Simultaneous modelling was carried out using the neural networks with three inputs including a distinguishing variable for the steam table. It covered whole steam tables including the compressed, saturated and superheated region of water. And relative errors of the thermodynamic properties such as specific volume, enthalpy, entropy were compared using the neural networks and the linear interpolation method. As a result of the analysis, The neural networks has proven to be powerful in modeling the steam table because it has slightly better results than the interpolation method.

1. 서 론
 2. 해 석
  2.1 상태량(state variable)
  2.2 신경회로망(neural networks)
  2.3(보간법 interpolation method)
 3. 결과 및 검토
 4. 결 론
 후 기
 References

• 이태환(Mechatronics Eng., Gyeongnam Nat‘l Univ. of Science and Technology) | Tae-Hwan Lee
• 박진현(Mechatronics Eng., Gyeongnam Nat‘l Univ. of Science and Technology) | Jin-Hyun Park Corresponding Author