Abstract

In the context of the current era, if China wants to implement the strategic goal of rural revitalization, it must promote the integrated development of urban and rural areas. This paper takes Shaanxi Province as the main research goal, which is at the strategic intersection of the "the Belt and Road", has an important position, can affect the process of regional coordination and urban and rural integration throughout the country, and is a major province of characteristic agriculture and a national transportation hub. In this context, this paper uses BP neural network algorithm to simulate and analyze the coordinated development of urban and rural areas based on the actual development of science and technology finance in Shaanxi Province. After obtaining the economic status data of the province, this paper builds a regional characteristic platform that can provide targeted science and technology finance services, which can achieve diversified processing, complete multi entity fund supply and maintain the transparency of information between the supply and demand sides. Based on the field survey and literature review and analysis, it can be seen that the ten prefecture level cities included in the study area and province have different levels of coordinated development of urban and rural economy, and there is a Matthew effect characteristic of uneven strength, so the regional differences show a weakening feature, and they need to be adjusted gradually to make them develop in an orderly manner. Based on the research conclusion, this paper carries out the construction of urban–rural economic coordinated development and scientific and technological financial model support, and analyzes the financial support function and actual effect of the province in detail. In this paper, the BP neural network algorithm is applied to the integration of urban and rural development in Shaanxi Province to conduct big data simulation for science and technology finance.

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