Evaluation and prediction of regional human capital based on optimised BP neural network

With the increasing role of knowledge and technology in the economy, human capital has become the decisive factor for economic development and social progress. Measuring, evaluating or predicting the level of regional human capital within a country can grasp the investment policy of human capital as a whole. Therefore, in this paper, a prediction model of regional human capital level based on optimised BP neural network is built. First, the evaluation system of the regional human capital is constructed by selecting 15 evaluation indexes in 5 categories, such as educational training, development of science and technology, medical care, labour migration and social security. Then, the PSO algorithm is used to optimise the BP neural network, and the core problems in the optimisation process are solved. Finally, the model is tested and analysed by the MATLAB simulation platform. The results show that the prediction accuracy of the model is high, and the output results are basically consistent with the reality, which is conducive to promoting the structural upgrading of human capital.