一个基于IQRBOW和MCDM的强大的混合权重体系:VIKOR框架中的稳定性和优势标准
Ali Erbey1, Üzeyir Fidan1, Cemil Gündüz1
1Department of Computer Programming, Distance Education Vocational School, Usak University, Usak 64200, Türkiye.
Entropy (Basel, Switzerland)
|August 28, 2025
概括
这项研究介绍了IQRBOW-E,一种混合权重方法,用于多标准决策 (MCDM),平衡稳定性和信息敏感性. 它提高了决策稳定性和绩效,特别是在数据不规则和异常值方面.
科学领域:
- 运营研究
- 决策科学
- 数据科学
背景情况:
- 多标准决策 (MCDM) 需要可靠的权重方法,特别是在不确定性和数据不规则的情况下.
- 现有的方法可能缺乏稳定性或无法捕获关键数据信息.
- 决策支持系统需要可适应的权重来确保准确的结果.
研究的目的:
- 引入一种新的混合目标权重方法,IQRBOW-E (基于四分位数范围的目标权重与值).
- 通过可调节的参数β实现统计稳定性和信息灵敏性的灵活控制.
- 在不确定的环境中提高决策支持系统的适应性和可靠性.
主要方法:
- 开发了IQRBOW-E方法,通过参数β将IQRBOW强度与度信息灵敏度结合起来.
- 将IQRBOW-E集成到VIKOR评估框架中
- 在10个模拟场景中进行了实验,不同的标准,替代品和异常值比率.
主要成果:
- IQRBOW-E表现出卓越的决策稳定性和性能,特别是在异常污染增加的情况下.
- 系统地适应不同数据条件的最佳β值,显示模型的灵敏度.
- 混合方法在处理数据不规则方面比传统方法更强大.
结论:
- 参数化混合权重模型推进了MCDM方法.
- IQRBOW-E为不确定性下的决策提供了强大的和可通用的权衡基础设施.
- 这种方法为面对复杂数据的决策支持系统提供了更好的适应性.
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