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. Ed(S): Pedrycz, Witold; Chen, Shyi-Ming - Information Granularity, Big Data, and Computational Intelligence - 9783319082530 - V9783319082530
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Information Granularity, Big Data, and Computational Intelligence

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Description for Information Granularity, Big Data, and Computational Intelligence Hardback. Editor(s): Pedrycz, Witold; Chen, Shyi-Ming. Series: Studies in Big Data. Num Pages: 455 pages, 97 black & white illustrations, 26 colour illustrations, biography. BIC Classification: UF; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 25. Weight in Grams: 842.

The recent pursuits emerging in the realm of big data processing, interpretation, collection and organization have emerged in numerous sectors including business, industry and government organizations. Data sets such as customer transactions for a mega-retailer, weather monitoring, intelligence gathering, quickly outpace the capacities of traditional techniques and tools of data analysis. The 3V (volume, variability and velocity) challenges led to the emergence of new techniques and tools in data visualization, acquisition, and serialization. Soft Computing being regarded as a plethora of technologies of fuzzy sets (or Granular Computing), neurocomputing and evolutionary optimization brings forward a number of unique features that might ... Read more

This carefully edited volume provides the reader with an updated, in-depth material on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of big data architectures, analysis, and interpretation as well as data analytics. The book is aimed at a broad audience of researchers and practitioners including those active in various disciplines in which big data, their analysis and optimization are of genuine relevance. One focal point is the systematic exposure of the concepts, design methodology, and detailed algorithms. In general, the volume adheres to the top-down strategy starting with the concepts and motivation and then proceeding with the detailed design that materializes in specific algorithms and representative applications. The material is self-contained and provides the reader with all necessary prerequisites and augments some parts with a step-by-step explanation of more advanced concepts supported by a significant amount of illustrative numeric material and some application scenarios to motivate the reader and make someabstract concepts more tangible.

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Product Details

Format
Hardback
Publication date
2014
Publisher
Springer International Publishing AG Switzerland
Number of pages
455
Condition
New
Series
Studies in Big Data
Number of Pages
444
Place of Publication
Cham, Switzerland
ISBN
9783319082530
SKU
V9783319082530
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

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