Artificial Intelligence in Forecasting
CRC Press (Verlag)
978-1-032-50615-9 (ISBN)
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.
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.
Pursuits of Forecasting: Revesting the claims of Artificial Intelligence. A Multilayered Feed-forward Neural network architecture for rainfall forecasting. Forecasting the Stock Market Index Using Artificial Intelligence Techniques. Forecasting of Environmental Sustainability through Green Innovation of E-Vehicle Industry. The Evolution of Forecasting Techniques: Traditional Versus Machine Learning Methods. Workforce Forecasting after COVID-19 Pandemics using Artificial Intelligence. Gender Disparity in Artificial Intelligence: Creating awareness of Unconscious Bias. Customer Perspective through Artificial Intelligence: Forecasting Green Products’ sustainable Development. Weather Forecasting and Climate behavioural analysis using artificial intelligence. Assessing Climate Change Through Ai: An Ethico-Legal Study. Workforce forecasting using Artificial Intelligence. Artificial Intelligence-Based Approaches for Anticipating Financial Market Index Trends. A Comparative Analysis of Traditional and Machine Learning Forecasting Techniques. Forecasting Demand for Paddy and Cotton in Andhra Pradesh: Empirical Analysis using Machine Learning Models. Business Forecasting and Error Handling Using AI. Practical benefits of using AI for more accurate forecasting- In Mental Health. Predicting stock market indexes with Artificial Intelligence. The intellectual structure of application of Artificial Intelligence in forecasting methods: A literature review using bibliometric analysis. Effective Temperature Prediction for an enhanced Climate Forecast System. Demand Forecasting Methods: Using Machine Learning to Predict Future Sales. Demand and Supply forecasts for supply chain and retail. Role of Artificial Intelligence in Weather Forecasting and Climate Behavioral Analysis.
| Erscheinungsdatum | 13.06.2024 |
|---|---|
| Zusatzinfo | 32 Tables, black and white; 10 Illustrations, color; 87 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 830 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management | |
| Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie | |
| ISBN-10 | 1-032-50615-6 / 1032506156 |
| ISBN-13 | 978-1-032-50615-9 / 9781032506159 |
| Zustand | Neuware |
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