大学生个人信用评价模型

College student personal credit evaluation model

首先改进萤火虫算法的初始种群与移动步长,并用来优化BP神经网络初始权值与阈值参数,以构建IGSO-BP神经网络协同集成学习算法。建立基于该学习算法的大学生个人信用评价模型,Matlab仿真验证了模型的可行性。

The improved initial populations and moving steps of glowworm algorithm are used to optimize the initial weights and threshold parameters of BP neural network for constructing IGSO-BP neural network collaborative ensemble learning algorithm. A college student credit evaluation model based on the learning algorithm is established with simulation verification.