高级检索

      基于改进模糊集与K-means聚类的水库汛期分期方法

      Reservoir Flood-Season Staging Method Based on Improved Fuzzy Sets and K-Means Clustering

      • 摘要: 为解决传统汛期分期方法主观性较强的问题,本文提出一种融合变异系数法与K-means聚类的综合分期方法。首先选取最大1日、3日、5日洪量作为关键指标,采用变异系数法进行客观权重赋值以改进模糊集分析,初步界定汛期范围;进而应用K-means聚类实现汛期分期的准确划分。将该方法应用于某水库汛期分期,可将汛期明确划分为前汛期(7/07–8/06)、主汛期(8/07–9/04)与后汛期(9/05–10/01)。通过与其他经典方法对比分析,验证了其划分结果的合理性与可靠性。该方法可实现汛期分期的更精准、客观的识别,为指导水库汛期防洪调度运行提供方法支撑。

         

        Abstract: To address the issue of strong subjectivity in traditional flood season staging methods, this paper proposes a comprehensive staging method that integrates the coefficient of variation method and K-means clustering. Firstly, the maximum flood volumes of 1 day, 3 days and 5 days are selected as key indicators. The coefficient of variation method is adopted for objective weight assignment to improve the fuzzy set analysis and preliminarily define the flood season range. Furthermore, K-means clustering is applied to achieve the accurate division of flood season stages. When this method is applied to the flood season staging of a certain reservoir, the flood season can be clearly divided into the pre-flood season (7/07-8/06), the main flood season (8/07-9/04), and the post-flood season (9/05-10/01). Through comparative analysis with other classic methods, the rationality and reliability of its division results were verified. This method can achieve more accurate and objective identification of flood season phases, providing methodological support for guiding the flood control and dispatching operation of reservoirs during the flood season.

         

      /

      返回文章
      返回