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.

Abstract
1. 서론
2. 지도학습을 통한 예제구조물 해석 모델
3. 강화학습을 이용한 준능동 중간층면진시스템의 제어알고리즘
4. 준능동 중간층면진시스템의 지진응답 제어성능
5. 결론
References

• 강주원(영남대학교 건축학부) | Kang Joo-Won (School of Architecture, Yeungnam University)
• 김현수(선문대학교 건축학부) | Kim Hyun-Su (Division of Architecture, Sunmoon University.) 교신저자