Nature-Inspired Algorithms for Big Data Frameworks

✍ Scribed by Hema Banati (editor), Shikha Mehta (editor), Parmeet Kaur (editor)

• Publisher: Engineering Science Reference
• Year: 2018
• Tongue: English
• Leaves: 436
• Series: Advances in Computational Intelligence and Robotics
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Dedications
Editorial Advisory Board
Table of Contents
Preface
Acknowledgment
Section 1: Nature-Inspired Algorithms for High Dimensions
1 Deep Learning for Big Data Analytics • Priti Srinivas Sajja, Rajendra Akerkar
2 Genetic Algorithm Based Pre-Processing Strategy for High Dimensional Micro-Array Gene Classification: Application of Nature Inspired Intelligence • Deepak Singh, Dilip Singh Sisodia, Pradeep Singh
3 Subspace Clustering of High Dimensional Data Using Differential Evolution • Parul Agarwal, Shikha Mehta
4 Nature Inspired Feature Selector for Effective Data Classification in Big Data Frameworks • Appavu Alias Balamurugan Subramanian
Section 2: Nature-Inspired Approaches for Complex Optimizations
5 Motion Planning of Non-Holonomic Wheeled Robots Using Modified Bat Algorithm • Abhishek Ghosh Roy, Pratyusha Rakshit
6 Application of Nature-Inspired Algorithms for Sensing Error Optimisation in Dynamic Environment • Sumitra Mukhopadhyay, Soumyadip Das
7 Wolf-Swarm Colony for Signature Gene Selection Using Weighted Objective Method • Prativa Agarwalla, Sumitra Mukhopadhyay
8 Scheduling Data Intensive Scientific Workflows in Cloud Environment Using Nature Inspired Algorithms • Shikha Mehta, Parmeet Kaur
9 PSO-Based Antenna Pattern Synthesis: A Paradigm for Secured Data Communications • Rathindra Nath Biswas, Anurup Saha, Swarup Kumar Mitra, Mrinal Kanti Naskar
10 Nature-Inspired Algorithms in Wireless Sensor Networks • Ajay Kaushik, S. Indu, Daya Gupta
11 Aircraft Aerodynamic Parameter Estimation Using Intelligent Estimation Algorithms • Abhishek Ghosh Roy, Naba Kumar Peyada
Section 3: Nature-Inspired Solutions for Web Analytics
12 Analysis of Multiplex Social Networks Using Nature-Inspired Algorithms • Ruchi Mittal, Netaji M. P. S. Bhatia
13 Pedagogical Software Agents for Personalized E-Learning Using Soft Computing Techniques • Mukta Goyal, Rajalakshmi Krishnamurthi
14 Graph and Neural Network-Based Intelligent Conversation System • Anuja Arora, Aman Srivastava, Shivam Bansal
15 Big Data Analytics Using Apache Hive to Analyze Health Data • Pavani Konagala
Compilation of References
About the Contributors
Index