Rough Fuzzy Inference Model and its Application in Multi-factor Medium and Long-term Hydrological Forecast
Rough Fuzzy Inference Model and its Application in Multi-factor Medium and Long-term Hydrological Forecast
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DOI：
10.1007/s11269-008-9285-1
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发表时间：
2009-02
影响因子：
4.3
通讯作者：
Yongjie Zhu;Huicheng Zhou
中科院分区：
文献类型：
--
作者：
Yongjie Zhu;Huicheng Zhou
本文的目标是将粗糙集理论和模糊推理技术结合到多要素中长期水文预报中。采用粗糙集理论对数据进行简化，处理冗余不一致的初始信息表。在此基础上，利用属性重要性概念对影响因素进行约简。根据属性显著性和组合显著性最大原则以及规则频次原则，得到模型中作为模糊推理预测模式规则集的最小解。应用该模型对大伙房水库年径流量进行了预测。结果表明，粗糙集提高了预报精度，模型能有效反映径流与因子之间的非线性关系，为解决复杂因子选择和最小推理规则集生成等预报问题提供了一种有效的适应性方法。
This paper targets efforts to integrate rough set theory and the fuzzy inference technique into the multi-element medium and long-term hydrological forecast. Rough set theory is used to predigest the data and deal with the redundant inconsistent initial information table. Accordingly, the factors are reduced with the attribute significance concept. The minimal solution which is as fuzzy inference forecast pattern rule set in the model is achieved according to the principle of maximal attribute significance and combination significance as well as rules frequency. The model is applied to forecast annual runoff of Dahuofang Reservoir in China. The results indicate that the forecast precision is improved with rough set and the model can effectively reflect the non-linear relations between the runoff and factors and provide an effective and adaptable method to solve forecast problems related to complex factors selection and minimal inference rule set generation.