Integrated Computer-Aided Engineering

Aims & Scope

Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal.

The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems.

The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering.

It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality.

Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.

Metrics & Ranking

Abstracting & Indexing

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

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

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

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Apc url

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.

• Improved spiking neural networks for EEG classification and epilepsy and seizure detection

  Citation: 367

  Authors: Samanwoy, Hojjat

• Rediscovering workflow models from event-based data using little thumb

  Citation: 330

  Authors: A.J.M.M., W.M.P

• Enhanced probabilistic neural network with local decision circles: A robust classifier

  Citation: 328

  Authors: Mehran, Hojjat

• Process Monitoring and Modeling Using the Self-Organizing Map

  Citation: 148

  Authors: Esa, Jaakko, Olli, Juha

• Image recognition with deep neural networks in presence of noise – Dealing with and taking advantage of distortions

  Citation: 142

  Authors: Michał, Bogusław

• A multiscale approach to pixel-level image fusion

  Citation: 111

  Authors: A., Yun, Hamid, Alan

• 3D mesh simplification with feature preservation based on Whale Optimization Algorithm and Differential Evolution

  Citation: 108

  Authors: Yaqian, Fazhi, Xiantao

• A scalable approach based on deep learning for big data time series forecasting

  Citation: 105

  Authors: J.F., A., A., F.

• Design and implementation of membrane controllers for trajectory tracking of nonholonomic wheeled mobile robots

  Citation: 89

  Authors: Xueyuan, Gexiang, Ferrante, Tao, Junbo, Marian, Florentin, Raluca

• Global path planning of wheeled robots using multi-objective memetic algorithms

  Citation: 86

  Authors: Zexuan, Jun, Jian-Qiang, Fangxiao, Qingfu