工程设计学报Issue(5)：412-419,8.DOI:10.3785/j.issn.1006-754X.2015.05.002
构建起重机载荷谱v-SVRM预测模型的改进方法
Improved modeling method for prediction model of crane load spectrum based on support vector regression machine
摘要
Abstract
The load spectrum simulation of actual working status is the key factor to solve the problem of crane endurance failure . T he precision and robustness of load spectrum predicting have great significance for reliability analysis of crane fatigue fracture and evaluation of its safety life .However ,the predicting performance of classic linear regression model is weaker .Compared with other data analysis algorithms ,support vector regression machine (SVRM ) has excellent performance for small sample and nonlinear properties ,including higher prediction accuracy and nice robustness .It can also overcome the difficulty of the curse of dimensionality ,local minima and over‐fitting and under‐fitting for traditional pattern recognition methods .So ,accuracy pre‐diction precision and reliability can be obtained by using SVRM .Furthermore ,an improved v‐SVRM prediction model was established with constructing new kernel function and decision func‐tion .T he results of engineering application show ed that the values of Er and of RMSRE all the three models (the BP neural network model and the SVRM model and the modified model of v‐SVRM ) gradually decreased while the fitting degrees R2 gradually increased .It proves that the modified method has higher prediction precision and nicer robustness and it also provides a new way for ob‐taining and predicting crane load spectrum .关键词
v-支持向量回归机/核函数/决策函数/载荷谱Key words
v-SVRM/kernel function/decision function/load spectrum分类
机械制造引用本文复制引用
陆凤仪,王爽,徐格宁,戚其松..构建起重机载荷谱v-SVRM预测模型的改进方法[J].工程设计学报,2015,(5):412-419,8.基金项目
“十二五”国家科技支撑计划资助项目（2011BAK06B05-05）；山西省研究生创新项目（201214502）． （）
