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基于模糊神经网络的柴油机排气噪声预测 被引量:2

Forecast of Exhaust Noise for Diesel Engines Based on FNN
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摘要 应用模糊神经网络FNN(FuzzyNeuralNetworks)的模糊推理对噪声数据的预测进行了研究分析。和传统的BP网络方法相比 ,模糊神经网络具有概念清晰 ,逻辑清楚 ,且不会限于局部极小点等特点 ,实验结果充分证明了这种方法的有效性 ,并且本文用较小规模的正交试验数据作为训练样本 ,达到了试验量少效果好的目的。 Forecast the noise data using the reasoning of FNN. Compared with the conventional BP network, FNN is more logical and clearer; moreover, it won't fall into local minimum often. The results of the experimentation proves the validity of FNN. By using FNN, a conclusion is successfully drawn with small dimension data.
出处 《华东船舶工业学院学报》 EI 2001年第6期54-57,共4页 Journal of East China Shipbuilding Institute(Natural Science Edition)
关键词 排气噪声 预测 柴油机 模糊神经网络 正交试验 diesel fuzzy neural network orthogonal experiment noise
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