摘要
为从复杂数据中挖掘监狱警察心理健康状况,提出一种改进的Apriori算法进行监狱警察心理健康监测和评估,并根据狱警心理表现症状进行疏导。针对传统Apriori算法计算量大、遍历数据长的问题,对数据库集心理健康调查结果进行矩阵化处理和和运算,采用自连接操作方式删除非频繁项集,降低数据计算量。将改进算法应用于监狱警察心理健康调查,应用结果表明:监狱警察普遍存在“内向、抑郁、焦虑、坚强”的心理特征,后续心理辅导工作中,需加强户外锻炼,多接触外界事物,培养活泼开朗、积极乐观的情绪。
In order to mine the mental health status of prison police from complex data,an improved Apriori algorithm is proposed for monitoring and evaluating the mental health of prison police,and guidance is provided based on the psychological symptoms of prison police.In response to the problems of high computational complexity and long traversal data in the traditional Apriori algorithm,the mental health survey results of the database set are matrix processed and summed,and non-frequent item sets are removed through self connection operation to reduce data computation.The improved algorithm was applied to the mental health survey of prison police,and the application results showed that prison police generally have psychological characteristics of“introversion,depression,anxiety,and resilience”.In subsequent psychological counseling work,it is necessary to strengthen outdoor exercise,have more contact with external things,and cultivate lively,cheerful,positive and optimistic emotions.
作者
吴萌
Wu Meng(Shaanxi Police Vocational College,Xi’an 710021,China)
出处
《兵工自动化》
北大核心
2024年第9期24-27,共4页
Ordnance Industry Automation
基金
陕西警官职业学院重点课题(YJKY1901)。
