Behnaz Alafchi¹, Leili Tapak^1,*, Hassan Doosti², Christophe Chesneau³, Ghodratollah Roshanaei¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2047-2064, 2023, DOI:10.32604/cmes.2022.022647 - 23 November 2022

Abstract Survival data with a multi-state structure are frequently observed in follow-up studies. An analytic approach based on a multi-state model (MSM) should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events. One main objective in the MSM framework is variable selection, where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression. The usual variable selection methods, including stepwise and penalized methods, do not provide information about the importance of variables. In this context, we present a two-step More >

Meng Da¹, Huiqin Wang^1,*, Ke Wang¹, Zhan Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 513-527, 2022, DOI:10.32604/cmes.2022.019040 - 24 January 2022

Abstract The properties of the same pigments in murals are affected by different concentrations and particle diameters, which cause the shape of the spectral reflectance data curve to vary, thus influencing the outcome of matching calculations. This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences. Fast principal component analysis (FPCA) was used to calculate the eigenvalue variance of pigment spectral reflectance, then applied to the original reflectance values for parameter characterization. We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify… More >

Fangjun Zuo^*, Meiwei Jia, Guang Wen, Huijie Zhang, Pingping Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 993-1012, 2021, DOI:10.32604/cmes.2021.016870 - 08 October 2021

Abstract In the traditional reliability evaluation based on the Bayesian method, the failure probability of nodes is usually expressed by the average failure rate within a period of time. Aiming at the shortcomings of traditional Bayesian network reliability evaluation methods, this paper proposes a Bayesian network reliability evaluation method considering dynamics and fuzziness. The fuzzy theory and the dynamic of component failure probability are introduced to construct the dynamic fuzzy set function. Based on the solving characteristics of the dynamic fuzzy set and Bayesian network, the fuzzy dynamic probability and fuzzy dynamic importance degree of the More >

C. Sivamani¹, M. Rajeswari², E. Golden Julie³, Y. Harold Robinson⁴, Vimal Shanmuganathan⁵, Seifedine Kadry⁶, Yunyoung Nam^7,*

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.013705 - 07 January 2021

Abstract Road accident is a potential risk to the lives of both drivers and passers-by. Many road accidents occur due to the improper condition of the vehicle tyres after long term usage. Thus, tyres need to be inspected and analyzed while manufacturing to avoid serious road problems. However, tyre wear is a multifaceted happening. It normally needs the non-linearly on many limitations, like tyre formation and plan, vehicle category, conditions of the road. Yet, tyre wear has numerous profitable and environmental inferences particularly due to maintenance costs and traffic safety implications. Thus, the risk to calculate… More >