| 于慧鹏,马新新,施会玲.灰色 GM(1,1)预测模型在特种设备安全事故状况预测中的应用[J].安徽建筑大学学报,2021,29(): |
| 灰色 GM(1,1)预测模型在特种设备安全事故状况预测中的应用 |
| Application of Grey Prediction Model GM(1,1) in Prediction of Special Equipment Safety Accidents |
| 投稿时间：2021-01-18 修订日期：2021-03-12 |
| DOI： |
| 中文关键词: 特种设备 安全事故预测 二阶弱化因子 GM(1,1)预测 |
| 英文关键词: special equipment safety accident prediction second order weakening factor GM(1,1)prediction |
| 基金项目:安徽省教育厅科学研究项目(SK 2019JD01) |
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| 中文摘要: |
| 依据2007年—2016年全国特种设备安全状况数据(安全事故总量、受伤人数、死亡人数等)作为初始数据建立GM(1,1)预测模型,并用2017年—2019年的数据进行验证。引入二阶弱化因子D^2对传统GM(1,1)预测模型进行改进,以适应初始数据震荡变化趋势,提高模拟精准度。结果表明改进后的预测模型的精准度符合实际要求,能够在一定程度上反映特种设备安全状况,同时为统筹特种设备安全工作提供方向,并提出特种设备安全管理措施,对政府有关部门在安全事故预防及措施制定上具有一定的现实参考价值。 |
| 英文摘要: |
| Based on the national special equipment safety data (total number of safety accidents, number of injured, number of dead, etc.) from 2007 to 2016 as the initial data, the prediction model GM(1,1) is established and verified with the data from 2017 to 2019. Second order weakening factor D^2 is introduced to improve the traditional prediction model GM(1,1) to adapt to the fluctuation trend of initial data and improve the simulation accuracy. The results show that the accuracy of the improved prediction model is in line with the actual requirements, which can reflect the safety status of special equipment to a certain extent, provide direction for coordinating the safety work of special equipment, and put forward the safety management measures of special equipment, which has a certain practical reference value for the relevant government departments in the prevention of safety accidents and the formulation of measures. |
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