Reference64 articles.
1. Towards buildings energy management: using seasonal schedules under time of use pricing tariff via deep neuro-fuzzy optimizer;Javaid,2019
2. State-of-the-art artificial intelligence techniques for distributed smart grids: A review;Ali;Electronics,2020
3. Li, L., Ota, K., & Dong, M. (2017). Everything is image: CNN-based short-term electrical load forecasting for smart grid. In 2017 14th international symposium on pervasive systems, algorithms and networks & 2017 11th international conference on frontier of computer science and technology & 2017 third international symposium of creative computing (ISPAN-FCST-ISCC) (pp. 344-351). IEEE.
4. HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey;Akhtaruzzaman;IEEE Access,2020
5. Recent challenges and methodologies in smart grid demand side management: state-of-the-art literature review;Nasir;Math. Probl. Eng.,2021
Cited by
1 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