Vol. 2 No. 5 (2024)

View Vol. 2 No. 5 (2024)

All content published in this issue has undergone peer review and strict repetition rate checks have been conducted.

Number of articles in this issue: 6
Number of pages in this issue: 53

If you have any questions about the content of this issue, you can contact each author via email. For questions about the journal itself, you can directly contact SUAS Press.

Published: 2024-09-16

Articles

  • Research on Optimization of Chip Development Management Based on Modular Design
    Authors: Chengye Liu
    Resource Type: Article
    Publication ID: v2n5a01
    Abstract: Chip development is an ever-evolving field that demands efficient management to meet rising expectations for performance, flexibility, and scalability. Modular design offers one potential solution by enabling more effective reuse of components,...
    1-5
    DOI Icon Abstract views: 99 | DOI Icon PDF downloads: 24 | DOI Icon references: 20
    DOI Icon DOI: 10.5281/zenodo.13755252
    DOI Icon ARK: ark:/40704/AJSM.v2n5a01
  • Research on Risk Management Strategies and Implementation Paths in Chip Design
    Authors: Chengye Liu
    Resource Type: Article
    Publication ID: v2n5a02
    Abstract: Chip design has emerged as an essential field due to the increasing complexity of semiconductor systems and demand for faster, more cost-effective solutions across industries. Unfortunately, chip production comes with many risks, from technical...
    6-10
    DOI Icon Abstract views: 828 | DOI Icon PDF downloads: 59 | DOI Icon references: 24
    DOI Icon DOI: 10.5281/zenodo.13755264
    DOI Icon ARK: ark:/40704/AJSM.v2n5a02
  • Utilizing Artificial Intelligence for Financial Risk Monitoring in Asset Management
    Authors: Shikai Wang, Yida Zhu, Qi Lou, Ming Wei
    Resource Type: Article
    Publication ID: v2n5a03
    Abstract: This paper explores the application and advantages of artificial intelligence (AI) in financial risk monitoring in asset management. With the increasing dynamics and complexity of the financial market, traditional risk management methods are...
    11-19
    DOI Icon Abstract views: 478 | DOI Icon PDF downloads: 137 | DOI Icon references: 25
    DOI Icon DOI: 10.5281/zenodo.13762069
    DOI Icon ARK: ark:/40704/AJSM.v2n5a03
  • LSTM-Based Financial Statement Fraud Prediction Model for Listed Companies
    Authors: Yanli Pu, Yida Zhu, Haosen Xu, Zeyu Wang, Ming Wei
    Resource Type: Article
    Publication ID: v2n5a04
    Abstract: This research investigates the ability of Long Short-Term Memory (LSTM) networks to forecast financial statement fraud in publicly traded firms. Data was collected from S&P 500 companies for a decade, including 20,000 observations of...
    20-31
    DOI Icon Abstract views: 371 | DOI Icon PDF downloads: 131 | DOI Icon references: 42
    DOI Icon DOI: 10.5281/zenodo.13762976
    DOI Icon ARK: ark:/40704/AJSM.v2n5a04
  • AI-Driven Financial Reporting and Risk Management: A Path to Economic Growth and Market Efficiency
    Authors: Huining Wang
    Resource Type: Article
    Publication ID: v2n5a05
    Abstract: Recent advances in Artificial Intelligence (AI) are having a tremendous effect on the financial industry, particularly in areas of reporting and risk management. Literature research makes it evident that artificial intelligence technologies are...
    32-37
    DOI Icon Abstract views: 190 | DOI Icon PDF downloads: 62 | DOI Icon references: 21
    DOI Icon DOI: 10.5281/zenodo.13765776
    DOI Icon ARK: ark:/40704/AJSM.v2n5a05
  • Leveraging Artificial Intelligence for Enhanced Risk Management in Financial Services: Current Applications and Future Prospects
    Authors: Haosen Xu, Kaiyi Niu, Tianyi Lu, Siyang Li, Qi Lou
    Resource Type: Article
    Publication ID: v2n5a06
    Abstract: This study examines the application of artificial intelligence (AI) in enhancing risk management within financial services. Through comprehensive analysis, the research reveals that AI technologies, particularly machine learning, and deep learning...
    38-53
    DOI Icon Abstract views: 1326 | DOI Icon PDF downloads: 475 | DOI Icon references: 40
    DOI Icon DOI: 10.5281/zenodo.13765819
    DOI Icon ARK: ark:/40704/AJSM.v2n5a06