Theory and Application of Neural Networks and Complex Networks, 2nd Edition
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 14
Special Issue Editors
Interests: complex networks; machine learning; spatial networks; multilayer networks
Special Issues, Collections and Topics in MDPI journals
Interests: complex networks; urban networks; multilayer networks; spatial networks
Special Issues, Collections and Topics in MDPI journals
Interests: complex networks; machine learning; spatial networks; multilayer networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The analysis of complex networks has focused the attention of researchers in recent years. Complex network theory allows us to understand, model and try to solve problems in a great variety of real systems such as transport networks, urban networks, and social networks.
Artificial neural networks are recognized as a powerful tool that can help identify intertwined and complex relationships in a large number of systems. With the advent of new information technologies, the ability to generate data has increased considerably, representing a phenomenon that, when studied and analyzed, can provide important advances in science. In this context, artificial intelligence—and, in particular, artificial neural networks—can lead to more interpretable models and results.
This Special Issue aims to collect theories or applications that utilize artificial neural networks and complex network methods to address all types of challenges. The topics of interest include, but are not limited to, the following:
- Artificial neural networks.
- Machine and deep learning models.
- Clustering and classification algorithms.
- Predictive models.
- Graph neural networks.
- Models of complex networks.
- Centrality measures.
- Multiplex networks.
- Algorithms for network analysis.
- Spatial networks.
- Dynamic networks.
- Complex networks and epidemics.
- Applications of neural networks and complex network domains in transport, energy, the IoT, and smart cities, amongst others.
Prof. Dr. José F. Vicent
Prof. Dr. Leandro Tortosa
Dr. Manuel Curado
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- centrality measures
- neural networks
- machine learning
- complex networks
- predictive models
- multiplex networks
- graph neural networks
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