Shorouq Alshawabkeh, Li Wu^*, Daojun Dong, Yao Cheng, Liping Li, Mohammad Alanaqreh

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 63-77, 2023, DOI:10.32604/cmc.2023.042183

Abstract Pavement crack detection plays a crucial role in ensuring road safety and reducing maintenance expenses. Recent advancements in deep learning (DL) techniques have shown promising results in detecting pavement cracks; however, the selection of relevant features for classification remains challenging. In this study, we propose a new approach for pavement crack detection that integrates deep learning for feature extraction, the whale optimization algorithm (WOA) for feature selection, and random forest (RF) for classification. The performance of the models was evaluated using accuracy, recall, precision, F1 score, and area under the receiver operating characteristic curve (AUC). Our findings reveal that Model… More >

Zhenhan Zhang, Jun Ye^*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 887-916, 2023, DOI:10.32604/cmes.2023.022961

Abstract Neutrosophic theory can effectively and reasonably express indeterminate, inconsistent, and incomplete information. Since Smarandache proposed the neutrosophic theory in 1998, neutrosophic theory and related research have been developed and applied to many important fields. Indeterminacy and fuzziness are one of the main research issues in the field of civil engineering. Therefore, the neutrosophic theory is very suitable for modeling and applications of civil engineering fields. This review paper mainly describes the recent developments and applications of neutrosophic theory in four important research areas of civil engineering: the neutrosophic decision-making theory and applied methods, the neutrosophic evaluation methods and applications of… More >

Youqin Huang¹, Jiayong Li¹, Jiyang Fu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.3, pp. 845-875, 2019, DOI:10.32604/cmes.2019.07653

Abstract In last few years, big data and deep learning technologies have been successfully applied in various fields of civil engineering with the great progress of machine learning techniques. However, until now, there has been no comprehensive review on its applications in civil engineering. To fill this gap, this paper reviews the application and development of artificial intelligence in civil engineering in recent years, including intelligent algorithms, big data and deep learning. Through the work of this paper, the research direction and difficulties of artificial intelligence in civil engineering for the past few years can be known. It is shown that… More >

Quan Gu¹, Lei Wang¹, Surong Huang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 471-489, 2019, DOI:10.32604/cmes.2019.05757

Abstract Peridynamics (PD) is a powerful method to simulate the discontinuous problems in civil engineering. However, it may take a lot of effort to implement the material constitutive models into PD program for solving a broad range of problems. OpenSees is an open source software which includes a versatile material library and has been widely used by researchers and engineers in civil engineering. In this context, the paper presents a simple but effective approach to integrate PD with OpenSees by using a Client-Server (CS) software integration technique, such that the existing material constitutive models in OpenSees can be directly used by… More >

Joel Conte¹, Frank McKenna², Quan Gu^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 467-470, 2019, DOI:10.32604/cmes.2019.08174

Abstract This article has no abstract. More >