| 基于蚁群神经网络的飞灰含碳量测量方法 |
| Prediction Method of Unburned Carbon Content in Fly Ash Based on Ant Colony Algorithm |
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| 中文摘要: |
| 飞灰含碳量是衡量电站锅炉燃烧效率的重要参数，飞灰含碳量的准确测量有助于调整锅炉燃烧, 提高锅炉运行的经济性和安全性。本文采用了蚁群神经网络算法，利用蚁群算法对神经网络进行优化，将优化过后的神经网络用于飞灰含碳量的预测，并分析了经过蚁群神经算法与遗传神经网络的预测效果。 |
| 英文摘要: |
| unburned carbon content of fly ash is an important index reflecting the combustion efficiency of utility boiler. Measuring the carbon content in the fly ash accurately is beneficial to the detection and adjustment of boiler combustion. This paper uses the ant colony neural network which optimized the initializing weights, thresholds and numbers of node in hidden layer of BP neural network. The optimized neural network is used to predict the unburned carbon content of fly ash. And the prediction result is also analyzed in this paper. |
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| 中文关键词: 蚁群算法 神经网络 飞灰含碳量 |
| 英文关键词:ant colony algorithm neural network unburned carbon content |
| 基金项目: |
| DOI：10.11823/j.issn.1674-5795.2017.01.05 |
| 引用本文：张正友,钱家俊,冯旭刚.基于蚁群神经网络的飞灰含碳量测量方法[J].计测技术,2017,37(1):18~20. |
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