| 煤的工业分析至元素分析的BP神经网络预测模型 |
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| 引用本文： | 殷春根,骆仲泱.煤的工业分析至元素分析的BP神经网络预测模型[J].燃料化学学报,1999,27(5):408-414. |
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| 作者姓名： | 殷春根 骆仲泱 |
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| 作者单位： | 浙江大学热能工程研究所!杭州310027 |
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| 基金项目： | 浙江省中青年科技人才基金 |
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| 摘 要： | 以大量煤质分析数据为基础，建立了利用煤工业分析数据（ 包括水份、灰份、挥发份及热值） 计算元素分析数据的ＢＰ神经网络预测模型，并将该模型与现有经验公式进行了比较，结果表明神经网络模型有很好的推广能力。可以满足工业应用的要求
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| 关 键 词： | 工业分析 元素分析 神经网络 |
RELATIONSHIPBETWEEN ULTIMATEANALYSISOF ANY COAL ANDITSPROXIMATEANALYSISDATA |
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| Yin Chungen,Luo Zhongyang,Ni Mingjiang,Cen Kefa.RELATIONSHIPBETWEEN ULTIMATEANALYSISOF ANY COAL ANDITSPROXIMATEANALYSISDATA[J].Journal of Fuel Chemistry and Technology,1999,27(5):408-414. |
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| Authors: | Yin Chungen Luo Zhongyang Ni Mingjiang Cen Kefa |
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| Institution: | Institutefor Thermal Power Engineering Zhejian University Hangzhou |
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| Abstract: | There existsintrinsicrelation between the primary elements such as carbon , hydrogen ,oxygen and nitrogen and so on ,and the proximate analysis data including mois ture content,ash content,volatile content,fixed carbon and heatvalue ofcoal- However, thisrelationis much complicated and difficultto understandfully- Based on alarge quantity of coaldata ,a BPneuralnetwork modelis putforward inthis paperto predictthe ultimate analysisofa coalfrom its proximate analysis data- Comparison with the existing empirical modelsindicatesthat neuralnetwork techniqueis quite effectivein drawingtheintrinsic and intricate relationship betweenthe ultimate analysis ofa coaland its proximate analysis data- |
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| Keywords: | proximate analysis ultimate analysis artificial neuralnetwork |
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