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ORCIDYingjun Deng
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2020 – today
- 2024
[j12]Nan Zhang
, Kaiquan Cai, Yingjun Deng, Jun Zhang:
Joint optimization of condition-based maintenance and condition-based production of a single equipment considering random yield and maintenance delay. Reliab. Eng. Syst. Saf. 241: 109694 (2024)- [j11]Weiyao Zhu, Ou Wu, Fengguang Su, Yingjun Deng:
Exploring the Learning Difficulty of Data: Theory and Measure. ACM Trans. Knowl. Discov. Data 18(4): 84:1-84:37 (2024) - 2023
- [j10]Nan Zhang, Sen Tian, Jiatao Xu, Yingjun Deng, Kaiquan Cai:
Optimal production lot-sizing and condition-based maintenance policy considering imperfect manufacturing process and inspection errors. Comput. Ind. Eng. 177: 108929 (2023) - [j9]Chuang Yu, Zhuhua Hu, Bing Han, Yutong Dai, Yaochi Zhao, Yingjun Deng:
An intelligent measurement scheme for basic characters of fish in smart aquaculture. Comput. Electron. Agric. 204: 107506 (2023) - [j8]Jianpeng Zhang, Hongchang Chen, Dingjiu Yu, Yulong Pei, Yingjun Deng:
Cluster-preserving sampling algorithm for large-scale graphs. Sci. China Inf. Sci. 66(1) (2023) - [j7]Nan Zhang, Yingjun Deng, Bin Liu, Jun Zhang:
Condition-based maintenance for a multi-component system in a dynamic operating environment. Reliab. Eng. Syst. Saf. 231: 108988 (2023) - [j6]Nan Zhang, Kaiquan Cai, Yingjun Deng, Jun Zhang:
Determining the optimal production-maintenance policy of a parallel production system with stochastically interacted yield and deterioration. Reliab. Eng. Syst. Saf. 237: 109342 (2023) - 2022
- [c5]Fengguang Su, Yu Zhu, Ou Wu, Yingjun Deng:
Submodular Meta Data Compiling for Meta Optimization. ECML/PKDD (3) 2022: 493-511 - [i1]Weiyao Zhu, Ou Wu, Fengguang Su, Yingjun Deng:
Exploring the Learning Difficulty of Data Theory and Measure. CoRR abs/2205.07427 (2022) - 2021
- [j5]Tian Wang, Jiakun Li, Yingjun Deng, Chuang Wang, Hichem Snoussi, Fei Tao:
Digital twin for human-machine interaction with convolutional neural network. Int. J. Comput. Integr. Manuf. 34(7-8): 888-897 (2021) - [j4]Huaming Wu, Katinka Wolter, Pengfei Jiao, Yingjun Deng, Yubin Zhao, Minxian Xu:
EEDTO: An Energy-Efficient Dynamic Task Offloading Algorithm for Blockchain-Enabled IoT-Edge-Cloud Orchestrated Computing. IEEE Internet Things J. 8(4): 2163-2176 (2021) - [c4]Yingjun Deng, Mingpeiyu Zhang, Tian Wang, Huaming Wu:
Time-Gated Remaining Useful Life Prediction with Non-Periodical Inspection Data. CASE 2021: 264-269 - 2020
- [j3]Huaming Wu, Xiangyi Li, Yingjun Deng:
Deep learning-driven wireless communication for edge-cloud computing: opportunities and challenges. J. Cloud Comput. 9: 21 (2020) - [j2]Yingjun Deng, Alessandro Di Bucchianico, Mykola Pechenizkiy:
Controlling the accuracy and uncertainty trade-off in RUL prediction with a surrogate Wiener propagation model. Reliab. Eng. Syst. Saf. 196: 106727 (2020) - [c3]Yingjun Deng, Huaming Wu, Chao Jiang:
Uncertainty Quantification for Remaining Useful Lifetime Prediction with Multi-Channel Sensory Data. ICASSP 2020: 8299-8303 - [c2]Ying-Jun Deng, Hao-Lun Hu, Yu-Han Liang, Jian-Ming Chen, Ching-Chuan Chou, Shea-Jue Wang, Mu-Chun Wang:
Q-factor Integrity of 28nm-node High-k Gate Dielectric. ICKII 2020: 71-73 - [c1]Lin Gan, Likai Wei, Yingjun Deng:
Rule-Based Composition Grammar Analysis and Applications. MIPR 2020: 404-407
2010 – 2019
- 2016
- [j1]Yingjun Deng, Anne Barros, Antoine Grall:
Degradation Modeling Based on a Time-Dependent Ornstein-Uhlenbeck Process and Residual Useful Lifetime Estimation. IEEE Trans. Reliab. 65(1): 126-140 (2016) - 2015
- [b1]Yingjun Deng:
Degradation modeling based on a time-dependent Ornstein-Uhlenbeck process and prognosis of system failures. (Modélisation des dégradations par un processus d'Ornstein-Uhlenbeck et pronostic de défaillances du système). University of Technology of Troyes, France, 2015
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