Personal credit risk measurement model based on PSO-BP

The invention provides a personal credit risk measurement model based on PSO-BP, and relates to the technical field of finance. The personal credit risk measurement model based on PSO-BP comprises a PSO-BP model, the PSO-BP model is based on a neural network and a particle swarm optimization algorithm, the BP neural network algorithm comprises a signal forward transmission part and an error reverse transmission part, the number of neuron nodes of an input layer is supposed to be n, the number of neuron nodes of a hidden layer is supposed to be s, and the number of neuron nodes of an output layer is supposed to be 1, according to the principle of the PSO algorithm, Vi = (vi1, vi2,... vin) and Xi = (xi1, xi2,... xin) are used for representing the speed and the position of an ith particle in an n-dimensional space respectively, the fitness function value of each particle is evaluated in each iteration, the optimal position pbest of an individual passed by each particle at the t moment and the optimal position gb