Prediction Method of Government Economic Situation based on Big Data Analysis

Abstract

In order to improve the forecasting accuracy of economic situation, a government economic situation forecasting method based on big data analysis is proposed. According to the hardware structure of the system, STC12C5608AD is used as the data acquisition terminal chip to simplify the circuit. The proposed forecasting method can give real-time early warning to the government's economic situation. The software part screens the influencing factors of government economic development, constructs a government economic development index system, collects government economic index data, cleans, clusters, classifies, and standardizes the government economic index data, and extracts the preprocessed government economic index data from the preprocessed government economic index data through data mining. The economic development features are extracted and then input into the neural network. After training and learning, the predicted value of the economic situation is output, and the economic situation level is classified. The experimental results show that the proposed method reduces the error rate of economic situation forecast, shortens the forecast time, improves the forecast accuracy and efficiency, with the peak error ratio not exceeding 15%.