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基于BIP模型的绿色流域指标体系优化方法

王梅 李冰 胡虎

人民长江2025,Vol.56Issue(12):88-95,8.
人民长江2025,Vol.56Issue(12):88-95,8.DOI:10.16232/j.cnki.1001-4179.2025.12.009

基于BIP模型的绿色流域指标体系优化方法

Optimization methodology for constructing indicator system of green basins based on Binary Integer Programming model

王梅 1李冰 1胡虎1

作者信息

  • 1. 郑州大学 水利与交通学院,河南 郑州 450001
  • 折叠

摘要

Abstract

With the initial achievements in basin ecological protection,the advancement of green basins has gained increasing attention.Establishing a rational evaluation indicator system is essential for supporting the planning and implementation of green basin initiatives.This study proposes a method for selecting green basin indicators based on a Binary Integer Programming(BIP)model,aiming to optimize the construction of a green basin indicator system.The methodology includes:①constructing a prelimi-nary evaluation indicator system and eliminating indicators with significant data gaps through data analysis to improve data quali-ty;②determining the weight of each indicator using a combined entropy weight and CRITIC method and excluding indicators with extremely low weights to enhance the representativeness of the indicator system;③formulating a BIP model and applying a genet-ic algorithm to solve for the optimal indicator set.A evaluation approach of"single indicator quantification-multi-indicator synthesis-multi-criteria integration"is adopted to validate the optimized indicator system.An empirical study is conducted in the Changjiang River Basin.The results show that the proposed method can effectively identify 25 key indicators closely associated with green basin performance.The research findings provide an effective indicator selection and optimization approach for the sci-entific management of green basins.

关键词

绿色流域/指标体系/熵权-CRITIC法/BIP模型/遗传算法/长江流域

Key words

green basin/indicator system/entropy weight-CRITIC method/Binary Integer Programming model/genetic al-gorithm/Changjiang River Basin

分类

建筑与水利

引用本文复制引用

王梅,李冰,胡虎..基于BIP模型的绿色流域指标体系优化方法[J].人民长江,2025,56(12):88-95,8.

基金项目

国家重点研发计划项目(2023YFC3205600) (2023YFC3205600)

人民长江

OA北大核心

1001-4179

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