Journal of Computing in Civil Engineering

Aims & Scope

The Journal of Computing in Civil Engineering serves as a resource to researchers, practitioners, and students on advances and innovative ideas in computing as applicable to the engineering profession.

Many such ideas emerge from recent developments in computer science, information science, computer engineering, knowledge engineering, and other technical fields.

Some examples are innovations in artificial intelligence, parallel processing, distributed computing, graphics and imaging, and information technology.

The journal publishes research, implementation, and applications in cross-disciplinary areas including software, such as new programming languages, database-management systems, computer-aided design systems, and expert systems; hardware for robotics, bar coding, remote sensing, data mining, and knowledge acquisition; and strategic issues such as the management of computing resources, implementation strategies, and organizational impacts.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	5.2

SJR (SCImago Journal Rank)

Year	Value
2024	1.244

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	107

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Engineering, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Nonlinear Finite-Element Analysis Software Architecture Using Object Composition

  Citation: 716

  Authors: Frank, Michael H., Gregory L.

• Analysis of Edge-Detection Techniques for Crack Identification in Bridges

  Citation: 710

  Authors: Ikhlas, Osama, Michael E.

• Neural Networks for River Flow Prediction

  Citation: 502

  Authors: Nachimuthu, William J., Darrell, Ken

• Model Induction with Support Vector Machines: Introduction and Applications

  Citation: 494

  Authors: Yonas B., Slavco, Dimitri, Michael B.

• Neural Networks in Civil Engineering. I: Principles and Understanding

  Citation: 435

  Authors: Ian, Nabil

• Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods

  Citation: 373

  Authors: Jian, Xibing, Hani S.

• Machine Learning for Crack Detection: Review and Model Performance Comparison

  Citation: 330

  Authors: Yung-An, Yichang James

• Using Genetic Algorithms to Solve Construction Time-Cost Trade-Off Problems

  Citation: 324

  Authors: Chung-Wei, Liang, Scott A.

• Internal Structure Characterization of Asphalt Concrete Using Image Analysis

  Citation: 317

  Authors: E., B., N., T.

• Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques

  Citation: 317

  Authors: Jui-Sheng, Chien-Kuo, Mahmoud, Ismail

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