【文章內(nèi)容簡介】 ng system.. 2. A TWO STAGE RBF NEURAL NETWORK A twostage RBF neural work is adopted. The first stage is used to determine the optimum value of the cold storage temperature, and the second is used to predict the temperature. Generally, suppose that there are n input variables 1x ,… , nx and m output variables 1y ,… , my . Let 1( ,..., )Tnx x x= (1) 1( ,..., )Tmy y y= (2) Using RBF Neural Network for Optimum control of a Cold Storage where x denotes a point in the n dimensional input space nR ,while y denotes a point in the m dimensional output space mR ,Suppose that the number of the hidden units is H .Every hidden unit uses two parameters, one is scalar quantity ( 0)hs ,the other is vector ()hx .Suppose that the set of the training samples is ( ) ( ){ ( , )}kkx y k K＃ .Generally, n H K＃ should be satisfied. RBF neural works are based on the interpolating value performance of radiusbased functions. To improve this performance ,the following equation is used to calculate the j the output of an RBF neural work. ^ 221^ 221()e xp( ),1()e xp( )Hjhh hjH hh hxxy j mxxv ss=== ＃229。229。 (3) Here, the numerator is a traditional RBF interpolating algorithm expression, and the denominator is the interpolating expression of constant this denominator, the attenuation of exponent functions in the numerator is canceled out greatly by that of the denominator. In this way ,the improved RBF neural work has a better performance. 3. THE ONLINE CALCULATION OF THE COLD STORAGE TEMPERATURE To choose the target value of the cold storage temperature, it is needed to take overall considerations about all factors. In order to use energy reasonably, the refrigeration process should have a high performance coefficient 0e which is the ratio of the refrigeration quantum 0Q to the needed energy P satisfying 00 Qe P= (4) Research results show that 0e increases as the evaporation temperature increases or the condensation temperature decreases [4,6],and a higher evaporation temperature and a lower condensation temperature are beneficial to keep fruits and vegetable fresh . Thus the refrigeration system should run under a higher evaporation temperature and a lower condensation temperature. However the evaporation temperature is apparently limited by the temperature of the object under refrigeration. For a special kind of fruit or vegetable just entering the cold storage, its optimum storage temperature can be got with the orthogonal experimental method. The optimum storage temperature decreases with the increasing of the storage time. The loss of per unit of i th fruit or vegetable is (1) ( 2 )i i iL L L=+ (5) where (1)iL is produced by frostbiting, while (2)iL by deteriorating .When temperature increases , (1)iL decreases and (2)iL increases .Both of them are related to the storage time t , thus ( 1 ) ( 2 )( 1 ) 0 ( 2 ) 0[ , ] , [ , ]iii i i iLLf T t t f T t ttt抖 = = 抖 (6) where (1)if decreases and (2)if increases respectively when the temperature T increases , 0it denotes the time of entering the storage, while 0itt denotes the storage time, then we have 0( 1 ) 0 ( 2 ) 0{ [ , ] [ , ] }iti i i i itL f T t t f T t t d t= + 242。 (7) For i th fruit or vegetable, its optimum storage temperature *iT should satisfy the following equation ( 1 ) * 0 ( 2 ) * 0[ , ] [ , ] 0i i i i i if T t t f T t tTT?? +=抖 (8) Let the gravity of i th fruit or vegetable be ig ,its storage loss iigL , then the total storage loss in a unit time interval is ( 1 ) 0 ( 2 ) 01 { [ , ] [ , ] }n i i i i iiL g f T t t f T t tt=182。 = + 182。 229。 (9) Let *T denote the optimum storage temperature in general .It should satisfy 2*( , ) 0L T ttT182。 =抖 (10) that is, ( 1 ) * 0 ( 2 ) * 01[ , ] [ , ]{ } 0n i i i i i iiif T t t f T t tg TT=?? +=抖229。 (11) The calculation of *iT in above formulae with traditional methods is time consuming. Hence we use an RBF neural work to acplish the solution of *iT . This RBF neural work is the first part of the twostage RBF neural work proposed in the paper .It has only one output , ..ie , *iT ,and 2n inputs, that is ig ,1 in＃ and 0itt ,1 in＃ . Hn= hidden units are used here .Equation(11) is used to produce enough training samples. 4 、 THE ONLINE PREDICTION OF THE C