TY - GEN
T1 - Intelligent model selection for refrigerating compressors
AU - Sun, Ying
AU - Tan, Yufei
PY - 2011
Y1 - 2011
N2 - The traditional methods used to select refrigerating compressors have errors, such as consulting values from charts or estimating values subjectively. It leads to selecting the models of compressors inaccurately. During the course of model selection for compressor, too many parameters are concerned, which leads to a large amount of work and calculation. Method of minimum squares can be used to imitate the performance curves of compressor. It makes selecting compressor without chart and only concerned with condensation temperature and evaporation temperature, which greatly improves the speed and quality of selecting compressor.
AB - The traditional methods used to select refrigerating compressors have errors, such as consulting values from charts or estimating values subjectively. It leads to selecting the models of compressors inaccurately. During the course of model selection for compressor, too many parameters are concerned, which leads to a large amount of work and calculation. Method of minimum squares can be used to imitate the performance curves of compressor. It makes selecting compressor without chart and only concerned with condensation temperature and evaporation temperature, which greatly improves the speed and quality of selecting compressor.
KW - method of minimum squares
KW - model selection
KW - performance curve
KW - refrigerating compressor
UR - https://www.scopus.com/pages/publications/79960160836
U2 - 10.1109/ISA.2011.5873441
DO - 10.1109/ISA.2011.5873441
M3 - 会议稿件
AN - SCOPUS:79960160836
SN - 9781424498574
T3 - 2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011 - Proceedings
BT - 2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011 - Proceedings
T2 - 2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011
Y2 - 28 May 2011 through 29 May 2011
ER -