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TITLE: Large Scale Multi-level Model: Solar Energy Prediction Combining Information from Multiple Sources
ABSTRACT:
We propose a hierarchical modeling approach appropriate for a data where the measurements and associated information are taken repeatedly over a large monitoring network. The proposed method is to make improved inferences by dividing a large scale data into manageable sizes and combining them. Our approach also provides a natural and flexible framework for situations where the data are available in different resolution. The proposed method is applied to the solar energy prediction problem for U.S. Department of Energy's SunShot initiative.
