Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset

History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining

(2018) Dazhi Yang et al.   SOLAR ENERGY

Data driven prediction models of energy use of appliances in a low-energy house

(2017) Luis M. Candanedo et al.   ENERGY AND BUILDINGS

A survey of deep neural network architectures and their applications

(2017) Weibo Liu et al.   NEUROCOMPUTING

A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting

(2017) Walter Richardson et al.   Sustainability

Understanding deep convolutional networks

(2016) Stéphane Mallat   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Wind Power Pattern Forecasting Based on Projected Clustering and Classification Methods

(2015) Heon Gyu Lee et al.   ETRI JOURNAL

Deep learning

(2015) Yann LeCun et al.   NATURE

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Crop Yield Forecasting Using Artificial Neural Networks: A Comparison between Spatial and Temporal Models

(2014) William W. Guo et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Representation Learning: A Review and New Perspectives

(2013) Y. Bengio et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Hybrid intra-hour DNI forecasts with sky image processing enhanced by stochastic learning

(2013) Yinghao Chu et al.   SOLAR ENERGY

Thin Cloud Detection of All-Sky Images Using Markov Random Fields

(2011) Qingyong Li et al.   IEEE Geoscience and Remote Sensing Letters

Evolution problems in spaces of probability measures

(2009) Luigi Ambrosio   PHYSICA D-NONLINEAR PHENOMENA