Calculation of coating consumption quota for ship painting: a CS-GBRT approach

Autor: Zhuwen Yan, Lei Li, Henan Bu, Yuan Xin, Ji Xingyu, Han Ziyan
Rok vydání: 2020
Předmět:
Zdroj: Journal of Coatings Technology and Research. 17:1597-1607
ISSN: 1935-3804
1547-0091
DOI: 10.1007/s11998-020-00376-7
Popis: This paper focuses on the prediction of the coating amount before the construction of ship painting, i.e., the calculation of coating consumption quota. At present, each shipyard uses a larger coating loss coefficient to calculate the coating consumption quota; after the construction, there is often a lot of inventory left, which is not conducive to the scientific management of the ship coating process and the cost control of shipbuilding. Therefore, this paper proposes a coating consumption prediction method based on ensemble learning, using cosine similarity and gradient boosting regression tree hybrid algorithm (CS-GBRT) to calculate the coating loss coefficient under different working conditions. Cosine similarity is used to select similar data with less difference from the target to be predicted as the training set, and the loss function in GBRT is improved based on similarity weight to improve the prediction performance and calculation accuracy of GBRT. The coating data recorded by a shipyard from 2014 to 2019 are randomly selected to evaluate the prediction ability of the model established in the paper. The results show that when the proposed CS-GBRT algorithm is used to calculate the coating loss coefficient, the mean absolute error of training set and test set are both
Databáze: OpenAIRE
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