1st Edition
Hybrid Computational Intelligence Research and Applications
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.
1 Nature-Inspired Algorithms: A Comprehensive Review 1
Essam H. Houssein, Mina Younan, and Aboul Ella Hassanien
2 Hybrid Cartesian Genetic Programming Algorithms:
A Review 27
Johnathan Melo Neto, Heder S. Bernardino, and
Helio J.C. Barbosa
3 Tuberculosis Detection from Conventional Sputum Smear
Microscopic Images Using Machine Learning Techniques 63
Rani Oomman Panicker, Biju Soman, and M.K. Sabu
4 Privacy towards GIS Based Intelligent Tourism
Recommender System in Big Data Analytics 81
Abhaya Kumar Sahoo, Chittaranjan Pradhan, and Siddhartha
Bhattacharyya
5 Application of Artificial Neural Network: A Case Study
of Biomedical Alloy 101
Amit Aherwar and Amar Patnaik
6 Laws Energy Measure Based on Local Patterns for Texture
Classification 131
Sonali Dash and Manas R. Senapati
7 Analysis of BSE Sensex Using Statistical and Computational
Tools 153
Soumya Chatterjee and Indranil Mukherjee
8 Automatic Sheep Age Estimation Based on Active
Contours without Edges 177
Aya Abdelhady, Aboul Ella Hassanien, and Aly Fahmy
9 Diversity Matrix Based Performance Improvement for
Ensemble Learning Approach 195
Rajdeep Chatterjee, Siddhartha Chatterjee, Ankita Datta,
and Debarshi Kumar Sanyal
Biography
Siddhartha Bhattacharyya, Václav Snášel, Indrajit Pan, Debashis De
