Forecast of safety situation in construction industry based on composite model

摘要：

　　Forecast of production safety situation in construction industry is a complicated non-linear problem,whose evolutional process has apparent randomness and volatility.According to the data of production safety situation in construction industry between 2010 and 2011,the back-propagation neural network model,the moving average model and the exponential smoothing model are adopted to predict,respectively.Combined with the characteristics of the three forecast models,a new forecast model with non-negative weights is proposed.Comparison with practical situation indicates that the proposed forecast model can overcome the shortcomings of the single forecast model and solve the forecast difficulties caused by safety indicators under random system states.The studied results shows that the proposed composite model with non-negative weights is feasible for the forecast of production safety situation in construction industry.

关键词： neural network moving average model exponential smoothing model composite forecasting non-negative weights safety indicators

作者: XU Yabo WANG Tong SONG Bingxue PANG Lei XIE Yushu

作者单位: Beijing Municipal Institute of Labour Protection,Beijing 100054,China

会议类型: 国际会议

会议名称: 2012 International Symposium on Safety Science and Technology (2012安全科学与技术国际会议)

会议地点: 南京

会议语种:英文

页码: 119-124

在线出版日期: 2012-10-23（万方平台首次上网日期，不代表论文的发表时间）