Short-term power consumption forecasting using neural networks with first- and second-order differencing
Electricity consumption forecasting is critical for efficient energy management and planning. Traditional time series models, such as ARIMA (AutoRegressive Integrated Moving Average), have been widely used due to their simplicity and interpretability. However, they often struggle with cap...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Academia.edu Journals
2024-10-01
|
| Series: | Academia Green Energy |
| Online Access: | https://www.academia.edu/125009859/Short_term_power_consumption_forecasting_using_neural_networks_with_first_and_second_order_differencing |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Be the first to leave a comment!