Recent Advances in Mathematical Models and Algorithms for Big Data Analytics
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 158
Special Issue Editors
Interests: multiobjective optimization; evolutionary computation; machine learning
Interests: network modelling; task scheduling and resource allocation; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: computational intelligence; image processing; pattern recognition; software reliability engineering; optical computing; big astronomical data analysis
Special Issue Information
Dear Colleagues,
Nowadays, mathematical models and information technology in a big data context have become a popular new research topic among academics and the industry. Big data refers to a collection of data sets that are too large or too complex for efficient processing and analysis using traditional database management tools. The development of mathematics models and information technology in a big data context will enhance decision making, insight discovery, and process optimization. However, there are still numerous technical challenges and issues that need to be improved and broadly explored. This Special Issue aims to provide readers with the latest and most innovative research on all theoretical and practical aspects of information technology and mathematical models for big data analytics.
The aim of this Special Issue is to present a collection of high-quality research articles on state-of-the-art mathematical models, information technology, and big data analytics. The topics of interest include, but are not limited to:
Information technology and Computer Science
- artificial intelligence in big data;
- computer graphics and image processing;
- computer networks and security;
- computer science and engineering;
- computer simulation and modeling;
- computer-aided design / manufacturing;
- database technology and data warehousing;
- e-commerce and e-government;
- geographical information systems (GIS);
- grid computing;
- image processing and acquisition;
- information retrieval and information security;
- Internet and Web applications;
- knowledge discovery and data mining;
- management information system;
- neural networks and evolutionary algorithms;
- pattern recognition and machine learning;
- programming languages and techniques;
- semantic grid and natural language processing;
- smart city and intelligent transportation;
- software engineering;
- system modeling and simulation.
Electronics and Communication Technology
- antennas design, modeling, and measurement;
- audio/speech signal processing;
- bioinformatics;
- biomedical electronics;
- channel coding;
- communication and wireless systems;
- cryptography;
- electronic devices in communications;
- image/video processing and coding;
- industrial electronics and automations;
- integrated optics;
- medical imaging and image analysis;
- microwave circuits;
- multimedia communications;
- optical communications;
- photonic technologies;
- radio propagations;
- signal detection and estimation;
- signal and informatics processing;
- telecommunication services and applications;
- wireless communication and wireless networking;
- UAV technology.
Big data Analytics
- mathematical models for big data analytics;
- mathematics of machine learning and application;
- machine learning for big data;
- traditional and emerging methods for big data;
- privacy preservation for big data;
- intelligent and unconventional methods for big data;
- search and optimization for big data;
- parallel, accelerated, and distributed big data analysis;
• high-performance computing for big data; - novel hardware and software architectures for big data;
- real-world applications and success stories of big data analysis;
- mining of unstructured, spatio-temporal, streaming, and multimedia data.
Prof. Dr. Hai-Lin Liu
Prof. Dr. Yuping Wang
Prof. Dr. Ping Guo
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. 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.
