Fuzzy Logic Augmentation Of Neural And Optimization Algorithms Theoretical Aspects And Real Applications

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Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Fuzzy Logic Augmentation of Neural and Optimization Algorithms Theoretical Aspects and Real Applications Book PDF

Author : Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Publisher : Springer
Page : 546 pages
File Size : 55,8 Mb
Release : 2018-01-10
Category : Technology & Engineering
ISBN : 9783319710082

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Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications by Oscar Castillo,Patricia Melin,Janusz Kacprzyk Pdf

This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book is organized into seven main parts, each with a collection of papers on a similar subject. The first part presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory and applications, and includes papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The third part addresses the theory and practice of meta-heuristics in different areas of application, while the fourth part describes diverse fuzzy logic applications in the control area, which can be considered as intelligent controllers. The next two parts explore applications in areas, such as time series prediction, and pattern recognition and new optimization and evolutionary algorithms and their applications respectively. Lastly, the seventh part addresses the design and application of different hybrid intelligent systems.

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

Oscar Castillo,Patricia Melin
Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms Theory and Applications Book PDF

Author : Oscar Castillo,Patricia Melin
Publisher : Springer Nature
Page : 383 pages
File Size : 43,9 Mb
Release : 2021-03-24
Category : Technology & Engineering
ISBN : 9783030687762

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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications by Oscar Castillo,Patricia Melin Pdf

We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that presents theory and practice of meta-heuristics in different areas of application. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.

Fuzzy Techniques: Theory and Applications

Ralph Baker Kearfott,Ildar Batyrshin,Marek Reformat,Martine Ceberio,Vladik Kreinovich
Fuzzy Techniques Theory and Applications Book PDF

Author : Ralph Baker Kearfott,Ildar Batyrshin,Marek Reformat,Martine Ceberio,Vladik Kreinovich
Publisher : Springer
Page : 823 pages
File Size : 47,8 Mb
Release : 2019-06-10
Category : Technology & Engineering
ISBN : 9783030219208

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Fuzzy Techniques: Theory and Applications by Ralph Baker Kearfott,Ildar Batyrshin,Marek Reformat,Martine Ceberio,Vladik Kreinovich Pdf

This book describes the latest findings related to fuzzy techniques, discussing applications in control, economics, education, humor studies, industrial engineering, linguistics, management, marketing, medicine and public health, military engineering, robotics, ship design, sports, transportation, and many other areas. It also presents recent fuzzy-related algorithms and theoretical results that can be used in other application areas. Featuring selected papers from the Joint World Congress of the International Fuzzy Systems Association (IFSA) and the Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) IFSA-NAFIPS’2019, held in Lafayette, Louisiana, USA, on June 18–21, 2019, the book is of interest to practitioners wanting to use fuzzy techniques to process imprecise expert knowledge. It is also a valuable resource for researchers wishing to extend the ideas from these papers to new application areas, for graduate students and for anyone else interested in problems involving fuzziness and uncertainty.

Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications

Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Intuitionistic and Type 2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms Theory and Applications Book PDF

Author : Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Publisher : Springer Nature
Page : 792 pages
File Size : 43,8 Mb
Release : 2020-02-27
Category : Technology & Engineering
ISBN : 9783030354459

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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications by Oscar Castillo,Patricia Melin,Janusz Kacprzyk Pdf

This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.

Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

Oscar Castillo,Patricia Melin
Hybrid Intelligent Systems in Control Pattern Recognition and Medicine Book PDF

Author : Oscar Castillo,Patricia Melin
Publisher : Springer Nature
Page : 354 pages
File Size : 53,6 Mb
Release : 2019-11-23
Category : Technology & Engineering
ISBN : 9783030341350

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine by Oscar Castillo,Patricia Melin Pdf

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their applications in areas such as: intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. The book is divided into five main parts. The first part proposes new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to recognition. The third part examines the theory and practice of meta-heuristics in various areas of application, while the fourth highlights diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical contexts. Finally, the fifth part focuses on applications of fuzzy logic, neural networks and meta-heuristics to robotics problems.

Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation

Cengiz Kahraman,Selcuk Cebi,Sezi Cevik Onar,Basar Oztaysi,A. Cagri Tolga,Irem Ucal Sari
Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation Book PDF

Author : Cengiz Kahraman,Selcuk Cebi,Sezi Cevik Onar,Basar Oztaysi,A. Cagri Tolga,Irem Ucal Sari
Publisher : Springer Nature
Page : 954 pages
File Size : 51,9 Mb
Release : 2021-08-23
Category : Technology & Engineering
ISBN : 9783030856267

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Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation by Cengiz Kahraman,Selcuk Cebi,Sezi Cevik Onar,Basar Oztaysi,A. Cagri Tolga,Irem Ucal Sari Pdf

This book presents recent research in intelligent and fuzzy techniques. Emerging conditions such as pandemic, wars, natural disasters and various high technologies force people for significant changes in business and social life. The adoption of digital technologies to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technologies through intelligent systems is the main scope of this book. It focuses on revealing the reflection of digital transformation in our business and social life under emerging conditions through intelligent and fuzzy systems. The latest intelligent and fuzzy methods and techniques on digital transformation are introduced by theory and applications. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc. and Ph.D. students studying digital transformation. Usage of ordinary fuzzy sets and their extensions, heuristics and metaheuristics from optimization to machine learning, from quality management to risk management makes the book an excellent source for researchers.

New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics

Oscar Castillo,Patricia Melin
New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic Neural Networks and Metaheuristics Book PDF

Author : Oscar Castillo,Patricia Melin
Publisher : Springer Nature
Page : 471 pages
File Size : 46,9 Mb
Release : 2022-09-30
Category : Technology & Engineering
ISBN : 9783031082665

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New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics by Oscar Castillo,Patricia Melin Pdf

In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.

Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control

Oscar Castillo,Patricia Ochoa,Jose Soria
Differential Evolution Algorithm with Type 2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control Book PDF

Author : Oscar Castillo,Patricia Ochoa,Jose Soria
Publisher : Springer Nature
Page : 66 pages
File Size : 51,7 Mb
Release : 2020-11-19
Category : Technology & Engineering
ISBN : 9783030621339

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Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control by Oscar Castillo,Patricia Ochoa,Jose Soria Pdf

This book focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results. In this book, the authors test the proposed method using five benchmark control problems. First, the water tank, temperature, mobile robot, and inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval Type-2 system. The last control problem was the D.C. motor, for which the experiments were performed with Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results obtained in each of the controllers are better and with increasing uncertainty, the results are even better. For this reason, the authors consider in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers’ behavior in complex control problems.

General Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm

Fevrier Valdez,Cinthia Peraza,Oscar Castillo
General Type 2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm Book PDF

Author : Fevrier Valdez,Cinthia Peraza,Oscar Castillo
Publisher : Springer Nature
Page : 86 pages
File Size : 48,7 Mb
Release : 2020-03-27
Category : Technology & Engineering
ISBN : 9783030439507

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General Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm by Fevrier Valdez,Cinthia Peraza,Oscar Castillo Pdf

This book focuses on the fields of fuzzy logic and metaheuristic algorithms, particularly the harmony search algorithm and fuzzy control. There are currently several types of metaheuristics used to solve a range of real-world of problems, and these metaheuristics contain parameters that are usually fixed throughout the iterations. However, a number of techniques are also available that dynamically adjust the parameters of an algorithm, such as probabilistic fuzzy logic. This book proposes a method of addressing the problem of parameter adaptation in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic. The authors applied this methodology to the resolution of problems of classical benchmark mathematical functions, CEC 2015, CEC2017 functions and to the optimization of various fuzzy logic control cases, and tested the method using six benchmark control problems – four of the Mamdani type: the problem of filling a water tank, the problem of controlling the temperature of a shower, the problem of controlling the trajectory of an autonomous mobile robot and the problem of controlling the speed of an engine; and two of the Sugeno type: the problem of controlling the balance of a bar and ball, and the problem of controlling control the balance of an inverted pendulum. When the interval type-2 fuzzy logic system is used to model the behavior of the systems, the results show better stabilization because the uncertainty analysis is better. As such, the authors conclude that the proposed method, based on fuzzy systems, fuzzy controllers and the harmony search optimization algorithm, improves the behavior of complex control plants.

Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

Patricia Melin,Oscar Castillo,Janusz Kacprzyk
Recent Advances of Hybrid Intelligent Systems Based on Soft Computing Book PDF

Author : Patricia Melin,Oscar Castillo,Janusz Kacprzyk
Publisher : Springer Nature
Page : 341 pages
File Size : 54,5 Mb
Release : 2020-11-06
Category : Technology & Engineering
ISBN : 9783030587284

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Recent Advances of Hybrid Intelligent Systems Based on Soft Computing by Patricia Melin,Oscar Castillo,Janusz Kacprzyk Pdf

This book describes recent advances on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There are also some papers that present theory and practice of meta-heuristics in different areas of application. Another group of papers describes diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.

Nature-Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems

Radu-Emil Precup,Radu-Codrut David
Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems Book PDF

Author : Radu-Emil Precup,Radu-Codrut David
Publisher : Butterworth-Heinemann
Page : 148 pages
File Size : 51,8 Mb
Release : 2019-05-15
Category : Technology & Engineering
ISBN : 9780128163580

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Nature-Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems by Radu-Emil Precup,Radu-Codrut David Pdf

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems suits the general need of a book that explains the major issues to fuzzy control in servo systems without any solid mathematical prerequisite. In addition, pertinent information on nature-inspired optimization algorithms is offered. The book is intended to rapidly make intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience. The attractive analysis and design methodologies dedicated to fuzzy controllers are accompanied by applications to servo systems and case studies in fuzzy controlled servo systems are organized in a special chapter of this book, and allow simple implementations of low-cost automation solutions. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation results and real-time experimental results as well. This book aims at a large category of audience including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems. Gives a merge between classical and modern approaches to fuzzy control Presents in a unified structure from the point of view of a control engineer the essential aspects regarding fuzzy control in servo systems Makes intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience

Advances in Soft Computing

Ildar Batyrshin,María de Lourdes Martínez-Villaseñor,Hiram Eredín Ponce Espinosa
Advances in Soft Computing Book PDF

Author : Ildar Batyrshin,María de Lourdes Martínez-Villaseñor,Hiram Eredín Ponce Espinosa
Publisher : Springer
Page : 454 pages
File Size : 51,7 Mb
Release : 2019-01-02
Category : Computers
ISBN : 9783030044916

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Advances in Soft Computing by Ildar Batyrshin,María de Lourdes Martínez-Villaseñor,Hiram Eredín Ponce Espinosa Pdf

The two-volume set LNAI 11288 and 11289 constitutes the proceedings of the 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, held in Guadalajara, Mexico, in October 2018. The total of 62 papers presented in these two volumes was carefully reviewed and selected from 149 submissions. The contributions are organized in topical as follows: Part I: evolutionary and nature-inspired intelligence; machine learning; fuzzy logic and uncertainty management. Part II: knowledge representation, reasoning, and optimization; natural language processing; and robotics and computer vision.

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic

Patricia Melin,Emanuel Ontiveros-Robles,Oscar Castillo
New Medical Diagnosis Models Based on Generalized Type 2 Fuzzy Logic Book PDF

Author : Patricia Melin,Emanuel Ontiveros-Robles,Oscar Castillo
Publisher : Springer Nature
Page : 85 pages
File Size : 40,5 Mb
Release : 2021-06-03
Category : Technology & Engineering
ISBN : 9783030750978

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New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic by Patricia Melin,Emanuel Ontiveros-Robles,Oscar Castillo Pdf

This book presents different experimental results as evidence of the good results obtained compared with respect to conventional approaches and literature references based on fuzzy logic. Nowadays, the evolution of intelligence systems for decision making has been reached considerable levels of success, as these systems are getting more intelligent and can be of great help to experts in decision making. One of the more important realms in decision making is the area of medical diagnosis, and many kinds of intelligence systems provide the expert good assistance to perform diagnosis; some of these methods are, for example, artificial neural networks (can be very powerful to find tendencies), support vector machines, that avoid overfitting problems, and statistical approaches (e.g., Bayesian). However, the present research is focused on one of the most relevant kinds of intelligent systems, which are the fuzzy systems. The main objective of the present work is the generation of fuzzy diagnosis systems that offer competitive classifiers to be applied in diagnosis systems. To generate these systems, we have proposed a methodology for the automatic design of classifiers and is focused in the Generalized Type-2 Fuzzy Logic, because the uncertainty handling can provide us with the robustness necessary to be competitive with other kinds of methods. In addition, different alternatives to the uncertainty modeling, rules-selection, and optimization have been explored. Besides, different experimental results are presented as evidence of the good results obtained when compared with respect to conventional approaches and literature references based on Fuzzy Logic.

Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities

Ochoa Ortiz-Zezzatti, Alberto,Rivera, Gilberto,Gómez-Santillán, Claudia,Sánchez–Lara, Benito
Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities Book PDF

Author : Ochoa Ortiz-Zezzatti, Alberto,Rivera, Gilberto,Gómez-Santillán, Claudia,Sánchez–Lara, Benito
Publisher : IGI Global
Page : 498 pages
File Size : 41,9 Mb
Release : 2019-04-05
Category : Business & Economics
ISBN : 9781522581321

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Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities by Ochoa Ortiz-Zezzatti, Alberto,Rivera, Gilberto,Gómez-Santillán, Claudia,Sánchez–Lara, Benito Pdf

Building accurate algorithms for the optimization of picking orders is a difficult task, especially when one considers the delays of real-world situations. In warehouse environments, diverse algorithms must be developed to enhance the global performance relating to combining customer orders into picking orders to reduce wait times. The Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities is a pivotal reference source that addresses strategies for developing able algorithms in order to build better picking orders and the impact of these strategies on the picking systems in which diverse algorithms are implemented. While highlighting topics such ABC optimization, environmental intelligence, and order batching, this publication examines common picking aspects in warehouse environments ranging from manual order picking systems to automated retrieval systems. This book is intended for researchers, teachers, engineers, managers, and practitioners seeking research on algorithms to enhance the order picking performance.

Evolutionary Machine Learning Techniques

Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah
Evolutionary Machine Learning Techniques Book PDF

Author : Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah
Publisher : Springer Nature
Page : 286 pages
File Size : 43,9 Mb
Release : 2019-11-11
Category : Technology & Engineering
ISBN : 9789813299900

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Evolutionary Machine Learning Techniques by Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah Pdf

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.