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Artificial Intelligence in Forecasting
Forecasting deals with the uncertainty of the future. To be effective, forecasting models should be timely available, accurate, reliable, and compatible with existing database. Accurate projection of the future is of vital importance in supply chain management, inventory control, economic condition, technology, growth trend, social change, political change, business, weather forecasting, stock price prediction, earthquake prediction, etc. AI powered tools and techniques of forecasting play a major role in improving the projection accuracy. The software running AI forecasting models use machine learning to improve accuracy. The software can analyse the past data and can make better prediction about the future trends with higher accuracy and confidence that favours for making proper future planning and decision. In other words, accurate forecasting requires more than just the matching of models to historical data. The book covers the latest techniques used by managers in business today, discover the importance of forecasting and learn how it's accomplished. Readers will also be familiarised with the necessary skills to meet the increased demand for thoughtful and realistic forecasts.
Smart Power Systems
As the demand for electricity grows, the need for efficient and cleaner energy sources becomes increasingly critical. This book looks at the world of smart power systems, where artificial intelligence (AI) and the Internet of Things (IoT) are revolutionizing traditional power grids. This book covers a wide range of topics, starting with smart grid fundamentals, benefits, and deployment strategies. It explores power system models and the application of AI and IoT in power forecasting and the assembly of smart grids, the benefits and limitations of grid automation, and the use of machine-learning algorithms to identify equipment congestion. Efficient power distribution methods with AI-IoT and ...
Data-centric Approaches to Industrial Decisions
This book explores mathematical modeling, predictive analytics, and interdisciplinary tools in formulating, implementing, and evaluating industrial strategies. This book presents cutting-edge research that intersects advanced computational techniques with practical decision-making across industries. This edited book showcases a curated collection of peer-reviewed contributions from international scholars and practitioners, addressing the growing complexity of business decisions in the era of big data, AI, and digital transformation. From cyber-physical systems to sustainability analytics and business intelligence, each chapter provides a robust academic foundation while offering real-world implications for policymakers, managers, and researchers. With a focus on actionable insights, the book is a vital reference for operations research, analytics, and digital strategy professionals and an enriching resource for postgraduate and doctoral scholars across business and engineering disciplines.
