文件名称:BP5
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [PDF]
- 上传时间：
- 2012-11-26
- 文件大小：
- 176kb
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- 0次
- 提 供 者：
- 杜**
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回转窑的生产过程是一个复杂的物理化学反应过程，具有大惯性、纯滞后、非线性等
特点。工艺过程复杂多变，难以得到精确的数学模型.本文利用BP神经网络可以实现任意非
线性映射的特点建立其神经网络预测模型,结合广西某大型水泥厂实时采集的生产数据，进
行仿真研究。仿真结果表明，该模型能够很好的预测水泥回转窑的温度。 -Rotary kiln production process is a complex physical and chemical reaction process, with a large inertia, pure lag and nonlinear characteristics. Complex process, difficult to get a precise mathematical model. In this paper, BP neural network can implement any nonlinear mapping to establish the characteristics of the neural network prediction model, combined with a large cement plant in Guangxi real-time collection of production data, the simulation study. Simulation results show that the model can well predict the temperature of the cement kiln.
特点。工艺过程复杂多变，难以得到精确的数学模型.本文利用BP神经网络可以实现任意非
线性映射的特点建立其神经网络预测模型,结合广西某大型水泥厂实时采集的生产数据，进
行仿真研究。仿真结果表明，该模型能够很好的预测水泥回转窑的温度。 -Rotary kiln production process is a complex physical and chemical reaction process, with a large inertia, pure lag and nonlinear characteristics. Complex process, difficult to get a precise mathematical model. In this paper, BP neural network can implement any nonlinear mapping to establish the characteristics of the neural network prediction model, combined with a large cement plant in Guangxi real-time collection of production data, the simulation study. Simulation results show that the model can well predict the temperature of the cement kiln.
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