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机译:深度自回归神经网络,用于地下水污染源源识别的高维逆问题
Key Laboratory of Surficial Geochemistry of Ministry of Education School of Earth Sciences and Engineering Nanjing University Nanjing China;
Center for Informatics and Computational Science University of Notre Dame Notre Dame IN USA;
Key Laboratory of Surficial Geochemistry of Ministry of Education School of Earth Sciences and Engineering Nanjing University Nanjing China;
Key Laboratory of Surficial Geochemistry of Ministry of Education School of Earth Sciences and Engineering Nanjing University Nanjing China;
inverse problem; source identification; high dimensionality; deep autoregressive neural networks; iterative ensemble smoother;
机译:深度自回归神经网络用于地下水污染源识别中的高维反问题
机译:基于污染物源神经网络定位器和优化传感器网络的室内污染物源位置实时识别
机译:多元统计方法和神经网络识别污染源并对普利亚地区地下水进行分类。
机译:人工神经网络在地下水系统污染源识别中的应用。
机译:使用基于概率的逆建模方法识别室内空气污染物源。
机译:深度卷积神经网络征用众包路景观作物类型
机译:深度自回归神经网络,用于地下水污染源源识别的高维逆问题