Title :
Study on the Method of Forecasting Casualty in Building Construction Based on SVM
Author :
Li, Shu-quan ; Feng, Li-jun ; Fan, Li-xia ; Ma, Lan ; Gao, Qiu-li
Author_Institution :
Tianjin Univ. of Finance & Econ.
Abstract :
In view of the shortage of building safety data and the difficulty to collect them, we propose a new forecasting method based on support vector machine in this paper. We analyze some casualty data and construct a forecasting model with the method of support vector machine. The experiments prove that the method has advantages of lower error in simulation and higher precision in forecasting comparing with artificial neural network (back propagation, BP). So it has a variety of application in the field
Keywords :
building; construction industry; forecasting theory; occupational safety; statistical analysis; support vector machines; SVM; artificial neural network; back propagation; building construction; building safety data; casualty data; forecasting method; support vector machine; Accidents; Appraisal; Buildings; Construction industry; Economic forecasting; Expert systems; Personnel; Predictive models; Safety; Support vector machines; Building; Forecast; Safety; Support vector machine;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258549
