A New Belief Rule Base Model With Attribute Reliability

In current studies of the belief rule base (BRB) model, the attributes are assumed to be fully reliable and the observation data are directly used as input. However, in engineering practice, the observation data may be affected by some disturbance factors, including the quality of the sensors and noise in the environment. Then, the reliability of observation data may be affected and the modeling accuracy of the BRB is therefore influenced. As such, a new BRB model with attribute reliability (BRB-r) is proposed in this paper. In particular, a calculation method of attribute reliability is given based on the statistical method. Moreover, to integrate the attribute reliability into the BRB-r, a new calculation method of matching degree is developed. The model's overall reliability denotes its ability to provide the correct result. When the attributes are unreliable, the overall reliability of the BRB-r is degraded. Thus, a calculation method for the overall reliability of the BRB-r is developed to support decision-making in engineering practice. A case study of the safety assessment of a diesel engine is conducted to demonstrate the efficiency of the proposed BRB-r model.