Computational Intelligence
Theoretical Advances and Advanced Applications
1st Edition
Published on 10. August 2020
XVI, 264 pages
978-3-11-067135-3 (ISBN)
Description
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 surveys of most recent theoretical approaches focusing on fuzzy systems, neurocomputing, and nature inspired algorithms. It also presents surveys of up-to-date research and application with special focus on fuzzy systems as well as on applications in life sciences and neuronal computing.
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01/2016
2nd Edition
De Gruyter Oldenbourg
€39.95
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Additional editions
Dinesh C.S. Bisht | Mangey Ram
Computational Intelligence
Theoretical Advances and Advanced Applications
Book
08/2020
1st Edition
De Gruyter
€169.95
Shipment within 7-9 days
Dinesh C.S. Bisht | Mangey Ram
Computational Intelligence
Theoretical Advances and Advanced Applications
E-Book
08/2020
1st Edition
De Gruyter
€169.95
Available for download
Persons
Dinesh C.S. Bisht
, Noida, India.
Mangey Ram
, Dehradun, India.
Content
- Intro
- 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
