Nature-Inspired Optimization Algorithms: Recent Advances in Natural Computing and Biomedical Applications

by Aditya Khamparia (Editor), Ashish Khanna (Editor), Nhu Gia Nguyen (Editor), Bao Le Nguyen (Editor)

Overview

This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems.

Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications.

Tentative Table of Contents/Topic Coverage:　

- Neural Computation

- Evolutionary Computing Methods

- Neuroscience driven AI Inspired Algorithms

- Biological System based algorithms

- Hybrid and Intelligent Computing Algorithms

- Application of Natural Computing

- Review and State of art analysis of Optimization algorithms

- Molecular and Quantum computing applications

- Swarm Intelligence

- Population based algorithm and other optimizations

Product Details

ISBN-13:	9783110676068
Publisher:	De Gruyter
Publication date:	02/08/2021
Series:	Intelligent Biomedical Data Analysis , #4
Pages:	168
Product dimensions:	6.69(w) x 9.45(h) x (d)
Age Range:	18 Years

About the Author

A. Khamparia, Lovely Professional Univ.; A. Khanna, M. Agrasen Inst. of Techn., India; N. Nhu, B. Nguyen, Duy Tan University, Vietnam.

Table of Contents

Preface v

About the editors xi

List of contributors xiii

1 Selecting and assessing the importance of malware analysis methods for web-based biomedical services through fuzzy-based decision-making procedure Abhishek Kumar Pandey Ashutosh Tripathi Alka Agrawal Rajeev Kumar Raees Ahmad Khan 1

2 A medical intelligent system for diagnosis of chronic kidney disease using adaptive neuro-fuzzy inference system Jimmy Singla Balwinder Kaur 19

3 Contrast enhancement approach for satellite images using hybrid fusion technique and artificial bee colony optimization Rahul Malik Sagar Pande Bharat Bhushan Aditya Khamparia 33

4 Role of intelligent IoT applications in fog computing Gunturu Harika Arun Malik Isha Batra 55

5 Energy-efficient routing employing neural networks along with vector-based pipeline in underwater wireless sensor networks Reeta Bhardwaj Harpreet Kaur Rajeev Kumar 71

6 A review of global optimization problems using meta-heuristic algorithm D. K. Mishra Vikas Shinde 87

7 Secure indexing and storage of big data Poonam Kumari Amit Kumar Mishra Vivek Sharma Ramakant Bhardwaj 107

8 Genetic algorithm and normalized text feature based document classification Vishal Sahu Amit Kumar Mishra Vivek Sharma Ramakant Bhardwaj 123

9 Nature-inspired optimization techniques Pratyush Shukla Sanjay Kumar Singh Aditya Khamparia Anjali Goyal 137

Index 153