Engineering Applications of AI for Demand Forecasting

Foreword

Preface

List of Abbreviations

AI-Driven Demand Forecasting in Industry 4.0: Techniques, Applications, and Future Trends

Kushagra Agrawal and Polat Goktas

AI Engineering for Meeting the Demand of Open-Source Cyber Analytics

Fahim K Sufi

Application of AI for Anomaly Detection and Failure Prediction to Optimize Cost of Service

Debabrata Bera, Bhaskar Roy and Ankan Pattanayak

Generative AI Based Demand Forecasting for Third-Party Logistics

M. Kmiecik

Demand Forecasting for Sustainable Supply Chain Management Leveraging AI

Izabela Rojek and Dariusz Mikołajewski

Demand Forecasting for AI in Supply Chain Management

Harika Rajashekaraiah, Noor Sakina, Ajith Pulinchuvattil Arun, Praveen Kumar Gupta and Thippareddy

Artificial Intelligence Based Alternate Energy Demand Forecasting Incorporating Weather Data Analysis

Pratapa Raju Moola, Gopi Krishna Pasam, Praveen N and Sami Al Ghnimi

Electricity Demand Forecasting during Special Events Using AI

Oscar Trull, J. Carlos García-Díaz and A. Peiró-Signes

Predicting Peak Energy Demand Using Machine Learning Techniques for Efficient Electricity Supply Management

Imrus Salehin, Nazmul Huda Badhon, Md. Tomal Ahmed Sajib, Md. Sakibul Hassan Rifat and Nazmun Nessa Moon

AI-based Electrical Load Forecasting for Residential Sector Using Smart Meter Data

Barkha Parkash, Tek Tjing Lie, Weihua Li and Shafiqur Rahman Tito

Prosumer Electricity Demand Forecasting Using Artificial Intelligence-based Algorithms Incorporating Meteorological Data

Gülizar Gizem Tolun, Ömer Can Tolun and Kasım Zor

Index

Biography

Dr. Bhargav Appasani received the Ph.D. (Engg.) degree from Birla Institute of Technology, Mesra, India. He is currently an Associate Professor with the School of Electronics Engineering, KIIT University, Bhubaneswar, India. He has published more than 160 articles in international journals and conference proceedings. He has also published six book chapters with Springer and Elsevier. He has authored one book and has edited three books. He also has a patent filed to his credit. He is an academic editor of the Journal of Electrical and Computer Engineering (Wiley) and reviewer for IEEE Transactions on Smart Grid, IEEE Transactions on Antennas and Propagation, and IEEE Access. Dr. Appasani has taught many courses such as machine learning, data structure algorithm, microwave, control system, etc. for several years.

Dr. Amitkumar Vidyakant Jha received M.Tech degree from Indian Institute of Industrial Technology Guwahati, India and Ph.D. degree from Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India. He works as an associate professor at the KIIT. He has authored more than 60 articles in international journals, and conference proceedings. He has also authored 4 book chapters published by Springer and Elsevier. He has also edited two books which have been published by Nova Science and Taylor & Francis. To his credit, he has 4 patents. He has been honored with various awards including Best paper award in IEEE ECAI conference, Pitesti, Romania, Best paper award in IEEE CEES, Tokyo, Japan, Best Paper Award in IEEE STPEC 2023, KIIT University, India. He serves also as an editor to Scientific Reports journal of Springer Nature portfolio. He is an active reviewer of many international journals from the portfolio of IEEE, Springer, Elsevier, Wiley, Frontier, IOP, etc. Dr. Jha has vast teaching experience for many core engineering subjects such as data communication and networking, computer networks, data structure & algorithms, wireless sensor networks, digital system design, etc. He is a member of various professional societies including a life-time member of Indian Science Congress (ISC), International Association of Engineers (IAENG), and World Leadership Academy.