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Photovoltaic (PV) power generation has emerged as one of the lead renewable energy sources.
Long Short-Term Memory
Hochreiter, S. and Schmidhuber, J · 1997
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Bidirectional Recurrent Neural Networks
Schuster, M. and Paliwal, K. K · 1997
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An ANN-based Approach for Forecasting the Power Output of Photovoltaic System
Ding, M., Wang, L., and Bi, R · 2011
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The Effect of Temperature on Photovoltaic Cell Efficiency
Fesharaki, V. J., Dehghani, M., Fesharaki, J. J., and Tavasoli, H · 2011
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Local and regional photovoltaic power prediction for large scale grid integration: Assessment of a new algorithm for snow detection
Lorenz, E., Heinemann, D., and Christian, K · 2011
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Solar forecasting methods for renewable energy integration
Inman, R. H., Pedro, H. T. C., and Coimbra, C. F. M · 2013
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Application of time series and artificial neural network models in short-term forecasting of PV power generation
Kardakos, E. G., Alexiadis, M. C., Vagropoulos, S. I., Simoglou, C. K., Biskas, P. N., and Bakirtzis, A. G · 2013
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An ARMAX model for forecasting the power output of a grid connected photovoltaic system
Li, Y., Su, Y., and Shu, L · 2013
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Photovoltaic power forecasting using statistical methods: impact of weather data
Malvoni, M., De Giorgi, M. G., and Congedo, P. M · 2013
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Visualizing and Understanding Convolutional Networks
Zeiler, M. D. and Fergus, R · 2013
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Master optimization process based on neural networks ensemble for 24-h solar irradiance forecast
Cornaro, C., Pierro, M., and Bucci, F · 2014
Cited alongside, same era.
Adam: A Method for Stochastic Optimization
Kingma, D. P. and Ba, J · 2014
Cited alongside, same era.
Bidirectional recurrent neural network language models for automatic speech recognition
Arisoy, E., Sethy, A., Ramabhadran, B., and Chen, S · 2015
Cited alongside, same era.
A physical hybrid artificial neural network for short term forecasting of PV plant power output
Dolara, A., Grimaccia, F., Leva, S., Mussetta, M., and Ogliari, E · 2015
Cited alongside, same era.
Long-term recurrent convolutional networks for visual recognition and description
Donahue, J., Hendricks, L. A., Guadarrama, S., Rohrbach, M., Venugopalan, S., Darrell, T., and Saenko, K · 2015
Cited alongside, same era.
Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines
Li, Y., He, Y., Su, Y., and Shu, L · 2016
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LSTM network: a deep learning approach for short-term traffic forecast
Zhao, Z., Chen, W., Wu, X., Chen, P. C. Y., and Liu, J · 2016
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Accurate photovoltaic power forecasting models using deep LSTM-RNN
Abdel-Nasser, M. and Mahmoud, K · 2017
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Application of extreme learning machine for short term output power forecasting of three grid-connected PV systems
Hossain, M., Mekhilef, S., Danesh, M., Olatomiwa, L., and Shamshirband, S · 2017
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Data-driven photovoltaic power production nowcasting and forecasting for polygeneration microgrids
Oneto, L., Laureri, F., Robba, M., Delfino, F., and Anguita, D · 2017
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Shi, X., Chen, Z., Wang, H., Yeung, D.-Y., Wong, W.-k., and Woo, W.-c · 2015
Cited alongside, same era.
Solar and wind forecasting by NARX neural networks
Di Piazza, A., Di Piazza, M. C., and Vitale, G · 2016
Cited alongside, same era.
Deep Learning for solar power forecasting - An approach using AutoEncoder and LSTM Neural Networks
Gensler, A., Henze, J., Sick, B., and Raabe, N · 2016
Cited alongside, same era.
Forecasting short-term solar irradiance based on artificial neural networks and data from neighboring meteorological stations
Gutierrez-Corea, F. V., Manso-Callejo, M. A., Moreno-Regidor, M. P., and Manrique-Sancho, M. T · 2016
Cited alongside, same era.
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X., and Research, G
Cited in the paper.
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
He, K., Zhang, X., Ren, S., and Sun, J
Cited in the paper.
A hierarchical approach using machine learning methods in solar photovoltaic energy production forecasting
Li, Z., Mahbobur Rahman, S. M., Vega, R., and Dong, B
Cited in the paper.
Solar photovoltaic generation forecasting methods: A review
Sobri, S., Koohi-Kamali, S., and Rahim, N. A · 2017
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Probabilistic Model for Spatio-Temporal Photovoltaic Power Forecasting
Agoua, X. G., Girard, R., and Kariniotakis, G · 2018
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pvlib python: a python package for modeling solar energy systems
Holmgren, W. F., Hansen, C. W., and Mikofski, M. A · 2018
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Photovoltaic Modules Operating Temperature Estimation Using a Simple Correlation
Muzathik, A. M · 2045
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