【摘要】 研究了一种基于特征变量的复杂生产过程预测模型．与传统的建模方法相比，该方法不需要经过机理分析，而从信息科学的角度出发，在对反映生产过程工况原始动态数据进行特征选择的基础上，运用时间序列分析法建立其预测模型．同时讨论了它的神经网络实现方法．仿真结果表明了该方法的可行性．更多还原

【Abstract】 A feature variables based predicting model for complex production process waspresented. Comparing with traditional methods，it bypasses the mechanism analysis，using time seriesanalysis technology and feature variables，selected from original dynamicaldatad which can reflect theoperating mode of complex production process build a new kind of predicting model.The neuralnetwork realization of this model is discussed.The results obtained by simulation show the feasibleof this method.更多还原