微型电脑应用2024,Vol.40Issue(12) :63-66.

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

龚致富 王清华 姬静怡 林昊 王金元
微型电脑应用2024,Vol.40Issue(12) :63-66.

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

龚致富 1王清华 2姬静怡 3林昊 1王金元1
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作者信息

  • 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
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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.

Abstract

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 hu-man 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 re-sults show that the model training performance and data processing speed of the proposed algorithm are better than other simi-lar 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

Key words

fuzzy cluster/radial basis function neural network/orthogonal least squares method/data preprocessing/workload analysis

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出版年

2024
微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
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