SNAK(Smart Nexus for Agriculture in Korea)을 위한 생물물리학적(Biophysical) 통합 모델 개발 및 기후 변화 연계기술 개발

  • Published : 2019.02.28

Abstract

Keywords

References

  1. Chen, Lijun, Shangfeng Du, Yaofeng He, Meihui Liang and Dan Xu, 2018. Robust model predictive control for greenhouse temperature based on particle swarm optimization. Information Processing in Agriculture 5(3): 329-338. doi:10.1016/j.inpa.2018.04.003.
  2. Shin, H. and S. Nam, 2015. Validation of load calculation method for greenhouse heating design and analysis of the influence of infiltration loss and ground heat exchange. Korean Society of Horticultural Science 33(5): 647-657. doi: 10.7235/hort.2015.15007. (in Korean)
  3. Steduto, Pasquale & Hsiao, Theodore & Fereres, E & Raes, Dirk, 2012. Crop yield response to water. FAO.
  4. T. Foster, N. Brozovic, A.P. Butler, C.M.U. Neale, D. Raes, P. Steduto, E. Fereres, T.C. Hsiao, 2017. AquaCrop-OS: An open source version of FAO's crop water productivity model. Agricultural Water Management 181: 18-22. https://doi.org/10.1016/j.agwat.2016.11.015
  5. Van Beveren, P.J.M., J. Bontsema, G. van Straten and E.J. van Henten, 2015. Optimal control of greenhouse climate using minimal energy and grower defined bounds. Applied Energy 159: 509-519. doi: 10.1016/j.apenergy.2015.09.012.6.
  6. Van Henten, E.J. and J. Bontsema, 2009. Time-scale decomposition of an optimal control problem in greenhouse climate management, Control Engineering Practice 17(1): 88-96. doi:10.1016/j.conengprac.2008.05.008.