张春梅,刘庆玉,易维明,柏雪卫,张文基,来世鹏.玉米秸秆热裂解产物产率预测分析[J].农业机械学报,2011,42(9):120-123,185.
Zhang Chunmei,Liu Qingy,Yi Weiming,Bai Xuewei,Moonki Jang,Lai Shipeng.Predict Product Yields of Corn Stalk Plasma Pyrolysis[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(9):120-123,185.
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玉米秸秆热裂解产物产率预测分析   [下载全文]
Predict Product Yields of Corn Stalk Plasma Pyrolysis   [Download Pdf][in English]
  
DOI:10.3969/j.issn.1000-1298.[year].[issue].[sequence]
中文关键词:  玉米秸秆  热裂解  神经网络模型  产率  预测
基金项目:辽宁省秸秆能源化利用项目
作者单位
张春梅 沈阳农业大学 
刘庆玉 沈阳农业大学 
易维明 山东理工大学 
柏雪卫 沈阳农业大学 
张文基 沈阳农业大学 
来世鹏 建设部沈阳煤气热力研究设计院 
中文摘要:以影响热裂解液化过程的因素(输入功率、压差、氩气流量和进料率)为网络输入,热裂解液化产物为网络输出,应用BP神经网络模型法对玉米秸秆热裂解液化产物产率进行了预测分析,并将预测结果与非线性回归分析法进行了比较分析。结果表明,采用BP神经网络模型预测输出值与试验值间的相对误差总体上在5%之内,说明模拟预测的效果较好。对BP神经网络模型法与非线性回归方法的预测结果对比分析显示:在试验数据范围内,BP神经网络模型对玉米秸秆热裂解3种产物产率的预测值更接近试验值,计算精度比非线性回归方法略高。
Zhang Chunmei  Liu Qingy  Yi Weiming  Bai Xuewei  Moonki Jang  Lai Shipeng
Shenyang Agricultural University;Shenyang Agricultural University;Shandong University of Technology;Shenyang Agricultural University;Shenyang Agricultural University;Construction Ministry Shenyang Gas & Heat Research and Design Institute
Key Words:Corn stalk  Pyrolysis  Neural network  Product yields  Predict
Abstract:A method for predicting product-yield of corn stalk pyrolysis was established by means of BP neural network model. The model consisted of three neuron layers: input layer with four nodes which affected the pyrolysis process. It included input power, air flow rate, feeding rate and pressure, output layer with pyrolysis liquid yield and hidden layer. If the training data were representative, the results obtained by neural network model could be well in accordance with the experimental results and its errors would be less than 5%. The results obtained by neural network are more accurate than those obtained by non-linear regression.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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