Research on predicting insulation performance of vacuum glass based on belief rule base with attribute reliability

Vacuum glass is an energy-efficient material with exceptional insulation performance. In order to quantify this property, a prediction method based on belief rule base (BRB) is proposed. In the process of collecting temperature-related data of vacuum glass, environmental interference factors will affect the accuracy of input information, resulting in limited accuracy of the generated belief degree. To solve this challenge, a BRB prediction model considering attribute reliability (BRB-r) is proposed. By calculating the reliability of each attribute and incorporating it into the matching degree calculation, the negative influence of environmental interference factors on the prediction model is effectively reduced.