Based on the non-mechanism modelling principle for soft-measurement

an on-line soft-measuring model used for coal quality has been established by using genetic algorithm(GA) combined with artificial neural network.The BP neural network and GA have been presented

and the modelling mode of their combination being determined.The whole process

including the raw coal entering into the coal-pulverizing system to being fully burnt-up and discharged away has been analysed

obtaining a collection of parameters at the input and output nodal points

through actual number programming of initial values in weighing parameters

the process of GA-BP algorithm based on actual number programming has been designed

and the working-out of GA-BP algorithm programming and its debugging are completed on the developing platform Visual Studio 2005.By using real-time operation data of a 200 MW unit in one power plant of Shanxi Province

the model training and detection have been carried out

results show that the said model can more accurately predict the coal quality parameters.