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首页> 外文期刊>Applied thermal engineering: Design, processes, equipment, economics >Application of artificial neural network to predict specific fuel consumption and exhaust temperature for a Diesel engine
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Application of artificial neural network to predict specific fuel consumption and exhaust temperature for a Diesel engine

机译:人工神经网络在预测柴油机比油耗和排气温度中的应用

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摘要

The ability of an artificial neural network model, using a back propagation learning algorithm, to predict specific fuel consumption and exhaust temperature of a Diesel engine for various injection timings is studied. The proposed new model is compared with experimental results. The comparison showed that the consistence between experimental and the network results are achieved by a mean absolute relative error less than 2%. It is considered that a well-trained neural network model provides fast and consistent results, making it an easy-to-use tool in preliminary studies for such thermal engineering problems. (c) 2005 Elsevier Ltd. All rights reserved.
机译:研究了使用反向传播学习算法的人工神经网络模型预测各种喷射正时的柴油机比燃料消耗和排气温度的能力。将提出的新模型与实验结果进行比较。比较表明,实验结果和网络结果之间的一致性是通过平均绝对相对误差小于2%来实现的。人们认为,训练有素的神经网络模型可以提供快速且一致的结果,使其成为针对此类热工程问题的初步研究中易于使用的工具。 (c)2005 Elsevier Ltd.保留所有权利。

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