Suneel Kumar Rath¹, Madhusmita Sahu¹, Shom Prasad Das², Junali Jasmine Jena³, Chitralekha Jena⁴, Baseem Khan^5,6,7,*, Ahmed Ali⁷, Pitshou Bokoro⁷

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1513-1536, 2024, DOI:10.32604/csse.2024.057067 - 22 November 2024

Abstract Redundancy, correlation, feature irrelevance, and missing samples are just a few problems that make it difficult to analyze software defect data. Additionally, it might be challenging to maintain an even distribution of data relating to both defective and non-defective software. The latter software class’s data are predominately present in the dataset in the majority of experimental situations. The objective of this review study is to demonstrate the effectiveness of combining ensemble learning and feature selection in improving the performance of defect classification. Besides the successful feature selection approach, a novel variant of the ensemble learning… More >

Muhammad Azhar Ali Khan¹, Syed Sohail Akhtar^2,3,*, Abba A. Abubakar^2,4, Muhammad Asad¹, Khaled S. Al-Athel^2,5

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2325-2350, 2024, DOI:10.32604/cmes.2024.054741 - 31 October 2024

Abstract The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations. The optimization of the mold is carried out using MAGMASoft mainly based on porosity reduction as a response. After validating the initial mold design with experimental data, a spring flap, a common component of an automotive suspension system is designed and optimized followed by fatigue life prediction based on simulation using Fe-safe. By taking into consideration the variation in both stress and strength, the stress-strength model is used… More >

Yunwen Feng¹, Zhicen Song^1,*, Cheng Lu²

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1925-1942, 2023, DOI:10.32604/cmes.2022.022680 - 20 September 2022

Abstract To effectively predict the mechanical dispatch reliability (MDR), the artificial neural networks method combined with aircraft operation health status parameters is proposed, which introduces the real civil aircraft operation data for verification, to improve the modeling precision and computing efficiency. Grey relational analysis can identify the degree of correlation between aircraft system health status (such as the unscheduled maintenance event, unit report event, and services number) and dispatch release and screen out the most closely related systems to determine the set of input parameters required for the prediction model. The artificial neural network using radial… More >

Xueping Fan^*, Guanghong Yang, Zhipeng Shang, Xiaoxiong Zhao, Yuefei Liu^*

Structural Durability & Health Monitoring, Vol.15, No.1, pp. 69-83, 2021, DOI:10.32604/sdhm.2021.011922 - 22 March 2021

Abstract This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder. Firstly, multivariate Bayesian dynamic linear model (MBDLM) considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections; secondly, with the proposed MBDLM, the dynamic correlation coefficients between any two performance functions can be predicted; finally, based on MBDLM and Gaussian copula technique, a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder, and the monitoring extreme deflection data from an actual bridge is provided to More >

Kavita Sahu¹, Fahad A. Alzahrani², R. K. Srivastava¹, Rajeev Kumar^3,4,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1471-1488, 2021, DOI:10.32604/cmc.2021.014868 - 05 February 2021

Abstract Maintaining software reliability is the key idea for conducting quality research. This can be done by having less complex applications. While developers and other experts have made significant efforts in this context, the level of reliability is not the same as it should be. Therefore, further research into the most detailed mechanisms for evaluating and increasing software reliability is essential. A significant aspect of growing the degree of reliable applications is the quantitative assessment of reliability. There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software. However,… More >