DESIGN OF REAL-TIME PUSH SOFTWARE FOR ENVIRONMENT METEOROGICAL MONITORING DATA BASED ON BIG DATA.

A real-time push software for environmental meteorological monitoring data based on big data was designed to improve the real-time and accuracy of data push. The data source module in the real-time push software for environmental meteorological monitoring data based on big data is responsible for storing environmental meteorological monitoring data. The integration module is responsible for extracting the required data. The big data module is responsible for preprocessing the extracted data, using RBF artificial neural network algorithm to build a meteorological prediction model for it, and obtaining the prediction results. Module, intelligent information push through regression restricted boltzmann machine recommendation algorithm, to extract the predicted results of interest to the user in the environmental meteorological monitoring data, restricted boltzmann machine recommendation algorithm based on regression is introduced in collaborative filtering algorithm restricted boltzmann machine, formed based on the user and the project of restricted boltzmann machine collaborative filtering algorithm, by using linear model integration of recommended results, through intelligent notification module will recommend the push to the intelligent terminal, to achieve environmental meteorological monitoring data real-time push. The experiment proves that the software can effectively push the environmental meteorological monitoring data to users in real time, with fast speed and high accuracy. [ABSTRACT FROM AUTHOR]