Dynamic Parameter Adaptation For Meta Heuristic Optimization Algorithms Through Type 2 Fuzzy Logic


Dynamic Parameter Adaptation For Meta Heuristic Optimization Algorithms Through Type 2 Fuzzy Logic
DOWNLOAD

Download Dynamic Parameter Adaptation For Meta Heuristic Optimization Algorithms Through Type 2 Fuzzy Logic PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Dynamic Parameter Adaptation For Meta Heuristic Optimization Algorithms Through Type 2 Fuzzy Logic book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page





Dynamic Parameter Adaptation For Meta Heuristic Optimization Algorithms Through Type 2 Fuzzy Logic


Dynamic Parameter Adaptation For Meta Heuristic Optimization Algorithms Through Type 2 Fuzzy Logic
DOWNLOAD

Author : Frumen Olivas
language : en
Publisher: Springer
Release Date : 2018-03-14

Dynamic Parameter Adaptation For Meta Heuristic Optimization Algorithms Through Type 2 Fuzzy Logic written by Frumen Olivas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-14 with Technology & Engineering categories.


In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is based on using met-rics about the population of the meta-heuristic methods, to decide through a fuzzy inference system the best parameter values that were carefully se-lected to be adjusted. With this modification of parameters we want to find a better model of the behavior of the optimization method, because with the modification of parameters, these will affect directly the way in which the global or local search are performed.Three different optimization methods were used to verify the improve-ment of the proposed methodology. In this case the optimization methods are: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), where some parameters are se-lected to be dynamically adjusted, and these parameters have the most im-pact in the behavior of each optimization method.Simulation results show that the proposed methodology helps to each optimization method in obtaining better results than the results obtained by the original method without parameter adjustment.



General Type 2 Fuzzy Logic In Dynamic Parameter Adaptation For The Harmony Search Algorithm


General Type 2 Fuzzy Logic In Dynamic Parameter Adaptation For The Harmony Search Algorithm
DOWNLOAD

Author : Fevrier Valdez
language : en
Publisher: Springer Nature
Release Date : 2020-03-27

General Type 2 Fuzzy Logic In Dynamic Parameter Adaptation For The Harmony Search Algorithm written by Fevrier Valdez and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-27 with Technology & Engineering categories.


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.



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


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

Author : Oscar Castillo
language : en
Publisher: Springer
Release Date : 2018-01-10

Fuzzy Logic Augmentation Of Neural And Optimization Algorithms Theoretical Aspects And Real Applications written by Oscar Castillo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-10 with Technology & Engineering categories.


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.



A New Bio Inspired Optimization Algorithm Based On The Self Defense Mechanism Of Plants In Nature


A New Bio Inspired Optimization Algorithm Based On The Self Defense Mechanism Of Plants In Nature
DOWNLOAD

Author : Camilo Caraveo
language : en
Publisher: Springer
Release Date : 2018-12-30

A New Bio Inspired Optimization Algorithm Based On The Self Defense Mechanism Of Plants In Nature written by Camilo Caraveo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-30 with Technology & Engineering categories.


This book presents a new meta-heuristic algorithm, inspired by the self-defense mechanisms of plants in nature. Numerous published works have demonstrated the various self-defense mechanisms (survival strategies) plants use to protect themselves against predatory organisms, such as herbivorous insects. The proposed algorithm is based on the predator–prey mathematical model originally proposed by Lotka and Volterra, consisting of two nonlinear first-order differential equations, which allow the growth of two interacting populations (prey and predator) to be modeled. The proposed meta-heuristic is able to produce excellent results in several sets of benchmark optimization problems. Further, fuzzy logic is used for dynamic parameter adaptation in the algorithm.



Differential Evolution Algorithm With Type 2 Fuzzy Logic For Dynamic Parameter Adaptation With Application To Intelligent Control


Differential Evolution Algorithm With Type 2 Fuzzy Logic For Dynamic Parameter Adaptation With Application To Intelligent Control
DOWNLOAD

Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2020-11-19

Differential Evolution Algorithm With Type 2 Fuzzy Logic For Dynamic Parameter Adaptation With Application To 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 2020-11-19 with Technology & Engineering categories.


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.



Fuzzy Logic In Intelligent System Design


Fuzzy Logic In Intelligent System Design
DOWNLOAD

Author : Patricia Melin
language : en
Publisher: Springer
Release Date : 2017-09-30

Fuzzy Logic In Intelligent System Design written by Patricia Melin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-30 with Technology & Engineering categories.


This book describes recent advances in the use of fuzzy logic for the design of hybrid intelligent systems based on nature-inspired optimization and their applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Based on papers presented at the North American Fuzzy Information Processing Society Annual Conference (NAFIPS 2017), held in Cancun, Mexico from 16 to 18 October 2017, the book is divided into nine main parts, the first of which first addresses theoretical aspects, and proposes new concepts and algorithms based on type-1 fuzzy systems. The second part consists of papers on new concepts and algorithms for type-2 fuzzy systems, and on applications of type-2 fuzzy systems in diverse areas, such as time series prediction and pattern recognition. In turn, the third part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques describing new nature-inspired optimization algorithms that use fuzzy dynamic adaptation of parameters. The fourth part presents emergent intelligent models, which range from quantum algorithms to cellular automata. The fifth part explores applications of fuzzy logic in diverse areas of medicine, such as the diagnosis of hypertension and heart diseases. The sixth part describes new computational intelligence algorithms and their applications in different areas of intelligent control, while the seventh examines the use of fuzzy logic in different mathematic models. The eight part deals with a diverse range of applications of fuzzy logic, ranging from environmental to autonomous navigation, while the ninth covers theoretical concepts of fuzzy models



Type 3 Fuzzy Logic In Intelligent Control


Type 3 Fuzzy Logic In Intelligent Control
DOWNLOAD

Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2023-12-17

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 2023-12-17 with Technology & Engineering 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



Optimization Of Type 2 Fuzzy Controllers Using The Bee Colony Algorithm


Optimization Of Type 2 Fuzzy Controllers Using The Bee Colony Algorithm
DOWNLOAD

Author : Leticia Amador
language : en
Publisher: Springer
Release Date : 2017-04-27

Optimization Of Type 2 Fuzzy Controllers Using The Bee Colony Algorithm written by Leticia Amador and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-27 with Technology & Engineering categories.


This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.



Hybrid Intelligent Systems In Control Pattern Recognition And Medicine


Hybrid Intelligent Systems In Control Pattern Recognition And Medicine
DOWNLOAD

Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2019-11-23

Hybrid Intelligent Systems In Control Pattern Recognition And Medicine 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 2019-11-23 with Technology & Engineering categories.


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.



A New Meta Heuristic Optimization Algorithm Based On The String Theory Paradigm From Physics


A New Meta Heuristic Optimization Algorithm Based On The String Theory Paradigm From Physics
DOWNLOAD

Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2021-08-18

A New Meta Heuristic Optimization Algorithm Based On The String Theory Paradigm From Physics 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 2021-08-18 with Technology & Engineering categories.


This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.