TEMPERATURE AND COMPONENTS IN FURNACE BATH USING NEURAL NETWORK

The ingot steel temperature and component variation predicting method using an artificial neural network comprises the steps of: inputting initial operation condition and factors of continuous sampling data to the artificial neural network to obtain an ingot steel temperature and component value according to the operation time; comparing past continuous sampling data obtained by the same operation condition and factors with the obtained ingot steel temperature and component value in the artificial neural network to execute learning for weighting value within an allowable error range; setting the weighting value when the addition of each error reaches the allowable error range and completing the learning; and inputting an initial operation condition to the learned artificial neural network to predict the ingot steel temperature and component value. 내용없음