Abnormal behavior prediction system for forcibly isolating drug addicts based on big data

Abstract

The invention discloses a big data-based abnormal behavior prediction system for forcibly isolating drug rehabilitation personnel. The system comprises a data acquisition unit, a data storage unit, adata analysis unit and a data application unit, The data acquisition unit is used for acquiring data information of the compulsory isolation drug rehabilitation personnel from a business system and asecurity system of the compulsory isolation drug rehabilitation station; The data analysis unit performs model learning according to the data information of the known personnel to obtain a learning model, and utilizes the learning model to predict the abnormal behavior of the to-be-predicted personnel to obtain a prediction result; And the data application unit is used as a related response according to the prediction result. According to the method, the behavior feature integrated learning model is constructed based on the big data, so that accurate prediction and alarming are carried out onabnormal behaviors of the forced isolation drug rehabilitation personnel, occurrence of the abnormal behaviors of the forced isolation drug rehabilitation personnel is effectively prevented, and the safety protection and personnel supervision level of the forced isolation drug rehabilitation personnel are improved.

Description

technical field [0001] The present invention relates to the technical field of prediction and analysis based on big data, in particular to a system for predicting abnormal behavior of people who are forcibly isolated and rehabilitated based on big data. Background technique [0002] Compulsory isolation and detoxification personnel are prone to escape, suicide, violence, destruction and other unknown and abnormal behaviors that cannot be judged. These unknown and abnormal behaviors that cannot be judged have brought unprecedented challenges to the safety and stability of the drug treatment system and personnel supervision, and have also become the informationization of the drug treatment system. Issues that must be addressed in construction. [0003] At present, the evaluation of abnormal behaviors of compulsory isolation drug rehabilitation personnel is mainly conducted through manual experience evaluation, psychological test scale evaluation, and single classification mode...

AI Technical Summary

Problems solved by technology

[0002] Compulsory isolated detoxification personnel are prone to unknown and abnormal behaviors such as escape, suicide, violence, and destruction that cannot be judged. These unknown and abnormal behaviors that cannot be judged have brought unprecedented challenges to the safety and stability of the detoxification system and personnel supervision. Issues that must be solved in construction

[0003] At present, the evaluation of abnormal behaviors of persons in compulsory isolation and detoxification is mainly carried out by means of manual experience evaluation, psychological test scale evaluation, and single classification model evaluation. 1. Accurately predict abnormal behaviors; 2. The category of predicted abnormal behaviors is not subdivided, which is not conducive to the police to take targeted measures to prevent the occurrence of different abnormal behaviors; 3. The classification of abnormal behaviors relies heavily on artificially designed indicators. poor predictive performance

Therefore, it is difficult to achieve the ideal classification accuracy and stability for the current evaluation methods for the abnormal behavior of the compulsory isolation drug rehabilitation personnel.

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