Project cycle budget evaluation based on least squares

Wentao Dong; Xiaowei Zhang; Yucal Dong

doi:10.1117/12.2692814

23 August 2023 Project cycle budget evaluation based on least squares

Wentao Dong, Xiaowei Zhang, Yucal Dong

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 1278415 (2023) https://doi.org/10.1117/12.2692814
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

The least squares polynomial fitting algorithm is used to establish an evaluation model of the project cycle, including the determination of the mean absolute error test by determining the function class, solving the least squares term, and determining the mean absolute error test, etc. Based on the previous project cycle history data, the fitting functions of the normal production cycle, the shortest production cycle, the normal inspection cycle, and the emergency inspection cycle of a project product are fitted, and the MAE method is used to determine the fitted The mean absolute error of the fitted curve is compared with the corresponding cycle prediction results, which confirms the accuracy and reliability of the model based on the least squares polynomial prediction and provides a more scientific calculation model to promote the development of weapons and equipment production and accurately assess the production cycle.

Citation Download Citation

Wentao Dong, Xiaowei Zhang, and Yucal Dong "Project cycle budget evaluation based on least squares", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 1278415 (23 August 2023); https://doi.org/10.1117/12.2692814

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