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Granular Neural Networks, Pattern Recognition and Bioinformatics

Author: Sankar K. Pal

Publisher: Springer

Published: 2017-05-02

Total Pages: 241

ISBN-13: 331957115X

This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.

Biological and Artificial Intelligence Environments

Author: Bruno Apolloni

Publisher: Springer Science & Business Media

Published: 2007-11-04

Total Pages: 389

ISBN-13: 1402034326

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The book reports the proceedings of the 15th Italian workshop on neural networks issued by the Italian Society on Neural Networks SIREN. The longevity recipe of this conference stands in three main points that normally renders the reading of these proceedings so interesting as appealing. 1. The topics of the neural networks is considered an attraction pole for a set of researches centered on the inherent paradigm of the neural networks, rather than on a specific tool exclusively. Thus, the subsymbolic management of the data information content constitutes the key feature of papers in various fields such as Pattern Recognition, Stochastic Optimization, Learning, Granular Computing, and so on, with a special bias toward bioinformatics operational applications. An excerpt of all these matters may be found in the book. 2. Though managed at domestic level, the conference attracts contributions from foreign researchers as well, so that in the book the reader may capture the flavor of the state of the art in the international community. 3. The conference is a meeting of friends as well. Thus the papers generally reflect a relaxed atmosphere where researchers meet to generously exchange their thought and explain their actual results in view of a common cultural growing of the community.

Rough-Fuzzy Pattern Recognition

Author: Pradipta Maji

Publisher: John Wiley & Sons

Published: 2012-02-14

Total Pages: 312

ISBN-13: 111800440X

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Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems development, making it easier to master such tasks as classification, clustering, and feature selection. Rough-Fuzzy Pattern Recognition examines the important underlying theory as well as algorithms and applications, helping readers see the connections between theory and practice. The first chapter provides an introduction to pattern recognition and data mining, including the key challenges of working with high-dimensional, real-life data sets. Next, the authors explore such topics and issues as: Soft computing in pattern recognition and data mining A mathematical framework for generalized rough sets, incorporating the concept of fuzziness in defining the granules as well as the set Selection of non-redundant and relevant features of real-valued data sets Selection of the minimum set of basis strings with maximum information for amino acid sequence analysis Segmentation of brain MR images for visualization of human tissues Numerous examples and case studies help readers better understand how pattern recognition models are developed and used in practice. This text—covering the latest findings as well as directions for future research—is recommended for both students and practitioners working in systems design, pattern recognition, image analysis, data mining, bioinformatics, soft computing, and computational intelligence.

Pattern Recognition And Big Data

Author: Sankar Kumar Pal

Publisher: World Scientific

Published: 2016-12-15

Total Pages: 875

ISBN-13: 9813144564

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Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.

Pattern Recognition in Bioinformatics

Author: Tetsuo Shibuya

Publisher: Springer

Published: 2012-11-04

Total Pages: 288

ISBN-13: 3642341233

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This book constitutes the refereed proceedings of the 7th International Conference on Pattern Recognition in Bioinformatics, PRIB 2012, held in Tokyo, Japan, in November 2012. The 24 revised full papers presented were carefully reviewed and selected from 33 submissions. Their topics are widely ranging from fundamental techniques, sequence analysis to biological network analysis. The papers are organized in topical sections on generic methods, visualization, image analysis, and platforms, applications of pattern recognition techniques, protein structure and docking, complex data analysis, and sequence analysis.

Handbook of Granular Computing

Author: Witold Pedrycz

Publisher: John Wiley & Sons

Published: 2008-07-31

Total Pages: 1148

ISBN-13: 0470724153

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Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest in the topic as it begins to play a key role in bioinformatics, e-commerce, machine learning, security, data mining and wireless mobile computing when it comes to the issues of effectiveness, robustness and uncertainty. The Handbook of Granular Computing offers a comprehensive reference source for the granular computing community, edited by and with contributions from leading experts in the field. Includes chapters covering the foundations of granular computing, interval analysis and fuzzy set theory; hybrid methods and models of granular computing; and applications and case studies. Divided into 5 sections: Preliminaries, Fundamentals, Methodology and Algorithms, Development of Hybrid Models and Applications and Case Studies. Presents the flow of ideas in a systematic, well-organized manner, starting with the concepts and motivation and proceeding to detailed design that materializes in specific algorithms, applications and case studies. Provides the reader with a self-contained reference that includes all pre-requisite knowledge, augmented with step-by-step explanations of more advanced concepts. The Handbook of Granular Computing represents a significant and valuable contribution to the literature and will appeal to a broad audience including researchers, students and practitioners in the fields of Computational Intelligence, pattern recognition, fuzzy sets and neural networks, system modelling, operations research and bioinformatics.

Pattern Recognition in Bioinformatics

Author: Jagath C.- Rajapakse

Publisher: Springer Science & Business Media

Published: 2007-09-17

Total Pages: 427

ISBN-13: 3540752854

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This book constitutes the refereed proceedings of the International Workshop on Pattern Recognition in Bioinformatics, PRIB 2007, held in Singapore in October 2007. The 38 revised full papers presented were carefully reviewed and selected from 125 submissions. The papers discuss the applications of pattern recognition methods in the field of bioinformatics to solve problems in life sciences.

Pattern Recognition in Bioinformatics

Author: Marco Loog

Publisher: Springer

Published: 2011-10-29

Total Pages: 356

ISBN-13: 3642248551

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This book constitutes the refereed proceedings of the 6th International Conference on Pattern Recognition in Bioinformatics, PRIB 2011, held in Delft, The Netherlands, in November 2011. The 29 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers cover the wide range of possible applications of bioinformatics in pattern recognition: novel algorithms to handle traditional pattern recognition problems such as (bi)clustering, classification and feature selection; applications of (novel) pattern recognition techniques to infer and analyze biological networks and studies on specific problems such as biological image analysis and the relation between sequence and structure. They are organized in the following topical sections: clustering, biomarker selection and classification, network inference and analysis, image analysis, and sequence, structure, and interactions.

Applied Decision-Making

Author: Mauricio A. Sanchez

Publisher: Springer

Published: 2019-05-18

Total Pages: 215

ISBN-13: 3030179850

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This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions. Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.

Pattern Recognition in Bioinformatics

Author: Matteo Comin

Publisher: Springer

Published: 2014-08-13

Total Pages: 146

ISBN-13: 3319091921

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This book constitutes the refereed proceedings of the 8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2014, held in Stockholm, Sweden in August 2014. The 9 revised full papers and 9 revised short papers presented were carefully reviewed and selected from 29 submissions. The focus of the conference was on the latest Research in Pattern Recognition and Computational Intelligence-Based Techniques Applied to Problems in Bioinformatics and Computational Biology.