Work

Transformer-KAN: A Novel Deep Learning Model for Improving Wind Power Forecasting Accuracy by Integrating Multi-source Data

Year: 2024

Type: conference-paper

Source: International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)

DOI: 10.1109/isceic63613.2024.10810201

Authors: Yajuan Zhang, Tao Gu, Limin Wang

Institution: Guangdong University Of Finances and Economics

Language: English

Topic: Energy Load and Power Forecasting

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: closed

Funder: National Office for Philosophy and Social Sciences

Award: G6509742006

OpenAlex ID: W4405846322

FWCI: 3.9

Cites: 8

Cited by: 5

Related to: 10