Data-Driven Approaches for Big Data Analysis of Intelligent Systems
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 January 2026 | Viewed by 10
Special Issue Editor
Special Issue Information
Dear Colleagues,
The rapid evolution of intelligent systems has generated vast, heterogeneous datasets, demanding advanced mathematical frameworks to unlock actionable insights. This Special Issue, "Data-Driven Approaches for Big Data Analysis of Intelligent Systems", focuses on rigorous computational methodologies, including statistical learning models, optimization algorithms, and stochastic processes, to address scalability, efficiency, and robustness in intelligent systems. Key topics encompass machine learning architectures (e.g., deep neural networks and reinforcement learning), distributed computing paradigms (e.g., MapReduce and Spark), and mathematical techniques for high-dimensional data (e.g., tensor decomposition and sparse linear algebra). Computational analysis of time-series forecasting, nonlinear dynamics, and graph-based algorithms for network-structured data will be explored. Submissions should emphasize mathematical innovations, such as differential equations for predictive modeling, convex/non-convex optimization for parameter tuning, or probabilistic graphical models for uncertainty quantification. This issue aims to bridge mathematical theory with real-world implementations, fostering advancements in intelligent systems through data-driven computational science.
Dr. Qiuyang Huang
Guest Editor
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. 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
- big data analytics
- machine learning algorithms
- mathematical modeling
- computational intelligence
- optimization techniques
- deep neural networks
- intelligent systems
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.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.