| 非参数统计理论与人工智能技术在水土空间变异中的应用研究 |
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| 引用本文： | 刘全明,陈亚新,魏占民,史海滨. 非参数统计理论与人工智能技术在水土空间变异中的应用研究[J]. 灌溉排水学报, 2006, 25(1): 49-53 |
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| 作者姓名： | 刘全明 陈亚新 魏占民 史海滨 |
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| 作者单位： | 内蒙古农业大学,水资源与水土工程研究所,内蒙古,呼和浩特,010018;内蒙古农业大学,水资源与水土工程研究所,内蒙古,呼和浩特,010018;内蒙古农业大学,水资源与水土工程研究所,内蒙古,呼和浩特,010018;内蒙古农业大学,水资源与水土工程研究所,内蒙古,呼和浩特,010018 |
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| 基金项目： | 国家自然科学基金资助项目(50179013) |
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| 摘 要： | 采用非参数统计理论中的指示克立格与BP神经网络技术,以河套灌区内一典型实验区的土壤水盐预测为例,在一条采样基线上比较了指示克立格与BP神经网络技术的优劣,发现指示克立格与BP神经网络技术在一维空间的土壤水盐预测中能改进普通克立格平滑效应,具有条件模拟的仿真功能,可用于空间水盐插值与预测。
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| 关 键 词： | 非参数统计理论 人工智能技术 水土空间变异 |
| 文章编号： | 1000-646X(2006)01-0049-05 |
| 收稿时间： | 2005-10-31 |
| 修稿时间： | 2005-10-31 |
Applied Research Based on the Non-parametric Approach and Artificial Intelligence Computing Technique in Water Soil Spatial Variation |
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| LIU Quan-ming,CHEN Ya-xin,WEI Zhan-min,SHI Hai-bin. Applied Research Based on the Non-parametric Approach and Artificial Intelligence Computing Technique in Water Soil Spatial Variation[J]. Journal of Irrigation and Drainage, 2006, 25(1): 49-53 |
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| Authors: | LIU Quan-ming CHEN Ya-xin WEI Zhan-min SHI Hai-bin |
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| Affiliation: | Institute of Wate Resource and Water-soil Engineering, Inner Mongolia Agricultural University, Huhhot 010018, China |
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| Abstract: | Using indicator Kriging in non-parametric approach and BP neural net technique,this paper made the zonal soil water-salt forecasting of a representative experimental section in Hetao irrigation zone as example,contrasted and analyzed two methods in a sampling baseline.It showed that indicator Kriging and BP neural net technique can eliminate glabrous effect of OK method and retrofit conventional GS in threadlike space,they all can be used in spatial water-salt forecasting. |
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| Keywords: | Non-parametric approach artificial intelligence technique water soil spatial variation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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