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VACUUM ›› 2023, Vol. 60 ›› Issue (5): 55-59.doi: 10.13385/j.cnki.vacuum.2023.05.08

• Thin Film • Previous Articles     Next Articles

Prediction of Vacuum Glass Insulation Performance Based on Random Forest

WANG Yuan-qi1, HU Yang-gang2, WANG Lei2   

  1. 1. Funky-tech(Shenzhen) Co., Ltd., Shenzhen 518000, China;
    2. State Key Lab of Marine Resource Utilisation in South China Sea, College of Information and Communication Engineering, Hainan University, Haikou 570228, China
  • Received:2021-10-28 Online:2023-09-25 Published:2023-09-26

Abstract: The thermal insulation performance of vacuum glass is closely related to the heat transfer coefficient. However, due to the interference of various uncertain factors such as environmental factors and the heat source temperature of measuring instruments, the thermal conductivity of vacuum glass in industrial circles is difficult to measure, which greatly reduces the production efficiency and production accuracy. By constructing the random forest algorithm model, the heat transfer coefficient of vacuum glass was predicted, and the results were evaluated by mean squared error(MSE). The results show that the MSE is 0.004148, the random forest algorithm is the most suitable algorithm for this experiment, and has a good prediction effect on the heat transfer coefficient of vacuum glass. The effects of environmental factors and dominant factors on the predicted results are obtained through the analysis of characteristic importance. By applying the intelligent algorithm to the production of vacuum glass, the measurement time is shortened from a few hours to 5min.

Key words: vacuum glass, thermal insulation performance, heat transfer coefficient, random forest

CLC Number:  TB43;TB71+3

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