A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers

23 February 2023

Papers citing "A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers"

8 / 8 papers shown

Title
In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance Sotiris Pelekis Evangelos Karakolis Francisco Silva Vasileios Schoinas S. Mouzakitis Georgios Kormpakis N. Amaro J. Psarras AI4TS 43 15 0 25 Feb 2023
The Shapley Value in Machine Learning Benedek Rozemberczki Lauren Watson Péter Bayer Hao-Tsung Yang Oliver Kiss Sebastian Nilsson Rik Sarkar TDI FAtt 79 210 0 11 Feb 2022
Darts: User-Friendly Modern Machine Learning for Time Series J. Herzen Francesco Lässig Samuele Giuliano Piazzetta T. Neuer Léo Tafti ... Mounir Benheddi Camila Williamson Michal Kosinskihttps://www.semanticscholar.org/me/account M. Petrik Gaël Grosch AI4TS 167 220 0 07 Oct 2021
A Survey of Transformers Tianyang Lin Yuxin Wang Xiangyang Liu Xipeng Qiu ViT 117 1,115 0 08 Jun 2021
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting Bryan Lim Sercan O. Arik Nicolas Loeff Tomas Pfister AI4TS 102 1,449 0 19 Dec 2019
Optuna: A Next-generation Hyperparameter Optimization Framework Takuya Akiba Shotaro Sano Toshihiko Yanase Takeru Ohta Masanori Koyama 625 5,769 0 25 Jul 2019
Deep Learning for Time Series Forecasting: The Electric Load Case Alberto Gasparin S. Lukovic Cesare Alippi AI4TS 45 223 0 22 Jul 2019
An Introduction to Convolutional Neural Networks K. O’Shea Ryan Nash FaML HAI 62 3,140 0 26 Nov 2015