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Type: Conference paper
Title: Knowledge and data-driven robotic decision scheme for modern wastewater treatment plants
Author: Cheng, X.
Guo, Z.
Shen, Y.
Shi, P.
Citation: Proceedings of the IEEE International Conference on Intelligence and Safety for Robotics (ISR 2021), 2021, pp.101-105
Publisher: IEEE
Publisher Place: online
Issue Date: 2021
ISBN: 9781665438629
Conference Name: IEEE International Conference on Intelligence and Safety for Robotics (ISR) (4 Mar 2021 - 6 Mar 2021 : virtual online)
Statement of
Xuhong Cheng, Zhiwei Guo, Yu Shen, Peng Shi
Abstract: Multi-variable and non-linear features for wastewater treatment process (WTP), traditional expert experience-based decision making scheme can not well express the WTP. To overcome the challenge, this paper proposes to build Robotic Decision scheme based on joint awareness of knowledge and data for modeling of WTP. Firstly, Modeling WTP by knowledge modeling system and neural network modeling system respectively. After that, Establish a collaboration awareness layer to ingeniously combine knowledge model with data model. At last, a series of experiments are carried out on a dataset obtained from a realistic wastewater treatment plant, in order to evaluate the performance and reliability of the proposed RD-ACL. The results show that the proposal improves modeling efficiency compared with typical existing methods. Through such a collaborative modeling scheme, intelligent management degree of WTP can be improved to some extent.
Keywords: wastewater treatment process; robotic decision making; neural networks; knowledge model; data model
Rights: ©2021 IEEE
DOI: 10.1109/ISR50024.2021.9419512
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Appears in Collections:Aurora harvest 8
Electrical and Electronic Engineering publications

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