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为满足水土工程深入研究及复杂系统建模优化的需要,针对利用高含沙洪水治沙淤地后土壤养分、颗粒组成变化的复杂性,采用人工智能技术、传统多元逐步回归技术,以分析利用高含沙洪水治沙淤地后土壤养分含量与颗粒组成之间的关系,建立了二者间的关系模型,通过对比分析,两种模型均能利用土壤颗粒组成来预测土壤养分含量,但在精度上,人工神经网络模型要远远好于多元逐步回归模型。
In order to meet the need of in-depth study of soil and water engineering and the optimization of complex system modeling, aiming at the complexity of soil nutrient and particle composition change after using sandy sediment with high sediment concentration, artificial intelligence and traditional multiple stepwise regression are used to analyze and utilize The relationship between soil nutrient content and grain composition after sandy sediment was controlled by high silt flood was established and the relationship model between the two was established. Through comparative analysis, both models can use soil grain composition to predict soil nutrient content, Accuracy, artificial neural network model is much better than multiple stepwise regression model.