摘要
考虑到医院人力资源的实际需求,提出将定量分析与定性分析相结合的灰色神经网络预测模型,并且采用粒子群算法对灰色神经网络结构参数进行优化。将所提模型和灰色神经网络模型、神经网络模型、GM(1,1)进行比较,结果表明,灰色神经网络模型和所提模型的预测精度明显高于神经网络模型和GM(1,1),但所提模型的预测偏保守,预测精度更高。
Considering the reality of hospital human resource demand,a grey neural network prediction model combining quantitative analysis and qualitative analysis is proposed,the structural parameters of grey neural network are optimized by particle swarm optimization algorithm,and the model for hospital human resource demand prediction is obtained.The proposed model is compared with grey neural network model,neural network model and GM(1,1)grey model.The results show that the prediction accuracy of grey neural network model and improved grey neural network model is significantly higher than that of neural network model and GM(1,1)grey model.But the prediction of improved grey neural network prediction model is conservative,and the prediction accuracy is relatively high.
作者
张建学
李钰
ZHANG Jianxue;LI Yu(Beijing Daxing District People’s Hospital,Beijing 102600,China;School of Computer&Communication Engineering,University of Science and Technology Beijing,Beijing 100083,China)
出处
《微型电脑应用》
2023年第12期9-11,15,共4页
Microcomputer Applications
基金
国家自然科学基金项目(517084408)。
关键词
灰色神经网络
粒子群优化算法
人力资源
需求预测
grey neural network
particle swarm optimization algorithm
human resource
demand prediction