Type 3 Fuzzy Logic In Time Series Prediction
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Type 3 Fuzzy Logic In Time Series Prediction
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2024-05-13
Type 3 Fuzzy Logic In Time Series Prediction 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 2024-05-13 with Computers categories.
This book focuses on the field of type-3 fuzzy logic for applications in time series prediction. The main idea is that a higher type and order of fuzzy logic can help in solving various prediction problems and find better results. In addition, neural networks and fractal theory are employed in enhancing prediction results. In this regard, several hybrid intelligent methods are offered. In this book we test the proposed methods using several prediction problems, like predicting COVID-19 and the stock market. We can notice that when Type-3 fuzzy systems are implemented to model the behavior of systems, the results in prediction are enhanced, because the management of uncertainty is better. For this reason, we consider in this book the proposed methods using type-3 fuzzy systems, neural networks and fractal theory to improve the prediction behavior of the complex nonlinear systems. This book is intended to be a reference for scientists and engineers interested in applying type-3 fuzzy logic techniques for solving complex prediction problems. This book can also be used as a reference for graduate courses like the following: soft computing, fuzzy logic, neural networks, bio-inspired algorithms, intelligent prediction, and similar ones. 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.
Type 3 Fuzzy Logic And Fractal Theory For Medical Diagnosis
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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2025-02-19
Type 3 Fuzzy Logic And Fractal Theory For Medical Diagnosis 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 2025-02-19 with Computers categories.
This book is intended to be a reference for scientists and engineers interested in applying type-3 fuzzy logic and fractal theory techniques in medical diagnosis. In this book, a new model based on type-3 fuzzy logic and fractal theory for applications in medical diagnosis is presented. The main idea is that a higher type and order of fuzzy logic can help in solving various diagnosis problems and find better results. In addition, fractal theory is also employed for enhancing medical diagnosis. In this regard, several hybrid intelligent methods are offered. In this book, the authors test the proposed methods using several medical diagnosis problems, like diagnosis of problems in the brain, hearth, lungs, and others. The authors can notice that when type-3 fuzzy systems are implemented to model the behavior of systems, the results in diagnosis are enhanced, because the management of uncertainty is better. For this reason, the authors consider in this book the proposed methods using type-3 fuzzy systems and fractal theory to improve the diagnosis in complex medical problems.
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
Interval Type 3 Fuzzy Systems Theory And Design
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2022-03-13
Interval Type 3 Fuzzy Systems Theory And Design 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 2022-03-13 with Technology & Engineering categories.
This book briefly reviews the basic concepts of type-2 fuzzy systems and then describes the proposed definitions for interval type-3 fuzzy sets and relations, also interval type-3 inference and systems. The use of type-2 fuzzy systems has become widespread in the leading economy sectors, especially in industrial and application areas, such as services, health, defense, and so on. However, recently the use of interval type-3 fuzzy systems has been receiving increasing attention and some successful applications have been developed in the last year. These issues were taken into consideration for this book, as we did realize that there was a need to offer the main theoretical concepts of type-3 fuzzy logic, as well as methods to design, develop and implement the type-3 fuzzy systems. A review of basic concepts and their use in the design and implementation of interval type-3 fuzzy systems, which are relatively new models of uncertainty and imprecision, are presented. The main focus of this work is based on the basic reasons of the need for interval type-3 fuzzy systems in different areas of application. In addition, we describe methods for designing interval type-3 fuzzy systems and illustrate this with some examples and simulations.
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.
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.
Time Series Prediction And Applications
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Author : Amit Konar
language : en
Publisher: Springer
Release Date : 2017-03-25
Time Series Prediction And Applications written by Amit Konar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-25 with Technology & Engineering categories.
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.
Applications Of Soft Computing In Time Series Forecasting
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Author : Pritpal Singh
language : en
Publisher: Springer
Release Date : 2015-11-22
Applications Of Soft Computing In Time Series Forecasting written by Pritpal Singh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-22 with Technology & Engineering categories.
This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations.
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
Hybrid Intelligent Systems Based On Extensions Of Fuzzy Logic Neural Networks And Metaheuristics
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2023-06-12
Hybrid Intelligent Systems Based On Extensions Of 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 2023-06-12 with Technology & Engineering categories.
In this book, recent theoretical developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are presented in application areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, 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 a group of 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 a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines 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 application areas. In addition, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas. Finally, there are a group of papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.