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Research on modeling method of coke oven's blast blower suction based on improved BP neural network

机译:基于改进BP神经网络的焦炉鼓风机吸风建模方法研究

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For the complicated mechanism and difficult traditional modeling of the blast blower cooling system of coke oven, a new dynamic mathematic model for the fore end suction of blast blower cooling system has been firstly established. This model avoids the complex process of analysis on blast blower cooling system, makes full use of the existing field data, and traverses to all sections of the production process. Then artificial bee colony (ABC) algorithm is used to optimize the BP neural network's structure parameters and an analysis is conducted on different type of input variables. Finally, a validation for the established model is performed with the test samples that collected from different process sections, and simulation results show that the obtained model has a faster convergence and higher approximation accuracy.
机译:针对焦炉鼓风机冷却系统机理复杂,传统建模困难的问题,首先建立了鼓风机冷却系统前端吸力的动态数学模型。该模型避免了对鼓风机冷却系统进行复杂的分析过程,充分利用了现有的现场数据,并遍历了生产过程的所有部分。然后使用人工蜂群算法(ABC)对BP神经网络的结构参数进行优化,并对不同类型的输入变量进行分析。最后,使用从不同过程部分收集的测试样本对建立的模型进行验证,仿真结果表明所获得的模型具有更快的收敛性和更高的逼近精度。

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