基于PSO/SVM的地铁车站安全态势预测模型研究

Yong Qin, Zhenyu Zhang, Bo Chen, Z. Xing, Jing Liu, Jun Li
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引用次数: 3

摘要

安全态势感知是一种新的安全技术。本文将其引入地铁车站安全态势评估,为保障乘客安全和地铁车站运营提供了一种新的途径。本文通过大量的研究和分析,建立了安全态势感知评价指标体系,并建立了基于粒子群算法/支持向量机的地铁车站安全态势预测模型。通过实例分析,发现该模型具有较高的准确率,能够准确预测未来地铁车站的安全状况,具有一定的实用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Prediction Model for the Security Situation of Metro Station Based on PSO/SVM
Security situation awareness is a new technology about security. This paper brings it to the assessment of security situation of metro station which serves as a new way to secure the security of passengers as well as the operation of the metro station. This paper sets up an index system for assessing the security situation awareness and makes a prediction model for the security situation of metro station based on PSO/SVM after doing lots of researches and analyses. Furthermore, through case studies, we find that the model has high accuracy and ability to accurately predict the security situation of metro station in the future and a certain practical value.
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