Peng Li, Dr.-Ing.
Peng Li, Dr.-Ing.
Research Fellow, Institute Industrial IT-TH OWL
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Cited by
Cited by
Smart factory of industry 4.0: Key technologies, application case, and challenges
B Chen, J Wan, L Shu, P Li, M Mukherjee, B Yin
Ieee Access 6, 6505-6519, 2017
Cross-network fusion and scheduling for heterogeneous networks in smart factory
J Wan, J Yang, S Wang, D Li, P Li, M Xia
IEEE Transactions on Industrial Informatics 16 (9), 6059-6068, 2019
Data Driven Modeling for System-Level Condition Monitoring on Wind Power Plants.
J Eickmeyer, P Li, O Givehchi, F Pethig, O Niggemann
DX, 43-50, 2015
Non-convex hull based anomaly detection in CPPS
P Li, O Niggemann
Engineering Applications of Artificial Intelligence 87, 103301, 2020
Data driven condition monitoring of wind power plants using cluster analysis
P Li, J Eickmeyer, O Niggemann
2015 International Conference on Cyber-Enabled Distributed Computing and …, 2015
Improving clustering based anomaly detection with concave hull: An application in fault diagnosis of wind turbines
P Li, O Niggemann
2016 IEEE 14th International Conference on Industrial Informatics (INDIN …, 2016
A nonconvex archetypal analysis for one-class classification based anomaly detection in cyber-physical systems
P Li, O Niggemann
IEEE transactions on industrial informatics 17 (9), 6429-6437, 2020
A geometric approach to clustering based anomaly detection for industrial applications
P Li, O Niggemann, B Hammer
IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society …, 2018
Why symbolic ai is a key technology for self-adaption in the context of cpps
A Bunte, P Wunderlich, N Moriz, P Li, A Mankowski, A Rogalla, ...
2019 24th IEEE International Conference on Emerging Technologies and Factory …, 2019
A data provenance based architecture to enhance the reliability of data analysis for Industry 4.0
P Li, O Niggemann
2018 IEEE 23rd International Conference on Emerging Technologies and Factory …, 2018
Mapping Data Sets to Concepts using Machine Learning and a Knowledge based Approach.
A Bunte, P Li, O Niggemann
ICAART (2), 430-437, 2018
Intelligente Zustandsüberwachung v. on Windenergie· anlangen als Cloud-Service
J Eickmeyer, F Pethig, S Schriegel, O Niggemann, O Givechi, P Li, ...
Automation, 2015
Learned Abstraction: Knowledge Based Concept Learning for Cyber Physical Systems.
A Bunte, P Li, O Niggemann
Machine Learning for Cyber Physical Systems: Selected papers from the …, 2020
On the identification of decision boundaries for anomaly detection in CPPS
P Li, O Niggemann, B Hammer
2019 IEEE International Conference on Industrial Technology (ICIT), 1311-1316, 2019
Transformer in Reinforcement Learning for Decision-Making: A Survey
W Yuan, J Chen, S Chen, L Lu, Z Hu, P Li, D Feng, F Liu, J Chen
TechRxiv, 2023
Universal process optimization assistant for medium-sized manufacturing enterprises as self-learning expert system
A Diedrich, J Eickmeyer, O Niggemann, P Li, T Hoppe, M Fuchs
Bayesian predictive assistance system: An embedded application for resource optimization in industrial cleaning processes
GM Shrestha, P Li, O Niggemann
2015 IEEE 13th International Conference on Industrial Informatics (INDIN …, 2015
A dynamic core evolutionary clustering algorithm based on saturated memory
H Xie, P Li, Z Ding
Autonomous Intelligent Systems 3 (1), 8, 2023
A Rule Embbeding Method of Winrate Approximation for Texas Hold’em
Z Hu, S Chen, W Yuan, P Li, M Zou, J Chen, J Chen
2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT), 1-9, 2022
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