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  • Open Access


    Safety Assessment of Liquid Launch Vehicle Structures Based on Interpretable Belief Rule Base

    Gang Xiang1,2, Xiaoyu Cheng3, Wei He3,4,*, Peng Han3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 273-298, 2023, DOI:10.32604/csse.2023.037892

    Abstract A liquid launch vehicle is an important carrier in aviation, and its regular operation is essential to maintain space security. In the safety assessment of fluid launch vehicle body structure, it is necessary to ensure that the assessment model can learn self-response rules from various uncertain data and not differently to provide a traceable and interpretable assessment process. Therefore, a belief rule base with interpretability (BRB-i) assessment method of liquid launch vehicle structure safety status combines data and knowledge. Moreover, an innovative whale optimization algorithm with interpretable constraints is proposed. The experiments are carried out based on the liquid launch… More >

  • Open Access


    Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

    Xiaoyu Cheng1, Mingxian Long1, Wei He1,2,*, Hailong Zhu1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2821-2844, 2023, DOI:10.32604/csse.2023.037330

    Abstract Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base. The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model. However, due to the complexity of the milling system structure and the uncertainty of the milling failure index, it is often impossible to construct model expert knowledge effectively. Therefore, a milling system fault detection method based on fault tree analysis and hierarchical BRB (FTBRB) is proposed. Firstly, the proposed method uses a fault tree and hierarchical BRB modeling. Through fault tree analysis (FTA),… More >

  • Open Access


    A New Prediction System Based on Self-Growth Belief Rule Base with Interpretability Constraints

    Yingmei Li, Peng Han, Wei He*, Guangling Zhang, Hongwei Wei, Boying Zhao

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3761-3780, 2023, DOI:10.32604/cmc.2023.037686

    Abstract Prediction systems are an important aspect of intelligent decisions. In engineering practice, the complex system structure and the external environment cause many uncertain factors in the model, which influence the modeling accuracy of the model. The belief rule base (BRB) can implement nonlinear modeling and express a variety of uncertain information, including fuzziness, ignorance, randomness, etc. However, the BRB system also has two main problems: Firstly, modeling methods based on expert knowledge make it difficult to guarantee the model’s accuracy. Secondly, interpretability is not considered in the optimization process of current research, resulting in the destruction of the interpretability of… More >

  • Open Access


    A New Model for Network Security Situation Assessment of the Industrial Internet

    Ming Cheng1, Shiming Li1,3,*, Yuhe Wang1, Guohui Zhou1, Peng Han1, Yan Zhao2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2527-2555, 2023, DOI:10.32604/cmc.2023.036427

    Abstract To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the projection covariance matrix adaptive evolution… More >

  • Open Access


    A Novel Belief Rule-Based Fault Diagnosis Method with Interpretability

    Zhijie Zhou1, Zhichao Ming1,*, Jie Wang1, Shuaiwen Tang1, You Cao1, Xiaoxia Han1, Gang Xiang2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1165-1185, 2023, DOI:10.32604/cmes.2023.025399

    Abstract Fault diagnosis plays an irreplaceable role in the normal operation of equipment. A fault diagnosis model is often required to be interpretable for increasing the trust between humans and the model. Due to the understandable knowledge expression and transparent reasoning process, the belief rule base (BRB) has extensive applications as an interpretable expert system in fault diagnosis. Optimization is an effective means to weaken the subjectivity of experts in BRB, where the interpretability of BRB may be weakened. Hence, to obtain a credible result, the weakening factors of interpretability in the BRB-based fault diagnosis model are firstly analyzed, which are… More > Graphic Abstract

    A Novel Belief Rule-Based Fault Diagnosis Method with Interpretability

  • Open Access


    A WSN Node Fault Diagnosis Model Based on BRB with Self-Adaptive Quality Factor

    Guo-Wen Sun1, Gang Xiang2,3, Wei He1,4,*, Kai Tang1, Zi-Yi Wang1, Hai-Long Zhu1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1157-1177, 2023, DOI:10.32604/cmc.2023.035667

    Abstract Wireless sensor networks (WSNs) operate in complex and harsh environments; thus, node faults are inevitable. Therefore, fault diagnosis of the WSNs node is essential. Affected by the harsh working environment of WSNs and wireless data transmission, the data collected by WSNs contain noisy data, leading to unreliable data among the data features extracted during fault diagnosis. To reduce the influence of unreliable data features on fault diagnosis accuracy, this paper proposes a belief rule base (BRB) with a self-adaptive quality factor (BRB-SAQF) fault diagnosis model. First, the data features required for WSN node fault diagnosis are extracted. Second, the quality… More >

  • Open Access


    A Processor Performance Prediction Method Based on Interpretable Hierarchical Belief Rule Base and Sensitivity Analysis

    Chen Wei-wei1, He Wei1,2,*, 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 >

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