Explainable machine learning techniques based on attention gate recurrent unit and local interpretable model-agnostic explanations for multivariate wind speed forecasting
Year of publication: |
2024
|
---|---|
Authors: | Peng, Lu ; Lv, Sheng-Xiang ; Wang, Lin |
Published in: |
Journal of forecasting. - New York, NY : Wiley Interscience, ISSN 1099-131X, ZDB-ID 2001645-1. - Vol. 43.2024, 6, p. 2064-2087
|
Subject: | attention-based mechanism | gate recurrent unit | LIME | variational mode decomposition | wind speed forecasting | Prognoseverfahren | Forecasting model | Künstliche Intelligenz | Artificial intelligence | Theorie | Theory |
-
Song, Yuping, (2023)
-
Decomposition methods for tourism demand forecasting : a comparative study
Zhang, Chengyuan, (2022)
-
Predicting zombie firms after the COVID-19 pandemic using explainable artificial intelligence
Seo, Dongwook, (2024)
- More ...
-
Wang, Lin, (2023)
-
Reducing Complexity of Processor Front Ends with Static Analysis and Selective Preloading
Verma, Santhosh, (2011)
-
Investment by Chinese Enterprise in Infrastructure Construction in Malaysia
Zhang, Xiekui, (2020)
- More ...