Fuzzy Optimization Techniques in the Areas of Science and Management
CRC Press (Verlag)
978-1-032-34286-3 (ISBN)
This book helps to enhance the application of fuzzy logic optimization in the areas of science and engineering. It includes implementation and models and paradigms, such as path planning and routing design for different wireless networks, organization behavior strategies models, and so forth. It also:
Explains inventory control management, uncertainties management, loss minimization, game optimization, data analysis and prediction, different decision-making
system and management, and so forth
Describes applicability of fuzzy optimization techniques in areas of science and management
Resolves several issues based on uncertainty using member function
Helps map different problems based on mathematical models
Includes issues and problems based on linear and nonlinear optimizations
Focuses on management science such as manpower management and inventory planning
This book is aimed at researchers and graduate students in signal processing, power systems, systems and industrial engineering, and computer networks.
Santosh Kumar Das received his Ph.D. degree in Computer Science and Engineering from Indian Institute of Technology (ISM), Dhanbad, India, in 2018 and completed his M. Tech. degree in Computer Science and Engineering from Maulana Abul Kalam Azad University of Technology (erstwhile WBUT), West Bengal, India, in 2013. He has about to three years teaching experience as Assistant Professor at School of Computer Science and Engineering, National Institute of Science and Technology (Autonomous), Institute Park, Pallur Hills, Berhampur, Odisha, India. He is currently working as Assistant Professor at Department of Computer Science and Engineering, Sarala Birla University, Birla Knowledge City, P.O.-Mahilong, Purulia Road, Ranchi, India. He has more than eight years teaching experience. He has authored/edited of five books with Springer in series as Lecture Notes in Networks and Systems, Tracts in Nature-Inspired Computing and Studies in Computational Intelligence. He has contributed more than 35 research papers. His research interests mainly focus on Ad-hoc & Sensor Network, Artificial Intelligence, Soft Computing, and Mathematical modelling. His h-index is 16 with more than 700 citations. Google Scholar Profile: https://scholar.google.com/citations?user=AkQx5KoAAAAJ&hl=en Massimiliano Giacalone received his Ph.D. degree in “Computational Statistics and Applications” from the University of Naples “Federico II”, Department of Mathematics and Statistics. He received his graduate in “Statistics and Economics Sciences”, magna cum laude (Faculty of Economics-University of Palermo). He is currently “Researcher in Statistics” and teaching staff member of the Department of Economics and Statistics, University of Naples “Federico II”. He has contributed more than 100 research papers. His research area encompasses the following subjects: Multidimensional Data Analysis - Big Data for Social Statistics - Norm-p linear and nonlinear regression - Permutation Tests-Control Charts and Economic Statistics -Applications of Statistics in Medicine, in Justice and in Finance. Google Scholar Profile: https://scholar.google.com/citations?hl=en&user=O912O0MAAAAJ&view_op=list_works&sortby=pubdate
Section 1 Energy Resources Management 1. Routing Recovery Protocol for Wireless Sensor Network Based on PSO-ACO and Neural Network 2. Fuzzy Inference-Based Optimal Route-Selection Technique in Wireless Ad Hoc Network 3. Fuzzy-Based Mathematical Model for Optimizing Network Lifetime in MANET Section 2 Modelling and Aggregation 4. Game Theory–Based Conflicting Strategy Management Technique in Wireless Sensor Network 5. Cluster-Based Routing Protocol for WSN Using Fusion of Swarm Intelligence and Neural Network 6. Nonlinear Fuzzy Optimization Technique for WSN Based on Quadratic Programming Section 3 Data Analysis and Prediction 7. A Review Based on Prediction Analysis to Mitigate the Issues of COVID-19 8. Data Analysis and Prediction for WSN Based on Linear and Quadratic Optimization Techniques 9. Machine Learning-Based Data Analysis for Managing Challenges of COVID-19: A Survey 10. Fuzzy Geometric-Based Cost-Optimization Technique for Company
| Erscheinungsdatum | 28.09.2022 |
|---|---|
| Reihe/Serie | Computational Intelligence in Engineering Problem Solving |
| Zusatzinfo | 57 Tables, black and white; 27 Line drawings, black and white; 52 Halftones, black and white; 79 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 152 x 229 mm |
| Gewicht | 421 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-032-34286-2 / 1032342862 |
| ISBN-13 | 978-1-032-34286-3 / 9781032342863 |
| Zustand | Neuware |
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