Yuhang Jin^1,2, Endong Guo^1,2,*, Houli Wu^1,2, peilei Yan^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 167-186, 2022, DOI:10.32604/cmes.2022.018113

Abstract There are few studies on the dynamic-response mechanism of near-fault and far-field ground motions for large underground structures, especially for the branch joint of a utility tunnel (UT) and its internal pipeline. Based on the theory of a 3D viscous-spring artificial boundary, this paper deduced the equivalent nodal force when a P wave and an SV wave were vertically incident at the same time and transformed the ground motion into an equivalent nodal force using a self-developed MATLAB program, which was applied to an ABAQUS finite element model. Based on near-fault and far-field ground motions obtained from the NGA-WEST2 database,… More >

Biyao Zhai, Lu Liu, Shunying Ji^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 1-22, 2022, DOI:10.32604/cmes.2022.018652

Abstract Freezing in ice rubble is a common phenomenon in cold regions, which can consolidate loose blocks and change their mechanical properties. To model the cohesive effect in frozen ice rubble, and to describe the fragmentation behavior with a large external forces exerted, a freeze-bond model based on the dilated polyhedral discrete element method (DEM) is proposed. Herein, imaginary bonding is initialized at the contact points to transmit forces and moments, and the initiation of the damage is detected using the hybrid fracture model. The model is validated through the qualitative agreement between the simulation results and the analytical solution of… More >

Manh Duc Nguyen¹, Ha Nguyen Hai¹, Nadhir Al-Ansari^2,*, Mahdis Amiri³, Hai-Bang Ly⁴, Indra Prakash⁵, Binh Thai Pham^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 149-166, 2022, DOI:10.32604/cmes.2022.017355

Abstract One of the important geotechnical parameters required for designing of the civil engineering structure is the compressibility of the soil. In this study, the main purpose is to develop a novel hybrid Machine Learning (ML) model (ANFIS-DE), which used Differential Evolution (DE) algorithm to optimize the predictive capability of Adaptive-Network-based Fuzzy Inference System (ANFIS), for estimating soil Compression coefficient (Cc) from other geotechnical parameters namely Water Content, Void Ratio, Specific Gravity, Liquid Limit, Plastic Limit, Clay content and Depth of Soil Samples. Validation of the predictive capability of the novel model was carried out using statistical indices: Root Mean Square… More >

Shouzhen Zeng^1,2, Shahbaz Ali^3,*, Muhammad Khalid Mahmood⁴, Florentin Smarandache⁵, Daud Ahmad⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 581-606, 2022, DOI:10.32604/cmes.2022.017397

Abstract Fuzzy models are present everywhere from natural to artificial structures, embodying the dynamic processes in physical, biological, and social systems. As real-life problems are often uncertain on account of inconsistent and indeterminate information, it seems very demanding for an expert to solve those problems using a fuzzy model. In this regard, we develop a hybrid new model m-polar Diophantine neutrosophic N-soft set which is based on neutrosophic set and soft set. Additionally, we define several different sorts of compliments on the proposed set. A proposed set is a generalized form of fuzzy, soft, Pythagorean fuzzy, Pythagorean fuzzy soft, and Pythagorean… More >

Xing Guo^1,#, Yu-Dong Zhang^2,#, Siyuan Lu², Zhihai Lu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 23-71, 2022, DOI:10.32604/cmes.2021.017679

Abstract Since Corona Virus Disease 2019 outbreak, many expert groups worldwide have studied the problem and proposed many diagnostic methods. This paper focuses on the research of Corona Virus Disease 2019 diagnosis. First, the procedure of the diagnosis based on machine learning is introduced in detail, which includes medical data collection, image preprocessing, feature extraction, and image classification. Then, we review seven methods in detail: transfer learning, ensemble learning, unsupervised learning and semi-supervised learning, convolutional neural networks, graph neural networks, explainable deep neural networks, and so on. What’s more, the advantages and limitations of different diagnosis methods are compared. Although the… More >

Andi Tang, Huan Zhou^*, Tong Han, Lei Xie

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 331-364, 2022, DOI:10.32604/cmes.2021.017310

Abstract The sparrow search algorithm (SSA) is a newly proposed meta-heuristic optimization algorithm based on the sparrow foraging principle. Similar to other meta-heuristic algorithms, SSA has problems such as slow convergence speed and difficulty in jumping out of the local optimum. In order to overcome these shortcomings, a chaotic sparrow search algorithm based on logarithmic spiral strategy and adaptive step strategy (CLSSA) is proposed in this paper. Firstly, in order to balance the exploration and exploitation ability of the algorithm, chaotic mapping is introduced to adjust the main parameters of SSA. Secondly, in order to improve the diversity of the population… More >

Rabha W. Ibrahim^1,*, Ahmed M. Ajaj², Nadia M.G. Al-Saidi³, Dumitru Balean^4,5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 221-232, 2022, DOI:10.32604/cmes.2022.018348

Abstract The science of strategy (game theory) is known as the optimal decision-making of autonomous and challenging players in a strategic background. There are different strategies to complete the optimal decision. One of these strategies is the similarity technique. Similarity technique is a generalization of the symmetric strategy, which depends only on the other approaches employed, which can be formulated by altering diversities. One of these methods is the fractal theory. In this investigation, we present a new method studying the similarity analytic solution (SAS) of a 3D-fractal nanofluid system (FNFS). The dynamic evolution is completely given by the concept of… More >

Debiao Meng^1,2,3,*, Hongtao Wang¹, Shiyuan Yang¹, Zhiyuan Lv¹, Zhengguo Hu¹, Zihao Wang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 543-558, 2022, DOI:10.32604/cmes.2022.018123

Abstract In a wind turbine, the rolling bearing is the critical component. However, it has a high failure rate. Therefore, the failure analysis and fault diagnosis of wind power rolling bearings are very important to ensure the high reliability and safety of wind power equipment. In this study, the failure form and the corresponding reason for the failure are discussed firstly. Then, the natural frequency and the characteristic frequency are analyzed. The Empirical Mode Decomposition (EMD) algorithm is used to extract the characteristics of the vibration signal of the rolling bearing. Moreover, the eigenmode function is obtained and then filtered by… More >

Hongqiao Wang^1,*, Yanning Cai²

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 187-203, 2022, DOI:10.32604/cmes.2022.018000

Abstract Inertial system platforms are a kind of important precision devices, which have the characteristics of difficult acquisition for state data and small sample scale. Focusing on the model optimization for data-driven fault state prediction and quantitative degree measurement, a fast small-sample supersphere one-class SVM modeling method using support vectors pre-selection is systematically studied in this paper. By theorem-proving the irrelevance between the model's learning result and the non-support vectors (NSVs), the distribution characters of the support vectors are analyzed. On this basis, a modeling method with selected samples having specific geometry character from the training sets is also proposed. The… More >

Jing Lu¹, Yan Wu^2,#, Mingyan Hu¹, Yao Xiong¹, Yapeng Zhou¹, Ziliang Zhao¹, Liutong Shang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 365-377, 2022, DOI:10.32604/cmes.2021.017897

Abstract Background: The main cause of breast cancer is the deterioration of malignant tumor cells in breast tissue. Early diagnosis of tumors has become the most effective way to prevent breast cancer. Method: For distinguishing between tumor and non-tumor in MRI, a new type of computer-aided detection CAD system for breast tumors is designed in this paper. The CAD system was constructed using three networks, namely, the VGG16, Inception V3, and ResNet50. Then, the influence of the convolutional neural network second migration on the experimental results was further explored in the VGG16 system. Result: CAD system built based on VGG16, Inception… More >