基于改进PSO-SVM的智能化医疗数据处理技术研究

Research on intelligent medical data processing technology based on improved PSO⁃SVM

针对众多医疗机构采用传统统计或报表的方式对财务数据进行分析,而现有数据处理方法效率低下、准确率不足且难以发现数据之间深层信息等问题,文中提出了一种基于改进PSO-SVM的智能化医疗数据处理技术。该技术利用SA算法对PSO进行优化以解决其早收敛的问题,然后采用优化后的PSO算法获取SVM算法所需的最优参数,最后通过样本数据进行SVM模型训练,得到所需的数据处理模型。实验结果说明,相较于同类数据处理算法,所提算法可以在保证处理效率的情况下,准确率达到95%以上。

Aiming at the problems of many institutions using traditional statistical or reporting methods to analyze financial data,such as inefficient and inaccurate data processing methods,and difficulty in discovering deep information between data,an intelligent medical data processing technology is proposed based on improved PSO⁃SVM.This technology uses SA algorithm to optimize PSO to solve its early convergence problem,and then uses the optimized PSO algorithm to obtain the optimal parameters required by the SVM algorithm.Finally,through sample data for SVM model training,the required data processing model is obtained.Experimental results show that compared to similar data processing algorithms,the proposed algorithm can achieve an accuracy rate of over 95%while ensuring processing efficiency.