摘要
公路施工企业内部定额是反映企业管理水平的重要指标,但现有的测算方法大都消除了原始数据中的粗大误差和系统误差,对数据中存在的随机误差却束手无策,由于公路工程施工环境多变,随机误差对数据的波动影响很大,严重地影响定额水平的测定.为减少原始数据对定额水平的影响,文章根据现场采集数据,基于卡尔曼滤波原理,以观测时长作为一个统计周期,将每次的定额消耗量作为观测值,通过预测和校正过程对原始数据进行过滤,以减少基础数据的偏差.以贵州交通建设集团有限公司的内部数据,对该方法进行检验,结果表明:基于卡尔曼滤波的企业定额测算方法能够消除随机误差的影响,提高定额的编制精度,使定额水平更加符合实际.
The highway construction enterprise quota is an important index to reflect the level of enterprise management,but most of the existing calculation methods ignore the gross error and system error in the original data,incapable of random error action on the data.Because the highwayengineering construction environment is changeable,the random error has a great influence on the fluctuation of the data and seriously affects the measurement of the quota level.In order to decrease the error of quota derived from the raw data,this paper proposed the Kalman filter to filter the raw data by regarding the actual matter consumption of every observation duration as observation value,and regarding a observation time as the discrete time phase.After predicting and verifying,we test the method based on the internal data of Guizhou communications construction group co.Ltd.,the testing result shows this method can eliminate the effects of random errors and improve the accuracy of quota,and make the level of quota more in accordance with the actual situation.
作者
田丰
臧晓冬
欧阳凤
罗强
TIAN Feng;ZANG Xiao-dong;OUYANG Feng;LUO Qiang(School of Civil Engineering,Guangzhou University,Guangzhou 510006;Guizhou Communications Construction Group CO.,LTD,Guiyang 550000,China)
出处
《广州大学学报（自然科学版）》
CAS
2018年第1期54-58,共5页
Journal of Guangzhou University:Natural Science Edition
关键词
企业定额
随机误差
卡尔曼滤波
公路施工
quota of company
random error
Kalman filter
highway construction
