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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 indiverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. 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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.\u003cbr\u003e","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52613576491281,"sku":"NLS9783030822187","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783030822187.jpg?v=1786032172"},{"product_id":"new-directions-on-hybrid-intelligent-systems-based-on-neural-networks-fuzzy-logi-book-patricia-melin-9783031537127","title":"New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms","description":"\u003cp\u003eThis 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\u003c\/p\u003e\u003cbr\u003e\u003cp\u003e\u003c\/p\u003e","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52656914497809,"sku":"NLS9783031537127","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783031537127.jpg?v=1789212174"},{"product_id":"foundations-of-fuzzy-logic-and-soft-computing-book-patricia-melin-9783540729174","title":"Foundations of Fuzzy Logic and Soft Computing","description":"This book comprises a selection of papers from IFSA 2007 on new methods and theories that contribute to the foundations of fuzzy logic and soft computing. These papers were selected from over 400 submissions and constitute an imp- tant contribution to the theory and applications of fuzzy logic and soft c- puting methodologies. Soft computing consists of several computing paradigms, including fuzzy logic, neural networks, genetic algorithms, and other techniques, which can be used to produce powerful intelligent systems for solving real-world problems. The papers of IFSA 2007 also make a contribution to this goal. This book is intended to be a major reference for scientists and engineers interested in applying new computational and mathematical tools to achieve intelligent solutions to complex problems. 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 papers contained in the book. The book is divided into 14 main parts.Eachpart contains a set of papers on a common subject, so that the reader can ?nd similar papers grouped together. Some of these parts comprise the papers of organized sessions of IFSA 2007 and we thank the session organizers for their incredible job in forming these sessions with invited and regular paper submissions.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52660505903377,"sku":"NLS9783540729174","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783540729174.jpg?v=1786097130"},{"product_id":"modular-neural-networks-and-type-2-fuzzy-systems-for-pattern-recognition-book-patricia-melin-9783642241383","title":"Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition","description":"\u003cp\u003eThis book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.\u003c\/p\u003e","brand":"WoB","offers":[{"title":"- \/ - \/ INTERNAL","offer_id":52674947711249,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ INGRAM","offer_id":52674948497681,"sku":"NLS9783642241383","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783642241383.jpg?v=1786615277"},{"product_id":"soft-computing-for-recognition-based-on-biometrics-book-patricia-melin-9783642151101","title":"Soft Computing for Recognition based on Biometrics","description":"We describe in this book, bio-inspired models and applications of hybrid intel- gent systems using soft computing techniques for image analysis and pattern r- ognition based on biometrics and other information sources. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of classification methods and applications, which are basically papers that propose new models for classification to solve general pr- lems and applications. The second part contains papers with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques, like modular neural networks, for achieving pattern r- ognition based on biometric measures. The third part contains papers with the theme of bio-inspired optimization methods and applications to diverse problems. The fourth part contains papers that deal with general theory and algorithms of bio-inspired methods, like neural networks and evolutionary algorithms. The fifth part contains papers on computer vision applications of soft computing methods. In the part of classification methods and applications there are 5 papers that - scribe different contributions on fuzzy logic and bio-inspired models with appli- tion in classification for medical images and other data.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52676084531473,"sku":"NLS9783642151101","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783642151101.jpg?v=1786614305"},{"product_id":"modular-neural-networks-and-type-2-fuzzy-systems-for-pattern-recognition-book-patricia-melin-9783642270277","title":"Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition","description":"\u003cp\u003eThis book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. 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The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.\u003c\/p\u003e","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52676631494929,"sku":"NLS9783642270277","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783642270277.jpg?v=1786614218"},{"product_id":"soft-computing-applications-in-optimization-control-and-recognition-book-patricia-melin-9783642353222","title":"Soft Computing Applications in Optimization, Control, and Recognition","description":"\u003cp\u003eSoft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.\u003c\/p\u003e","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52677370052881,"sku":"NLS9783642353222","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783642353222.jpg?v=1786007884"},{"product_id":"clustering-classification-and-time-series-prediction-by-using-artificial-neural-book-patricia-melin-9783031711008","title":"Clustering, Classification, and Time Series Prediction by Using Artificial Neural Networks","description":"\u003cp\u003eThis 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. 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