Update cookies preferences

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

Edited by , Edited by , Edited by , Edited by
  • Format: Hardback, 168 pages, height x width: 240x170 mm, weight: 421 g, 29 Illustrations, color; 20 Tables, black and white; 25 Illustrations, black and white
  • Series: Intelligent Biomedical Data Analysis
  • Pub. Date: 08-Feb-2021
  • Publisher: De Gruyter
  • ISBN-10: 3110676060
  • ISBN-13: 9783110676068
  • Hardback
  • Price: 166,25 €
  • This book is not in stock. Book will arrive in about 2-4 weeks. Please allow another 2 weeks for shipping outside Estonia.
  • Quantity:
  • Add to basket
  • Delivery time 4-6 weeks
  • Add to Wishlist
  • Format: Hardback, 168 pages, height x width: 240x170 mm, weight: 421 g, 29 Illustrations, color; 20 Tables, black and white; 25 Illustrations, black and white
  • Series: Intelligent Biomedical Data Analysis
  • Pub. Date: 08-Feb-2021
  • Publisher: De Gruyter
  • ISBN-10: 3110676060
  • ISBN-13: 9783110676068
Computer scientists in India provide a detailed understanding of natural computing with distinct optimization algorithms, and demonstrate applications in the fields of computer science and medicine. Their topics include a medical intelligent system for the diagnosis of chronic kidney disease using an adaptive neuro-fuzzy inference system, an approach to enhancing the contrast of satellite images using a hybrid fusion technique and artificial bee colony optimization, the role of intelligent Internet of Things applications in fog computing, and secure indexing and storage of big data. Annotation ©2021 Ringgold, Inc., Portland, OR (protoview.com)

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

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