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Fuzzy rules and inference

Fuzzy Inference Algorithm based on Quantitative Association Rules

Fuzzy Inference Algorithm based on Quantitative Association Rules

... the fuzzy inference rules from the data, in this paper a fuzzy inference algorithm based on quantitative association rule (FI-QAR) is ...association rules mining. On the basis of ...

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Neuro Fuzzy Inference Approach : A Survey

Neuro Fuzzy Inference Approach : A Survey

... of fuzzy inference system and artificial neural network have attracted the researchers and scholars in various scientific and engineering areas to the growing need of adaptive intelligent ...whereas ...

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Edge Detection Fuzzy Inference System

Edge Detection Fuzzy Inference System

... 2 Assitant Professor, Department of IT, GNDEC, Ludhiana Abstract — In this paper a method has been developed for automatic edge detection of an digital image. An edge is made up of those pixels at which there is an ...

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Survey of fuzzy inference model and impact on QOS parameters using 
		adaptive neuro fuzzy inference system in MANET

Survey of fuzzy inference model and impact on QOS parameters using adaptive neuro fuzzy inference system in MANET

... Adaptive fuzzy inference system is proposed to improve the scalability of adhoc ...networks. Fuzzy network consist of three ...represents fuzzy rules and third layer denotes the output ...

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Optimization of Tsukamoto Fuzzy Inference System
using Fuzzy Grid Partition

Optimization of Tsukamoto Fuzzy Inference System using Fuzzy Grid Partition

... the rules that we use in the Tsukamoto Method. Fuzzy grid partition can determine the number of fuzzy rules comprising the underlying model as ...In Fuzzy Grid Partition, we can make ...

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Adaptive fuzzy & Neuro Fuzzy Inference controller based MPPT for photovoltaic systems

Adaptive fuzzy & Neuro Fuzzy Inference controller based MPPT for photovoltaic systems

... Keywords: PV panel, ANFIS, Output scaling factor, Fuzzy rules. 1. INTRODUCTION The ever-increasing utilization of energy, fossil fuels soaring costs and exhaustible nature, and worsening global environment ...

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Generation of Fuzzy Rules by Subtractive ‎ Clustering

Generation of Fuzzy Rules by Subtractive ‎ Clustering

... construct fuzzy IF…THEN rules, which controls how the system ...of rules and its parts depend on these ...(TSK) fuzzy inference modal was ...

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IF-THEN RULES AND FUZZY INFERENCE

IF-THEN RULES AND FUZZY INFERENCE

... A rule is also called a fuzzy implication “x is A” is called the antecedent or premise “y is B” is called the consequence or conclusion.. http://if.kaist.ac.kr/lecture/cs670/textbook/.[r] ...

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Reduction of Data Sparsity in Collaborative Filtering based on Fuzzy Inference Rules

Reduction of Data Sparsity in Collaborative Filtering based on Fuzzy Inference Rules

... Methodology proposed in the paper improves recommendation accuracy to a great extent. When user rating matrix is generated there is also some loss of feature value which results in data sparsity. To regain the values and ...

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Fuzzy integral for rule aggregation in fuzzy inference systems

Fuzzy integral for rule aggregation in fuzzy inference systems

... The fuzzy inference system (FIS) has been tuned and re- vamped many times over and applied to numerous ...between rules. Herein, we show how the fuzzy integral, a parametric non-linear ...

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Fuzzy integral for rule aggregation in fuzzy inference systems

Fuzzy integral for rule aggregation in fuzzy inference systems

... The fuzzy inference system (FIS) has been tuned and re- vamped many times over and applied to numerous ...between rules. Herein, we show how the fuzzy integral, a parametric non-linear ...

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MSAFIS: an evolving fuzzy inference system

MSAFIS: an evolving fuzzy inference system

... The rules have a potential difference’s between the inside and outside which is called rest potential, this potential represents constant changes because of the impulses given by the neighbor ...

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Optimization under fuzzy if-then rules

Optimization under fuzzy if-then rules

... i.e. z 0 is computed by the discrete Center-of-Gravity method. Figure 3: Illustration of Tsukamoto’s inference mechanism. If W = IR then all linguistic values of x 1 , . . . , x n also should have strictly ...

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On the Capability of a Fuzzy Inference System with Improved Interpretability

On the Capability of a Fuzzy Inference System with Improved Interpretability

... construct fuzzy inference system that mobile object avoids obstacle and arrives at the designated ...data, fuzzy inference rules for Model 1 and Model 2 are constructed from learning ...

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ANFIS: Adaptive Neuro-Fuzzy Inference Systems

ANFIS: Adaptive Neuro-Fuzzy Inference Systems

... number of rules and antecedent membership functions and then uses linear least squares. estimation to determine each rule’s consequent equations..[r] ...

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Fuzzy Inference System for Productivity and Fertility of Soil

Fuzzy Inference System for Productivity and Fertility of Soil

... of fuzzy logic ...fuzzification, fuzzy inference rule,memebership function and defuzzification ...that fuzzy inference system is an efficient method to demonstrate defuzzification of ...

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Integration of Interpolation and Inference with Multi-antecedent Rules

Integration of Interpolation and Inference with Multi-antecedent Rules

... efficacious fuzzy rule based systems perform their tasks with ei- ther a dense rule base or a sparse rule ...of inference (CRI) or fuzzy rule interpolation (FRI) should be ...where rules do ...

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A fuzzy similarity inference method for fuzzy reasoning

A fuzzy similarity inference method for fuzzy reasoning

... two fuzzy sets, i.e. fuzzy similarity ...measure, fuzzy similarity measure is more suitable for the presentation of uncertainty ...the fuzzy similarity measure, we propose a novel fuzzy ...

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Discrete Structures Rules of inference

Discrete Structures Rules of inference

... • "Everyone in this discrete mathematics class has taken a course in computer science" and “Aslam is a student in this class". • Imply the conclusion “Aslam has taken a cou[r] ...

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Fuzzy Association Rules

Fuzzy Association Rules

... association rules by combining them with fuzzy set theory has already been around since several ...borders. Fuzzy sets can overcome that problem by al- lowing partial memberships to the different ...

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