Rainfall weather condition prediction based on embedded system and big data financial management

Abstract

This paper analyzes the practical application requirements of embedded systems. According to the analysis, we conceive and develop a general experimental platform composed of embedded processor motherboard, general peripheral equipment, and custom connection board. We completed the selection and design of hardware peripherals, driver creation, and testing and showed how to transplant the basic driver for each module. Then embedded system is used in rainfall prediction, which plays an important role. The distribution of four different types of representative stations is analyzed, and the probability characteristics of different precipitation forecast levels are summarized. Secondly, from the point of view of time and space, we will study the total precipitation and flood index during the Meiyu period in Northwest China, and understand their spatial and temporal characteristics. Finally, the precipitation in the coming Meiyu period is predicted by R/S analysis and stationary time series prediction method. However, in the era of big data, the competition is becoming more and more fierce. For the financial industry, financial risk is an inevitable problem of financial development, especially in the competitive market environment; the abnormal competition behavior of some financial companies is destroying the financial market. Financial management is an important task for financial institutions. Only with good performance in risk management can big data be better applied to and stimulate the financial industry. In this paper, through the establishment of risk management mechanism, the comprehensive analysis of big data enterprises, the identification of risk factors of big data enterprises, the development of preventive strategies, and other measures, we can effectively reduce the risk loss and promote the stable development of big data financial management.