Rui Wang¹, Zhihui Liu^2,*, Hongdi Liu³, Baozhong Su⁴, Chuanyi Ma⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3035-3049, 2024, DOI:10.32604/cmes.2024.050806

Abstract In underground engineering, the detection of structural cracks on tunnel surfaces stands as a pivotal task in ensuring the health and reliability of tunnel structures. However, the dim and dusty environment inherent to underground engineering poses considerable challenges to crack segmentation. This paper proposes a crack segmentation algorithm termed as Focused Detection for Subsurface Cracks YOLOv8 (FDSC-YOLOv8) specifically designed for underground engineering structural surfaces. Firstly, to improve the extraction of multi-layer convolutional features, the fixed convolutional module is replaced with a deformable convolutional module. Secondly, the model’s receptive field is enhanced by introducing a multi-branch More >

Refah Alotaibi¹, Hoda Rezk², Ahmed Elshahhat^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3073-3103, 2024, DOI:10.32604/cmes.2024.050606

Abstract A new one-parameter Chris-Jerry distribution, created by mixing exponential and gamma distributions, is discussed in this article in the presence of incomplete lifetime data. We examine a novel generalized progressively hybrid censoring technique that ensures the experiment ends at a predefined period when the model of the test participants has a Chris-Jerry (CJ) distribution. When the indicated censored data is present, Bayes and likelihood estimations are used to explore the CJ parameter and reliability indices, including the hazard rate and reliability functions. We acquire the estimated asymptotic and credible confidence intervals of each unknown quantity. More >

Ibraheem Abu Falahah¹, Osama Al-Baik², Saleh Alomari³, Gulnara Bektemyssova⁴, Saikat Gochhait^5,6, Irina Leonova⁷, Om Parkash Malik⁸, Frank Werner^9,*, Mohammad Dehghani¹⁰

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3631-3678, 2024, DOI:10.32604/cmc.2024.053189

Abstract This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization (FLO), which emulates the unique hunting behavior of frilled lizards in their natural habitat. FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards. The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases: (i) an exploration phase, which mimics the lizard’s sudden attack on its prey, and (ii) an exploitation phase, which simulates the lizard’s retreat to the treetops after feeding. To assess FLO’s efficacy in addressing optimization problems, its performance is rigorously tested on fifty-two… More >

Mudassir Shams¹, Nasreen Kausar², Ebru Ozbilge^3,*, Alper Bulut³

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2617-2633, 2023, DOI:10.32604/csse.2023.034370

Abstract Engineering and applied mathematics disciplines that involve differential equations in general, and initial value problems in particular, include classical mechanics, thermodynamics, electromagnetism, and the general theory of relativity. A reliable, stable, efficient, and consistent numerical scheme is frequently required for modelling and simulation of a wide range of real-world problems using differential equations. In this study, the tangent slope is assumed to be the contra-harmonic mean, in which the arithmetic mean is used as a correction instead of Euler’s method to improve the efficiency of the improved Euler’s technique for solving ordinary differential equations with… More >

Refah Alotaibi¹, Hassan Okasha^2,3, Mazen Nassar^2,4, Ahmed Elshahhat^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2065-2089, 2023, DOI:10.32604/cmes.2023.023408

Abstract This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique. We refer to the new model as modified alpha power transformed Weibull distribution. The attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions, which are quite familiar in environmental investigations. Its hazard rate function can be decreasing, increasing, bathtub and upside-down then bathtub shaped. Diverse structural properties of the proposed model are acquired including quantile function, moments, entropies, order statistics, More >

Refah Alotaibi¹, Hassan Okasha^2,3, Hoda Rezk⁴, Mazen Nassar^2,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1255-1274, 2023, DOI:10.32604/cmes.2022.022623

Abstract The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility. This addition is beneficial in a variety of fields, including reliability, economics, engineering, biomedical science, biological research, environmental studies, and finance. For modeling real data, several expanded classes of distributions have been established. The modified alpha power transformed approach is used to implement the new model. The data matches the new inverse Weibull distribution better than the inverse Weibull distribution and several other competing models. It appears to More >

Hao Liu¹, Xiaoyang Zhang¹, Zhongjie Yan^1,*, Yingjian Yang^2,3, Qing’an Li^3,4,5, Chang Cai^3,4

Energy Engineering, Vol.120, No.1, pp. 163-179, 2023, DOI:10.32604/ee.2022.019927

Abstract The typical location and number of anemometer towers in the assessed area are the key to the accuracy of wind resource assessment in complex topography. As calculation examples, this paper used two typical complex topography wind farms in Guangxi, Yunnan province in China. Firstly, we simulated the wind resource status of the anemometer tower in the Meteodyn WT software. Secondly, we compared the simulated wind resource with the actual measured data by the anemometer tower in the same situation. Thirdly, we analyzed the influence of anemometer tower location and quantity in the accuracy of wind… More >

Shunying Ji^1,*, Michael Zhuravkov², Zongyan Zhou³, Yuntian Feng⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 1-3, 2022, DOI:10.32604/cmes.2022.023238

Abstract This article has no abstract. More >

Kai Long^1,*, Xiaodong Huang², Zunyi Duan³, Xuan Wang⁴, Quhao Li⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 27-29, 2022, DOI:10.32604/cmes.2022.020822

Abstract This article has no abstract. More >