Study on the method of forecasting casualty in building construction based on SVM

被引：0

作者：

Li, Shu-Quan ^{[1
]}

Feng, Li-Jun ^{[1
,2
]}

Fan, Li-Xia ^{[3
]}

Ma, Lan ^{[4
]}

Gao, Qiu-Li ^{[4
]}

机构：

[1] Tianjin Univ Finance & Econ, Tianjin 300222, Peoples R China

[2] Univ Agr, Sch Urban & Rural Construct, Hebei, Peoples R China

[3] Baoding Bur Bldg Construct Safety Supervis Heibei, Hebei 07100, Peoples R China

[4] Construct Grp Ltd Corp, Hebei, Peoples R China

来源：

PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年

关键词：

building; safety; forecast; support vector machine;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：3547 / +

页数：2