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What is fuzzy inference system explain its architecture and different components in detail? 

Fuzzy logic
Fuzzy number
Neuro-fuzzy
Fuzzy set operations
Adaptive neuro fuzzy inference system

Answers from top 9 papers

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Papers (9)Insight
Journal Article•DOI
Increasing Fuzzy Rules Cooperation Based on Evolutionary Adaptive Inference Systems
Jesús Alcalá-Fdez, Francisco Herrera, Francisco Alfredo Márquez, Antonio Peregrín 
01 Sep 2007-International Journal of Intelligent Systems
50 Citations
This approach produces a kind of rule cooperation by means of the inference system, increasing the accuracy of the fuzzy system without losing its interpretability.
Open access•Journal Article•DOI
A fuzzy inference system applied to value of information assessment for oil and gas industry.
Martin J. Vilela, Gbenga Folorunso Oluyemi, Andrei Petrovski 
23 May 2019
23 Citations
To the authors’ knowledge, this is the first use of a fuzzy inference system in the domain of value of information.
Open access•Journal Article•DOI
A fuzzy inference model based on an uncertainty forward propagation approach
Luis M. de Campos, Antonio González 
01 Sep 1993-International Journal of Approximate Reasoning
10 Citations
The proposed model is able to handle very general kinds of facts and rules, and it also verifies the most usual properties required by a fuzzy inference model.
Journal Article•DOI
A fuzzy relational inference language
James F. Baldwin, S.Q Zhou 
01 Nov 1984-Fuzzy Sets and Systems
121 Citations
It incorporates an automated fuzzy inference mechanism and should find applications in many areas of knowledge engineering such as expert systems, linguistic controllers, etc.
Journal Article•DOI
Statistical analysis of the main parameters: in the fuzzy inference process
Ignacio Rojas, Julio Ortega, Francisco J. Pelayo, Alberto Prieto 
01 Mar 1999-Fuzzy Sets and Systems
28 Citations
The results obtained show that the defuzzifier and the T-norm operator are the most relevant factors in the fuzzy inference process.
Journal Article•DOI
Optimization of type-1, interval type-2 and general type-2 fuzzy inference systems using a hierarchical genetic algorithm for modular granular neural networks
Patricia Melin, Daniela Sánchez 
01 Apr 2019
16 Citations
The results obtained show the effectiveness of the proposed method to design structures of fuzzy inference systems.
Open access•Journal Article•DOI
New Investment Decision-Making Tool that Combines a Fuzzy Inference System with Real Option Analysis
Maria Kozlova, Mikael Collan, Pasi Luukka 
01 Jan 2018-Fuzzy economic review
3 Citations
The obtained results highlight how the construct of a fuzzy inference system must be adapted to the perspective of the application for which it is used.
Proceedings Article•DOI
A variable ordinal structure model for fuzzy reasoning and its application to decision problem of working order
Y. Naitoh, Takeshi Furuhashi, Yoshiki Uchikawa 
28 Oct 1991
11 Citations
The model coincides well with the human image of fuzzy inference rules in the case where a system has multi-inputs and multi-outputs thereby facilitating the construction and modification of fuzzy inference rules.
Journal Article•DOI
Missile Control Using Fuzzy Cerebellar Model Arithmetic Computer Neural Networks
Z. Jason Geng, Claire L. McCullough 
01 May 1997-Journal of Guidance Control and Dynamics
53 Citations
It also has the capability of conveniently incorporating human knowledge into the system and processing information based on fuzzy inference rules.

Related Questions

What is fuzzy system in medical?5 answersA fuzzy system in medicine refers to the use of fuzzy logic, which is a soft-computing technique that considers truth and falsehood in a graded fashion. It is suitable for developing knowledge-based systems in medicine and can be applied in tasks such as disease diagnosis, treatment selection, and real-time patient monitoring. Fuzzy systems in medicine can be implemented through fuzzy expert systems, which are intelligent programs that use fuzzy inference and reasoning to handle incomplete and fuzzy information in medical diagnosis. These systems allow medical experts to define fuzzy variables and rules for any medical application, and users can input symptoms and obtain medical conditions through the inference engine. Fuzzy systems also play a role in processing and analyzing fuzzy data generated from medical examinations, aiding in clinical diagnosis, predicting patient outcomes, and optimizing decision support in medical diagnostics.
What is fuzzy logic?5 answersFuzzy logic is a mathematical framework that allows reasoning about ambiguous or inaccurate information by representing truth as a degree of membership in a fuzzy set rather than a binary value of true or untrue. It is used in control systems, artificial intelligence, and decision-making. Fuzzy logic is based on the concept of fuzzy numbers, which are variable states that represent linguistic concepts and are usually called linguistic variables. Fuzzy logic extends classical logic by introducing the notion of degree or possibility, which allows for the consideration of imprecision and uncertainties. In a narrow sense, fuzzy logic refers to a logical system that generalizes classical two-valued logic for reasoning under uncertainty, while in a broad sense, it refers to all theories and technologies that employ fuzzy sets. Fuzzy logic finds its use in various areas where binary representations are insufficient, facilitating the representation of approximate reasoning.
How does fuzzy neural inference work?9 answers
How many layers are in neuro fuzzy inference?9 answers
What are the steps of Mamdani fuzzy inference?8 answers
Which fuzzy inference system is used more and why?10 answers

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