Balamurugan S., Jain A., Sharma S., Goyal D., Duggal S., Sharma S. (eds.) Nature-Inspired Algorithms and Applications

Scrivener Publishing, 2022. — 633 p. — (Artificial Intelligence and Soft Computing for Industrial Transformation). — ISBN 978-1-119-68166-3.The purpose of designing this book is to portray certain practical applications of nature-inspired computation in machine learning for the better understanding of the world around us. The focus is to portray and present recent developments in the areas where nature- inspired algorithms are specifically designed and applied to solve complex real-world problems in data analytics and pattern recognition, by means of domain-specific solutions. Various nature-inspired algorithms and their multidisciplinary applications (in mechanical engineering, electrical engineering, machine learning, image processing, data mining and wireless network domains are detailed, which will make this book a handy reference guide.Introduction to Nature-Inspired Computing
Applications of Hybridized Algorithms and Novel Algorithms in the Field of Machine Learning
Efficiency of Finding Best Solutions Through Ant Colony Optimization (ACO) Technique
A Hybrid Bat-Genetic Algorithm–Based Novel Optimal Wavelet Filter for Compression of Image Data
A Swarm Robot for Harvesting a Paddy Field
Firefly Algorithm
The Comprehensive Review for Biobased FPA Algorithm
Nature-Inspired Computation in Data Mining
Optimization Techniques for Removing Noise in Digital Medical Images
Performance Analysis of Nature-Inspired Algorithms in Breast Cancer Diagnosis
Applications of Cuckoo Search Algorithm for Optimization Problem
Mapping of Real-World Problems to Nature-Inspired Algorithm Using Goal-Based Classification and TRIZ