Computational Intelligence : : Theoretical Advances and Advanced Applications / / ed. by Dinesh C.S. Bisht, Mangey Ram.

• Superior document: Title is part of eBook package: De Gruyter DG Ebook Package English 2020
• MitwirkendeR: Bakshi, Tuli,; Bhattacharjee, Chiranjib,; Bisht, Dinesh C. S.,; Bisht, Dinesh,; Chhibber, Divya,; Choudhury, Abhinav,; Das, B. K.,; Dasgupta, Nataraj,; Dutt, Varun,; Enneya, Nourddine,; Farhadinia, B.,; Goyal, Gunjan,; Gulyas, Balazs,; Herrmann, J. Michael,; Jain, Pankhuri,; Jena, Bibekananda,; Joyce, Thomas,; Kaushik, Shruti,; Khanna, Vandana,; Kumar Naik, Manoj,; Kumar Srivastava, Pankaj,; Kumar Tiwari, Anoop,; Kumar, Ajay H.,; Kumar, S. N.,; Laassiri, Jalal,; Lenin Fred, A.,; Mazumder, Ankita,; Natarajan, Sayee,; Padmanabhan, Parasuraman,; Pamučar, Dragan,; Panda, Rutuparna,; Pickett, Larry A.,; Price, Adam,; Sen, Dwaipayan,; Shanmugavadivu, P.,; Shanthi Rani, M. Mary,; Sinharay, Arindam,; Som, Tanmoy,; Wunnava, Aneesh,; Zettam, Manal,; Žižović, Mališa R.,
• HerausgeberIn: Bisht, Dinesh C.S. ,; Ram, Mangey,
• Place / Publishing House: Berlin ;, Boston : : De Gruyter, , [2020]; ©2020
• Year of Publication: 2020
• Language: English
• Series: De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences , 3
• Physical Description: 1 online resource (XVI, 264 p.)

Computational intelligence (CI) lies at the interface between engineering and computer science; control engineering, where problems are solved using computer-assisted methods. Thus, it can be regarded as an indispensable basis for all artificial intelligence (AI) activities. This book collects surve...

Table of Contents

• Frontmatter
• Acknowledgments
• Preface
• About the Editors
• Contents
• List of contributing authors
• Part I: Theoretical advances
• 1. Nature-inspired optimization algorithm and benchmark functions: a literature survey
• 2. Genetic algorithm: a metaheuristic approach of optimization
• 3. Ant colony optimization and reinforcement learning
• 4. Fuzzy informative evidence theory and application in the project selection problem
• 5. The fuzzy model for determining criteria weights based on level construction
• 6. Fuzzy transportation problems and variants
• 7. Hesitant fuzzy sets: distance, similarity and entropy measures
• 8. A prediction MapReduce-based TLBO-FLANN model for angiographic disease status value
• Part II: Advanced applications
• 9. Analysis of credit card fraud detection using fuzzy rough and intuitionistic fuzzy rough feature selection techniques
• 10. Evaluating single- and multi-headed neural architectures for time-series forecasting of healthcare expenditures
• 11. Optimization of oily wastewater treatment process using a neuro-fuzzy adaptive model
• 12. Deep learning based food image classification
• 13. Particle swarm optimization and differential evolution algorithms: application to solar photovoltaic cells
• 14. Multilevel thresholding using crow search optimization for medical images
• Index