Data-Driven Processing from Complex Systems Perspective
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 13144
Special Issue Editors
Interests: complex systems; computational complexity; fractals; multifractal methods; fractional methods; fractional calculus; computational methods; wavelets and entropy along with their applications; AI applications; structure analysis; data analysis
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: action recognition; activity recognition; anomaly recognition; computer vision; video analytics; deep learning; video summarization
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; unsupervised learning; biomedical image analysis; pattern recognition; transfer learning; data analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Complex networked systems with interacting elements characterized by non-linearity, high dimensionality, and heterogeneity in the interconnected universe of today require a solid understanding and control of their structure and dynamics, which has become a grand challenge for various fields of science. Complex systems and their conceptual knowledge along with the related approaches and methodologies are geared toward a viable model regarding how different data entities and streams have an impact on and interact with one another for the generation of features and trends on a multitude of spatiotemporal scales. Computational predictive analytics in highly complex and diverse fields have been and are currently developed for the characterization and quantification of concurrently and mutually interacting facets of different scenarios regarding real-world, universal, and natural phenomena.
New computational methods with complex data and the related advancements in computations aim at a more profound and versatile understanding of the substantial masses of data and have enabled an improvement of predictions by transferring the results based on data analytics into the benefits at large, which underpins the utility and interdisciplinary approach of the domain. Accordingly, data-driven and multifarious methods are required for the optimal prediction solutions and critical decision-making processes, whereby Artificial Intelligence (AI), fractional calculus, and multifractal methods have the capability of learning and modeling the system’s complex behavior, establishing the governing methods from the experimental data. Science pertaining to complex systems relies on data-driven approaches that obtain rigorous principles that generate accurate predictions and reliable laws, enabling the parametrization of models given the available and viable quantification and optimization.
This Special Issue, considering the fact that driven models bring a novel ingredient in the overall modeling of complex systems, focuses on recent advancements, applications, and contributions in Artificial Intelligence (AI) applications, machine learning methods, data analysis, big data analytics, computational predictive analytics, computational complexity, spatiotemporal scales, fractals and multifractional methods, fractional calculus, dynamical processes as per fixed, variable, and distributed systems, nonlinear dynamics and non-equilibrium processes, stochastic processes, fractional order integrodifferentiation, hierarchical nonlinear principal component analyses by machine learning, and related concepts. With this endeavor, we aim at contributing to the research areas of diverse fields on nonlinear integrated systems in complex natural phenomena, complex signal and image processing, recurrent neural networks, differential/integral equations, multiresolution analysis, entropy, wavelets as a reflection of the versatile dimensions of the theoretical and applied areas concerned with mathematics, information science, computer science, physics, biology, medicine, genetics, neuroscience, chemistry, engineering, and social sciences , in addition to the extensive line of other applied sciences.
Potential topics of the special issue include but are not limited to:
- Advanced data analysis and/or data visualization in complex models;
- Big data analysis within multifractal analysis or fractional calculus methods in complex systems;
- Advanced topics in fractional calculus and complex systems;
- Quantization optimization algorithms for complex systems;
- AI approaches in complex systems for real-world, universal, and natural phenomena;
- Data-driven stochastic differential equations;
- Machine learning applications in complex data;
- Optimization by deep neural networks;
- Medical algorithmic applications;
- AI applications in signal processing;
- Advanced AI and embedded vision for complex surveillance environments;
- Advanced computational imaging;
- Fractional dynamical models in complex systems;
- Fractal dynamics and kinetics of complex systems;
- Discrete, stochastic, and hybrid dynamics;
- Multifractal systems in real-world, universal, and natural phenomena.
Dr. Yeliz Karaca
Prof. Dr. Yudong Zhang
Dr. Khan Muhammad
Dr. Shuihua Wang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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. Electronics 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 2400 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.
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.