Mechanical Parameter Identification of Hydraulic Engineering with the Improved Deep Q-Network Algorithm
Joint Authors
Li, Tongchun
Ji, Wei
Liu, Xiaoqing
Qi, Huijun
Liu, Xunnan
Lin, Chaoning
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-28
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
During the long-term operating period, the mechanical parameters of hydraulic structures and foundation deteriorated gradually because of the environmental factors.
In order to evaluate the overall safety and durability, these parameters should be calculated by some accurate analysis methods, which are hindered by slow computational efficiency and optimization performance.
The improved deep Q-network (DQN) algorithm combined with the deep neural network (DNN) surrogate model was proposed in this paper to ameliorate the above problems.
Through the study cases of different zoning in the dam body and the actual engineering foundation, it is shown that the improved DQN algorithm has a good application effect on inversion analysis of material mechanical parameters in this paper.
American Psychological Association (APA)
Ji, Wei& Liu, Xiaoqing& Qi, Huijun& Liu, Xunnan& Lin, Chaoning& Li, Tongchun. 2020. Mechanical Parameter Identification of Hydraulic Engineering with the Improved Deep Q-Network Algorithm. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1196775
Modern Language Association (MLA)
Ji, Wei…[et al.]. Mechanical Parameter Identification of Hydraulic Engineering with the Improved Deep Q-Network Algorithm. Mathematical Problems in Engineering No. 2020 (2020), pp.1-20.
https://search.emarefa.net/detail/BIM-1196775
American Medical Association (AMA)
Ji, Wei& Liu, Xiaoqing& Qi, Huijun& Liu, Xunnan& Lin, Chaoning& Li, Tongchun. Mechanical Parameter Identification of Hydraulic Engineering with the Improved Deep Q-Network Algorithm. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1196775
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196775