一种适当的人工智能技术用于塑料材料回收利用双极双犹的模糊集
Lakshmanaraj Ramya1, Chakkarapani Sumathi Thilagasree2, Thippan Jayakumar2
1Department of Mathematics, Bharathiar University, Coimbatore, 641046, India.
Scientific reports
|October 22, 2024
概括
这项研究强调了塑料回收利用对抗环境问题的关键需求. 机械回收被认为是可持续塑料废物管理的最有效方法,优先考虑经济因素.
科学领域:
- 环境科学 环境科学
- 材料科学 材料科学 材料科学
- 决策科学 决策科学 决策科学
背景情况:
- 塑料垃圾对环境和健康构成重大风险,导致污染和气候变化.
- 有效的塑料回收对于生态保护和可持续发展至关重要.
- 目前的塑料废物管理策略需要强大的决策框架.
研究的目的:
- 通过多标准决策 (MCDM) 方法评估和排名塑料回收方法.
- 确定最有效和可持续的塑料回收策略.
- 解决塑料回收的环境,经济,社会,技术和安全方面的问题.
主要方法:
- 利用双极双犹模糊集 (BDHFs) 框架与消除和选择表达现实 (ELECTRE) 方法相结合.
- 使用距离度量来计算各种决策标准的权重.
- 进行了敏感和比较分析,以验证拟议的MCDM技术的稳定性.
主要成果:
- 经济因素获得了最高的权重 (0.2945),这强调了其在选择塑料回收方法方面的重要性.
- 机械回收被确定为有效的塑料废物管理的最佳方法.
- BDHF-ELECTRE方法被证明是环境管理中复杂决策的通用和有效工具.
结论:
- 拟议的MCDM技术为减轻塑料废物的不利影响提供了可行的解决方案.
- 优先考虑机械回收利用,并支持经济可行性,对于可持续的塑料废物管理至关重要.
- 这项研究有助于为环境保护和资源保护做出明智的决策.
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