Machine Learning And Granular Computing A Synergistic Design Environment
DOWNLOAD
Download Machine Learning And Granular Computing A Synergistic Design Environment PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning And Granular Computing A Synergistic Design Environment book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Machine Learning And Granular Computing A Synergistic Design Environment
DOWNLOAD
Author : Witold Pedrycz
language : en
Publisher: Springer Nature
Release Date : 2024-09-21
Machine Learning And Granular Computing A Synergistic Design Environment written by Witold Pedrycz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-21 with Computers categories.
This volume provides the reader with a comprehensive and up-to-date treatise positioned at the junction of the areas of Machine Learning (ML) and Granular Computing (GrC). ML offers a wealth of architectures and learning methods. Granular Computing addresses useful aspects of abstraction and knowledge representation that are of importance in the advanced design of ML architectures. In unison, ML and GrC support advances of the fundamental learning paradigm. As built upon synergy, this unified environment focuses on a spectrum of methodological and algorithmic issues, discusses implementations and elaborates on applications. The chapters bring forward recent developments showing ways of designing synergistic and coherently structured ML-GrC environment. The book will be of interest to a broad audience including researchers and practitioners active in the area of ML or GrC and interested in following its timely trends and new pursuits.
Computational Intelligence Methods For Bioinformatics And Biostatistics
DOWNLOAD
Author : Martina Vettoretti
language : en
Publisher: Springer Nature
Release Date : 2025-06-13
Computational Intelligence Methods For Bioinformatics And Biostatistics written by Martina Vettoretti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-13 with Computers categories.
The book constitutes the refereed post-conference proceedings of the 18th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2023, held in Padova, Italy, during September 6–8, 2023. The 23 full papers presented in these proceedings were carefully reviewed and selected from 24 submissions. They focuses on topics such as machine learning in healthcare informatics and medical biology; machine learning explainability in medical imaging; prediction uncertainty in machine learning; advanced statistical and computational methodologies for single-cell omics data; present and future research in bioinformatics; distributed computing in bioinformatics and computational biology; and modelling and simulation methods for computational biology and systems medicine.
Computational Intelligence In Telecommunications Networks
DOWNLOAD
Author : Witold Pedrycz
language : en
Publisher: CRC Press
Release Date : 2018-10-03
Computational Intelligence In Telecommunications Networks written by Witold Pedrycz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Technology & Engineering categories.
Telecommunications has evolved and grown at an explosive rate in recent years and will undoubtedly continue to do so. As its functions, applications, and technology grow, it becomes increasingly complex and difficult, if not impossible, to meet the demands of a global network using conventional computing technologies. Computational intelligence (CI) is the technology of the future-and the future is now. Computational Intelligence in Telecommunications Networks offers an in-depth look at the rapid progress of CI technology and shows its importance in solving the crucial problems of future telecommunications networks. It covers a broad range of topics, from Call Admission Control, congestion control, and QoS-routing for ATM networks, to network design and management, optical, mobile, and active networks, and Intelligent Mobile Agents. Today's telecommunications professionals need a working knowledge of CI to exploit its potential to overcome emerging challenges. The CI community must become acquainted with those challenges to take advantage of the enormous opportunities the telecommunications field offers. This text meets both those needs, clearly, concisely, and with a depth certain to inspire further theoretical and practical advances.
Computational Intelligence And Quantitative Software Engineering
DOWNLOAD
Author : Witold Pedrycz
language : en
Publisher: Springer
Release Date : 2016-01-14
Computational Intelligence And Quantitative Software Engineering written by Witold Pedrycz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-14 with Technology & Engineering categories.
In a down-to-the earth manner, the volume lucidly presents how the fundamental concepts, methodology, and algorithms of Computational Intelligence are efficiently exploited in Software Engineering and opens up a novel and promising avenue of a comprehensive analysis and advanced design of software artifacts. It shows how the paradigm and the best practices of Computational Intelligence can be creatively explored to carry out comprehensive software requirement analysis, support design, testing, and maintenance. Software Engineering is an intensive knowledge-based endeavor of inherent human-centric nature, which profoundly relies on acquiring semiformal knowledge and then processing it to produce a running system. The knowledge spans a wide variety of artifacts, from requirements, captured in the interaction with customers, to design practices, testing, and code management strategies, which rely on the knowledge of the running system. This volume consists of contributions written by widely acknowledged experts in the field who reveal how the Software Engineering benefits from the key foundations and synergistically existing technologies of Computational Intelligence being focused on knowledge representation, learning mechanisms, and population-based global optimization strategies. This book can serve as a highly useful reference material for researchers, software engineers and graduate students and senior undergraduate students in Software Engineering and its sub-disciplines, Internet engineering, Computational Intelligence, management, operations research, and knowledge-based systems.
Ecg Signal Processing Classification And Interpretation
DOWNLOAD
Author : Adam Gacek
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-18
Ecg Signal Processing Classification And Interpretation written by Adam Gacek 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 2011-09-18 with Technology & Engineering categories.
The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.
Soft Computing Techniques In Solid Waste And Wastewater Management
DOWNLOAD
Author : Rama Rao Karri
language : en
Publisher: Elsevier
Release Date : 2021-07-24
Soft Computing Techniques In Solid Waste And Wastewater Management written by Rama Rao Karri and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-24 with Technology & Engineering categories.
Soft Computing Techniques in Solid Waste and Wastewater Management is a thorough guide to computational solutions for researchers working in solid waste and wastewater management operations. This book covers in-depth analysis of process variables, their effects on overall efficiencies, and optimal conditions and procedures to improve performance using soft computing techniques. These topics coupled with the systematic analyses described will help readers understand various techniques that can be effectively used to achieve the highest performance. In-depth case studies along with discussions on applications of various soft-computing techniques help readers control waste processes and come up with short-term, mid-term and long-term strategies. Waste management is an increasingly important field due to rapidly increasing levels of waste production around the world. Numerous potential solutions for reducing waste production are underway, including applications of machine learning and computational studies on waste management processes. This book details the diverse approaches and techniques in these fields, providing a single source of information researchers and industry practitioners. It is ideal for academics, researchers and engineers in waste management, environmental science, environmental engineering and computing, with relation to environmental science and waste management. - Provides a comprehensive reference on the implementation of soft computing techniques in waste management, drawing together current research and future implications - Includes detailed algorithms used, enabling authors to understand and appreciate potential applications - Presents relevant case studies in solid and wastewater management that show real-world applications of discussed technologies
Emerging Research In Computing Information Communication And Applications
DOWNLOAD
Author : N. R. Shetty
language : en
Publisher: Springer Nature
Release Date : 2022-12-12
Emerging Research In Computing Information Communication And Applications written by N. R. Shetty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-12 with Technology & Engineering categories.
This book presents the proceedings of the International Conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2022. The conference provides an interdisciplinary forum for researchers, professional engineers and scientists, educators, and technologists to discuss, debate, and promote research and technology in the upcoming areas of computing, information, communication, and their applications. The book discusses these emerging research areas, providing a valuable resource for researchers and practicing engineers alike.
International Aerospace Abstracts
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1999
International Aerospace Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Aeronautics categories.
Granular Computing Based Machine Learning
DOWNLOAD
Author : Han Liu
language : en
Publisher: Springer
Release Date : 2017-11-04
Granular Computing Based Machine Learning written by Han Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-04 with Technology & Engineering categories.
This book explores the significant role of granular computing in advancing machine learning towards in-depth processing of big data. It begins by introducing the main characteristics of big data, i.e., the five Vs—Volume, Velocity, Variety, Veracity and Variability. The book explores granular computing as a response to the fact that learning tasks have become increasingly more complex due to the vast and rapid increase in the size of data, and that traditional machine learning has proven too shallow to adequately deal with big data. Some popular types of traditional machine learning are presented in terms of their key features and limitations in the context of big data. Further, the book discusses why granular-computing-based machine learning is called for, and demonstrates how granular computing concepts can be used in different ways to advance machine learning for big data processing. Several case studies involving big data are presented by using biomedical data and sentiment data, in order to show the advances in big data processing through the shift from traditional machine learning to granular-computing-based machine learning. Finally, the book stresses the theoretical significance, practical importance, methodological impact and philosophical aspects of granular-computing-based machine learning, and suggests several further directions for advancing machine learning to fit the needs of modern industries. This book is aimed at PhD students, postdoctoral researchers and academics who are actively involved in fundamental research on machine learning or applied research on data mining and knowledge discovery, sentiment analysis, pattern recognition, image processing, computer vision and big data analytics. It will also benefit a broader audience of researchers and practitioners who are actively engaged in the research and development of intelligent systems.
Emerging Paradigms In Machine Learning
DOWNLOAD
Author : Sheela Ramanna
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-31
Emerging Paradigms In Machine Learning written by Sheela Ramanna 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 2012-07-31 with Technology & Engineering categories.
This book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The multidisciplinary nature of machine learning makes it a very fascinating and popular area for research. The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems. Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary data streams are a key part of this book.