CAJ | 학술논문

针对军用无人机研制费用预测样本数据缺乏、影响因素复杂的问题,利用Gram-Schmidt回归方法提取无人机研制费用预测的关键参数,给出了基于Gram-Schmidt回归的军用无人机研制费用预测模型和算法步骤。利用样本数据进行检验,并与逐步多元回归、人工神经网络和偏最小二乘等预测方法进行了比较。结果表明Gram-Schmidt回归方法用于军用无人机研制费用预测具有实用性和优越性。
침대군용무인궤연제비용예측양본수거결핍、영향인소복잡적문제,이용Gram-Schmidt회귀방법제취무인궤연제비용예측적관건삼수,급출료기우Gram-Schmidt회귀적군용무인궤연제비용예측모형화산법보취。이용양본수거진행검험,병여축보다원회귀、인공신경망락화편최소이승등예측방법진행료비교。결과표명Gram-Schmidt회귀방법용우군용무인궤연제비용예측구유실용성화우월성。
In this paper,cost prediction of developing a military uninhabited air vehicle（ UAV） is addressed with the fact that the sample data are scarce. To overcome the difficulty resulting from the scarce sample data,Gram-Schmidt regression method is utilized to extract the key parameters. Based on the results obtained by Gram-Schmidt regression,the model and algorithm for predicting military UAV development cost are presented. By exploiting the limited sample data,an instantiated prediction model is built and tested. The proposed method is compared with Sequential Multivariable Regression,Artificial Neural Network,and Partial Least Squares. Results demonstrate the practicability and superiority of applying Gram-Schmidt regression method to the prediction of developing military UAV cost.