Uncertainty, Optimization and Machine Learning with Applications
Description
This book is a collection of select chapters on topics related to uncertainty, optimization techniques and machine learning applications, emphasizing applications that directly address topics related to five SDG goals:
SDG 3 (Good Health and Well-Being); SDG 7 (Affordable and Clean Energy); SDG 9 (Industry, Innovation and Infrastructure); SDG 12 (Responsible Consumption and Production); SDG 13 (Climate Action).The book studies the intricate landscape of these converging SDG fields. It is designed to facilitate a deeper understanding of the complexities involved in decision-making, risk management and predictive analysis in uncertain environments. The book serves as a comprehensive reference for researchers, practitioners and students, providing tools and insights to address real-world challenges through cutting-edge approaches in uncertainty, optimization and machine learning. Contents of the book are divided into seven parts:
Part 1: Advanced Mathematical Techniques. It offers foundational methods, including solidarity network allocation rules and applications of hidden Markov models in genomic analysis, setting the groundwork for advanced applications in diverse industries.
Part 2: Risk Assessment and Decision-Making Techniques. It addresses occupational risks, consumer behaviour in green product purchasing and optimal strategies in high-risk industries through refined decision-making models.
Part 3: Financial Analysis and Predictive Modelling. It helps readers explore anomaly detection in cryptocurrency markets and portfolio selection using genetic algorithms, as well as advanced probabilistic models that enhance predictive accuracy for financial and healthcare applications.
Part 4: Portfolio Optimization. It discusses the Markowitz portfolio optimization with beta weighting based on market trends. Evolutionary computation for portfolio optimization for Indian market and a comparison of meta-heuristic techniques for portfolio optimization has also been presented.
Part 5: Optimization and Inventory Management. It focuses on innovative inventory policies that account for factors like deteriorating demand and carbon emissions, incorporating fuzzy group decision-making to address sustainability.
Part 6: Renewable Energy and Environmental Management. It underscores sustainable practices through multi-attribute decision-making frameworks, examining the impact of government subsidies on green supply chains and optimizing renewable energy projects.
Part 7: Artificial Intelligence and Machine Learning Applications. It showcases AI's transformative impact, from algorithmic trading to advancements in healthcare and construction. Topics like deep learning in medical imaging and AI-driven portfolio optimization highlight the growing potential of AI across domains.
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Persons
Dr. Ranjan Kumar Jana
is currently an Associate Professor of Mathematics at the Sardar Vallabhbhai National Institute of Technology, Surat, India. He earned his M.Sc. and Ph.D. in Mathematics, later completed post-doctoral studies at the University of Illinois at Urbana-Champaign, USA by availing Indo-US Research Fellowship Award. Dr. Jana specializes in the field of special functions, integral transforms, operations research, and data assimilation, with additional interests in fractional calculus, numerical weather prediction, and Ramanujan's mathematics. With over 19 years of teaching experience and 22 years of research experience, he has published 89 research articles, including 63 journal articles, 10 conference proceedings, 11 book chapters, 2 technical reports and 3 books. He has completed six funded research projects totalling INR 130 lac, supported by SERB, CSIR, ISRO, DST, and SVNIT. Dr. Jana has successfully supervised one postdoctoral researcher, 10 Ph.D. scholars, and is currently guiding 11 additional Ph.D. students. He has also supervised 37 Master's dissertations, 15 summer internships, and several other student projects. An active contributor to academic conferences, he has presented at 75 events worldwide and regularly reviews for scientific journals in his field of expertise.
Dr. Laxminarayan Sahoo
is currently an Associate Professor of Computer and Information Science, Raiganj University, Raiganj, India. He obtained his M.Sc. from Vidyasagar University, India, and his Ph.D. from the University of Burdwan, India. He has received MHRD fellowship from Govt. of India during his M. Tech. course at ISM, Dhanbad, India, and received Prof. M.N. Gopalan Award for Best Ph.D. thesis in Operations Research from Operational Research Society of India (ORSI). Dr. Sahoo has successfully guided four research scholars for Ph.D. degree and four students continuing Ph.D. degree and has published more than 80 articles in international and national journals. He has also successfully completed one UGC minor research project. He is a reviewer of several international journals and an academic editor of International Journal "Mathematical Problems in Engineering," Hindawi Publication.
Dr. Nabendu Sen
presently working as Professor & Head, Department of Mathematics, Assam University, Silchar. He did his M.Sc. and Ph.D. from Assam University, Silchar under the supervision of Prof. Tanmoy Som who is now Professor in the Dept of Applied Mathematics, IIT(BHU), Varanasi- 221005. Prior to join in Department of Mathematics, AUS, he served as a lecturer of Mathematics in S.D Jain Girls college, Dimapur, Nagaland. He taught Mathematics in School of Technology, Assam University, Silchar. He was visiting lecturer in the Dept of Computer science, Assam University, Silchar. Dr. Sen is associated with various academic societies. He has published 44 research papers including two book chapters. Under his supervision three students have completed Ph.D, one M.Phil in Mathematics and three more students are registered for PhD(Mathematics) in the field of Optimization. Apart from these, Dr Sen has done some research works in collaboration with Professors from University of Delhi, University of Burdwan, University of Maryland.
Content
Chapter 1 The Weighted Myerson value for Network games.- Chapter 2 Weighted Gaussian fuzzy twin support vector machine with its application in handwritten digit classification.- Chapter 3Single Unit System with Preventive Maintenance, Standby, and Degradation.- Chapter 4 Validation of Refined Human Decision Making model with Intermediate Prediction.- Chapter 5 On Generalizations of Convex and Related Fuzzy Mappings.- Chapter 6 s-Regularity and s-Normality in Soft Bitopological Spaces.- Chapter 7 Predictive Anomaly Modelling in Bitcoin: Integrating Machine Learning with Technical Indicators.- Chapter 8 Advanced Probabilistic Techniques for Optimizing Predictive Models.- Chapter 9 Unveiling Hidden Associations in Healthcare Transactions through Market Basket Analysis.- Chapter 10 Predictive Analytics for Web Traffic: A Comparative Analysis of Time Series Models.- Chapter 11 Impact of Different Resolution Initial Data in Weather Research and Forecast Model.- Chapter 12 Markowitz Portfolio Optimization with Beta Weighting Based on Market Trends.- Chapter 13 Evolutionary Computation for Portfolio Optimization: Indian Market Insights.- Chapter 14 Portfolio Optimization: A Comparison of Meta-heuristic Techniques.- Chapter 15 Mathematical Metrics in Mutual Funds: A Comparative Analysis of Small Cap, Mid Cap and Large Cap Mutual Funds using PowerBI.- Chapter 16 An optimal two-warehouse policy for deteriorating inventory items with time-proportional demand under the conditions of permissible delay in payments.- Chapter 17 A Modified MABAC Technique for Interval-valued Picture Fuzzy Group Decision Making.- Chapter 18 Inventory Model with Price-, Stock-, and Emission-Dependent Demand under the Controllable Carbon Emission and Trade Credit Period.- Chapter 19 Solution of an Entropy-Based Optimization Model with Discounted Costs under Two-Fold Uncertainty.- Chapter 20 Pricing, Quantity and Shortages Decisions for Imperfect Production System, Reworking, Scrap, Optimization profit with Price-Sensitive Demand - in third order equation.- Chapter 21 Inventory model for deteriorating items with ramp-type demand under advance payment policy.- Chapter 22 Optimizing renewable energy projects with Pythagorean Fuzzy Multi-attribute Decision Making.- Chapter23 Analysis of Government subsidy in a dynamic green supply chain with revenue-sharing contract.- Chapter 24 Applications of Artificial Intelligence on Construction Management and Block Technology: A Study on Economic Development and Sustainable Practices.- Chapter 25Advanced Techniques in Machine Learning on Healthcare.