Author:
Oztaysi Basar,Çevik Onar Sezi,Bolturk Eda,Kahraman Cengiz
Publisher
Springer International Publishing
Reference50 articles.
1. Akdemir, B., & Cetinkaya, N. (2012). Long-term load forecasting based on adaptive neural fuzzy inference system using real energy data. Energy Procedia, 14, 794–799.
2. Arcos-Aviles, D., Pascual, J., Guinjoan, F., Marroyo, L., Sanchis, P., & Marietta, M. P. (2017). Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting. Applied Energy, 205, 69–84.
3. Atsalakis, G., Frantzis, D., & Zopounidis, C. (2015). Energy’s exports forecasting by a neuro-fuzzy controller. Energy Systems, 6(2), 249–267.
4. Bain, A., & Baracli, H. (2014). Modeling potential future energy demand for Turkey in 2034 by using an integrated fuzzy methodology. Journal of Testing and Evaluation, 42(6), 1466–1478.
5. Bisht, K., & Kumar, S. (2016). Fuzzy time series forecasting method based on hesitant fuzzy sets. Expert Systems with Applications, 64, 557–568.
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