fig1 shows a cross section through a rolled strip , where b is a width of the strip , h m is a thickness of the strip in the middle of the rolled strip , h l is a thickness of the strip at the left edge of the rolled strip and h r is a thickness of the strip at the right edge of the rolled strip . a possible definition of a thickness profile p of the rolled strip is provided by the following function : ## equ3 ## fig2 shows a functional block diagram of a system according to the present invention for determining the final thickness profile of a rolled strip . the system according to the present invention may be a one - chip computer or a multi - chip computer . the one - chip computer may include a microcontroller . the multi - chip computer may be a single - board computer or an automation device . the automation device may include a programmable controller , a vme bus or an industrial computer . fig2 also shows a roll stand model 1 of a roll stand 7 . the roll stand model 1 has a profile model 2 and a preprocessing block 3 . the profile model 2 determines the thickness profile p i of a rolled strip downstream from the roll stand 7 as a function of the thickness profile p i - 1 upstream from the roll stand 7 , a factor k i representing properties of the roll stand or properties of the roll stand taking into account properties of the rolled stock , of load roll nip profile π 1 which is calculated in the preprocessing block 3 , and of the strip thicknesses h i - 1 and h i upstream and downstream from the roll stand 7 . the factor k i is determined in a neural network - based information processing block 4 which includes a neural network 5 and a normalization block 6 . the modular structure of the system , i . e ., the separation into the roll stand model 1 and the neural network - based information processing block 4 , makes it possible to reuse known algorithms for determining the thickness profile of a rolled strip downstream from a roll stand . the roll stand model 1 preferably contains the models and algorithms of known processes . however , the known determination of the factor k i is replaced by the neural network - based information processing block 4 of the system of the present invention . by using proven algorithms and models in the roll stand model 1 , the neural network - based information processing block 4 can be made especially simple , because neither the profile model 1 nor the models such as a bending model , temperature model , or wear model need be learned , as is usually the case when calculating the load roll gap profile . the training for the neural network - based information processing 4 is strictly limited to the relationships between the roll stand and the rolled strip which are necessary to determine the factor k i . the input variable to the profile model 1 , the thickness profile p i - 1 upstream from the roll stand , may be either the output quantity of a profile model for an ( i - 1 ) th roll stand or a measured value . fig3 shows the latter case . fig4 shows a system for determining the final thickness profile of a rolled strip in a mill train 8 . the mill train 8 has four roll stands . the system for determining the thickness profile of the mill train 8 has four systems 9 , 10 , 11 and 12 , each one for determining the thickness profile of the rolled strip downstream from one roll stand . measured values 13 , 14 , 15 and 16 are sent to each of the systems 9 , 10 , 11 and 12 and serve as input quantities to the neural network - based information processing , for the preprocessing , and for the profile model . a chemical composition of a rolled stock can also be such input quantity . a measured value of thickness profile p 0 of the rolled strip upstream from the first roll stand is also sent to the system for determining the thickness profile of the rolled strip downstream from the first roll stand . the system 10 for determining the thickness profile p 2 of the rolled strip downstream from the second roll stand determines the strip thickness profile p 2 as a function of measured values 14 and strip thickness profile p 1 which is determined as the output quantity of system 9 for determining the strip thickness profile p i of the rolled strip downstream from the first roll stand . accordingly , each thickness profile p i , p 2 , and p 3 , which is supplied by an upstream system 9 , 10 , and 11 for determining the thickness profile of the rolled strip downstream from a roll stand , is the input quantity of the downstream system 10 , 11 , 12 for determining the thickness profile of the rolled strip downstream from the respective roll stand .