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Mathematics
Special Issues
Computational Approaches in Computer Science: Methods, Algorithms, and Applications
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Computational Approaches in Computer Science: Methods, Algorithms, and Applications

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 1720

Special Issue Editor

Prof. Dr. Oded Margalit

E-Mail Website
Guest Editor
Computer Science, Ben-Gurion University of the Negev, Beer Sheva, Israel
Interests: machine learning; formal verification; cyber security; testing

Special Issue Information

Dear Colleagues,

This Special Issue aims to bring together cutting-edge research that explores computational techniques and methodologies across various domains of computer science.

We are particularly interested in contributions that showcase novel algorithms, groundbreaking methods, and their applications in solving complex real-world problems.

We are seeking original research articles, comprehensive reviews, and insightful case studies that align with the following themes:

  • Advanced Algorithms and Data Structures;
  • Machine Learning and Artificial Intelligence;
  • Computational Complexity and Optimization;
  • Formal Methods and Verification;
  • Compilers and Computer Languages;
  • Data Science and Big Data Analytics;
  • Computational Mathematics;
  • Computational Biology and Bioinformatics;
  • Testing Methods;
  • Cybersecurity and Cryptography;
  • High-Performance Computing and Cloud Computing.

This Special Issue offers an excellent platform to reach a broad audience of researchers, practitioners, and educators in the field of computer science.

Prof. Dr. Oded Margalit
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

  • artificial intelligence (AI)
  • machine learning
  • computational complexity
  • optimization
  • data structures
  • computational mathematics
  • formal methods
  • testing methods
  • high-performance computing (HPC)

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.

Published Papers (2 papers)

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Research

21 pages, 2639 KiB  
Article
A Hybrid Model of Multi-Head Attention Enhanced BiLSTM, ARIMA, and XGBoost for Stock Price Forecasting Based on Wavelet Denoising
by Qingliang Zhao, Hongding Li, Xiao Liu and Yiduo Wang
Mathematics 2025, 13(16), 2622; https://doi.org/10.3390/math13162622 - 15 Aug 2025
Viewed by 339
Abstract
The stock market plays a crucial role in the financial system, with its price movements reflecting macroeconomic trends. Due to the influence of multifaceted factors such as policy shifts and corporate performance, stock prices exhibit nonlinearity, high noise, and non-stationarity, making them difficult [...] Read more.
The stock market plays a crucial role in the financial system, with its price movements reflecting macroeconomic trends. Due to the influence of multifaceted factors such as policy shifts and corporate performance, stock prices exhibit nonlinearity, high noise, and non-stationarity, making them difficult to model accurately using a single approach. To enhance forecasting accuracy, this study proposes a hybrid forecasting framework that integrates wavelet denoising, multi-head attention-based BiLSTM, ARIMA, and XGBoost. Wavelet transform is first employed to enhance data quality. The multi-head attention BiLSTM captures nonlinear temporal dependencies, ARIMA models linear trends in residuals, and XGBoost improves the recognition of complex patterns. The final prediction is obtained by combining the outputs of all models through an inverse-error weighted ensemble strategy. Using the CSI 300 Index as an empirical case, we construct a multidimensional feature set including both market and technical indicators. Experimental results show that the proposed model clearly outperforms individual models in terms of RMSE, MAE, MAPE, and R2. Ablation studies confirm the importance of each module in performance enhancement. The model also performs well on individual stock data (e.g., Fuyao Glass), demonstrating promising generalization ability. This research provides an effective solution for improving stock price forecasting accuracy and offers valuable insights for investment decision-making and market regulation. Full article
(This article belongs to the Special Issue Computational Approaches in Computer Science: Methods, Algorithms, and Applications)
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10 pages, 1635 KiB  
Article
Sphere Coverage in n Dimensions
by Tatiana Tabirca, Fangda Zou and Sabin Tabirca
Mathematics 2024, 12(23), 3772; https://doi.org/10.3390/math12233772 - 29 Nov 2024
Viewed by 971
Abstract
This paper presents some theoretical results on the sphere coverage problem in the n-dimensional space. These results refer to the minimal number of spheres, denoted by Nk(a), to cover a cuboid. The first properties outline some theoretical [...] Read more.
This paper presents some theoretical results on the sphere coverage problem in the n-dimensional space. These results refer to the minimal number of spheres, denoted by Nk(a), to cover a cuboid. The first properties outline some theoretical results for the numbers Nk(a), including sub-additivity and monotony on each variable. We use then these results to establish some lower and upper bounds for Nk(a), as well as for the minimal density of spheres to achieve k-coverage. Finally, a computation is proposed to approximate the Nk(a) numbers, and some tables are produced to show them for 2D and 3D cuboids. Full article
(This article belongs to the Special Issue Computational Approaches in Computer Science: Methods, Algorithms, and Applications)
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