An XGBoost-Based Effectiveness Prediction Method of Equipment System-of-Systems
ZHU Song1， QIAN Xiaochao2， LU Yingbo2， LIU Fei1
1. School of Software Engineering， South China University of Technology， Guangzhou 510006， Guangdong， China； 2. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China
Abstract：Aiming at the problem of equipment system-of-systems effectiveness prediction, an equipment system-of-systems effectiveness prediction method based on extreme gradient boosting （XGBoost） is proposed. First, the effectiveness prediction process based on XGBoost is given. Then XGBoost is used to establish a nonlinear mapping model between these indicators and effectiveness to realize the prediction of equipment system-of-systems effectiveness. In the process of model construction, the grid search is used to determine the optimal parameters of the model, which avoids the blindness of artificial setting. Taking the effectiveness prediction of a certain air-defense missile weapon system as an example, the above-proposed method is validated.
