基于专家系统为感染后咳嗽患者提供新鲜中药止咳方案

Providing Cough Relieving Scheme of Fresh Chinese Medicine for Patients with Cough after Infection Based on Expert System

目的鲜药治病是中医特色,也有着独特的功效,本文综合考虑时间、季节和空间距离等因素的影响,构建专家系统模型,为感染后患者提供一个采集新鲜中药的止咳方案,提高中药疗效。方法利用数据挖掘技术对原始数据进行了数据清洗和挖掘,并对完善后的中药数据按照季节分类。补充原始数据的缺失内容,对分类后的中药以地域分布的情况做出系统聚类并给出配伍方案,构建专家系统将止咳方案导入到规则库。结果基于规则的专家系统,通过仿真得出的结果和规则库中信息一致,没有匹配错误的情况。且专家系统所给出的新鲜止咳中药的方案满足运送距离最近和新鲜的要求。结论专家系统可以有效的为感染后的患者提供新鲜止咳中药。

Objective: Treating diseases with fresh medicine is a characteristic of traditional Chinese medicine, and it also has a unique effect. In this paper, the influence of time, season and spatial distance is comprehensively considered, and an expert system model is constructed to provide a cough relieving scheme for patients after infection and improve the efficacy of traditional Chinese medicine. Methods:Data mining technology was used to clean and mine the original data, and the improved TCM data was classified according to the season. Supplement the missing content of the original data, make a systematic clustering of the classified traditional Chinese medicine according to the geographical distribution and give the compatibility scheme, build an expert system to import the cough scheme into the rule base. Results:The simulation results of the rule-based expert system are consistent with the information in the rule base, and there is no matching error. And the scheme of fresh cough Chinese medicine given by the expert system can meet the requirements of the shortest transportation distance and freshness. Conclusion:The expert system can effectively provide fresh cough medicine for patients after infection.