Chen Wei-wei¹, He Wei^1,2,*, Zhu Hai-long¹, Zhou Guo-hui¹, Mu Quan-qi¹, Han Peng¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6119-6143, 2023, DOI:10.32604/cmc.2023.035743

Abstract The prediction of processor performance has important reference significance for future processors. Both the accuracy and rationality of the prediction results are required. The hierarchical belief rule base (HBRB) can initially provide a solution to low prediction accuracy. However, the interpretability of the model and the traceability of the results still warrant further investigation. Therefore, a processor performance prediction method based on interpretable hierarchical belief rule base (HBRB-I) and global sensitivity analysis (GSA) is proposed. The method can yield more reliable prediction results. Evidence reasoning (ER) is firstly used to evaluate the historical data of the processor, followed by a… More >

Shufang Song^*, Lu Wang, Yuhua Yan

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 383-399, 2020, DOI:10.32604/cmes.2020.09588

Abstract The robust design optimization (RDO) is an effective method to improve product performance with uncertainty factors. The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables. There are some important issues in RDO, such as how to judge robustness, deal with multi-objective problem and black-box situation. In this paper, two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment. The robustness measure based on maximum entropy is proposed. Weighted sum method is improved to deal with the objective function, and the basic framework of… More >