Zhihui Xu¹, Shuwen Shang², Yuntong Pu³, Xiaoyan Su^2,*, Hong Qian², Xiaolei Pan²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2597-2617, 2024, DOI:10.32604/cmes.2023.031247

Abstract Cognitive Reliability and Error Analysis Method (CREAM) is widely used in human reliability analysis (HRA). It defines nine common performance conditions (CPCs), which represent the factors that may affect human reliability and are used to modify the cognitive failure probability (CFP). However, the levels of CPCs are usually determined by domain experts, which may be subjective and uncertain. What’s more, the classic CREAM assumes that the CPCs are independent, which is unrealistic. Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation. To address the issue… More > Graphic Abstract

Raghunathan Krishankumar¹, Dhruva Sundararajan², K. S. Ravichandran², Edmundas Kazimieras Zavadskas^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2845-2872, 2024, DOI:10.32604/cmes.2023.029438

Abstract Hydrogen is the new age alternative energy source to combat energy demand and climate change. Storage of hydrogen is vital for a nation’s growth. Works of literature provide different methods for storing the produced hydrogen, and the rational selection of a viable method is crucial for promoting sustainability and green practices. Typically, hydrogen storage is associated with diverse sustainable and circular economy (SCE) criteria. As a result, the authors consider the situation a multi-criteria decision-making (MCDM) problem. Studies infer that previous models for hydrogen storage method (HSM) selection (i) do not consider preferences in the natural language form; (ii) weights… More >

Qing Xia¹, Yonghua Li^2,*, Dongxu Zhang², Yufeng Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1769-1794, 2024, DOI:10.32604/cmes.2023.030724

Abstract For high-reliability systems in military, aerospace, and railway fields, the challenges of reliability analysis lie in dealing with unclear failure mechanisms, complex fault relationships, lack of fault data, and uncertainty of fault states. To overcome these problems, this paper proposes a reliability analysis method based on T-S fault tree analysis (T-S FTA) and Hyper-ellipsoidal Bayesian network (HE-BN). The method describes the connection between the various system fault events by T-S fuzzy gates and translates them into a Bayesian network (BN) model. Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation, a reliability modeling method… More >

Xu Zhang¹, Jianchao Ni², Juxi Hu^3,*, Weisi Chen⁴

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1947-1960, 2023, DOI:10.32604/csse.2023.035118

Abstract Structural reliability is an important method to measure the safety performance of structures under the influence of uncertain factors. Traditional structural reliability analysis methods often convert the limit state function to the polynomial form to measure whether the structure is invalid. The uncertain parameters mainly exist in the form of intervals. This method requires a lot of calculation and is often difficult to achieve efficiently. In order to solve this problem, this paper proposes an interval variable multivariate polynomial algorithm based on Bernstein polynomials and evidence theory to solve the structural reliability problem with cognitive uncertainty. Based on the non-probabilistic… More >

Yujun Su¹, Xianghao Gao², Hong Qian², Xiaoyan Su^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 201-214, 2022, DOI:10.32604/cmes.2022.020541

Abstract Human Reliability Analysis (HRA) is an important part in safety assessment of a large complex system. Human Cognitive Reliability (HCR) model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time, which is widely used in HRA. In the application of this method, cognitive patterns of humans are required to be considered and classified, and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain. How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy… More >

Changting Shi^{1, *}

CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 635-652, 2018, DOI:10.32604/cmc.2018.03754

Abstract In the last decade, IoT has been widely used in smart cities, autonomous driving and Industry 4.0, which lead to improve efficiency, reliability, security and economic benefits. However, with the rapid development of new technologies, such as cognitive communication, cloud computing, quantum computing and big data, the IoT security is being confronted with a series of new threats and challenges. IoT device identification via Radio Frequency Fingerprinting (RFF) extracting from radio signals is a physical-layer method for IoT security. In physical-layer, RFF is a unique characteristic of IoT device themselves, which can difficultly be tampered. Just as people’s unique fingerprinting,… More >

Kehua Yang^1,2,*, Tian Tan¹, Wei Zhang¹

CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 269-281, 2018, DOI:10.32604/cmc.2018.03696

Abstract Dempster-Shafer (D-S) evidence theory is a key technology for integrating uncertain information from multiple sources. However, the combination rules can be paradoxical when the evidence seriously conflict with each other. In the paper, we propose a novel combination algorithm based on unsupervised Density-Based Spatial Clustering of Applications with Noise (DBSCAN) density clustering. In the proposed mechanism, firstly, the original evidence sets are preprocessed by DBSCAN density clustering, and a successfully focal element similarity criteria is used to mine the potential information between the evidence, and make a correct measure of the conflict evidence. Then, two different discount factors are adopted… More >