基于信息扩散近似推理的产流预报模型  

Runoff Yield Forecast Model Based on Information-diffusion Approximate Reasoning

作　　者：魏明华[1] 郑志宏[2] 

机构地区：[1]华北水利水电大学水利学院,郑州450045 [2]华北水利水电大学环境与市政工程学院,郑州450045

出　　处：《沈阳农业大学学报》2013年第2期208-212,共5页Journal of Shenyang Agricultural University

基　　金：水利部公益性行业专项经费项目(200801015);华北水利水电学院高层次人才科研启动项目(40227);河南省高校青年骨干教师资助计划项目(2010GGJS-126);河南省教育厅自然科学研究计划项目(2011A570009)

摘　　要：为了提高预报精度,充分利用和挖掘数据中包含的隐信息,以陡河水库为计算实例,应用信息扩散近似推理技术建立预报模型,并通过与遗传程序和传统线性回归方法对计算结果进行对比分析。结果表明:该模型预报精度较高,且具有前期数据处理简单的优势,可用于流域降雨、径流相关图的修正,有很好的应用价值。In order to improve the forecast precision, sufficiently utilize and mine latent information of data, with Douhe Reservoir as an example, we applied information-diffusion approximate reasoning technology to set up forecast model, and compare with calculation results of genetic programming and traditional linear regression methods. The results showed that the model had better forecast precision, and foregoing data disposal was simple. The model can apply on revising correlation chart of drainage basin precipitation and run-off, and it has extensive application value.

关 键 词：利用和挖掘 隐信息 信息扩散近似推理 预报精度 

分 类 号：P338.1[天文地球—水文科学]