Analysis on the impact factors of low-rent housing residents´ income in Shanghai based on BP neural network

Low-rent housing system is the necessary guarantee of building harmonious society and the urgent demand of establishing and perfecting social security system. It has realistically significance to study the low-rent housing by multi-level and multi-angle. Based on the data of income for low-rent housing residents, applying BP neural network model, the quantitative analysis on the influence of income factors of low-rent housing residents in Shanghai was given, and the mechanism of each factor was studied by further analysis. The result showed that BP neural network model could be successful to study the income of Shanghai low-rent housing residents. There are different influences and mechanisms on each factor to the segment income and total income. Furthermore, the top two influential factors on the wage income is the employment and marital status, and transfer income has the closest relationship with sexuality, region and employment status. Therefore, it reflects that the level of employment and social welfare play important roles for the income of low-rent housing residents.