Visualization Analysis of Meteorological Big Data through Deep Learning and Network Model

Abstract

With the continuous progress of meteorological data observation technology, meteorological data showed explosive growth, which brought new opportunities and challenges to the development of meteorological forecasting technology. In view of the complexity of multidimensional visualization analysis of meteorological big data resources, the business object model, visual analysis dimension and visual monitoring index of meteorological big data resources are constructed. In this paper, RBM, CNN and network model based on long and short memory are used to predict the refined temperature in the next 24 hours, and the prediction results of the models are compared and analyzed. The results show that compared with traditional RBM, the deep learning algorithm model can show good prediction ability and can be used as a common structure for refined temperature prediction.