Open AccessForecast of Development Cost of Missile Equipment Based on Partial Least Squares
Author(s) -
Qiaoyang Li,
Guiming Chen,
Ziqi Li,
Boxuan Fan
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032162
Subject(s) - partial least squares regression , missile , multivariate statistics , bayesian multivariate linear regression , linear regression , regression analysis , canonical correlation , computer science , sample (material) , regression , component (thermodynamics) , least squares support vector machine , statistics , data mining , support vector machine , mathematics , engineering , artificial intelligence , machine learning , chemistry , physics , chromatography , thermodynamics , aerospace engineering
Due to the complex and diverse influencing factors of the missile equipment development cost forecast and the lack of data, taking into account the partial least squares regression method (PLS) can perform main component analysis, canonical correlation analysis, and multiple regression on variables, and handle multiple linear correlations. The small sample multivariate data has the advantage of high accuracy, and a missile equipment development cost prediction model based on the partial least square method is established. Compared with multiple linear regression, least squares support vector machine and other methods, the results show the effectiveness of the model.