Nature-Inspired Algorithms for Big Data Frameworks

Nonfiction, Computers, Database Management, Data Processing, General Computing
Cover of the book Nature-Inspired Algorithms for Big Data Frameworks by , IGI Global
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9781522558545
Publisher: IGI Global Publication: September 28, 2018
Imprint: Engineering Science Reference Language: English
Author:
ISBN: 9781522558545
Publisher: IGI Global
Publication: September 28, 2018
Imprint: Engineering Science Reference
Language: English

As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.

More books from IGI Global

Cover of the book American Perspectives on Learning Communities and Opportunities in the Maker Movement by
Cover of the book Managerial Strategies for Business Sustainability During Turbulent Times by
Cover of the book Theoretical and Practical Advancements for Fuzzy System Integration by
Cover of the book Comprehensive Problem-Solving and Skill Development for Next-Generation Leaders by
Cover of the book Population Growth and Rapid Urbanization in the Developing World by
Cover of the book Decision Control, Management, and Support in Adaptive and Complex Systems by
Cover of the book Emerging Economic Models for Global Sustainability and Social Development by
Cover of the book Impact of Learning Analytics on Curriculum Design and Student Performance by
Cover of the book Innovative Approaches of Data Visualization and Visual Analytics by
Cover of the book Fostering Effective Student Communication in Online Graduate Courses by
Cover of the book Advanced Treatment Techniques for Industrial Wastewater by
Cover of the book Cases on Global Competencies for Educational Diplomacy in International Settings by
Cover of the book Handbook of Research on Workforce Diversity in a Global Society by
Cover of the book Examining the Potential for Response to Intervention (RTI) Delivery Models in Secondary Education by
Cover of the book Advanced Fuzzy Logic Approaches in Engineering Science by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy