Download or read book New Medical Diagnosis Models Based on Generalized Type 2 Fuzzy Logic written by Patricia Melin and published by Springer Nature. This book was released on 2021-06-03 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Type 3 Fuzzy Logic in Intelligent Control written by Oscar Castillo and published by Springer Nature. This book was released on 2023-12-17 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic Neural Networks and Metaheuristics written by Oscar Castillo and published by Springer Nature. This book was released on 2022-09-30 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book New Directions on Hybrid Intelligent Systems Based on Neural Networks Fuzzy Logic and Optimization Algorithms written by Patricia Melin and published by Springer Nature. This book was released on with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Clustering Classification and Time Series Prediction by Using Artificial Neural Networks written by Patricia Melin and published by Springer Nature. This book was released on with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Soft Computing for Data Analytics Classification Model and Control written by Deepak Gupta and published by Springer Nature. This book was released on 2022-01-30 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nature inspired Optimization of Type 2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis written by Patricia Melin and published by Springer Nature. This book was released on 2021-08-06 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Type 3 Fuzzy Logic in Time Series Prediction written by Oscar Castillo and published by Springer Nature. This book was released on with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fuzzy Logic Based Software Systems written by Konstantina Chrysafiadi and published by Springer Nature. This book was released on 2023-11-16 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy Logic in Medicine written by Senen Barro and published by Physica. This book was released on 2013-03-20 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: To say that Fuzzy Logic in Medicine, or FLM for short, is an important addi tion to the literature of fuzzy logic and its applications, is an understatement. Edited by two prominent informaticians, Professors S. Barro and R. Marin, it is one of the first books in its field. Between its covers, FLM presents authoritative expositions of a wide spectrum of medical and biological ap plications of fuzzy logic, ranging from image classification and diagnostics to anaesthesia control and risk assessment of heart diseases. As the editors note in the preface, recognition of the relevance of fuzzy set theory and fuzzy logic to biological and medical systems has a long history. In this context, particularly worthy of note is the pioneering work of Profes sor Klaus Peter Adlassnig of the University of Vienna School of Medicine. However, it is only within the past decade that we began to see an accelerat ing growth in the visibility and importance of publications falling under the rubric of fuzzy logic in medicine and biology -a leading example of which is the Journal of the Biomedical Fuzzy Systems Association in Japan. Why did it take so long for this to happen? First, a bit of history.

Download or read book Hybrid Intelligent Systems in Control Pattern Recognition and Medicine written by Oscar Castillo and published by Springer Nature. This book was released on 2019-11-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy Logic in Its 50th Year written by Cengiz Kahraman and published by Springer. This book was released on 2016-05-17 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a multifaceted perspective on fuzzy set theory, discussing its developments over the last 50 years. It reports on all types of fuzzy sets, from ordinary to hesitant fuzzy sets, with each one explained by its own developers, authoritative scientists well known for their previous works. Highlighting recent theorems and proofs, the book also explores how fuzzy set theory has come to be extensively used in almost all branches of science, including the health sciences, decision science, earth science and the social sciences alike. It presents a wealth of real-world sample applications, from routing problem to robotics, and from agriculture to engineering. By offering a comprehensive, timely and detailed portrait of the field, the book represents an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on new fuzzy set extensions.

Download or read book Fuzzy Logic in Intelligent System Design written by Patricia Melin and published by Springer. This book was released on 2017-09-30 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book International Conference on Innovative Computing and Communications written by Deepak Gupta and published by Springer Nature. This book was released on 2022-09-26 with total page 793 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality research papers presented at the Fifth International Conference on Innovative Computing and Communication (ICICC 2022), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 19–20, 2022. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.

Download or read book Future Data and Security Engineering Big Data Security and Privacy Smart City and Industry 4 0 Applications written by Tran Khanh Dang and published by Springer Nature. This book was released on 2022-11-19 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Future Data and Security Engineering, FDSE 2022, held in Ho Chi Minh City, Vietnam, during November 23–25, 2022. The 41 full papers(including 4 invited keynotes) and 12 short papers included in this book were carefully reviewed and selected from 170 submissions. They were organized in topical sections as follows: ​invited keynotes; big data analytics and distributed systems; security and privacy engineering; machine learning and artificial intelligence for security and privacy; smart city and industry 4.0 applications; data analytics and healthcare systems; and security and data engineering.

Download or read book Nature Inspired Design of Hybrid Intelligent Systems written by Patricia Melin and published by Springer. This book was released on 2016-12-08 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent advances in the design of hybrid intelligent systems based on 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 divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

Download or read book Intelligent and Fuzzy Systems written by Cengiz Kahraman and published by Springer Nature. This book was released on 2022-07-01 with total page 781 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent research in intelligent and fuzzy techniques on digital transformation and the new normal, the state to which economies, societies, etc. settle following a crisis bringing us to a new environment. Digital transformation and the new normal-appearing in many areas such as digital economy, digital finance, digital government, digital health, and digital education are the main scope of this book. The readers can benefit from this book for preparing for a digital “new normal” and maintaining a leadership position among competitors in both manufacturing and service companies. Digitizing an industrial company is a challenging process, which involves rethinking established structures, processes, and steering mechanisms presented in this book. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying digital transformation and new normal. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.