About the Journal

Journal of Intelligence and Engineering Technology (JIET) is a scholarly journal published by SUAS. It employs editor-invited peer review and editorial assessment through a standardized scoring framework evaluating submissions on originality, transparency, ethical integrity, and domain relevance.

Quarterly publication with Online First.

It covers domains including Intelligent Systems, Smart Manufacturing, Cyber–Physical Engineering, Engineering Data Science, Sustainable Infrastructure, Intelligent Materials, Human-Centered AI, Engineering Cybersecurity, and Emerging Convergent Engineering Domains; assigns DOIs and ARKs; and is indexed in WorldCat, OpenAIRE, Scilit, and BASE.

Announcements

Current Issue

Vol. 1 No. 3 (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: 1

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: 2026-07-26

Articles

  • Feature Mining and Node Prediction for Complex Correlation Datasets Based on Graph Neural Networks
    Authors: Wenhao Xu
    Resource Type: Article
    Disciplines: Intelligent Systems | Subjects: Other
    Publication ID: v1n3a01
    Abstract: Complex correlation datasets widely exist in social networks, citation networks, and biological systems, where traditional machine learning methods fail to effectively capture implicit topological correlation and high-dimensional feature...
    1-5
    DOI Icon Abstract views: 33 | DOI Icon PDF downloads: 20 | DOI Icon SUAS Digital Library downloads: 0 | DOI Icon references: 12
    DOI Icon DOI: 10.70393/6a696574.343331
    DOI Icon ARK: ark:/40704/JIET.v1n3a01
  • Reliability-Informed Life Prediction for New Energy Vehicle Components
    Authors: Zengcong Wang
    Resource Type: Article
    Disciplines: Intelligent Systems | Subjects: Other
    Publication ID: v1n3a02
    Abstract: For new energy vehicle components, remaining service life requires crucial maintenance, but operating conditions and incomplete fault records still limit the sustainable development of models. This study constructs a data-driven framework for...
    6-14
    DOI Icon Abstract views: 16 | DOI Icon PDF downloads: 9 | DOI Icon SUAS Digital Library downloads: 0 | DOI Icon references: 11
    DOI Icon DOI: 10.70393/6a696574.343332
    DOI Icon ARK: ark:/40704/JIET.v1n3a02
  • Environmental Assessment of Intelligent Logistics Automation
    Authors: Shengtao Lin
    Resource Type: Article
    Disciplines: Intelligent Systems | Subjects: Other
    Publication ID: v1n3a03
    Abstract: Currently, with the development of intelligent logistics automation, lower operating costs and higher service reliability are increasingly associated with it. However, its net environmental impact remains uncertain because improvements in physical...
    15-22
    DOI Icon Abstract views: 28 | DOI Icon PDF downloads: 6 | DOI Icon SUAS Digital Library downloads: 0 | DOI Icon references: 13
    DOI Icon DOI: 10.70393/6a696574.343333
    DOI Icon ARK: ark:/40704/JIET.v1n3a03
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