Granular Neural Networks, Pattern Recognition and Bioinformatics

by Sankar K. Pal

Author	: Sankar K. Pal
Publisher	: Springer
Total Pages	: 241
Release	: 2017-05-02
Genre	: Technology & Engineering
ISBN	: 331957115X

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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.

Pattern Recognition And Big Data

by Sankar Kumar Pal

Author	: Sankar Kumar Pal
Publisher	: World Scientific
Total Pages	: 875
Release	: 2016-12-15
Genre	: Computers
ISBN	: 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.

Broadband Communications, Networks, and Systems

by Qingshan Li

Author	: Qingshan Li
Publisher	: Springer Nature
Total Pages	: 303
Release	: 2019-11-29
Genre	: Computers
ISBN	: 3030364429

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This book constitutes the refereed post-conference proceedings of the 10th International Conference on Broadband Communications, Networks, and Systems, Broadnets 2019, which took place in Xi’an, China, in October 2019. The 19 full papers presented were carefully reviewed and selected from 61 submissions. The papers are thematically grouped as follows: Wireless Networks and Applications, Communication and Sensor Networks, Internet of Things, Pervasive Computing, Security and Privacy.

Rough Sets

by Hung Son Nguyen

Author	: Hung Son Nguyen
Publisher	: Springer
Total Pages	: 676
Release	: 2018-08-14
Genre	: Computers
ISBN	: 3319993682

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This LNAI 1103 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2018, held in Quy Nhon, Vietnam, in August 2018. The 40 full papers presented together with 5 short papers were carefully reviewed and selected from 61 submissions. The IJCRS conferences aim at bringing together experts from universities and research centers as well as the industry representing fields of research in which theoretical and applicational aspects of rough set theory already find or may potentially find usage.

Computational Intelligence for Pattern Recognition

by Witold Pedrycz

Author	: Witold Pedrycz
Publisher	: Springer
Total Pages	: 431
Release	: 2018-04-30
Genre	: Technology & Engineering
ISBN	: 3319896296

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The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.

Rough-Fuzzy Pattern Recognition

by Pradipta Maji

Author	: Pradipta Maji
Publisher	: John Wiley & Sons
Total Pages	: 312
Release	: 2012-02-14
Genre	: Technology & Engineering
ISBN	: 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.

Granular Computing: At the Junction of Rough Sets and Fuzzy Sets

by Rafael Bello

Author	: Rafael Bello
Publisher	: Springer Science & Business Media
Total Pages	: 339
Release	: 2008-02-20
Genre	: Computers
ISBN	: 3540769722

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Since their very inception, both fuzzy and rough set theories have earned a sound, well-deserved reputation owing to their intrinsic capabilities to model uncertainty coming from the real world. The increasing amount of investigations on both subjects reported every year in the literature vouches for the dynamics of the area and its rapid advancements. In the last few years the widespread utilization of fuzzy and rough sets as granulation sources has contributed to lay both methodologies in a privileged position within Granular Computing, thus giving rise to a sort a modeling which is far closer to the way human beings perceive their environment – via granulated knowledge. This volume is a compilation of the best papers presented at the First International Symposium on Fuzzy and Rough Sets (ISFUROS 2006) held in Santa Clara, Cuba. You will therefore find valuable contributions both in the theoretical field as in several application domains such as intelligent control, data analysis, decision making and machine learning, just to name a few. Together, they will catch you up with the huge potential of the aforementioned methodologies.

Machine Learning in Bioinformatics

by Yanqing Zhang

Author	: Yanqing Zhang
Publisher	: John Wiley & Sons
Total Pages	: 476
Release	: 2009-02-23
Genre	: Computers
ISBN	: 0470397411

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An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.

Pattern Recognition in Bioinformatics

by Jagath C.- Rajapakse

Author	: Jagath C.- Rajapakse
Publisher	: Springer
Total Pages	: 427
Release	: 2007-09-19
Genre	: Science
ISBN	: 3540752862

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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.