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Nature-Inspired Optimization Algorithms and Soft Computing - (Computing and Networks) (Hardcover)

Name: Nature-Inspired Optimization Algorithms and Soft Computing - (Computing and Networks) (Hardcover)
Brand: Institution of Engineering & Technology
SKU: 1012623605
Price: 107.99 USD
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Details

Highlights

We have witnessed an explosion of research activity around nature-inspired computing and bio-inspired optimization techniques, which can provide powerful tools for solving learning problems and data analysis in very large data sets.
Author(s): Rajeev Arya & Sangeeta Singh & Maheshwari P Singh & Brijesh R Iyer & Venkat N Gudivada
298 Pages
Computers + Internet, General
Series Name: Computing and Networks

Description

About the Book

This edited book reviews the intertwining disciplines of nature-inspired optimization algorithms and bio-inspired soft-computing for real world applications, with the interaction between metaheuristics with complex systems. The authors present methods and techniques in IoT, image processing, smart manufacturing and healthcare.

Book Synopsis

We have witnessed an explosion of research activity around nature-inspired computing and bio-inspired optimization techniques, which can provide powerful tools for solving learning problems and data analysis in very large data sets. To design and implement optimization algorithms, several methods are used that bring superior performance. However, in some applications, the search space increases exponentially with the problem size. To overcome these limitations and to solve efficiently large scale combinatorial and highly nonlinear optimization problems, more flexible and adaptable algorithms are necessary.

Nature-inspired computing is oriented towards the application of outstanding information-processing aptitudes of the natural realm to the computational domain. The discipline of nature-inspired optimization algorithms is a major field of computational intelligence, soft computing and optimization. Metaheuristic search algorithms with population-based frameworks are capable of handling optimization in high-dimensional real-world problems for several domains including imaging, IoT, smart manufacturing, and healthcare. The integration of intelligence with smart technology enhances accuracy and efficiency. Smart devices and systems are revolutionizing the world by linking innovative thinking with innovative action and innovative implementation.

The aim of this edited book is to review the intertwining disciplines of nature-inspired computing and bio-inspired soft-computing (BISC) and their applications to real world challenges. The contributors cover the interaction between metaheuristics, such as evolutionary algorithms and swarm intelligence, with complex systems. They explain how to better handle different kinds of uncertainties in real-life problems using state-of-art of machine learning algorithms. They also explore future research perspectives to bridge the gap between theory and real-life day-to-day challenges for diverse domains of engineering.

The book will offer valuable insights to researchers and scientists from academia and industry in ICTs, IT and computer science, data science, AI and machine learning, swarm intelligence and complex systems. It is also a useful resource for professionals in related fields, and for advanced students with an interest in optimization and IoT applications.

Specifications

Dimensions (Overall): 9.21 Inches (H) x 6.14 Inches (W) x .69 Inches (D)

Weight: 1.31 Pounds

Suggested Age: 22 Years and Up

Number of Pages: 298

Genre: Computers + Internet

Sub-Genre: General

Series Title: Computing and Networks

Publisher: Institution of Engineering & Technology

Format: Hardcover

Author: Rajeev Arya & Sangeeta Singh & Maheshwari P Singh & Brijesh R Iyer & Venkat N Gudivada

Language: English

Street Date: October 17, 2023

TCIN: 1012623605

UPC: 9781839535161

Item Number (DPCI): 247-56-0664

Origin: Made in the USA or Imported

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Shipping details

Estimated ship dimensions: 0.69 inches length x 6.14 inches width x 9.21 inches height

Estimated ship weight: 1.31 pounds

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