Accurate prediction of photovoltaic (PV) output power is of great significance for reasonable scheduling and development management of power grids. In PV power generation prediction system, there are two problems: the uncertainty of PV power generation and the inexplicability of the prediction result. The belief rule base (BRB) is a rule-based modeling method and can deal with uncertain information. Moreover, the modeling process of BRB has a certain degree of interpretability. However, rule explosion and the inexplicability of the optimized model limit the modeling ability of BRB in complex systems. Thus, a PV output power prediction model is proposed based on a deep belief rule base with interpretability (DBRB-I). In the DBRB-I model, the deep BRB structure is constructed to solve the rule explosion problem, and inefficient rules are simplified by a sensitivity analysis of the rules, which reduces the complexity of the model. Moreover, to ensure that the interpretability of the model is not destroyed, a new optimization method based on the projection covariance matrix adaptation evolution strategy (P-CMA-ES) algorithm is designed. Finally, a case study of the prediction of PV output power is conducted to illustrate the effectiveness of the proposed method.
Accurately predicting the capacity of lithium battery is conducive to improving its safety. Affected by complex internal electrochemical reaction and external use conditions, the prediction accuracy is difficult to guarantee; at the same time, the existing prediction methods are unexplainable, resulting in the inability to trace the prediction process. Therefore, a capacity prediction model based on belief rule base with interpretability and interval optimization strategy is proposed in this paper. First, the reasoning process is designed according to interpretability modeling criteria. Second, to achieve a balance of accuracy and interpretability, based on the whale optimization algorithm, a model parameter optimization method using interval optimization strategy is proposed. Finally, through a case study, the model's effectiveness is verified. Comparison with other models shows that the proposed model has certain advantages in accuracy and interpretability.
Combination rule explosion problem of belief rule base (BRB) is a difficult problem to solve in complex systems and has attracted wide attention at present. Aiming at the problem of combination rule explosion in belief rule base, a new interval constructed belief rule base with rule reliability (IBRB-r) is proposed. On the basis of BRB, IBRB-r innovatively introduced rule reliability and established the belief table in the form of interval. This approach can not only clearly indicate the contribution degree of each rule to the model but also solve the problem of combination rule explosion. Therefore, IBRB-r is more suitable for complex system modeling. In the case study section, the structural safety assessment of liquid launch vehicle is introduced to conduct a concrete example analysis. The experimental results show that the proposed model is effective and accurate.
Rolling Bearing is a key component of the transmission of rotating machinery, and it is widely used in industrial fields. Therefore, it is of vital importance to evaluate the performance and reliability of rolling bearing. Aiming at the interference problems faced by rolling bearings during operation, a performance evaluation model based on the evidential reasoning (ER) rule is proposed in this article. Firstly, the time domain and frequency domain characteristic indicators of bearing vibration signals are taken as evaluation indicators, and the evaluation system is constructed. Secondly, various indicator information is unified into a belief structure, and the reliability and the weight of the indicators are fully considered in the ER rule. Thirdly, to simulate the complex working environment of rolling bearings, the perturbation analysis method is adopted. After determining the maximum perturbation error and perturbation coefficient, the performance reliability of the rolling bearing is analysed, and a performance reliability evaluation model considering perturbation is proposed. Finally, based on the whole-life open data set of rolling bearing from the University of Cincinnati, the validity and reliability of the proposed model are verified in performance analysis.
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