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http://dx.doi.org/10.9712/KASS.2021.21.4.73

Optimal Design of Semi-Active Mid-Story Isolation System using Supervised Learning and Reinforcement Learning  

Kang, Joo-Won (School of Architecture, Yeungnam University)
Kim, Hyun-Su (Division of Architecture, Sunmoon University)
Publication Information
Journal of Korean Association for Spatial Structures / v.21, no.4, 2021 , pp. 73-80 More about this Journal
Abstract
A mid-story isolation system was proposed for seismic response reduction of high-rise buildings and presented good control performance. Control performance of a mid-story isolation system was enhanced by introducing semi-active control devices into isolation systems. Seismic response reduction capacity of a semi-active mid-story isolation system mainly depends on effect of control algorithm. AI(Artificial Intelligence)-based control algorithm was developed for control of a semi-active mid-story isolation system in this study. For this research, an practical structure of Shiodome Sumitomo building in Japan which has a mid-story isolation system was used as an example structure. An MR (magnetorheological) damper was used to make a semi-active mid-story isolation system in example model. In numerical simulation, seismic response prediction model was generated by one of supervised learning model, i.e. an RNN (Recurrent Neural Network). Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm The numerical simulation results presented that the DQN algorithm can effectively control a semi-active mid-story isolation system resulting in successful reduction of seismic responses.
Keywords
Supervised learning; Reinforcement learning; Semi-active control; Mid-story isolation system; Deep Q-network;
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