0
Your cart

Your cart is empty

Browse All Departments
  • All Departments
Price
  • R2,500 - R5,000 (1)
  • R5,000 - R10,000 (1)
  • -
Status
Brand

Showing 1 - 2 of 2 matches in All Departments

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
R4,924 Discovery Miles 49 240 Ships in 12 - 19 working days

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.

Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing (Paperback, 1st ed. 2021):... Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing (Paperback, 1st ed. 2021)
Simon James Fong, Richard C. Millham
R5,069 Discovery Miles 50 690 Ships in 10 - 15 working days

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.

Free Delivery
Pinterest Twitter Facebook Google+
You may like...
Unicorns & Other Magical Horses: 4 in 1…
Rae Ritchie Game R282 Discovery Miles 2 820
Awful Disclosures of Maria Monk - as…
Maria Monk Paperback R490 Discovery Miles 4 900
The Moth Presents: A Game of…
The Moth Cards R449 R393 Discovery Miles 3 930
Cristiano Ronaldo CR7 Game On Gift Set…
R527 Discovery Miles 5 270
Black And White Bioscope - Making Movies…
Neil Parsons Hardcover R339 Discovery Miles 3 390
SoccerStarz - Dimitri Payet Figurines…
R309 Discovery Miles 3 090
The Intelligent Movement Machine - An…
Michael Graziano Hardcover R3,088 Discovery Miles 30 880
Normativity, Meaning, and the Promise of…
Matthew Burch, Jack Marsh, … Paperback R1,426 Discovery Miles 14 260
Janesplains - A Compendium of Jane…
Jane Austen Hardcover R399 R364 Discovery Miles 3 640
Martin Heidegger and the Truth About the…
Friedrich-Wilhelm Von Herrmann, Francesco Alfieri Hardcover R2,678 Discovery Miles 26 780

 

Partners