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ORCIDMing Yin 0005
Person information
- affiliation: Northweastern Polytechnology University, Xi'an, China
Other persons with the same name
- Ming Yin — disambiguation page
- Ming Yin 0001
![[0000-0002-7364-139X]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-7364-139X")
— Purdue University, West Lafayette, IN, USA - Ming Yin 0002 — Guangdong University of Technology, School of Automation, Guangzhou, China (and 1 more)
- Ming Yin 0003 — University of California, Santa Barbara, CA, USA
- Ming Yin 0004 — Sichuan University, Chengdu, China
- Ming Yin 0006 — University of Science and Technology of China, Hefei, China
- Ming Yin 0007 — Chengdu University of Technology, Chengdu, China
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Journal Articles
- 2024
[j7]Jiayi Tian, Ming Yin, Jijiao Jiang:
Fault self-healing: A biological immune heuristic reinforcement learning method with root cause reasoning in industrial manufacturing process. Eng. Appl. Artif. Intell. 133: 108553 (2024)- [j6]Ming Yin, Jiayi Tian, Dan Zhu, Yibo Wang, Jijiao Jiang:
A data-driven distributed process monitoring method for industry manufacturing systems. Trans. Inst. Meas. Control 46(7): 1296-1316 (2024) - 2023
- [j5]Ming Yin, Jiaze Wang, Dan Zhu, Cunzhi Gao:
A two-stage approach for identifying and interpreting self-admitted technical debt. Appl. Intell. 53(22): 26592-26602 (2023) - [j4]Ming Yin, Pan Zhou, Taige Xu, Jijiao Jiang:
Extracting actors and use cases from requirements text with BiLSTM-CRF. J. Intell. Fuzzy Syst. 44(3): 4285-4299 (2023) - [j3]Kuiyu Zhu, Ming Yin, Dan Zhu, Xiaogang Zhang, Cunzhi Gao, Jijiao Jiang:
SCGRU: A general approach for identifying multiple classes of self-admitted technical debt with text generation oversampling. J. Syst. Softw. 195: 111514 (2023) - [j2]Ming Yin, Danli Meng, Dan Zhu, Yibo Wang, Jijiao Jiang:
Predicting Changes in User-Driven Requirements Using Conditional Random Fields in Agile Software Development. IEEE Trans. Engineering Management 70(11): 3715-3727 (2023) - 2022
- [j1]Ming Yin, Kuiyu Zhu, Hongli Xiao, Dan Zhu, Jijiao Jiang:
Deep neural network ensembles for detecting self-admitted technical debt. J. Intell. Fuzzy Syst. 43(1): 93-105 (2022)
Coauthor Index
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