About the Journal

Journal of Computer Technology and Applied Mathematics is peer-reviewed journal of Southern United Academy of Sciences published in the field of Applied Mathematics, Computer Science and Technology. The journal registers independent DOI and ARK for each article. The DOI prefix is ​​10.70393 and the ARK prefix is ​​40704.

ISSN 3007-4126 (Print), ISSN 3007-4134 (Online), ISSN 3007-4142 (Digital), International CODEN (CAS): JCTAAD

The topics related to this journal include:

  • Applied Mathematics - Computational Mathematics, Mathematical Modeling, Numerical Analysis
  • Statistical Analysis - Probability Theory, Data Mining, Bayesian Statistics
  • Geometric Theory - Algebraic Geometry, Differential Geometry, Topology
  • Network Technology - Wireless Networks, Network Security, Internet of Things (IoT)
  • Artificial Intelligence and Intelligence - Machine Learning, Deep Learning, Neural Networks
  • Big Data Technology - Data Warehousing, Data Analytics, Distributed Computing
  • Computer Vision - Image Recognition, Object Detection, Motion Analysis
  • Natural Language Processing - Text Mining, Speech Recognition, Machine Translation
  • Computer Application Technology - Human-Computer Interaction, Embedded Systems, Mobile Computing
  • Software Technology - Software Engineering, Software Testing, Software Architecture

All articles published by JCTAM are indexed by OpenAIRE, BASE, WorldCat and ICI.

(OpenAIRE - DataSources | BASE - Bielefeld Academic Search Engine | WorldCat - OCLC | ICI - European Funds)

All articles published are rigorously reviewed meeting the Journal Quality standards.

Announcements

Current Issue

Vol. 2 No. 1 (2025)
View Vol. 2 No. 1 (2025)

All articles published in this issue have undergone a thorough peer review process, and stringent checks for repetition rates have been implemented to ensure the integrity of the content.

Total number of articles in this issue: 5
Total number of pages in this issue: 32

For inquiries regarding the content of specific articles, please feel free to contact the respective authors via their provided email addresses. For questions related to the journal itself, please reach out directly to SUAS Press.

Published: 2025-01-01

Articles

  • Knowledge Graph Construction for the U.S. Stock Market: A Statistical Learning and Risk Management Approach
    Authors: Wei Yang, Jincan Duan
    Resource Type: Article
    Disciplines: Artificial Intelligence | Subjects: Statistical Analysis
    Publication ID: v2n1a01
    Abstract: This paper explores the integration of dynamic knowledge graphs (DKGs) and advanced AI techniques, such as large language models (LLMs) and graph neural networks (GNNs), for enhancing financial market analysis and risk management. By developing...
    1-7
    DOI Icon Abstract views: 39 | DOI Icon PDF downloads: 24 | DOI Icon references: 39
    DOI Icon DOI: 10.70393/6a6374616d.323439
    DOI Icon ARK: ark:/40704/JCTAM.v2n1a01
  • Using Machine Learning for Sustainable Concrete Material Selection and Optimization in Building Design
    Authors: Qian Meng, Haoran Xu, Jingwen He
    Resource Type: Article
    Disciplines: Machine Learning | Subjects: Computer Application Technology
    Publication ID: v2n1a02
    Abstract: This paper explores the application of machine learning (ML) in the selection and optimization of concrete materials for sustainable building design. It discusses how AI-driven platforms, such as Concrete Copilot and SmartMix, are revolutionizing...
    8-14
    DOI Icon Abstract views: 28 | DOI Icon PDF downloads: 17 | DOI Icon references: 35
    DOI Icon DOI: 10.70393/6a6374616d.323530
    DOI Icon ARK: ark:/40704/JCTAM.v2n1a02
  • Innovative Applications of Machine Learning in Image Recognition
    Authors: Ke Qian
    Resource Type: Article
    Disciplines: Artificial Intelligence and Intelligence | Subjects: Machine Learning
    Publication ID: v2n1a03
    Abstract: Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the...
    15-20
    DOI Icon Abstract views: 15 | DOI Icon PDF downloads: 51 | DOI Icon references: 18
    DOI Icon DOI: 10.70393/6a6374616d.323533
    DOI Icon ARK: ark:/40704/JCTAM.v2n1a03
  • Integrating Machine Learning for Optimal Path Planning
    Authors: Shiru Xiao
    Resource Type: Article
    Disciplines: Artificial Intelligence | Subjects: Machine Learning
    Publication ID: v2n1a04
    Abstract: In the area of AI based path planning, the learner is not told which actions to take, as is common in most forms of machine learning. Instead, the learner must discover through trial and error, which actions yield the most rewards. In the most...
    21-26
    DOI Icon Abstract views: 13 | DOI Icon PDF downloads: 9 | DOI Icon references: 22
    DOI Icon DOI: 10.70393/6a6374616d.323534
    DOI Icon ARK: ark:/40704/JCTAM.v2n1a04
  • Machine Learning for Enhanced Classification and Geospatial Distribution Analysis
    Authors: Yuxi Huang
    Resource Type: Article
    Disciplines: Artificial Intelligence | Subjects: Machine Learning
    Publication ID: v2n1a05
    Abstract: Combining geospatial analysis with machine learning creates a novel synergy beyond conventional approaches to comprehending our spatial surroundings. The ability of machine learning to recognize intricate patterns and connections within data has...
    27-32
    DOI Icon Abstract views: 13 | DOI Icon PDF downloads: 8 | DOI Icon references: 23
    DOI Icon DOI: 10.70393/6a6374616d.323535
    DOI Icon ARK: ark:/40704/JCTAM.v2n1a05
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