KFFM-based Large-scale Project Earned Value Management Completion Prediction

摘要：

　　Earned value management lacks research on the project completion trend forecasting method at the following two points: The project completion trend forecast is based on the state indicators at the project monitoring point,and the project execution efficiency before the monitoring time point is rarely considered; the project performance evaluation index How to reduce the non-efficiency noise caused by uncontrollable factors in the existing prediction methods when singularities occur.The above issues will affect the accuracy and stability of the earned value management forecasting system.This paper attempts to introduce the Kalman filtering method(KFFM)into the earned value management completion prediction calculation,and comprehensively considers the project execution efficiency in the logical order of “prediction-measure-correction,and improves the prediction accuracy through dynamic correction of cost/progress indicators.And effectively reduce the impact of the earned value management forecasting system due to singularities.

关键词： Earned value method Kalman filtering forecasting method Forecast Optimizing

作者: Ge-di JI Yi-dan WANG Jing-jing LI

作者单位: School of Economics and Management,Inermongolia Industrial University,Hohhot 010051,China

会议类型: 国际会议

会议名称: 2019 International Conference on Informatics, Control and Robotics 2019信息学、控制和机器人学国际会议(ICICR2019)

会议地点: 上海

会议语种:英文

页码: 423-428

在线出版日期: 2019-06-16（万方平台首次上网日期，不代表论文的发表时间）