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Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition, Serkan Kiranyaz; Turker Ince; Moncef Gabbouj


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Автор: Serkan Kiranyaz; Turker Ince; Moncef Gabbouj
Название:  Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition
ISBN: 9783642378454
Издательство: Springer
Классификация:
ISBN-10: 3642378455
Обложка/Формат: Hardcover
Страницы: 321
Вес: 0.63 кг.
Дата издания: 30.07.2013
Серия: Adaptation, Learning, and Optimization
Язык: English
Издание: 2014 ed.
Иллюстрации: 78 illustrations, color; 17 illustrations, black and white; xxviii, 321 p. 95 illus., 78 illus. in color.
Размер: 242 x 168 x 25
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book explores multidimensional particle swarm optimization, a technique developed by the authors and presented in a well-defined algorithmic approach. All featured applications are supported with fully documented source code as well as sample datasets.


Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 1493938436 ISBN-13(EAN): 9781493938438
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Pattern Recognition and Machine Learning

Автор: King-Sun Fu
Название: Pattern Recognition and Machine Learning
ISBN: 1461575680 ISBN-13(EAN): 9781461575689
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This book contains the Proceedings of the US-Japan Seminar on Learning Process in Control Systems. The papers cover a great variety of topics related to learning processes and systems, ranging from pattern recognition to systems identification, from learning control to biological modelling.

Swarm, Evolutionary, and Memetic Computing

Автор: Bijaya Ketan Panigrahi; Ponnuthurai Nagaratnam Sug
Название: Swarm, Evolutionary, and Memetic Computing
ISBN: 3319037552 ISBN-13(EAN): 9783319037554
Издательство: Springer
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Цена: 13974.00 р.
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Описание: The two-volume set LNCS 8297 and LNCS 8298 constitutes the proceedings of the 4th International Conference on Swarm, Evolutionary and Memetic Computing, SEMCCO 2013, held in Chennai, India, in December 2013. They cover cutting-edge research on swarm, evolutionary and memetic computing, neural and fuzzy computing and its application.

Swarm, Evolutionary, and Memetic Computing

Автор: Bijaya Ketan Panigrahi; Ponnuthurai Nagaratnam Sug
Название: Swarm, Evolutionary, and Memetic Computing
ISBN: 3319037528 ISBN-13(EAN): 9783319037523
Издательство: Springer
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Цена: 6986.00 р.
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Описание: The two-volume set LNCS 8297 and LNCS 8298 constitutes the proceedings of the 4th International Conference on Swarm, Evolutionary and Memetic Computing, SEMCCO 2013, held in Chennai, India, in December 2013. They cover cutting-edge research on swarm, evolutionary and memetic computing, neural and fuzzy computing and its application.

Swarm, Evolutionary, and Memetic Computing

Автор: Bijaya Ketan Panigrahi; Ponnuthurai Nagaratnam Sug
Название: Swarm, Evolutionary, and Memetic Computing
ISBN: 3319202936 ISBN-13(EAN): 9783319202938
Издательство: Springer
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Цена: 13416.00 р.
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Описание:

Differential Evolution with Two Subpopulations.- Intelligent Water Drops Algorithm for Multimodal Spaces.- Glowworm Swarm based Informative attribute.- Simultaneous Feature Selection and Classification.- TLBO Based Hybrid Forecasting Model for Prediction of Exchange Rates.- Evaluating Internet Information Search Channels using Hybrid MCDM technique.- Image Restoration with Fuzzy Coefficient Driven Anisotropic Diffusion.- Principal Component Analysis and General Regression Auto Associative Neural Network Hybrid as One-Class Classifier.- Software Effort Estimation Using Functional Link Neural Networks Tuned with Active Learning and Optimized with Particle Swarm Optimization.- Fraud Detection in Financial Statements using Evolutionary Computation based Rule Miners.- A Fuzzy Entropy based Multi-level Image Thresholding using Differential Evolution.

Machine Learning and Data Mining in Pattern Recognition

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319419196 ISBN-13(EAN): 9783319419190
Издательство: Springer
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Цена: 13416.00 р.
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Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Grouping Multidimensional Data

Автор: Jacob Kogan; Charles Nicholas; Marc Teboulle
Название: Grouping Multidimensional Data
ISBN: 3642066542 ISBN-13(EAN): 9783642066542
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.Kogan and his co-editors have put together recent advances in clustering large and high-dimension data.

Applied Multidimensional Systems Theory

Автор: Nirmal K. Bose; Nirmal K. Bose
Название: Applied Multidimensional Systems Theory
ISBN: 3319468243 ISBN-13(EAN): 9783319468242
Издательство: Springer
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Цена: 11179.00 р.
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Описание:

Revised and updated, this concise new edition of the pioneering book on multidimensional signal processing is ideal for a new generation of students. Multidimensional systems or m-D systems are the necessary mathematical background for modern digital image processing with applications in biomedicine, X-ray technology and satellite communications.
Serving as a firm basis for graduate engineering students and researchers seeking applications in mathematical theories, this edition eschews detailed mathematical theory not useful to students. Presentation of the theory has been revised to make it more readable for students, and introduce some new topics that are emerging as multidimensional DSP topics in the interdisciplinary fields of image processing. New topics include Groebner bases, wavelets, and filter banks.
Modern Multidimensional Scaling

Автор: I. Borg; P. J. F. Groenen
Название: Modern Multidimensional Scaling
ISBN: 1441920463 ISBN-13(EAN): 9781441920461
Издательство: Springer
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Цена: 24456.00 р.
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Описание: The first edition was released in 1996 and has sold close to 2200 copies. Provides an up-to-date comprehensive treatment of MDS, a statistical technique used to analyze the structure of similarity or dissimilarity data in multidimensional space. The authors have added three chapters and exercise sets.

Machine Learning and Data Mining in Pattern Recognition

Автор: Petra Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319210238 ISBN-13(EAN): 9783319210230
Издательство: Springer
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Цена: 8944.00 р.
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Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Mathematical Methodologies in Pattern Recognition and Machine Learning

Автор: Pedro Latorre Carmona; J. Salvador S?nchez; Ana L.
Название: Mathematical Methodologies in Pattern Recognition and Machine Learning
ISBN: 1493900927 ISBN-13(EAN): 9781493900923
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012.

Machine Learning and Data Mining in Pattern Recognition

Автор: Petra Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319624156 ISBN-13(EAN): 9783319624150
Издательство: Springer
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Цена: 9781.00 р.
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Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.


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