应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测

环境工程学报

应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测

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梁静, 张衍国, 蒙爱红, 李清海. 应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测[J]. 环境工程学报, 2009, 3(11): 2087-2090.

引用本文:

梁静, 张衍国, 蒙爱红, 李清海. 应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测[J]. 环境工程学报, 2009, 3(11): 2087-2090.

Liang Jing, Zhang Yanguo, Meng Aihong, Li Qinghai. Applying neural network to optimize the melting point prediction of simulant solid waste ash[J]. Chinese Journal of Environmental Engineering, 2009, 3(11): 2087-2090.

Citation:

Liang Jing, Zhang Yanguo, Meng Aihong, Li Qinghai. Applying neural network to optimize the melting point prediction of simulant solid waste ash[J]. Chinese Journal of Environmental Engineering, 2009, 3(11): 2087-2090.

应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测

1.
清华大学热能工程系热科学与动力工程教育部重点实验室，北京 100084
基金项目:
中图分类号: TK09

Applying neural network to optimize the melting point prediction of simulant solid waste ash

1.
Key Laboratory for Thermal Science and Power Engineering， Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China
Fund Project:

摘要: 采用SiO2、Al2O3、CaO、Na2CO3、NaCl和Fe2O3等物质来模拟垃圾焚烧的真实灰渣组成，通过实验测定模拟灰渣熔点，建立神经网络模型进行熔点预测，由预测结果来指导进一步实验，得到修正的模型，最终预测出的半球温度（HT）平均误差低于5%。
- 熔融 /
- 熔点 /
- 模拟灰渣 /
- 神经网络
Abstract: The experiment of slag melting point measurement has been done using compounds of SiO2, Al2O3, CaO, Na2CO3, NaCl and Fe2O3, which are mixed to simulate real slag. Then a neural network model is set up to predict the melting point, which is used to direct further experiments and improve the model. This model can predit HT (hemisphere temperature) with an average error of less than 5%.
- melting /
- melting point /
- simulant slag /
- neural network

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梁静, 张衍国, 蒙爱红, 李清海. 应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测[J]. 环境工程学报, 2009, 3(11): 2087-2090.

引用本文:

梁静, 张衍国, 蒙爱红, 李清海. 应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测[J]. 环境工程学报, 2009, 3(11): 2087-2090.

Liang Jing, Zhang Yanguo, Meng Aihong, Li Qinghai. Applying neural network to optimize the melting point prediction of simulant solid waste ash[J]. Chinese Journal of Environmental Engineering, 2009, 3(11): 2087-2090.

Citation:

Liang Jing, Zhang Yanguo, Meng Aihong, Li Qinghai. Applying neural network to optimize the melting point prediction of simulant solid waste ash[J]. Chinese Journal of Environmental Engineering, 2009, 3(11): 2087-2090.

应用神经网络方法优化垃圾焚烧模拟灰渣熔点的预测

1. 清华大学热能工程系热科学与动力工程教育部重点实验室，北京 100084

收稿日期: 2009-03-20

基金项目:

关键词:

熔融 /
熔点 /
模拟灰渣 /
神经网络

摘要: 采用SiO2、Al2O3、CaO、Na2CO3、NaCl和Fe2O3等物质来模拟垃圾焚烧的真实灰渣组成，通过实验测定模拟灰渣熔点，建立神经网络模型进行熔点预测，由预测结果来指导进一步实验，得到修正的模型，最终预测出的半球温度（HT）平均误差低于5%。

English Abstract

Applying neural network to optimize the melting point prediction of simulant solid waste ash

1. Key Laboratory for Thermal Science and Power Engineering， Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China

Received Date: 2009-03-20

Fund Project:

Keywords:

Abstract: The experiment of slag melting point measurement has been done using compounds of SiO2, Al2O3, CaO, Na2CO3, NaCl and Fe2O3, which are mixed to simulate real slag. Then a neural network model is set up to predict the melting point, which is used to direct further experiments and improve the model. This model can predit HT (hemisphere temperature) with an average error of less than 5%.

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