| 基于神经网络方法的土壤流失量预测研究 |
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| 引用本文： | 钱爱国,高荣,彭琦.基于神经网络方法的土壤流失量预测研究[J].中国水土保持,2013(5). |
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| 作者姓名： | 钱爱国 高荣 彭琦 |
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| 作者单位： | 1. 中国水电顾问集团华东勘测设计研究院,浙江杭州,310014
2. 深圳地铁集团深圳市政设计研究院有限公司,广东深圳,518029 |
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| 摘 要： | 生产建设项目土壤流失量的预测直接关系到建设项目的水土保持分析、评价和防治措施体系的布局,目前常用的预测方法因其局限性、不合理性以及精度差等问题往往难以实现准确预测。将人工神经网络的BP算法引入到土壤流失量预测中,将降雨侵蚀力、土壤可蚀性、坡长、坡度、水土保持措施作为影响土壤流失量的主要因子,并以17个生产建设项目水土保持监测实例作为学习样本和检测样本,建立了基于神经网络方法的土壤流失量预测模型。预测结果表明,该模型拟合和预测精度高,具有很强的应用价值,能够满足工程应用需要。
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| 关 键 词： | 生产建设项目 土壤流失量预测 神经网络方法 |
Soil Loss Prediction Based on Neural Network Method |
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| Abstract: | The prediction of soil loss of production and construction projects is directly related to the analysis and evaluation of soil and water conservation and the layout of prevention and control measures of construction projects.The current prediction methods commonly used usually are difficult to achieve accurate prediction because of their limitations,irrationality and poor accuracy.The paper introduced the BP algorithm of artificial neural network into the prediction of soil loss,and took erosive force of rainfall,soil erodibility,slope length,slope and soil and water conservation measures as the main factors that effects the soil loss and established a soil loss prediction model based on neural network method by taking 17 examples of soil and water conservation monitoring of production and construction projects as a study sample and a test sample.The outcomes show that the fitting and prediction accuracy of the model are high and has great application value.It can meet the requirements of engineering application. |
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| Keywords: | production and construction projects soil loss prediction neural network method |
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