| 基于遗传算法和径向基函数神经网络的转炉炼钢模型 |
| |
| 引用本文： | 陶钧,谢书明,柴天佑.基于遗传算法和径向基函数神经网络的转炉炼钢模型[J].系统仿真学报,2000,12(3):241-244,277. |
| |
| 作者姓名： | 陶钧 谢书明 柴天佑 |
| |
| 作者单位： | 东北大学自动化研究中心,沈阳,110006 |
| |
| 基金项目： | 国家九五重点攻关项目(专题号：97-562-03-02);自然
科学基金(69934020);863/CIMS高科技计划. |
| |
| 摘 要： | 针对转炉传统模型的弱点 ,本文在转炉建模过程中引入了遗传算法和径向基函数神经网络 ,由遗传算法辨识转炉过程的脱碳与升温模型 ,并利用径向基函数神经网络及时补偿辨识模型的误差。实际结果表明这一方法效果明显。
|
| 关 键 词： | 转炉炼钢 遗传算法 径向基函数 神经网络 |
Steelmaking BOF Model Based on GAs and RBF Neural Network |
| |
| TAO Jun,XIE Shu-ming,CHAI Tian-you.Steelmaking BOF Model Based on GAs and RBF Neural Network[J].Journal of System Simulation,2000,12(3):241-244,277. |
| |
| Authors: | TAO Jun XIE Shu-ming CHAI Tian-you |
| |
| Abstract: | With respect to the shortcomings of traditional BOF model such as local convergence and poor precision, the paper introduces genetic algorithms (GAs) and radial basis function neural network (RBF NN) for the modeling of basic oxygen furnace (BOF) process, where the GAs is used to identify the model of decarbonisation and temperature rising of the bath, and RBF NN to compensate for the errors from the previous model. The results show the method is effective. |
| |
| Keywords: | basic oxygen furnace steelmaking genetic algorithms radial basis function neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
