姓名

穆国庆

单位部门

金沙8888js官方/自动化教研室

职称

副教授

电话/邮箱

16653207573/guoqingmu@foxmail.com

个人简介

穆国庆，工学博士，副教授，硕士研究生导师。主要研究方向为人工智能与深度学习在工业领域的应用，包括工业大数据分析与建模、工业过程与设备的关键指标软测量建模、故障智能分类与诊断、工业装置寿命预测等。截止到目前，一直与境内外知名学者（大连海事大学、中国石油大学（华东）、台湾中原大学等）保持密切联系，先后主持和参与国家自然科学基金项目和企业项目多项。已发表学术论文10余篇，其中SCI、EI检索10篇，已申请和授权国家发明专利8项。

研究领域

人工智能与深度学习在工业领域的应用，包括工业大数据分析与建模、工业过程与设备的关键指标软测量建模、故障智能分类与诊断、工业装置寿命预测等。

教科研情况

教学情况：主要承担工程项目管理、电气控制系统仿真等本科教学任务。

科研情况：主持国家自然科学基金项目1项，山东省自然科学基金项目1项，横向项目1项。参与国家自然科学基金重点项目1项，国家中组部青年计划项目1项以及企业项目2项。

学术成果

部分代表性论文和专利：

[1] Guoqing Mu, Junghui Chen, Jingxiang Liu, Weiming Shao, Dongya Zhao, State prediction of distributed parameter systems based on multi-source spatiotemporal information[J]. Journal of Process Control, 2022, 119: 55-67.

[2] Guoqing Mu and Junghui Chen. Developing a conditional variational autoencoder to guide spectral data augmentation for calibration modeling[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 2501008.

[3] Guoqing Mu, Tao Liu, Junghui Chen, Chao Shang and Chongquan Zhong. Variational PLS-Based calibration model building with semi-supervised learning for moisture measurement during fluidized bed drying by NIR spectroscopy[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1006713.

[4] Guoqing Mu, Tao Liu, Xue Chuang and Junghui Chen, Semi-supervised learning-based calibration model building of NIR spectroscopy for in situ measurement of biochemical processes under insufficiently and inaccurately labeled samples[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 2509912.

[5] Guoqing Mu, Tao Liu, Jingxiang Liu, Liangzhi Xia and Caiyuan Yu. Calibration model building for online monitoring of the granule moisture content during fluidized bed drying by NIR spectroscopy[J]. Industrial & Engineering Chemistry Research, 2019, 58(16): 6476-6485.

[6] Guoqing Mu, Tao Liu, Junghui Chen, Liangzhi Xia and Caiyuan Yu. 110th anniversary: Real-time end point detection of fluidized bed drying process based on a switching model of near-infrared spectroscopy[J]. Industrial & Engineering Chemistry Research, 2019, 58(36): 16777-16786.

[7]穆国庆等.一种基于多源时空信息的分布式参数系统状态预测方法.

[8]穆国庆等.一种基于条件变分自编码的光谱数据增强方法.