| 摘要: |
| 模糊划分理论具有严谨的理论和物理基础。考虑了水文现象发生的必然性与随机性以及在划分、识别中的模糊性，是一种无模式可参考的分类理论。文章应用模糊划分理论模型进行了年径流序列的模糊划分．根据划分结果。利用LVQ进行了年径流过程的枯、平、丰识别。建立了年径流序列的分类识别模型．并用黄河上游61年径流水文资料进行了验证。结果表明．建立的年径流系列分类识别理论模型是可行的。 |
| 关键词: 水文年份 模糊最优划分 LVQ神经网络 年径流分类 年径流识别 |
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| 基金项目:国家自然科学基金项目（50179031）；高等学校全国优秀博士学位论文作者专项基金（200052）；西北农林科技大学2004年优秀人才专项基金（04ZR014） |
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| The establishment and application of theory model for the classification and identification of runoff series |
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| Abstract: |
| Fuzzy classified theory has strict theory and physics base.It integrates inevitability and randomicity and fuzzy classification and identification of hydrological phenomenon.The author applied fuzzy classified theory model to fuzzily classify annual runoff series.According to classified results,using LVQ to identify dry year,normal year or wet year of annual runoff series,identification and classification model of annual runoff series was established,and 61 years' water-data in upper reach of Yellow River were confirmed.The results show that the model can be used to classify and identity runoff. |
| Key words: water year fuzzy optimum classification LVQ Networks runoff classification runoff identification |
