Uncertainty in Computational Intelligence-Based Decision Making
- 1st Edition - September 16, 2024
- Imprint: Academic Press
- Editors: Ali Ahmadian, Soheil Salahshour, Valentina Emilia 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
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- 1 TOPSIS for the selection of the prediction model in forensic ink analysis
- Abstract
- Acknowledgment
- 1 Introduction
- 2 Methodology
- 3 Results and discussions
- 4 Conclusions
- References
- 2 Effectiveness of artificial intelligence in determining foot pathologies and designing insoles using plain radiograph and digital photograph
- Abstract
- 1 Introduction
- 2 Classification of foot types using AI
- 3 Designing insoles using AI
- 4 Framework of determining foot pathologies and designing insoles
- 5 Data collection
- 6 Data preparation and annotation
- 7 Model training and evaluation
- 8 Statistical analysis
- 9 Conclusion
- References
- 3 Outbound logistics business process modeling: Analytic perspective with BPMN 2.0
- Abstract
- 1 Logistics business process and information system
- 2 Business process modeling methods
- 3 Development of outbound logistics business process modeling
- 4 Conclusion
- References
- 4 Revolutionizing diabetic foot ulcer treatment prediction: Harnessing the power of artificial intelligence and transfer learning
- Abstract
- 1 Introduction
- 2 Medical image classification using AI
- 3 Framework of DFU treatment prediction
- 4 Conclusion
- References
- 5 A systematic review on personalized hybrid diet recommendations
- Abstract
- 1 Introduction
- 2 Review methodology
- 3 Overview of diet recommendations in MCDM
- 4 Conclusion
- References
- 6 Impact of number and type of criteria on ranking abnormality in MCDM techniques
- Abstract
- 1 Introduction
- 2 Major contribution
- 3 RA
- 4 HetNet
- 5 Discussion and findings
- 6 Conclusion
- References
- 7 Comparison between some methods in fuzzy linear regression
- Abstract
- 1 Introduction
- 2 Fuzzy arithmetic
- 3 Possibilistic regression (Tanaka et al.’s method)
- 4 The method of the least square median
- 5 Possibilistic regression method of Nasrabadi et al.
- 6 The goal programming approach in estimating the coefficients of Hassanpour et al. [20]
- References
- 8 Artificial intelligence and decision making in climate change studies: A review
- Abstract
- 1 Climate change: Impacts, risks
- 2 Decision making
- 3 AI
- 4 Conclusions
- References
- 9 Computational decision intelligence approaches for drought prediction: A review
- Abstract
- 1 Introduction
- 2 Drought: Types and indices
- 3 Computation intelligence approaches
- 4 The role of artificial neural networks
- 5 Conclusions
- References
- 10 A review of the applications of computational decision intelligence approaches in agrometeorology
- Abstract
- 1 Introduction
- 2 Agrometeorology
- 3 Fuzzy logic in agrometeorology
- 4 Machine learning in agrometeorology
- 5 Mathematical decision making
- 6 Conclusions
- References
- 11 A fuzzy logic design for self-driving vehicle to avoid obstacles
- Abstract
- 1 Introduction
- 2 Objective
- 3 Related works
- 4 Architecture
- 5 Self-driving vehicle sensors
- 6 Deep neural network
- 7 Fuzzy logic controller
- 8 Fuzzy logic controller for stationary obstacle
- 9 Fuzzy logic controller for moving obstacle
- 10 Development of environment
- 11 Conclusion and future work
- References
- 12 K-means clustering over distributed environment: A review
- Abstract
- 1 Introduction
- 2 K-means clustering
- 3 Comparison
- 4 Experimental result and discussion
- 5 Conclusion and future research scope
- References
- 13 Advanced frequent itemset mining algorithm (AFIM)
- Abstract
- 1 Introduction
- 2 Related work
- 3 Methodology
- 4 Experiment
- 5 Conclusion and future extensions
- References
- 14 TEAM: Trust evaluation and analysis of misbehavior in WSNs
- Abstract
- Acknowledgments
- 1 Introduction
- 2 Related work
- 3 Proposed lightweight trust model
- 4 Simulation and results discussion
- 5 Conclusion
- Conflicts of interest
- References
- 15 Computational intelligence in decision support: Scope and techniques
- Abstract
- 1 Introduction
- 2 Computational decision science: An overview
- 3 Techniques in computational decision making
- 4 Computational intelligence for decision support
- 5 Challenges in computational decision making
- 6 Comparative analysis of computational techniques
- 7 Conclusion
- References
- 16 Automatic parallelization for multicore architectures: Role, importance, and opportunities
- Abstract
- 1 Introduction
- 2 Loop level automatic parallelization
- 3 Methods of parallelization for loops
- 4 Different stages in automatic parallelization
- 5 Automatic parallelization techniques
- 6 Speculative parallelism to handle implicit threads
- 7 Importance of multicore architecture
- 8 Thread distribution techniques
- 9 Beneficial effect of automatic parallelism
- 10 Challenges and opportunities
- 11 Conclusions and open research issues
- References
- 17 Using tensor processing units to identify the relationship between hypothesis and premise: A case of natural language inference problem
- Abstract
- 1 Introduction
- 2 Materials
- 3 Methodology
- 4 Results and discussion
- 5 Conclusions and future scope
- Conflicts of interest
- Data availability
- References
- 18 Secure and cost-effective key management scheme for the Internet of Things-supported WSN
- Abstract
- 1 Introduction
- 2 Multicasting message scheme
- 3 Group key management
- 4 Parameters of group key management
- 5 Designing a secure and cost-effective key management scheme
- 6 Robust mobility management scheme
- 7 Application scenario and case study
- 8 Conclusion and future work
- References
- 19 A deep learning-based integrated voice assistance system for partially disabled people
- Abstract
- 1 Introduction
- 2 Literature survey
- 3 Material
- 4 Methodology used
- 5 Results
- 6 Conclusions
- References
- Index
- Edition: 1
- Published: September 16, 2024
- No. of pages (Paperback): 338
- No. of pages (eBook): 350
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780443214752
- eBook ISBN: 9780443214769
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Ali Ahmadian
Dr. Ali Ahmadian is a senior research scientist the Mediterranea University of Reggio Calabria, Italy and an Associate Fellow Researcher at the Institute of IR 4.0, The National University of Malaysia. As an active researcher, he is dedicated to research in applied mathematics. He received his Ph.D. in early of 2014 as the best postgraduate student from Universiti Putra Malaysia (UPM). After his Ph.D. He took a postdoctoral fellowship at same university as part of the numerical analysis research group and at the same time joint to the University of Malaya as an Associate Researcher. He was promoted as a Fellow Researcher on December 2017 in UPM. In 2019, he joined the National University of Malaysia as a senior lecturer where he currently works in the Institute of IR 4.0. In general, 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. He is a member of editorial board in Sustainable Computing: Informatics and Systems, Soft Computing, Journal of control and Decision, Progress in Fractional Differentiation and Applications (Natural Sciences Publishing) and Mathematical Problems in Engineering (Hindawi) and lead guest editor of special issues in more than 50 international journals from Elsevier, Springer, Wiley and so on. He is an author of more than 350 research papers published in as Nature, IEEE, Elsevier, Springer, Wiley and etc. He is an author and editor of four books published and in process in CRC Press and Elsevier, respectively. He also presented his research works in 38 international conferences held in Canada, Serbia, China, Turkey, Malaysia and UAE. He also received Premio Anassilaos Giovani Award for his achievement in art, culture, economics and science from Italy in November 2021.
Affiliations and expertise
Decisions Lab, 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
Faculty of Engineering and Natural Sciences, Istanbul Okan University, Istanbul, TurkeyVB
Valentina Emilia 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 Scientists, RomaniaDB
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, RomaniaRead Uncertainty in Computational Intelligence-Based Decision Making on ScienceDirect