Vol. 3 No. 1 (2026)

					View Vol. 3 No. 1 (2026)

This issue contains articles accepted following editor-invited peer review and editorial assessment. All manuscripts underwent standardized similarity screening as part of SUAS Press’s quality assurance protocol.

Articles: 3

For scientific inquiries about a specific article, contact the corresponding author directly. To report concerns regarding editorial integrity, publication ethics, or content quality, please contact the SUAS Press Quality Supervision Committee at qsc@suaspress.org.

Published: 2026-02-18

Articles

  • Authors: Yang Ximeng, Zhang Yiming
    Resource Type: Article
    Disciplines: Business Analytics | Subjects: Econometric Modeling
    Publication ID: v3n1a01
    Abstract: This study instantiates credit strategy optimization at the transaction authorization layer, with actions approve, review, and decline. Within an Offline Conservative RL (CQL) framework, we co-optimize fraud loss, operational burden from manual...
    1-9
    DOI Icon Abstract views: 0 | DOI Icon PDF downloads: 0 | DOI Icon SUAS Digital Library downloads: 0 | DOI Icon references: 20
    DOI Icon DOI: 10.70393/6a6574626d.333932
    DOI Icon ARK: ark:/40704/JETBM.v3n1a01
  • Authors: Li Xiangmin, Zhang Ge
    Resource Type: Article
    Disciplines: Finance | Subjects: Financial Econometrics
    Publication ID: v3n1a02
    Abstract: The steps involved in applying the Analytic Hierarchy Process (AHP) to company sales data analysis include defining the analysis objectives, constructing a hierarchical model, conducting comparative analysis and constructing matrices, testing...
    10-17
    DOI Icon Abstract views: 0 | DOI Icon PDF downloads: 0 | DOI Icon SUAS Digital Library downloads: 0 | DOI Icon references: 26
    DOI Icon DOI: 10.70393/6a6574626d.333933
    DOI Icon ARK: ark:/40704/JETBM.v3n1a02
  • Authors: Li Wensi
    Resource Type: Article
    Disciplines: Business Analytics | Subjects: Machine Learning Applications
    Publication ID: v3n1a03
    Abstract: This paper investigates AI-assisted marketing content generation for non-standard (customized) industrial automation solutions, a domain characterized by fragmented orders, long project cycles, intense price competition, and limited content reuse...
    18-25
    DOI Icon Abstract views: 0 | DOI Icon PDF downloads: 0 | DOI Icon SUAS Digital Library downloads: 0 | DOI Icon references: 16
    DOI Icon DOI: 10.70393/6a6574626d.333937
    DOI Icon ARK: ark:/40704/JETBM.v3n1a03