Nature-Inspired Optimization Algorithms : : Recent Advances in Natural Computing and Biomedical Applications / / ed. by Aditya Khamparia, Ashish Khanna, Nhu Gia Nguyen, Bao Le Nguyen.

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, adaptiv...

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Bibliographic Details
Superior document:Title is part of eBook package: De Gruyter DG Ebook Package English 2021
MitwirkendeR:
HerausgeberIn:
Place / Publishing House:Berlin ;, Boston : : De Gruyter, , [2021]
©2021
Year of Publication:2021
Language:English
Series:Intelligent Biomedical Data Analysis , 4
Online Access:
Physical Description:1 online resource (XIV, 154 p.)
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Table of Contents:
  • Frontmatter
  • Preface
  • Contents
  • About the editors
  • List of contributors
  • 1 Selecting and assessing the importance of malware analysis methods for web-based biomedical services through fuzzy-based decision-making procedure
  • 2 A medical intelligent system for diagnosis of chronic kidney disease using adaptive neuro-fuzzy inference system
  • 3 Contrast enhancement approach for satellite images using hybrid fusion technique and artificial bee colony optimization
  • 4 Role of intelligent IoT applications in fog computing
  • 5 Energy-efficient routing employing neural networks along with vector-based pipeline in underwater wireless sensor networks
  • 6 A review of global optimization problems using meta-heuristic algorithm
  • 7 Secure indexing and storage of big data
  • 8 Genetic algorithm and normalized text feature based document classification
  • 9 Nature-inspired optimization techniques
  • Index