Evolving Connectionist Systems For On Line Knowledge Based Learning
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Evolving Connectionist Systems
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Author : Nikola Kasabov
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Evolving Connectionist Systems written by Nikola Kasabov and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Computers categories.
Many methods and models have been proposed for solving difficult problems such as prediction, planning and knowledge discovery in application areas such as bioinformatics, speech and image analysis. Most, however, are designed to deal with static processes which will not change over time. Some processes - such as speech, biological information and brain signals - are not static, however, and in these cases different models need to be used which can trace, and adapt to, the changes in the processes in an incremental, on-line mode, and often in real time. This book presents generic computational models and techniques that can be used for the development of evolving, adaptive modelling systems. The models and techniques used are connectionist-based (as the evolving brain is a highly suitable paradigm) and, where possible, existing connectionist models have been used and extended. The first part of the book covers methods and techniques, and the second focuses on applications in bioinformatics, brain study, speech, image, and multimodal systems. It also includes an extensive bibliography and an extended glossary. Evolving Connectionist Systems is aimed at anyone who is interested in developing adaptive models and systems to solve challenging real world problems in computing science or engineering. It will also be of interest to researchers and students in life sciences who are interested in finding out how information science and intelligent information processing methods can be applied to their domains.
Future Directions For Intelligent Systems And Information Sciences
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Author : Nikola Kasabov
language : en
Publisher: Physica
Release Date : 2013-11-11
Future Directions For Intelligent Systems And Information Sciences written by Nikola Kasabov and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Computers categories.
This edited volume comprises invited chapters that cover five areas of the current and the future development of intelligent systems and information sciences. Half of the chapters were presented as invited talks at the Workshop "Future Directions for Intelligent Systems and Information Sciences" held in Dunedin, New Zealand, 22-23 November 1999 after the International Conference on Neuro-Information Processing (lCONIPI ANZIISI ANNES '99) held in Perth, Australia. In order to make this volume useful for researchers and academics in the broad area of information sciences I invited prominent researchers to submit materials and present their view about future paradigms, future trends and directions. Part I contains chapters on adaptive, evolving, learning systems. These are systems that learn in a life-long, on-line mode and in a changing environment. The first chapter, written by the editor, presents briefly the paradigm of Evolving Connectionist Systems (ECOS) and some of their applications. The chapter by Sung-Bae Cho presents the paradigms of artificial life and evolutionary programming in the context of several applications (mobile robots, adaptive agents of the WWW). The following three chapters written by R.Duro, J.Santos and J.A.Becerra (chapter 3), GCoghill . (chapter 4), Y.Maeda (chapter 5) introduce new techniques for building adaptive, learning robots.
Evolving Fuzzy Systems Methodologies Advanced Concepts And Applications
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Author : Edwin Lughofer
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-01-19
Evolving Fuzzy Systems Methodologies Advanced Concepts And Applications written by Edwin Lughofer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-19 with Mathematics categories.
In today’s real-world applications, there is an increasing demand of integrating new information and knowledge on-demand into model building processes to account for changing system dynamics, new operating conditions, varying human behaviors or environmental influences. Evolving fuzzy systems (EFS) are a powerful tool to cope with this requirement, as they are able to automatically adapt parameters, expand their structure and extend their memory on-the-fly, allowing on-line/real-time modeling. This book comprises several evolving fuzzy systems approaches which have emerged during the last decade and highlights the most important incremental learning methods used. The second part is dedicated to advanced concepts for increasing performance, robustness, process-safety and reliability, for enhancing user-friendliness and enlarging the field of applicability of EFS and for improving the interpretability and understandability of the evolved models. The third part underlines the usefulness and necessity of evolving fuzzy systems in several online real-world application scenarios, provides an outline of potential future applications and raises open problems and new challenges for the next generation evolving systems, including human-inspired evolving machines. The book includes basic principles, concepts, algorithms and theoretic results underlined by illustrations. It is dedicated to researchers from the field of fuzzy systems, machine learning, data mining and system identification as well as engineers and technicians who apply data-driven modeling techniques in real-world systems.
Handbook On Computer Learning And Intelligence In 2 Volumes
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Author : Plamen Parvanov Angelov
language : en
Publisher: World Scientific
Release Date : 2022-06-29
Handbook On Computer Learning And Intelligence In 2 Volumes written by Plamen Parvanov Angelov and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-29 with Computers categories.
The Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)
Handbook On Computational Intelligence In 2 Volumes
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Author : Plamen Parvanov Angelov
language : en
Publisher: World Scientific
Release Date : 2016-03-18
Handbook On Computational Intelligence In 2 Volumes written by Plamen Parvanov Angelov and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-18 with Computers categories.
With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas — from social sciences, economics and biology, medicine and social networks, to cyber security.The Handbook of Computational Intelligence (in two volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems.This work is a 'one-stop-shop' for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike.
What Should Be Computed To Understand And Model Brain Function
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Author : Tadashi Kitamura
language : en
Publisher: World Scientific
Release Date : 2001
What Should Be Computed To Understand And Model Brain Function written by Tadashi Kitamura and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This volume is a guide to two types of transcendence of academic borders which seem necessary for understanding and modelling brain function. The first type is technical transcendence needed to make intelligent machines such as a humanoid robot, an animal-like behavior architecture, an interpreter of fiction, and an evolving learning machine. This technical erosion is conducted into areas such as biology, ethology, neuroscience and psychology, as well as robotics and soft computing. The second type of transcendence of cross-disciplinary boundaries cuts across scientific areas such as biology and cognitive science/philosophy, into comprehensive, less technical and more abstract aspects of brain function. These aspects enable us to know in what direction and how far an intelligent machine will go. Contents: Consideration of Emotion Model and Primitive Language of Robots (T Ogata & S Sugano); An Architecture for Animal-Like Behavior Selection (T Kitamura); A Computational Literary Theory: The Ultimate Products of the Brain/Mind Machine (A Tokosumi); Cooperation Between Neural Networks Within the Brain (M Dufoss(r) et al.); Brain-Like Functions in Evolving Connectionist Systems for On-Line, Knowledge-Based Learning (N Kasabov); Interrelationships, Communication, Semiotics, and Artificial Consciousness (H-N L Teodorescu); Time Emerges from Incomplete Clock, Based on Internal Measurement (Y-P Gunji et al.); The Logical Jump in Shell Changing in Hermit Crab and Tool Experiment in Ants (N Kitabayashi et al.); The Neurobiology of Semantics: How Can Machines be Designed to Have Meanings (W J Freeman); The Emergence of Contentful Experience (M H Bickhard); Intentionality and Foundations of Logic: A New Approach to Neurocomputation (G Basti). Readership: Graduate students, researchers and academics in robotics automated systems, biomedical engineering and bioengineering.
Autonomous Learning Systems
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Author : Plamen Angelov
language : en
Publisher: John Wiley & Sons
Release Date : 2012-11-06
Autonomous Learning Systems written by Plamen Angelov and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-06 with Science categories.
Autonomous Learning Systems is the result of over a decade of focused research and studies in this emerging area which spans a number of well-known and well-established disciplines that include machine learning, system identification, data mining, fuzzy logic, neural networks, neuro-fuzzy systems, control theory and pattern recognition. The evolution of these systems has been both industry-driven with an increasing demand from sectors such as defence and security, aerospace and advanced process industries, bio-medicine and intelligent transportation, as well as research-driven – there is a strong trend of innovation of all of the above well-established research disciplines that is linked to their on-line and real-time application; their adaptability and flexibility. Providing an introduction to the key technologies, detailed technical explanations of the methodology, and an illustration of the practical relevance of the approach with a wide range of applications, this book addresses the challenges of autonomous learning systems with a systematic approach that lays the foundations for a fast growing area of research that will underpin a range of technological applications vital to both industry and society. Key features: Presents the subject systematically from explaining the fundamentals to illustrating the proposed approach with numerous applications. Covers a wide range of applications in fields including unmanned vehicles/robotics, oil refineries, chemical industry, evolving user behaviour and activity recognition. Reviews traditional fields including clustering, classification, control, fault detection and anomaly detection, filtering and estimation through the prism of evolving and autonomously learning mechanisms. Accompanied by a website hosting additional material, including the software toolbox and lecture notes. Autonomous Learning Systems provides a ‘one-stop shop’ on the subject for academics, students, researchers and practicing engineers. It is also a valuable reference for Government agencies and software developers.
Intelligent Technologies Theory And Applications
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Author : Peter Sincak
language : en
Publisher: IOS Press
Release Date : 2002
Intelligent Technologies Theory And Applications written by Peter Sincak and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
Annotation Intelligent Technologies including neural network, evolutionary computations, fuzzy approach and mainly hybrid approaches are very promising tools to build intelligent technologies in general. The progress of each theory or application is provided by a number of various theoretical as well as applicational experiments. Machine intelligence is the only alternative how to increase the level of technology to make technology more human-centred and more effective for society. This book includes theoretical as well as applicational papers in the field of neural networks, fuzzy systems and mainly evolutionary computations which application potential was increased by enormous progress in computer power. Hybrid technologies are still progressing and are trying to make some more applications with their ability to learn and process fuzzy information. Neurogenetic systems are very interesting approach to make systems re-configurable and on-line systems for real-world applications. The book is presenting papers from Japan, USA, Hungary, Poland, Germany, Finland, France, Slovakia, United Kingdom, Czech Republic and some other countries. This publication provides the latest state of the art in the field and could be contributed to theory and applications in the machine intelligence tools and their wide application potential in current and future technologies within the Information Society.
Springer Handbook Of Computational Intelligence
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Author : Janusz Kacprzyk
language : en
Publisher: Springer
Release Date : 2015-05-28
Springer Handbook Of Computational Intelligence written by Janusz Kacprzyk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-28 with Technology & Engineering categories.
The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.
Machine Learning For Computer And Cyber Security
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Author : Brij B. Gupta
language : en
Publisher: CRC Press
Release Date : 2019-02-05
Machine Learning For Computer And Cyber Security written by Brij B. Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-05 with Computers categories.
While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques. This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals. Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.