基于模糊聚类与径向基神经网络的工作量智能分析算法研究  

Research on Workload Intelligent Analysis Algorithm Based on Fuzzy Cluster and Radial Basis Function Neural Network

作　　者：龚致富 王清华 姬静怡 林昊 王金元[1] GONG Zhifu;WANG Qinghua;JI Jingyi;LIN Hao;WANG Jinyuan(The First Affiliated Hospital of Hebei North University,Zhangjiakou 075000,China;The Second Affiliated Hospital of Hebei North University,Zhangjiakou 075100,China;School of Law and Politics,Hebei North University,Zhangjiakou 075000,China)

机构地区：[1]河北北方学院附属第一医院,河北张家口075000 [2]河北北方学院附属第二医院,河北张家口075100 [3]河北北方学院,法政学院,河北张家口075000

出　　处：《微型电脑应用》2024年第12期63-66,共4页Microcomputer Applications

基　　金：张家口市2022年度科技计划研究项目(2221186D);张家口市2022年度社会科学研究项目(2022057)。

摘　　要：传统医疗工作量评估分析算法模型存在训练时间较长、分析结果精度不足等问题,对此提出一种基于模糊聚类与径向基神经网络的工作量智能分析算法。所提算法对医疗人力资源系统中的绩效数据进行预处理,通过模糊聚类算法与正交最小二乘法来获取神经网络训练所需的最优聚类中心,利用该聚类中心对搭建好的径向基神经网络进行训练得到相关模型,利用该模型实现对工作量的智能分析。例子验算证明,所提算法的模型训练性能及数据处理速度均优于其他同类算法,且处理结果的准确性能够达到91%以上。Aimed at the problems of the traditional medical workload evaluation and analysis algorithm,such as longer training time and insufficient accuracy of analysis results,this paper proposes a workload intelligent analysis algorithm based on fuzzy cluster and radial basis function neural network.The proposed algorithm preprocesses the performance data in the medical human resource system,obtains the optimal cluster center required for the training of the neural network through the fuzzy cluster algorithm and the orthogonal least squares method,uses the cluster center to train the constructed radial basis function neural network to obtain the relevant model,and uses the model to realize the intelligent analysis of workload.The experimental results show that the model training performance and data processing speed of the proposed algorithm are better than other similar algorithms,and the accuracy of the processing results can reach more than 91%.

关 键 词：模糊聚类 径向基神经网络 正交最小二乘法 数据预处理 工作量分析 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TN929.5[自动化与计算机技术—计算机科学与技术]