Nature Inspired Optimization Of Type 2 Fuzzy Neural Hybrid Models For Classification In Medical Diagnosis

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Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis

Author : Patricia Melin,Ivette Miramontes,German Prado Arechiga
Publisher : Springer Nature
Page : 134 pages
File Size : 52,8 Mb
Release : 2021-08-06
Category : Technology & Engineering
ISBN : 9783030822194

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Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis by Patricia Melin,Ivette Miramontes,German Prado Arechiga Pdf

This book describes the utilization of different soft computing techniques and their optimization for providing an accurate and efficient medical diagnosis. The proposed method provides a precise and timely diagnosis of the risk that a person has to develop a particular disease, but it can be adaptable to provide the diagnosis of different diseases. This book reflects the experimentation that was carried out, based on the different optimizations using bio-inspired algorithms (such as bird swarm algorithm, flower pollination algorithms, and others). In particular, the optimizations were carried out to design the fuzzy classifiers of the nocturnal blood pressure profile and heart rate level. In addition, to obtain the architecture that provides the best result, the neurons and the number of neurons per layers of the artificial neural networks used in the model are optimized. Furthermore, different tests were carried out with the complete optimized model. Another work that is presented in this book is the dynamic parameter adaptation of the bird swarm algorithm using fuzzy inference systems, with the aim of improving its performance. For this, different experiments are carried out, where mathematical functions and a monolithic neural network are optimized to compare the results obtained with the original algorithm. The book will be of interest for graduate students of engineering and medicine, as well as researchers and professors aiming at proposing and developing new intelligent models for medical diagnosis. In addition, it also will be of interest for people working on metaheuristic algorithms and their applications on medicine.

Neuro Fuzzy Hybrid Models for Classification in Medical Diagnosis

Author : Patricia Melin,Juan Carlos Guzmán,German Prado-Arechiga
Publisher : Springer Nature
Page : 109 pages
File Size : 43,6 Mb
Release : 2020-10-27
Category : Technology & Engineering
ISBN : 9783030604813

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Neuro Fuzzy Hybrid Models for Classification in Medical Diagnosis by Patricia Melin,Juan Carlos Guzmán,German Prado-Arechiga Pdf

This book is focused on the use of intelligent techniques, such as fuzzy logic, neural networks and bio-inspired algorithms, and their application in medical diagnosis. The main idea is that the proposed method may be able to adapt to medical diagnosis problems in different possible areas of the medicine and help to have an improvement in diagnosis accuracy considering a clinical monitoring of 24 hours or more of the patient. In this book, tests were made with different architectures proposed in the different modules of the proposed model. First, it was possible to obtain the architecture of the fuzzy classifiers for the level of blood pressure and for the pressure load, and these were optimized with the different bio-inspired algorithms (Genetic Algorithm and Chicken Swarm Optimization). Secondly, we tested with a local database of 300 patients and good results were obtained. It is worth mentioning that this book is an important part of the proposed general model; for this reason, we consider that these modules have a good performance in a particular way, but it is advisable to perform more tests once the general model is completed.

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

Author : Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Publisher : Springer Nature
Page : 792 pages
File Size : 52,5 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.

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

Author : Oscar Castillo,Patricia Melin
Publisher : Springer Nature
Page : 471 pages
File Size : 42,5 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.

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

Author : Patricia Melin,Emanuel Ontiveros-Robles,Oscar Castillo
Publisher : Springer Nature
Page : 85 pages
File Size : 41,6 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.

Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

Author : Oscar Castillo,Patricia Melin
Publisher : Springer Nature
Page : 354 pages
File Size : 49,7 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.

Nature-Inspired Methods for Smart Healthcare Systems and Medical Data

Author : Ahmed M. Anter,Mohamed Elhoseny,Anuradha D. Thakare
Publisher : Springer Nature
Page : 265 pages
File Size : 45,5 Mb
Release : 2024-01-02
Category : Medical
ISBN : 9783031459528

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Nature-Inspired Methods for Smart Healthcare Systems and Medical Data by Ahmed M. Anter,Mohamed Elhoseny,Anuradha D. Thakare Pdf

This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry use. It explores the recent theoretical and practical applications of metaheuristics and optimization in various smart healthcare contexts. The book also discusses the capability of optimization techniques to obtain optimal parameters in ML and DL technologies. It provides an open platform for academics and engineers to share their unique ideas and investigate the potential convergence of existing systems and advanced metaheuristic algorithms. The book's outcome will enable decision-makers and practitioners to select suitable optimization approaches for scheduling patients in crowded environments with minimized human errors. The healthcare system aims to improve the lives of disabled, elderly, sick individuals, and children. IoT-based systems simplify decision-making and task automation, offering an automated foundation. Nature-inspired metaheuristics and mining algorithms are crucial for healthcare applications, reducing costs, increasing efficiency, enabling accurate data analysis, and enhancing patient care. Metaheuristics improve algorithm performance and address challenges in data mining and ML, making them essential in healthcare research. Real-time IoT-based healthcare systems can be modeled using an IoT-based metaheuristic approach to generate optimal solutions. Metaheuristics are powerful technologies for optimization problems in healthcare systems. They balance exact methods, which guarantee optimal solutions but require significant computational resources, with fast but low-quality greedy methods. Metaheuristic algorithms find better solutions while minimizing computational time. The scientific community is increasingly interested in metaheuristics, incorporating techniques from AI, operations research, and soft computing. New metaheuristics offer efficient ways to address optimization problems and tackle unsolved challenges. They can be parameterized to control performance and adjust the trade-off between solution quality and resource utilization. Metaheuristics manage the trade-off between performance and solution quality, making them highly applicable to real-time applications with pragmatic objectives.

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

Author : Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Publisher : Springer
Page : 546 pages
File Size : 47,9 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.

Advanced Computational Intelligence Methods for Processing Brain Imaging Data

Author : Kaijian Xia,Yizhang Jiang,Yu-Dong Zhang,Mohammad Khosravi,Yuanpeng Zhang
Publisher : Frontiers Media SA
Page : 754 pages
File Size : 46,9 Mb
Release : 2022-11-09
Category : Science
ISBN : 9782832504628

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Advanced Computational Intelligence Methods for Processing Brain Imaging Data by Kaijian Xia,Yizhang Jiang,Yu-Dong Zhang,Mohammad Khosravi,Yuanpeng Zhang Pdf

Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design

Author : Oscar Castillo,Patricia Melin
Publisher : Springer Nature
Page : 254 pages
File Size : 52,8 Mb
Release : 2023-01-27
Category : Technology & Engineering
ISBN : 9783031220425

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Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design by Oscar Castillo,Patricia Melin Pdf

This book covers recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations. 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. Nowadays, the main topic of the book is highly relevant, as most current intelligent systems and devices in use utilize some form of intelligent feature to enhance their performance. In addition, on the theoretical side, new and advanced models and algorithms of type-2 and type-3 fuzzy logic are presented, which are of great interest to researchers working on these areas. Also, new nature-inspired optimization algorithms and innovative neural models are put forward in the manuscript, which are very popular subjects, at this moment. There are contributions on theoretical aspects as well as applications, which make the book very appealing to a wide audience, ranging from researchers to professors and graduate students.

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Author : Patricia Melin,Oscar Castillo,Janusz Kacprzyk
Publisher : Springer
Page : 637 pages
File Size : 54,7 Mb
Release : 2015-06-12
Category : Computers
ISBN : 9783319177472

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Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization by Patricia Melin,Oscar Castillo,Janusz Kacprzyk Pdf

This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in eight main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents diverse applications of nature-inspired optimization algorithms. The sixth part contains papers describing new optimization algorithms. The seventh part contains papers describing applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. Finally, the eighth part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques.

Type-2 Fuzzy Logic: Theory and Applications

Author : Oscar Castillo,Patricia Melin
Publisher : Springer Science & Business Media
Page : 252 pages
File Size : 42,6 Mb
Release : 2008-02-20
Category : Mathematics
ISBN : 9783540762836

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Type-2 Fuzzy Logic: Theory and Applications by Oscar Castillo,Patricia Melin Pdf

This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing (SC) techniques. The authors extend the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. This book is intended to be a major reference tool and can be used as a textbook.

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

Author : Oscar Castillo,Patricia Melin
Publisher : Unknown
Page : 0 pages
File Size : 40,6 Mb
Release : 2021
Category : Electronic
ISBN : 3030687775

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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. .

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Author : Dash, Sujata,Tripathy, B.K.,Rahman, Atta ur
Publisher : IGI Global
Page : 538 pages
File Size : 49,6 Mb
Release : 2017-08-10
Category : Computers
ISBN : 9781522528586

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Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms by Dash, Sujata,Tripathy, B.K.,Rahman, Atta ur Pdf

The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.

Soft-Computing-Based Nonlinear Control Systems Design

Author : Singh, Uday Pratap,Tiwari, Akhilesh,Singh, Rajeev Kumar
Publisher : IGI Global
Page : 388 pages
File Size : 40,9 Mb
Release : 2018-02-09
Category : Computers
ISBN : 9781522535324

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Soft-Computing-Based Nonlinear Control Systems Design by Singh, Uday Pratap,Tiwari, Akhilesh,Singh, Rajeev Kumar Pdf

A critical part of ensuring that systems are advancing alongside technology without complications is problem solving. Practical applications of problem-solving theories can model conflict and cooperation and aid in creating solutions to real-world problems. Soft-Computing-Based Nonlinear Control Systems Design is a critical scholarly publication that examines the practical applications of control theory and its applications in problem solving to fields including economics, environmental management, and financial modelling. Featuring a wide range of topics, such as fuzzy logic, nature-inspired algorithms, and cloud computing, this book is geared toward academicians, researchers, and students seeking relevant research on control theory and its practical applications.