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Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing (Hardcover, 1st ed. 2021) Loot Price: R4,582
Discovery Miles 45 820
Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing (Hardcover, 1st ed. 2021):...

Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing (Hardcover, 1st ed. 2021)

Simon James Fong, Richard C. Millham

Series: Springer Tracts in Nature-Inspired Computing

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Loot Price R4,582 Discovery Miles 45 820 | Repayment Terms: R429 pm x 12*

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This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.

General

Imprint: Springer Verlag, Singapore
Country of origin: Singapore
Series: Springer Tracts in Nature-Inspired Computing
Release date: August 2020
First published: 2021
Editors: Simon James Fong • Richard C. Millham
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 226
Edition: 1st ed. 2021
ISBN-13: 978-981-15-6694-3
Categories: Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 981-15-6694-1
Barcode: 9789811566943

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