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| 摘要: |
| 传统风煤比寻优通常采用求解燃烧函数解析式，再求极值得出最佳风煤比，这一方法可靠性差而且工作量大。提出用BP神经网络拟合燃烧函数，并结合Matlab中的优化工具箱求解最佳风煤比。仿真计算的结果表明所用的方法能很好地适应（克服）燃烧函数的非线性，所得的风煤比可以取得较高的燃烧效率。 |
| 关键词: 风煤比 BP神经网络 燃烧效率 |
| DOI： |
| 分类号:TK16 |
| 基金项目: |
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| Optimization of air-coal ratio based on BP neural network |
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YOU Yi DU Hong-ji WANG Jun
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| Abstract: |
| In traditional ways,the optimal air-coal ratio is obtained by solving combustion function and finding out the extremum,which is time-consuming and unreliable. A new approach is presented,which fits the combustion function with BP neural network and seeks the optimal air-coal ratio with Matlab. Simulative results show that it suits with the nonlinearity of combustion function and the optimized air-coal ratio results in better combustion efficiency. |
| Key words: air-coal ratio BP neural network combustion efficiency |
