Funder
Dubai Electricity and Water Authority
Reference134 articles.
1. Short-term load forecasting for a single household based on convolution neural networks using data augmentation;Acharya;Energies (Basel),2019
2. Inverse modeling of the urban energy system using hourly electricity demand and weather measurements, part 1: Black-box model;Afshari;Energy Build.,2017
3. Towards short term electricity load forecasting using improved support vector machine and extreme learning machine;Ahmad;Energies (Basel),2020
4. Short-term multiple forecasting of electric energy loads for sustainable demand planning in smart grids for smart homes;Alani;Sustainability (Switzerland),2017
5. Almalaq, A., Edwards, G., 2017. A Review of Deep Learning Methods Applied on Load Forecasting. In: 2017 16th IEEE International Conference on Machine Learning and Applications. ICMLA, pp. 511–516. http://dx.doi.org/10.1109/ICMLA.2017.0-110.
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献