Abstract:Aim at actual complicacy and difficulty of BTP (Burning Through Point) control,a prediction system of neural network has been developed. The model of 4 layers feedforward neural network with many factors has been set up for forecasting BTP and the highest exhaust gas temperature, that network output is constituted by computing BTP and the highest exhaust gas temperature with extremum characteristic of conic, what is new method of locale BTP to control. The network possess advanced reasonable construction designs, high accuracy and strong generalization ability. The network training sum of squared error is 0.00001814. To test the output with the training sample set, the absolute average error of BTP is 0.04,and the highest exhaust gas temperature is 4.57℃ at BPT bellows. The maximal absolute error of BTP(NO.of bellows) is 0.09 when forecasting after neural network training, it is 3.57℃ for the highest exhaust gas temperature at BPT bellows,the rate in accuracy area of forecast is 100%. A well result will be obtained by adjusting sintering parameter with intention.