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| 用小波神经网络耦合模型预测流域年均产沙量 | |
| 引用本文： | 丁文荣,周跃,周晓路.用小波神经网络耦合模型预测流域年均产沙量[J].人民长江,2010,41(1):74-78. |
| 作者姓名： | 丁文荣 周跃 周晓路 |
| 作者单位： | 1. 云南师范大学,旅游与地理科学学院,云南,昆明,650092 2. 云南财经大学,气候流域管理中心,云南,昆明,650211 3. 国立新加坡大学,地理系,新加坡,119260 |
| 基金项目： | 国家重点基础研究发展计划"973"项目，云南省自然科学基金项目 |
| 摘 要： | 引入小波神经网络耦合模型对流域年均产沙量进行了定量研究。由于流域的地质、地貌、土壤在一定时间尺度内具有相对稳定的特性,选出年降雨量、年均气温、年径流量、大雨降雨量、暴雨降雨量、蒸发量、日照时数和汛期降雨量等8个要素作为模型的气候水文输入因子,而以耕地面积、林地面积、水库库容、修建公路、水土保持面积、裸地面积、年采矿量及年末总人口等8个要素作为模型的人类活动输入因子,对流域年均产沙量进行了定量建模预测。结果表明:小波神经网络耦合模型不仅拟合精度高,而且预测效果好,为流域产沙的定量研究提供了新的途径。 |
| 关 键 词： | 年均产沙量 小波神经网络耦合模型 盘龙河流域 预测 |
Prediction of average annual sediment yield of river basin based on wavelet neural network coupling model |
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| DING Wenrong,ZHOU Yue,ZHOU Xiaolu.Prediction of average annual sediment yield of river basin based on wavelet neural network coupling model[J].Yangtze River,2010,41(1):74-78. | |
| Authors: | DING Wenrong ZHOU Yue ZHOU Xiaolu |
| Affiliation: | DING Wenrong1,ZHOU Yue2,ZHOU Xiaolu3(1.College of Tourism , Geography Sciences,Yunnan Normal University,Kunming 650092,China,2.Yunnan University of Finance , Economics,Kunming 650211,3.Department of Geography,National University of Singapore,Singapore 119260,Singapore) |
| Abstract: | The application of wavelet neural network coupling model in quantitative study on yearly average sediment yield of a river basin is described.We select annual rainfall,air temperature and runoff,as well as heavy rain,rainstorm,amount of evaporation,sunshine hours and rainfall in flood season as main climate-hydrological factors of the model,and choose cultivated area,woodland area,reservoir storage capacity,road construction,water and soil conservation area,bare land area,annual mining amount and total popu... |
| Keywords: | average annual sediment yield wavelet neural network coupling model Panlong River Basin predicition |
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