Research for SARIMA and PatchTSMixer Models on the IEA Monthly Statistics Dataset
The rapid evolution of intelligent algorithms has led to their extensive application in time-series forecasting, particularly in predicting electricity consumption. Accurate forecasting is crucial for energy management, policy-making, and ensuring a stable power supply. However, a significant gap ex...
Saved in:
Main Author: | Hu Yuwei |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2025-01-01
|
Series: | ITM Web of Conferences |
Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_03011.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Forecast and Analysis of Coal Traffic in Daqin Railway Based on the SARIMA-Markov Model
by: Cheng Zhang, et al.
Published: (2020-01-01) -
Seasonal forecasting of Bactrocera dorsalis Hendel, 1912 (Diptera: Tephritidae) in bioclimatic zones of Sri Lanka using the SARIMA model
by: W. M. C. D. Wijekoon, et al.
Published: (2024-04-01) -
Summary of the 2023 (1st edition) Report of TCEP (Tracking Clean Energy Progress) by the International Energy Agency (IEA), and Proposed Process for Computing a Single Aggregate Rating
by: Marzouk Osama A.
Published: (2025-01-01) -
A dataset for evaluating clinical research claims in large language models
by: Boya Zhang, et al.
Published: (2025-01-01) -
Application of Dynamical and Statistical Downscaling to East Asian Summer Precipitation for Finely Resolved Datasets
by: Yoo-Bin Yhang, et al.
Published: (2017-01-01)