1st Edition
Artificial Intelligence in Forecasting Tools and Techniques
Pursuits of Forecasting: Revisiting the Claims of Artificial Intelligence
Kareti Payaswitha Harshini
A Multilayered Feed-Forward Neural Network Architecture for Rainfall Forecasting
Manikandan Rajagopal, and Dr. Ramkumar S
Forecasting the Stock Market Index Using Artificial Intelligence Techniques
Sunita Kumar, Shiv Onkar Deepak Kumar, and Sridharan A
Forecasting of Environmental Sustainability through Green Innovation of E-Vehicle Industry
Jobin Jacob, Pancinovia Neelu, and Arun C Antony
The Evolution of Forecasting Techniques: Traditional Versus Machine Learning Methods
Anna Thomas, Amala Johnson, and Meby Joseph Manoj
Workforce Forecasting after COVID-19 Pandemics Using Artificial Intelligence
Anjali Mathur
Gender Disparity in Artificial Intelligence: Creating Awareness of Unconscious Bias
Sugyanta Priyadarshini, and Sukanya Priyadarshini
Jobin Jacob, Jessia Saji, and Arun C Antony
Weather Forecasting and Climate Behavioural Analysis Using Artificial Intelligence
Murali Karuppusamy, Gurumoorthy Chelladurai, Sambath Krishnamoorthy, and Sudharshan Rathinavel
Assessing Climate Change through Artificial Intelligence: An Ethico-Legal Study
Achyutananda Mishra, Ananya Pandey, and Smruti Mohanty
Workforce Forecasting Using Artificial Intelligence
Alwin Joseph, Amala Johnson, and Aashiek Cheriyan
Artificial Intelligence-Based Approaches for Anticipating Financial Market Index Trends
Elian Jose, Shine Raju Kappil, and Aashiek Cheriyan
A Comparative Analysis of Traditional and Machine Learning Forecasting Techniques
Lija Jacob, and K T Thomas
Forecasting Demand for Paddy and Cotton in India: Empirical Analysis Using Machine Learning Models
Aketi Gayatri Jahnavi, and Shahid Bashir
Business Forecasting and Error Handling Using AI
Vaddadi Kamya Nagasri, M vasantha, Preethi Nanjundan, and Jossy P George
Practical Benefits of Using AI for More Accurate Forecasting in Mental Health
D Swainson Sujana, and D Peter Augustine
Predicting Stock Market Indexes with Artificial Intelligence
Yasmeen Fatima, Mohammad Asif, and Preethi Nanjundan, and Jossy P George
The Intellectual Structure of Application of Artificial Intelligence in Forecasting Methods: A Literature Review using Bibliometric Thematic Analysis
Anshul Saxena, Jayant Mahajan, Vandana Bhagat, Subha MV, Binu P Paul, and Vaishali Jain
Effective Temperature Prediction for An Enhanced Climate Forecast System
Mohammed Mueen Pasha M, and Sibu Cyriac
Demand Forecasting Methods: Using Machine Learning to Predict Future Sales
Sunanda Vincent Jaiwant, and Joseph Varghese Kureethara
Demand and Supply Forecasts for Supply Chain and Retail
Astha Gupta, Preethi Nanjundan, and Jossy P George
Role of Artificial Intelligence in Weather Forecasting and Climate Behavioral Analysis
Mahesh Kumar S V, and Sreya U Parvathi
Index
Biography
Dr. Sachi Nandan Mohanty obtained a PostDoc from IIT Kanpur in 2019 and Ph.D. from IIT Kharagpur, India in 2015, with MHRD scholarship from Government of India. He has authored/edited over 25 books, published by IEEE-Wiley, Springer, Wiley, CRC Press, NOVA and DeGruyter. His research areas include Data Mining, Big Data Analysis, Cognitive Science, Fuzzy Decision Making, Brain-Computer Interface, Cognition, and Computational Intelligence. Prof. S N Mohanty has received 4 Best Paper awards from an International Conference at Beijing, China, and the International Conference on Soft Computing Applications organized by IIT Rookee in 2013. He has awarded Best Thesis award first prize by Computer Society of India in 2015. He has guided 9 PH.D. Scholars. He has published 120 articles in reputable journals and has been elected as FELLOW of Institute of Engineers, European Alliance Innovation (EAI), and Senior member of IEEE Computer Society Hyderabad chapter. He has served as a reviewer of Journal of Robotics and Autonomous Systems (Elsevier), Computational and Structural Biotechnology Journal (Elsevier), Artificial Intelligence Review (Springer), Spatial Information Research (Springer).
Dr. Preethi Nanjundan is an Associate Professor in the Department of Data Science at Christ University, Pune, India. She received her doctorate degree (2014), Master of Philosophy in Computer Science (2014), and a master’s degree in computer applications (2004) all from Bharathiyar University, Coimbatore, TN, India. Her research and teaching experience spans almost 20 years. Besides publishing over 20 papers in reputed journals, she has contributed chapters to various books and published 5 books. She has 4 patents. In 2020, she received the Best Professor award from Lead India and Vision Digital India. Her contributions to a book titled "Covid 19 and its Impact'' have been inducted into the Indian and Asian books of records. Her research area includes machine learning, natural language processing, and neural network etc. She is a lifetime member of professional societies including Computer Society of India (CSI), International Association of Computer Science and Information Technology (IACSIT), Computer Science Teachers Association, and Indian Society for Technical Education (ISTE).
Tejaswini Kar received her B. Tech in Electronics and Telecommunication engineering from Biju Patnaik University of Technology, Odisha, Bhubaneswar, India in 2003. She obtained a M. Tech in communication system engineering from Kalinga Institute of Industrial Technology, in 2008 and Ph.D. degree in Electronics and Telecommunication engineering in 2018 from KIIT deemed to be university, Bhubaneswar, India. She has almost 20 years of teaching experience. She is currently an Assistant Professor with the School of Electronics Engineering, KIIT deemed to be University. She has published many research papers in important conferences and reputable journals. She has served as a reviewer in many peer reviewed journals and conferences. She received best paper award in ICDMAI 2019 held in Malaysia. She has been awarded with certificate of excellence award as a mentor by Samsung for Samsung Prism project in 2022. Her current research interests include image processing, video processing, Machine Learning and Deep Learning.
