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This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.
Book Synopsis Analysis and Design of Intelligent Systems Using Soft Computing Techniques by : Patricia Melin
Download or read book Analysis and Design of Intelligent Systems Using Soft Computing Techniques written by Patricia Melin and published by Springer Science & Business Media. This book was released on 2007-06-05 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.
This volume offers a general view of recent conceptual developments of Soft Computing (SC). It presents successful new applications of SC to real-world problems leading to better performance than "traditional" methods. The edited volume covers a wide spectrum of applications including areas such as: robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.
Book Synopsis Hybrid Intelligent Systems by : Oscar Castillo
Download or read book Hybrid Intelligent Systems written by Oscar Castillo and published by Springer. This book was released on 2007-07-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers a general view of recent conceptual developments of Soft Computing (SC). It presents successful new applications of SC to real-world problems leading to better performance than "traditional" methods. The edited volume covers a wide spectrum of applications including areas such as: robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.
This book presents high-quality research papers presented at the International Conference on Soft Computing for Intelligent Systems (SCIS 2020), held during 18–20 December 2020 at University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India. The book encompasses all branches of artificial intelligence, computational sciences and machine learning which is based on computation at some level such as AI-based Internet of things, sensor networks, robotics, intelligent diabetic retinopathy, intelligent cancer genes analysis using computer vision, evolutionary algorithms, fuzzy systems, medical automatic identification intelligence system and applications in agriculture, health care, smart grid and instrumentation systems. The book is helpful for educators, researchers and developers working in the area of recent advances and upcoming technologies utilizing computational sciences in signal processing, imaging, computing, instrumentation, artificial intelligence and their applications.
Book Synopsis Soft Computing for Intelligent Systems by : Nikhil Marriwala
Download or read book Soft Computing for Intelligent Systems written by Nikhil Marriwala and published by Springer Nature. This book was released on 2021-06-22 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents high-quality research papers presented at the International Conference on Soft Computing for Intelligent Systems (SCIS 2020), held during 18–20 December 2020 at University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India. The book encompasses all branches of artificial intelligence, computational sciences and machine learning which is based on computation at some level such as AI-based Internet of things, sensor networks, robotics, intelligent diabetic retinopathy, intelligent cancer genes analysis using computer vision, evolutionary algorithms, fuzzy systems, medical automatic identification intelligence system and applications in agriculture, health care, smart grid and instrumentation systems. The book is helpful for educators, researchers and developers working in the area of recent advances and upcoming technologies utilizing computational sciences in signal processing, imaging, computing, instrumentation, artificial intelligence and their applications.
Traditional artificial intelligence (AI) techniques are based around mathematical techniques of symbolic logic, with programming in languages such as Prolog and LISP invented in the 1960s. These are referred to as "crisp" techniques by the soft computing community. The new wave of AI methods seeks inspiration from the world of biology, and is being used to create numerous real-world intelligent systems with the aid of soft computing tools. These new methods are being increasingly taught at the upper end of the curriculum, sometimes as an adjunct to traditional AI courses, and sometimes as a replacement for them. Where a more radical approach is taken and the course is being taught at an introductory level, we have recently published Negnevitsky's book. Karray and Silva will be suitable for the majority of courses which will be found at an advanced level. Karray and de Silva cover the problem of control and intelligent systems design using soft-computing techniques in an integrated manner. They present both theory and applications, including industrial applications, and the book contains numerous worked examples, problems and case studies. Covering the state-of-the-art in soft-computing techniques, the book gives the reader sufficient knowledge to tackle a wide range of complex systems for which traditional techniques are inadequate.
Book Synopsis Soft Computing and Intelligent Systems Design by : Fakhreddine O. Karray
Download or read book Soft Computing and Intelligent Systems Design written by Fakhreddine O. Karray and published by Addison Wesley Longman. This book was released on 2004 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional artificial intelligence (AI) techniques are based around mathematical techniques of symbolic logic, with programming in languages such as Prolog and LISP invented in the 1960s. These are referred to as "crisp" techniques by the soft computing community. The new wave of AI methods seeks inspiration from the world of biology, and is being used to create numerous real-world intelligent systems with the aid of soft computing tools. These new methods are being increasingly taught at the upper end of the curriculum, sometimes as an adjunct to traditional AI courses, and sometimes as a replacement for them. Where a more radical approach is taken and the course is being taught at an introductory level, we have recently published Negnevitsky's book. Karray and Silva will be suitable for the majority of courses which will be found at an advanced level. Karray and de Silva cover the problem of control and intelligent systems design using soft-computing techniques in an integrated manner. They present both theory and applications, including industrial applications, and the book contains numerous worked examples, problems and case studies. Covering the state-of-the-art in soft-computing techniques, the book gives the reader sufficient knowledge to tackle a wide range of complex systems for which traditional techniques are inadequate.
This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.
Book Synopsis Analysis and Design of Intelligent Systems Using Soft Computing Techniques by : Patricia Melin
Download or read book Analysis and Design of Intelligent Systems Using Soft Computing Techniques written by Patricia Melin and published by Springer Science & Business Media. This book was released on 2007-09-20 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.
The proceedings of the Third International Conference on Intelligent Systems Design and Applications (ISDA 2003) held in Tulsa, USA, August 10-13. Current research in all areas of computational intelligence is presented including design of artificial neural networks, fuzzy systems, evolutionary algorithms, hybrid computing systems, intelligent agents, and their applications in science, technology, business and commerce. Main themes addressed by the conference are the architectures of intelligent systems, image, speech and signal processing, internet modeling, data mining, business and management applications, control and automation, software agents and knowledge management.
Book Synopsis Intelligent Systems Design and Applications by : Ajith Abraham
Download or read book Intelligent Systems Design and Applications written by Ajith Abraham and published by Springer. This book was released on 2013-12-20 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings of the Third International Conference on Intelligent Systems Design and Applications (ISDA 2003) held in Tulsa, USA, August 10-13. Current research in all areas of computational intelligence is presented including design of artificial neural networks, fuzzy systems, evolutionary algorithms, hybrid computing systems, intelligent agents, and their applications in science, technology, business and commerce. Main themes addressed by the conference are the architectures of intelligent systems, image, speech and signal processing, internet modeling, data mining, business and management applications, control and automation, software agents and knowledge management.
Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition comprises papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems. The articles are divided into four main parts. The first one consists of papers that propose new fuzzy and bio-inspired models to solve general problems. The second part deals with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques. The third part contains papers that apply hybrid intelligent systems to the problem of time series analysis and prediction, while the fourth one shows papers dealing with bio-inspired models in optimization and robotics applications. An edited book in which both theoretical and application aspects are covered.
Book Synopsis Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition by : Patricia Melin
Download or read book Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition written by Patricia Melin and published by Springer Science & Business Media. This book was released on 2009-09-30 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition comprises papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems. The articles are divided into four main parts. The first one consists of papers that propose new fuzzy and bio-inspired models to solve general problems. The second part deals with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques. The third part contains papers that apply hybrid intelligent systems to the problem of time series analysis and prediction, while the fourth one shows papers dealing with bio-inspired models in optimization and robotics applications. An edited book in which both theoretical and application aspects are covered.
In recent years, intelligent control has emerged as one of the most active and fruitful areas of research and development. Until now, however, there has been no comprehensive text that explores the subject with focus on the design and analysis of biological and industrial applications. Intelligent Control Systems Using Soft Computing Methodologies does all that and more. Beginning with an overview of intelligent control methodologies, the contributors present the fundamentals of neural networks, supervised and unsupervised learning, and recurrent networks. They address various implementation issues, then explore design and verification of neural networks for a variety of applications, including medicine, biology, digital signal processing, object recognition, computer networking, desalination technology, and oil refinery and chemical processes. The focus then shifts to fuzzy logic, with a review of the fundamental and theoretical aspects, discussion of implementation issues, and examples of applications, including control of autonomous underwater vehicles, navigation of space vehicles, image processing, robotics, and energy management systems. The book concludes with the integration of genetic algorithms into the paradigm of soft computing methodologies, including several more industrial examples, implementation issues, and open problems and open problems related to intelligent control technology. Suitable as a textbook or a reference, Intelligent Control Systems explores recent advances in the field from both the theoretical and the practical viewpoints. It also integrates intelligent control design methodologies to give designers a set of flexible, robust controllers and provide students with a tool for solving the examples and exercises within the book.
Book Synopsis Intelligent Control Systems Using Soft Computing Methodologies by : Ali Zilouchian
Download or read book Intelligent Control Systems Using Soft Computing Methodologies written by Ali Zilouchian and published by CRC Press. This book was released on 2001-03-27 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, intelligent control has emerged as one of the most active and fruitful areas of research and development. Until now, however, there has been no comprehensive text that explores the subject with focus on the design and analysis of biological and industrial applications. Intelligent Control Systems Using Soft Computing Methodologies does all that and more. Beginning with an overview of intelligent control methodologies, the contributors present the fundamentals of neural networks, supervised and unsupervised learning, and recurrent networks. They address various implementation issues, then explore design and verification of neural networks for a variety of applications, including medicine, biology, digital signal processing, object recognition, computer networking, desalination technology, and oil refinery and chemical processes. The focus then shifts to fuzzy logic, with a review of the fundamental and theoretical aspects, discussion of implementation issues, and examples of applications, including control of autonomous underwater vehicles, navigation of space vehicles, image processing, robotics, and energy management systems. The book concludes with the integration of genetic algorithms into the paradigm of soft computing methodologies, including several more industrial examples, implementation issues, and open problems and open problems related to intelligent control technology. Suitable as a textbook or a reference, Intelligent Control Systems explores recent advances in the field from both the theoretical and the practical viewpoints. It also integrates intelligent control design methodologies to give designers a set of flexible, robust controllers and provide students with a tool for solving the examples and exercises within the book.
Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. The papers in this book explore the possibility of bringing these two areas together. This book is unique in the way it concentrates on building intelligent software systems by combining methods from diverse disciplines, such as fuzzy set theory, neuroscience, agent technology, knowledge discovery, and symbolic artificial intelligence. The first part of the book focuses on foundational aspects and future directions; the second part provides the reader with an overview of recently developed software tools for building flexible intelligent systems; the final section studies developed applications in various fields.
Book Synopsis Intelligent Systems and Soft Computing by : Behnam Azvine
Download or read book Intelligent Systems and Soft Computing written by Behnam Azvine and published by Springer Science & Business Media. This book was released on 2000-07-26 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. The papers in this book explore the possibility of bringing these two areas together. This book is unique in the way it concentrates on building intelligent software systems by combining methods from diverse disciplines, such as fuzzy set theory, neuroscience, agent technology, knowledge discovery, and symbolic artificial intelligence. The first part of the book focuses on foundational aspects and future directions; the second part provides the reader with an overview of recently developed software tools for building flexible intelligent systems; the final section studies developed applications in various fields.
This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, individual role adaptation for team sports, application of polynomial neural networks, recursive neuro-fuzzy algorithm for water management, application of interactive genetic algorithm, and Artificial Neural Network (ANN) model. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verification.
Book Synopsis Soft Computing in Artificial Intelligence by : Young Im Cho
Download or read book Soft Computing in Artificial Intelligence written by Young Im Cho and published by Springer. This book was released on 2014-07-08 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, individual role adaptation for team sports, application of polynomial neural networks, recursive neuro-fuzzy algorithm for water management, application of interactive genetic algorithm, and Artificial Neural Network (ANN) model. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verification.
