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在孟加拉国Jamalganj煤矿区,采用优化模糊基于知识的绘图,对煤床甲开发进行了选择性风险因素分析

Jianhua Zhang¹, Md Helal Miah², Muin Abdullah Al³

¹School of Management, Zhengzhou University, Zhengzhou, Henan, China.

Scientific reports

|December 16, 2025

概括

本研究引入了一种先进的模糊认知图 (FCM) 模型与解释性结构建模 (ISM) 模型,以评估煤床甲发展风险. 贾马尔甘吉案例研究揭示了中等社会生态风险,突出了污染物度,职业危险和经济损失.

科学领域:

环境科学环境科学
风险评估风险评估
社会经济学社会经济学

背景情况:

传统的煤床甲开发风险评估仅限于经济因素.
在全面评估与煤床甲开采相关的社会和环境风险方面存在重大差距.

研究的目的:

引入一个先进的框架,用于煤床甲开发风险评估,使用与解释性结构建模 (ISM) 和三角模糊数字集成的模糊认知地图 (FCM).
分析孟加拉国贾马尔甘吉地区煤床甲开发的社会生态风险.

主要方法:

利用解释性结构建模 (ISM) 知识映射算法来分析指标节点之间的关系,构建一个全面的关系矩阵.
采用模糊认知图 (FCM) 模型与三角模糊数字和非线性Hebbian学习算法集成用于风险评估.
在孟加拉国Jamalganj进行了一项案例研究,以示范综合建模框架.

主要成果:

综合的FCM-ISM模型为贾马尔甘吉的煤床甲开发确定了0.665的社会生态风险值,表明中等风险水平.
确定了不同的风险阶段:早期阶段以高污染物度为特征,中期阶段以机械化和职业危险为特征,晚期阶段以经济损失为主.
非线性Hebbian学习算法改进了FCM模型,提高了环境和社会经济风险评估的精度.

结论:

开发的框架为评估煤床甲开发中的环境和社会经济风险提供了可靠的方法.
调查结果强调需要分阶段管理策略,以减轻不同发展阶段的特定风险.
该研究有助于政策制定者实现煤床甲项目的可持续资源管理.

关键词:

煤床甲的使用情况.模糊的认知地图模糊的认知地图解释性结构建模的解释性结构建模.知识映射知识映射风险因素分析风险因素分析

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