4[3]H.Bechtler,M.W.Browne,P.K.Bansal,V.Kecman.New approach to dynamic modeling of vapor-compression liquid chillers: artificial neural networks[J].Applied Thermal Engineering,2001(21):941-953.
5[4]A.T.P.So,T.T.Chow,W.L.Chan,W.L.Tse.A neural-network-based identifier/controller for modeling HAVC control [J].ASHRAE Transactions,1995,101(2):14-31.
6[5]P.S.Curtiss.Examples of neural networks used for building system control and energy management [J].ASHRAE Transaction,1997,103(2):909-913.
7[1]Mitra S.,Pal S.K.,Mitra P.Data mining in soft computing framework:a survey.IEEE Transaction on Neu ral Networks,2002,13(1).
8[2]Muller C.,Mangeas M..Systems, Man and Cybernetics,Neural networks and times series forecasting:a theoretical approach.Conference Proceedings, International Conference on Systems Engineering in the Service of Humans'.,Oct 1993,2:17～20.
9Haves P, Salsbury T I, Wright J A. Condition monitoring in HVAC subsystem using first principles models[J]. ASHRAE Transactions, 1996, 102 (1):519-527.
10Tsutsui H, Kamimura K. Chiller condition monitoring using topological tase-based modeling [J].ASHRAE Transactions, 1996, 102 (1): 641 - 648.
