Computational Intelligence for Pattern Recognition, Pedrycz
Автор: Pramod Kumar Pisharady; Prahlad Vadakkepat; Loh Ai Название: Computational Intelligence in Multi-Feature Visual Pattern Recognition ISBN: 9811011710 ISBN-13(EAN): 9789811011719 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds.
Автор: Pramod Kumar Pisharady; Prahlad Vadakkepat; Loh Ai Название: Computational Intelligence in Multi-Feature Visual Pattern Recognition ISBN: 9812870555 ISBN-13(EAN): 9789812870551 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds.
Автор: B. Uma Shankar; Kuntal Ghosh; Deba Prasad Mandal; Название: Pattern Recognition and Machine Intelligence ISBN: 3319698990 ISBN-13(EAN): 9783319698991 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2017,held in Kolkata, India, in December 2017. The total of 86 full papers presented in this volume were carefully reviewed and selected from 293 submissions.
Автор: Marzena Kryszkiewicz; Sanghamitra Bandyopadhyay; H Название: Pattern Recognition and Machine Intelligence ISBN: 3319199404 ISBN-13(EAN): 9783319199405 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 6th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2015, held in Warsaw, Poland, in June/July 2015. The total of 53 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 90 submissions. They were organized in topical sections named: foundations of machine learning; image processing; image retrieval; image tracking; pattern recognition; data mining techniques for large scale data; fuzzy computing; rough sets; bioinformatics; and applications of artificial intelligence.
Автор: Bishop, Christopher M. Название: Neural Networks for Pattern Recognition ISBN: 0198538642 ISBN-13(EAN): 9780198538646 Издательство: Oxford Academ Рейтинг: Цена: 14414.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.
Автор: Sergios Theodoridis Название: Introduction to Pattern Recognition: A Matlab Approach, ISBN: 0123744865 ISBN-13(EAN): 9780123744869 Издательство: Elsevier Science Рейтинг: Цена: 5557.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An accompanying manual to "Theodoridis/Koutroumbas, Pattern Recognition", that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.
Автор: Brian D. Ripley Название: Pattern Recognition and Neural Networks ISBN: 0521717701 ISBN-13(EAN): 9780521717700 Издательство: Cambridge Academ Рейтинг: Цена: 7762.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. Valuable advice is included on both theory and applications, while case studies based on real data sets help readers develop their understanding. All data sets are available from www.stats.ox.ac.uk/~ripley/PRbook/
Автор: Ngoc Thanh Nguyen; George A. Papadopoulos; Piotr J Название: Computational Collective Intelligence ISBN: 331967076X ISBN-13(EAN): 9783319670768 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This two-volume set (LNAI 10448 and LNAI 10449) constitutes the refereed proceedings of the 9th International Conference on Collective Intelligence, ICCCI 2017, held in Nicosia, Cyprus, in September 2017. The 117 full papers presented were carefully reviewed and selected from 248 submissions. The conference focuseson the methodology and applications of computational collective intelligence, included: multi-agent systems, knowledge engineering and semantic web, social networks and recommender systems, text processing and information retrieval, data mining methods and applications, sensor networks and internet of things, decision support & control systems, and computer vision techniques.
Описание: This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization – the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms.The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution.
Автор: Tshilidzi Marwala; Monica Lagazio Название: Militarized Conflict Modeling Using Computational Intelligence ISBN: 1447127013 ISBN-13(EAN): 9781447127017 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume offers a scientific approach to manage inter-country conflict. Readers will find that through simultaneous control of four specific aspects (democracy, dependency, allies and capacity), predicted dispute outcomes can be avoided.
Автор: Shubhabrata Datta Название: Materials Design Using Computational Intelligence Techniques ISBN: 1482238322 ISBN-13(EAN): 9781482238327 Издательство: Taylor&Francis Рейтинг: Цена: 25265.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book illustrates the alternative but effective methods of designing materials, where models are developed through capturing the inherent correlations among the variables on the basis of available imprecise knowledge in the form of rules or database.
Автор: Witold Pedrycz; Shyi-Ming Chen Название: Information Granularity, Big Data, and Computational Intelligence ISBN: 3319082531 ISBN-13(EAN): 9783319082530 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Nearest Neighbor Queries on Big Data.- Information Mining for Big Information.- Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression Analysis.- How to Understand Connections Based on Big Data: From Cliques to Flexible Granules.- Maintain 'Omics: When e-Maintenance Enters the Big Data Era.- Incrementally Mining Frequent Patterns for Large Database.- Improved Latent Semantic Indexing-based Data Mining Methods and An Application to Big.- The Property of Different Granule and Granular Methods Based on Quotient Space.- Towards An Optimal Task-Driven Information Granulation.- Unified Framework for Construction of Rule Based Classification Systems.- Multi-granular Evaluation Model through Fuzzy Random Regression to Improve Information.- Building Fuzzy Robust Regression Model Based on Granularity and Possibility Distribution.- The Role of Cloud Computing Architectures in Big Data.- Big Data Storage Techniques for Spatial Databases: Implications of Big Data Architecture on Spatial Query Processing.- The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases.- Customer Relationship Management and Big Data Mining.- Performance Competition for ISCIFCM and Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.-PEI Models under Uncontrolled Circumstances.- Rough Set Model based Knowledge Acquisition of Market Movements from Economic Data.- Deep Neural Network Modeling for Big Data Weather Forecast.- Current Knowledge and Future Challenge for Visibility Forecasting by Computational Intelligence.- Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
