Interpolation of environmental data using deep learning and model inference
Chibuike Chiedozie Ibebuchi,
Itohan-Osa Abu
Abstract:The temporal resolution of environmental data sets plays a major role in the granularity of the information that can be derived from the data. In most cases, it is required that different data sets have a common temporal resolution to enable their consistent evaluations and applications in making informed decisions. This study leverages deep learning with long short-term memory (LSTM) neural networks and model inference to enhance the temporal resolution of climate datasets, specifically temperature, and preci… Show more
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