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玉米秸稈熱裂解產(chǎn)物產(chǎn)率預測分析
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Predict Product Yields of Corn Stalk Plasma Pyrolysis
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    摘要:

    以影響熱裂解液化過程的因素(輸入功率、壓差,、氬氣流量和進料率)為網(wǎng)絡輸入,,熱裂解液化產(chǎn)物為網(wǎng)絡輸出,,應用BP神經(jīng)網(wǎng)絡模型法對玉米秸稈熱裂解液化產(chǎn)物產(chǎn)率進行了預測分析,,并將預測結果與非線性回歸分析法進行了比較分析。結果表明,,采用BP神經(jīng)網(wǎng)絡模型預測輸出值與試驗值間的相對誤差總體上在5%之內(nèi),,說明模擬預測的效果較好。對BP神經(jīng)網(wǎng)絡模型法與非線性回歸方法的預測結果對比分析顯示:在試驗數(shù)據(jù)范圍內(nèi),,BP神經(jīng)網(wǎng)絡模型對玉米秸稈熱裂解3種產(chǎn)物產(chǎn)率的預測值更接近試驗值,,計算精度比非線性回歸方法略高。

    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.

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張春梅,劉慶玉,易維明,柏雪衛(wèi),張文基,來世鵬.玉米秸稈熱裂解產(chǎn)物產(chǎn)率預測分析[J].農(nóng)業(yè)機械學報,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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