Electricity Demand Prediction: An Analytical Comparison of ARIMA and Artificial Neural Network
- Title
- Electricity Demand Prediction: An Analytical Comparison of ARIMA and Artificial Neural Network
- Creator
- Kumar Chandar, S.
- Description
- Electricity plays a dominant role globally, especially in the economies of India. Accurately projecting its consumption is crucial for energy planning. This study focuses on forecasting electricity consumption across distinct sectors using Autoregressive Integrate Moving Average (ARIMA) and Artificial Neural Network (ANN). The efficacy of the models is evaluated via various error metrics and compared, demonstrating the superior performance of the ANN model over ARIMA model. 2025 IEEE.
- Source
- 6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025 - Proceedings;pp.1272-1279
- Date
- 01-01-2025
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- ARIMA; Artificial neural network; Energy Consumption Prediction; India
- Coverage
- Kumar Chandar S., School of Business and Management, CHRIST University, Karnataka, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISBN: 979-833152266-7;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Kumar Chandar, S., “Electricity Demand Prediction: An Analytical Comparison of ARIMA and Artificial Neural Network,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 17, 2026, https://archives.christuniversity.in/items/show/26055.