were employed to design four thermal prediction models: ANFIS by dividing the ...
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USING OF ANFIS AND FIS METHODS TO IMPROVE THE UPQC PERFORMANCE
... the ANFIS architecture and its learning algorithm for the Sugeno fuzzy model ...the fuzzy inference system under consideration has two inputs m and n and one output ...Sugeno fuzzy model, a ...
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Utilization of new computational intelligence methods to estimate daily Evapotranspiration of wheat using Gamma pre processing
... Abstract: Estimation of evapotranspiration (ET) is needed in water resources management, scheduling of farm irrigation, and environmental assessment. Hence, in practical hydrology, it is often crucial to reliably and ...
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Efficient Hybrid Control of Shell and Tube Heat Exchanger Using Interval Type-2 and Adaptive Neuro Fuzzy Based Fuzzy Inference System
... the fuzzy sets, fi is the outputs within the fuzzy region specified by the fuzzy rule, pi, qi and ri are the design parameters that are determined during the training process (Widrow et ...proposed ...
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Comparison of Fuzzy Logic & Hybrid Controller based DTC Technique of Induction Motor
... proposed ANFIS speed controller provides smooth speed control performance with less amount of settling time, peak overshoot and steady state error when compared to the fuzzy logic ...The fuzzy ...
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An Intelligent Evaluation of Enterprise System
... Nowadays, individuals, organizations depend largely on software systems for smooth running of their businesses, unfortunately, most of the organizations fail to realize their set goal, due to software failure and ...
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Implementation of Computational Intelligent Techniques for Diagnosis of Cancer Using Digital Signal Processor
... like Fuzzy Logic, Adoptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network for diagnosis of cancer using TMS320C6713 (Texas Instruments) DSP (Digital Signal ...
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