BİLGİLİ, M. Et Al. 2021. Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting. INTERNATIONAL JOURNAL OF GREEN ENERGY , vol.18, no.6 , 578-594.

BİLGİLİ, M., Yildirim, A., ÖZBEK, A., ÇELEBİ, K., & Ekinci, F., (2021). Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting. INTERNATIONAL JOURNAL OF GREEN ENERGY , vol.18, no.6, 578-594.

BİLGİLİ, MEHMET Et Al. "Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting," INTERNATIONAL JOURNAL OF GREEN ENERGY , vol.18, no.6, 578-594, 2021

BİLGİLİ, MEHMET Et Al. "Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting." INTERNATIONAL JOURNAL OF GREEN ENERGY , vol.18, no.6, pp.578-594, 2021

BİLGİLİ, M. Et Al. (2021) . "Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting." INTERNATIONAL JOURNAL OF GREEN ENERGY , vol.18, no.6, pp.578-594.

@article{article, author={MEHMET BİLGİLİ Et Al. }, title={Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting}, journal={INTERNATIONAL JOURNAL OF GREEN ENERGY}, year=2021, pages={578-594} }