Uncertainty in Computational Intelligence-Based Decision Making
- 1st Edition - September 27, 2024
- Editors: Ali Ahmadian, Soheil Salahshour, Valentina Emila Balas, Dumitru Baleanu
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 1 4 7 5 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 1 4 7 6 - 9
Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificia… Read more
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Request a sales quoteUncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others.
The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science.
- Provides readers a thorough understanding of the uncertainty that arises in artificial intelligence (AI), computational intelligence (CI) paradigms, and algorithms
- Encourages readers to put concepts into practice and solve complex real-world problems using CI development frameworks like decision support systems and visual decision design
- Provides a comprehensive overview of the techniques used in computational intelligence, uncertainty, and decision
Graduate students, professors, researchers, and professionals in the fields of computational and artificial intelligence
Section 1. Uncertainty
1. Data Analytics Streaming for Data Lakes
2. Supply Chain Management Problem Modelling in Hesitant Fuzzy Environment
3. Impact of Number and Type of Criteria on Ranking Abnormality in MCDM Techniques
4. Fuzzy Approach for the LEACH Protocol for Real Time Applications
5. Application of Intuitionistic fuzzy TOPSIS for Cloud Service Selection Problem
6. Role of Uncertainty in Artificial Intelligence and Machine Learning
7. On the Study of the System of Uncertain Linear Differential Equations Under Neutrosophic Sense of Uncertainty
8. A Fuzzy Logic Design for Self-Driving Vehicle to Avoid Obstacles
Section 2. Computational Techniques
10. Soft Computing: A Systematic Review
11. K-Means Clustering Over Distributed Environment: A Review
12. Using TOPSIS to Select the Best Prediction Model Constructed Using Partial Least Squares-Discriminant Analysis (PLS-DA) Algorithms and Infrared Spectra: A Forensic Case Study
13. A Study on Blockchain-Based Security in UAV Fog Computing Networks
14. Advanced Frequent Itemsets Mining Algorithm (AFIM)
15. Bayesian Regularization Approach to Train Ann: An Application in Prediction of Air Temperature
16. SMS Spam Classification Using Machine Learning Techniques
17. Computational Intelligence in Decision Support: Scope and Techniques
Section 3. Decision Intelligence
18. A Review of Computational Decision Intelligence Tools in Climatology
19. Computational Decision Intelligence Approaches for Drought Prediction: A Review
20. TEAM: Trust Evaluation and Analysis of Misbehaviors in WSNs
21. Automatic Parallelization for Multicore Architectures: Role, Importance and Opportunities
22. Gradient Boosting Decision Tree Model for Estimating and Localize Covid-19 Abnormalities on Chest Radiographs
23. A Personalised Hybrid Diet Recommender Systems
24. Artificial Intelligence Enabled Knowledge Health Engine for Retrieval Based Chatbots in Healthcare
25. Secure and Cost-Effective Key Management scheme for the Internet of Things Supported WSN
1. Data Analytics Streaming for Data Lakes
2. Supply Chain Management Problem Modelling in Hesitant Fuzzy Environment
3. Impact of Number and Type of Criteria on Ranking Abnormality in MCDM Techniques
4. Fuzzy Approach for the LEACH Protocol for Real Time Applications
5. Application of Intuitionistic fuzzy TOPSIS for Cloud Service Selection Problem
6. Role of Uncertainty in Artificial Intelligence and Machine Learning
7. On the Study of the System of Uncertain Linear Differential Equations Under Neutrosophic Sense of Uncertainty
8. A Fuzzy Logic Design for Self-Driving Vehicle to Avoid Obstacles
Section 2. Computational Techniques
10. Soft Computing: A Systematic Review
11. K-Means Clustering Over Distributed Environment: A Review
12. Using TOPSIS to Select the Best Prediction Model Constructed Using Partial Least Squares-Discriminant Analysis (PLS-DA) Algorithms and Infrared Spectra: A Forensic Case Study
13. A Study on Blockchain-Based Security in UAV Fog Computing Networks
14. Advanced Frequent Itemsets Mining Algorithm (AFIM)
15. Bayesian Regularization Approach to Train Ann: An Application in Prediction of Air Temperature
16. SMS Spam Classification Using Machine Learning Techniques
17. Computational Intelligence in Decision Support: Scope and Techniques
Section 3. Decision Intelligence
18. A Review of Computational Decision Intelligence Tools in Climatology
19. Computational Decision Intelligence Approaches for Drought Prediction: A Review
20. TEAM: Trust Evaluation and Analysis of Misbehaviors in WSNs
21. Automatic Parallelization for Multicore Architectures: Role, Importance and Opportunities
22. Gradient Boosting Decision Tree Model for Estimating and Localize Covid-19 Abnormalities on Chest Radiographs
23. A Personalised Hybrid Diet Recommender Systems
24. Artificial Intelligence Enabled Knowledge Health Engine for Retrieval Based Chatbots in Healthcare
25. Secure and Cost-Effective Key Management scheme for the Internet of Things Supported WSN
- No. of pages: 350
- Language: English
- Edition: 1
- Published: September 27, 2024
- Imprint: Academic Press
- Paperback ISBN: 9780443214752
AA
Ali Ahmadian
Dr Ali Ahmadian is an adjunct professor at the Kean University - Wenzhou Campus, Associate Researcher at the Mediterranea University of Reggio Calabria, Italy and an Associate Fellow Researcher at the Institute of IR 4.0, The National University of Malaysia. His primary mathematical focus is the development of computational methods and models for problems arising in computer science, biology, physics, and engineering under fuzzy and fractional calculus (FC); in this context, he has worked on projects related to nano-communication networks, drug delivery systems, acid hydrolysis in palm oil frond, and carbon nanotubes dynamics, nanofluids, viscosity, AI and etc. Dr Ahmadian is an author of more than 300 research papers published in journals such as Nature, together with journals published by the IEEE, Elsevier, Springer and Wiley
Affiliations and expertise
Mediterranea University of Reggio Calabria, ItalySS
Soheil Salahshour
Soheil Salahshour has, since 2012, been a University Professor with the Department of Mathematics in different universities, and recently moved to the Istanbul Okan University. His research interests include fractional models and Calculus, Fuzzy expert systems, evolutionary algorithms, optical soliton solutions, data science and big data applications
Affiliations and expertise
Bahcesehir University, Istanbul, TurkeyVB
Valentina Emila Balas
Valentina E. Balas is a Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad, Romania. She holds a PhD Cum Laude, in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is the author of more than 350 research papers. Her research interests are in intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, modeling, and simulation. She is a member of the editorial boards of several national and international journals and evaluator expert for national, international projects, and PhD thesis. Dr. Balas is the Director of Intelligent Systems Research Centre and Director of the Department of International Relations, Programs, and Projects in Aurel Vlaicu University of Arad. She is the recipient of the "Tudor Tanasescu" Prize from the Romanian Academy for contributions in the field of soft computing methods (2019).
Affiliations and expertise
Professor, Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad, Romania, and Academy of Romanian ScientistsDB
Dumitru Baleanu
Dumitru Baleanu is a full professor at the Institute of Space Sciences, Romania. Fractional dynamics and its applications, fractional differential equations, discrete mathematics, dynamic systems on time scales, the wavelet method and its applications, quantization of the systems with constraints, the Hamilton-Jacobi formalism, and geometries admitting generic and non-generic symmetries are among Dumitru's research interests. He has edited five books and published more than 1400 papers. He serves on several journals' editorial boards. With more than 30000 citations, Dumitru has served as a referee for more than 200 journals. He was included in the 2015–2020 Thompson Reuter list of the top 1% of highly cited researchers.
Affiliations and expertise
Full Professor, Institute of Space Sciences, Magurele-Bucharest, Romania