Research and Design of Accurate Poverty Alleviation Data Analysis Model

In order to realize the poverty alleviation of China's current standards to achieve total poverty alleviation by 2020, the state has proposed a strategic plan for precision poverty alleviation. Based on the multidimensional poverty analysis methods and latest research results proposed by Alklre and Foster [1]. Taking the existing poverty data sources in Fengqing County of Yunnan Province as the research object, the selection of poverty dimension indicators is carried out. The multi-dimensional poverty threshold deprivation index system of five dimensions and seven indicators is designed, the multidimensional poverty measurement model is designed, and the RBF (radial basis function) neural network technology is used to measure the poverty depth of poor households. Using Python programming to achieve model programming, embedding the platform to achieve poverty measurement function, and constructing a scientific and accurate data analysis model for poverty alleviation, providing decision support for the government to carry out accurate poverty alleviation.