Data Analysis And Method Research Of Heroin Dependence And Relapse Psychology In Yunnan Province

Drugs,has becoming one of the main risk factors of society. In view of the situation,our country pays more attention to the rehabilitation of drug addicts in addition to anti-drug efforts. But now,the attention on drug addicts relapse is not enough,which leading to drug the patient’s back and forth, making it difficult for them completely out of the dangers of drugs.Therefore, using advanced computer knowledge to rehab drug inform ation database and identifying the factors which reduce the relapse rate and apply to the rehabilitation process, has become an important direction of development.This research work was carried out on real data,which using statistics analysis software IBM SPSS Statistics.The paper introduces the idea of principal component analysis and correlation,which analyzed the data of everal cases collected from a drug rehabilitation center of Yunnan province by our research group. According to the lack of SPSS software using principal component analysis algorithm,this paper introduced the algorithm of KPCA and solved the problem of each factor providing the low contribution.It presented Dual-core fusion method and improved the single kernel principal component used in the original algorithm of KPCA deficiencies.This paper studies is mainly divided into three stages. First,collecting the data needed and getting ease of calculation and analysis of valid data by pretreating the data. Second,using main components analysis method on many factors for drop dimension.It simplified data structures by extracting the common factors from the information variables overlap.And then,by using correlation method, it will associate the complex sucking of times with the main components factor aboved one by one and obtaine the complex sucking frequency related of factors: some mood,trust from others,happiness and positive aspect of my life, unfriendly,uhealthy, heartbeat and dizziness symptoms and physical pain.The third stage is introducing and improving the algorithm of KPCA based on the original in the original principal component analysis of SPSS.