scholarly journals Fuzzy logic research work in Mexico motivated by Lotfi Zadeh

2021 ◽  
Vol 27 (2) ◽  
pp. 1-10
Author(s):  
Oscar Castillo ◽  
◽  
Patricia Melin ◽  
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Systems ◽  
Intelligent Systems ◽  
High Performance ◽  
Research Work ◽  
Short Review ◽  
Swarm Algorithms ◽  
Soft Computing Techniques

We provide in this article a short review of the research work that has been done in Mexico on developing new methods and theory for designing intelligent systems utilizing type-2 fuzzy systems in combination with soft computing techniques. Soft Computing (SC) is an area formed by intelligent paradigms, like fuzzy systems, neural networks, and bio-inspired and swarm algorithms, which may be utilized to build high performance hybrid systems. The combination of type-2 fuzzy systems with SC enables the constructing of efficient intelligent systems for solving complex problems in a wide diversity of areas, such as control, pattern recognition, medical diagnosis and others. We also recall some of the main moments and memories of encounters and meetings with the father of fuzzy logic (Prof. L. Zadeh), which were very positive and motivated us to continue his work and legacy.

Fuzzy Systems for Spectrum Access, Mobility and Management for Cognitive Radios

2012 ◽  
pp. 205-218
Author(s):  
Prabhjot Kaur ◽  
Moin Uddin ◽  
Arun Khosla
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Systems ◽  
Spectrum Sharing ◽  
Cognitive Radios ◽  
Spectrum Access ◽  
Air Interface ◽  
Soft Computing Techniques ◽  
The One ◽  
Hierarchical Fuzzy Systems

This chapter addresses the issues in air interface designs for Cognitive Radios. Fuzzy logic system is used as one of the soft computing techniques to learn to sub optimality and vagueness. Many good, simple, and quick fuzzy based solutions have been developed since few decades in many diverse domains. Through this chapter, the authors first discuss the significance and need of soft computing techniques in designing such solutions and then present fuzzy based solutions for spectrum access, mobility, and management. Hierarchical fuzzy systems have been used to get over to the problem of curse of dimensionality. The proposed solutions consider an architecture, similar to the one proposed by IEEE 802.22 working group, for spectrum sharing and management. Models have been designed using fuzzy logic toolbox in MATLAB, and the system performance is checked using SIMULINK.

Fuzzy Systems for Spectrum Access, Mobility and Management for Cognitive Radios

2015 ◽  
pp. 1854-1867
Author(s):  
Prabhjot Kaur ◽  
Moin Uddin ◽  
Arun Khosla
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Systems ◽  
Spectrum Sharing ◽  
Cognitive Radios ◽  
Spectrum Access ◽  
Air Interface ◽  
Soft Computing Techniques ◽  
The One ◽  
Hierarchical Fuzzy Systems

This chapter addresses the issues in air interface designs for Cognitive Radios. Fuzzy logic system is used as one of the soft computing techniques to learn to sub optimality and vagueness. Many good, simple, and quick fuzzy based solutions have been developed since few decades in many diverse domains. Through this chapter, the authors first discuss the significance and need of soft computing techniques in designing such solutions and then present fuzzy based solutions for spectrum access, mobility, and management. Hierarchical fuzzy systems have been used to get over to the problem of curse of dimensionality. The proposed solutions consider an architecture, similar to the one proposed by IEEE 802.22 working group, for spectrum sharing and management. Models have been designed using fuzzy logic toolbox in MATLAB, and the system performance is checked using SIMULINK.

scholarly journals Fuzzy Logic in Agriculture – A Short Review

2020 ◽  
pp. 165-168
Author(s):  
Balaji Devarajan ◽  
Rajeshkumar L ◽  
Bhuvaneswari V ◽  
Priya A K ◽  
Rajesh P
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Soil Analysis ◽  
Short Review ◽  
Literature Survey ◽  
Plant Production ◽  
Complete Plant

The Fuzzy Logic (FL) is a variant of soft computing which its versatile it widens its applications to all domain. This article focuses on its application in agriculture. The scope of this logic is not limited to few areas of agriculture. It is extended from the soil analysis to complete plant production, all the areas are comprised by the usage of FL. The short wider literature survey is carried out to understand the FL in agriculture.

scholarly journals Fuzzy Dynamic Adaptation of Gap Generation and Mutation in Genetic Optimization of Type 2 Fuzzy Controllers

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Leticia Cervantes ◽  
Oscar Castillo ◽  
Denisse Hidalgo ◽  
Ricardo Martinez-Soto
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Flight Control ◽  
Fuzzy Systems ◽  
Performance Enhancement ◽  
Fuzzy Controller ◽  
Control Problems ◽  
Genetic Optimization ◽  
Two Parameters

We propose to use an approach based on fuzzy logic for the adaptation of gap generation and mutation probability in a genetic algorithm. The performance of this method is presented with the benchmark problem of flight control and results show how it can decrease the error during the flight of an airplane using fuzzy logic for some parameters of the genetic algorithm. In this case of study, we use fuzzy systems for adapting two parameters of the genetic algorithm to improve the design of a type 2 fuzzy controller and enhance its performance to achieve flight control. Finally, a statistical test is presented to prove the performance enhancement in the application using fuzzy adaptation in the genetic algorithm. It is important to mention that not only is this idea for control problems but also it can be used in pattern recognition and many different problems.

Soft case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 267-269 ◽  
Author(s):  
WILLIAM CHEETHAM ◽  
SIMON SHIU ◽  
ROSINA O. WEBER
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Network Theory ◽  
Probabilistic Reasoning ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Soft Computing Techniques ◽  
Neural Network Theory ◽  
Case Based

The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

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