Hybrid computational intelligence : research and applications
Author(s)
Bibliographic Information
Hybrid computational intelligence : research and applications
CRC Press, c2020
- : hardback
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Other editors: Václav Snášel, Indrajit Pan, Debashis De
Includes bibliographical references and index
Description and Table of Contents
Description
Hybrid computational intelligent techniques are efficient in dealing with the real-world problems encountered in engineering fields. The primary objective of this book is to provide an exhaustive introduction as well as review of the hybrid computational intelligent paradigm, with supportive case studies. In addition, it aims to provide a gallery of engineering applications where this computing paradigm can be effectively use. Finally, it focuses on the recent quantum inspired hybrid intelligence to develop intelligent solutions for the future. The book also incorporates video demonstrations of each application for better understanding of the subject matter.
Table of Contents
1 Nature-Inspired Algorithms: A Comprehensive Review. Essam H. Houssein, Mina Younan, and Aboul Ella Hassanie. 2 Hybrid Cartesian Genetic Programming Algorithms: A Review. Johnathan Melo Neto, Heder S. Bernardino, and Helio J.C. Barbosa. 3 Tuberculosis Detection from Conventional Sputum Smear Microscopic Images Using Machine Learning Techniques. Rani Oomman Panicker, Biju Soman, and M.K. Sabu. 4 Privacy towards GIS Based Intelligent Tourism Recommender System in Big Data Analytics. Abhaya Kumar Sahoo, Chittaranjan Pradhan, and Siddhartha Bhattacharyya. 5 Application of Artificial Neural Network: A Case Study of Biomedical Alloy.Amit Aherwar and Amar Patnaik. 6 Laws Energy Measure Based on Local Patterns for Texture Classification. Sonali Dash and Manas R. Senapati. 7 Analysis of BSE Sensex Using Statistical and Computational Tools. Soumya Chatterjee and Indranil Mukherjee. 8 Automatic Sheep Age Estimation Based on Active Contours without Edges. Aya Abdelhady, Aboul Ella Hassanien, and Aly Fahmy. 9 Diversity Matrix Based Performance Improvement for Ensemble Learning Approach.Rajdeep Chatterjee, Siddhartha Chatterjee, Ankita Datta, and Debarshi Kumar Sanyal.
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