원문정보
Modelling for the Full Ranges of the Steam Table using Neural Networks
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
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.
목차
ABSTRACT
1. 서론
2. 해석
2.1 상태량(state variable)
2.2 신경회로망(neural networks)
2.3(보간법 interpolation method)
3. 결과 및 검토
4. 결론
후기
References
1. 서론
2. 해석
2.1 상태량(state variable)
2.2 신경회로망(neural networks)
2.3(보간법 interpolation method)
3. 결과 및 검토
4. 결론
후기
References
키워드
- Steam table(증기표)
- Neural networks(신경회로망)
- Compressed region(압축영역)
- Saturated region(포화영역)
- Superheated region(과열영역)
- Interpolation method(보간법)
저자정보
참고문헌
자료제공 : 네이버학술정보