Knowledge and data-driven robotic decision scheme for modern wastewater treatment plants

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.