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机译:可持续蓄洪盆地的多标签分类模型
Institute for Infrastructure and Environment, School of Engineering, The University of Edinburgh, William Rankine Building, Mayfield Road,The King's Buildings, Edinburgh EH9 3JL, Scotland, United Kingdom;
Institute for Computer Science, University of Munich, 80937 Munich, Germany;
Institute for Infrastructure and Environment, School of Engineering, The University of Edinburgh, William Rankine Building, Mayfield Road,The King's Buildings, Edinburgh EH9 3JL, Scotland, United Kingdom Civil Engineering Research Centre, School of Computing, Science and Engineering, The University of Salford, Newton Building, Salford MS 4WT, England, United Kingdom;
Institute for Computer Science, University of Munich, 80937 Munich, Germany;
Department of Scientific Computing, Florida State University, Tallahassee, FL, USA;
flood control; multi-label support vector machine; multi-label K-nearest neighbor; back-propagation for multi-label learning; multiple function; classification framework; water resources; landscape management; scotland; baden;
机译:通过多实例多标签学习预测不确定性下的可持续洪灾盆地多功能
机译:可持续蓄洪盆地概念分类模型
机译:可持续蓄洪盆地分类方法。
机译:使用计算有效模型,在比利时腐败流域对河流洪水影响的量化
机译:通过基于物理的分布式模型改进流域的洪水预报。
机译:多标签分类模型在糖尿病并发症诊断中的应用
机译:利用多实例多标签学习预测不确定性可持续防洪流域的多重功能