微粒群神经网络在绩效评价系统中的应用

Applying particle swarm optimization algorithm-based artificial neural network to performance evaluation system

绩效评价系统是人力资源系统3P模型中的重要一环,是定期考察和评价个人或小组工作业绩的一种正式制度。利用微粒群算法对神经网络进行训练,再将此网络模型应用到人力资源管理系统中的绩效评价系统。最后通过在各级评价标准内按随机均匀分布方式生成的训练样本和测试样本来检测该微粒群神经网络。结果表明微粒群神经网络具有较强的泛化能力,应用在绩效评价系统中具有很高的评价准确率。

Performance evaluation system is an important part of the human resource performance evaluation system,which is a formal system of regular inspection and evaluation of individual or group work performance,is an important part of 3P model in human resources system.This paper uses PSO algorithm to train neural network.And then this network model is applied to performance evaluation system of the human resources management system.Finally,using training samples and test samples which are generated randomly by evaluation criteria at all levels within the uniform distribution methods,can detect the particle swarm neural network.Results show that the PSO neural network has strong generalization ability,and that application in the performance evaluation system has very high accuracy rate.