CAJ | 학술논문

结合粗糙集理论和 BP神经网络在信息处理方面的优势，建立了一个基于粗糙集理论和 BP 神经网络的系统模型，并在此基础上用于粮食产量预测。仿真结果表明，该模型较之传统的预测方法显著地提高了预测的速度和精度，在实际中有着良好的应用前景。
결합조조집이론화 BP신경망락재신식처리방면적우세，건립료일개기우조조집이론화 BP 신경망락적계통모형，병재차기출상용우양식산량예측。방진결과표명，해모형교지전통적예측방법현저지제고료예측적속도화정도，재실제중유착량호적응용전경。
Based on rough set theory and BP neural network advantages in information processing , establishes a system model based on rough set theory and BP neural network , on this basis for grain production prediction .The simulation re-sults show that compared with the traditional model and prediction method. The method in this paper significantly im-proves the speed and precision of prediction , so it has a good application prospect in practice .