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A NEURAL NETWORK BASED MODEL FOR URBAN NOISE PREDICTION

机译:基于神经网络的城市噪声预测模型

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This paper describes a model developed for the prediction of environmental urban noise using Soft Computing techniques, namely Artificial Neural Networks (ANN). The model is based on the analysis of variables regarded as influential by experts in the field and was applied to data collected on different types of streets. The results were compared to those obtained with other models. The study found that the ANN system was able to predict urban noise with great accuracy and thus, was an improvement over those models. The principal component analysis (PCA) was also used to try to simplify the model. Although there was a slight decline in the accuracy of the results, the values obtained were also quite acceptable.
机译:本文介绍了使用软计算技术(即人工神经网络(ANN))为预测城市环境噪声而开发的模型。该模型基于对该领域专家认为具有影响力的变量的分析,并应用于在不同类型的街道上收集的数据。将结果与其他模型获得的结果进行比较。研究发现,人工神经网络系统能够非常准确地预测城市噪声,因此是对那些模型的改进。主成分分析(PCA)也用于尝试简化模型。尽管结果的准确性略有下降,但获得的值也完全可以接受。

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