New Medical Diagnosis Models Based On Generalized Type 2 Fuzzy Logic
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New Medical Diagnosis Models Based On Generalized Type 2 Fuzzy Logic
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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2021-06-03
New Medical Diagnosis Models Based On Generalized Type 2 Fuzzy Logic written by Patricia Melin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-03 with Technology & Engineering categories.
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.
New Directions On Hybrid Intelligent Systems Based On Neural Networks Fuzzy Logic And Optimization Algorithms
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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2024-04-08
New Directions On Hybrid Intelligent Systems Based On Neural Networks Fuzzy Logic And Optimization Algorithms written by Patricia Melin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-08 with Computers categories.
This book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. In this book, new directions on the theoretical developments of fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are offered. In addition, the abovementioned methods are discussed in application areas such as control and robotics, pattern recognition, medical diagnosis, decision-making, prediction and optimization of complex problems. There are a group of papers with the main theme of type-1, type-2 and type-3 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There is also a set of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of hybrid intelligent systems in real problems. There are also some papers that presenttheory and practice of neural networks in different applications. Finally, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas
Type 3 Fuzzy Logic In Intelligent Control
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2023-11-15
Type 3 Fuzzy Logic In Intelligent Control written by Oscar Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-15 with Computers categories.
This book focuses on the field of type-3 fuzzy logic, also considering metaheuristics for applications in the control area. The main idea is that these areas together can solve various control problems and find better results. In this book, we test the proposed method using several benchmark problems, such as the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. We notice that when interval type-3 fuzzy systems are implemented to model the behavior of the systems, the results in control show a better stabilization, because the management of uncertainty is better. For this reason, we consider in this book the proposed method using type-3 fuzzy systems, fuzzy controllers, and metaheuristic algorithms to improve the control behavior of complex nonlinear plants. This book is intended to be a reference for scientists and engineers interested in applying type-3 fuzzy logic techniques for solving problems in intelligent control.We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book
New Perspectives On Hybrid Intelligent System Design Based On Fuzzy Logic Neural Networks And Metaheuristics
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2022-09-30
New Perspectives On Hybrid Intelligent System Design Based On Fuzzy Logic Neural Networks And Metaheuristics written by Oscar Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-30 with Technology & Engineering categories.
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.
Modern Artificial Intelligence Based On Soft Computing Techniques
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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2025-07-05
Modern Artificial Intelligence Based On Soft Computing Techniques written by Patricia Melin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-05 with Computers categories.
This book describes what we can call modern artificial intelligence that includes the theoretical developments and applications of soft computing techniques. Soft computing includes fuzzy logic, neural networks and meta-heuristic algorithms, as well as their hybrid combinations. There are papers with the main topics from type-1 to type-3 fuzzy logic, which basically consists of a group of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There are also papers that present theory and practice of meta-heuristics in diverse application areas. There are interesting papers on different applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. In addition, we can find papers describing applications of fuzzy logic, neural networks and meta-heuristics in robotics problems.
Intelligent Systems Design And Applications
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Author : Ajith Abraham
language : en
Publisher: Springer Nature
Release Date : 2022-03-26
Intelligent Systems Design And Applications written by Ajith Abraham and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-26 with Technology & Engineering categories.
This book highlights recent research on intelligent systems and nature-inspired computing. It presents 132 selected papers from the 21st International Conference on Intelligent Systems Design and Applications (ISDA 2021), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from 34 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Clustering Classification And Time Series Prediction By Using Artificial Neural Networks
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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2024-09-27
Clustering Classification And Time Series Prediction By Using Artificial Neural Networks written by Patricia Melin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-27 with Computers categories.
This book provides a new model for clustering, classification, and time series prediction by using artificial neural networks to computationally simulate the behavior of the cognitive functions of the brain is presented. This model focuses on the study of intelligent hybrid neural systems and their use in time series analysis and decision support systems. Therefore, through the development of eight case studies, multiple time series related to the following problems are analyzed: traffic accidents, air quality and multiple global indicators (energy consumption, birth rate, mortality rate, population growth, inflation, unemployment, sustainable development, and quality of life). The main contribution consists of a Generalized Type-2 fuzzy integration of multiple indicators (time series) using both supervised and unsupervised neural networks and a set of Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. The obtained results show the advantages of the proposed model of Generalized Type-2 fuzzy integration of multiple time series attributes. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic techniques for solving problems in classification and prediction. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.
Soft Computing For Data Analytics Classification Model And Control
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Author : Deepak Gupta
language : en
Publisher: Springer Nature
Release Date : 2022-01-30
Soft Computing For Data Analytics Classification Model And Control written by Deepak Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-30 with Technology & Engineering categories.
This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control. The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design of hybrid algorithms for applications in data analytics, classification model, and engineering control.
Fuzzy Logic Based Software Systems
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Author : Konstantina Chrysafiadi
language : en
Publisher: Springer Nature
Release Date : 2023-10-15
Fuzzy Logic Based Software Systems written by Konstantina Chrysafiadi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-15 with Technology & Engineering categories.
This book aims to provide information about significant advances of Fuzzy Logic in software systems to researchers, scientists, educators, students, software engineers and developers. In particular, this book explains how Fuzzy Logic, can be used in software systems to automatically predict, model, decide, diagnose, recommend etc.. In more details, Fuzzy Logic is an artificial intelligent technique that is ideal for successfully addressing, , the uncertainty, imprecision and vagueness that exist in many diverse scientific and technological areas. It was introduced by Lotfi A. Zadeh of the University of California at Berkeley, as a methodology for computing with words. This ability of Fuzzy Logic allows the representation of imprecise and vague data in a more realistic way. Therefore, Fuzzy Logic-based systems can simulate the human reasoning and decision-making processes, addressing the human subjectivity. Fuzzy Logic-based software systems are referred to any software that concerns an automated program or process that is used in everyday life, like heating or air-conditioning system, or in the scientific world, like a medical diagnostic system, which uses Fuzzy Logic in order to perform reasoning. A Fuzzy Logic-based system consists of three basic modules: Fuzzifier, Inference Engine and Defuzzifier. The Fuzzifier accepts as input numerical data and assigns them to fuzzy sets with some degree of membership, converting crisp data to fuzzy sets. The Inference Engine applies fuzzy rules over the defined fuzzy sets and produces outputs based on linguistic information. The Defuzzifier, converts fuzzy values into crisp values. The use of Fuzzy Logic in software systems constitutes a compelling and active research area in recent years, especially due to the increased interest in artificial intelligence. In the view of the above, this book presents thoroughly the Fuzzy Logic theory and the structure and operation of a Fuzzy Logic-based system. It also explains the role of Fuzzy Logic in artificial intelligence and smart applications, presenting how it can improve the efficiency and effectiveness of automatic processes and tasks. Furthermore, the book describes techniques of artificial intelligence with which the fuzzy logic is combined and how. Furthermore, this book presents several Fuzzy Logic-based software systems in the discipline of medicine, education, decision making and recommendation, natural language processing, automotive engineering and industry, heating, ventilation and air-conditioning, navigation, scheduling, network traffic and security. Thereby, this book can provide deep insights and valuable information not only to readers of computer science-related disciplines, but also to readers, who come from a variety of disciplines and are interesting in systems that perform tasks related to their discipline, in a more efficient way.
Analysis And Design For Fuzzy Systems
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Author : Changhong Wang
language : en
Publisher: Springer Nature
Release Date : 2025-03-20
Analysis And Design For Fuzzy Systems written by Changhong Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-20 with Technology & Engineering categories.
This book proposes analysis and design techniques for fuzzy systems using adaptive technology, event triggering mechanism, sampling control technology, and sliding mode control technology. The book covers stochastic stability, finite-time boundedness, actuator failure problems, fault-tolerant control, asynchronous control, and adaptive sliding mode control for uncertain fuzzy systems. The topic of fault-tolerant control will be of particular interest to readers because: (i) the internal hardware components of the system may age and fail to a greater or lesser extent; (ii) the external environment may suddenly change. With illustrations and tables, readers can easily follow the didactic approach and apply the methods to their own research. This book will be of particular interest to researchers and graduate students in control engineering and applied mathematics who are interested in the latest developments in fuzzy systems.