Uncertainty, Optimization and Machine Learning with Applications (Mathematics for Sustainable Developments)

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Uncertainty, Optimization and Machine Learning with Applications (Mathematics for Sustainable Developments)

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  • 製本 Hardcover:ハードカバー版
  • 言語 ENG
  • 商品コード 9789819545575

Full 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.

Contents

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.

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