This study deals with the application of an artificial neural network (ANN) model to predict power consumption for utilizing seawater source heat pumps of recirculating aquaculture system. An integrated dynamic simulation model was constructed using the TRNSYS program to obtain input and output data for the ANN model to predict the power consumption of the recirculating aquaculture system with a heat pump system. Data obtained from the TRNSYS program were analyzed using linear regression, and converted into optimal data necessary for the ANN model through normalization. To optimize the ANN-based power consumption prediction model, the hyper parameters of ANN were determined using the Bayesian optimization. ANN simulation results showed that ANN models with optimized hyper parameters exhibited acceptably high predictive accuracy conforming to ASHRAE standards.

서 론
재료 및 방법
    연구 방법
    해수 열원 HP 시스템을 갖는 RAS 양식장 모델과 동적열부하 분석
    동적 에너지 시뮬레이션 모델 구축 및 분석 결과
    전력 소비량 예측을 위한 ANN 모델의 입·출력 데이터세트 구성
    ANN 예측 모델 구축 및 하이퍼 파라미터의 최적화
결과 및 고찰
결 론
사 사
References

• 정현석(부경대학교 대학원 냉동공조공학과 대학원생) | Hyeon-Seok JEONG (Student, Graduate School of Refrigeration and Air-conditioning Engineering, Pukyong National University, Busan 48513, Korea)
• 류종혁(부경대학교 대학원 냉동공조공학과 대학원생) | Jong-Hyeok RYU (Student, Graduate School of Refrigeration and Air-conditioning Engineering, Pukyong National University, Busan 48513, Korea)
• 정석권(부경대학교 냉동공조공학과 교수) | Seok-Kwon JEONG (Professor, Department of Refrigeration and Air-conditioning Engineering, Pukyong National University, Busan 48513, Korea) Corresponding author