Scholarlink

This article explores the evaluation of sustainable performance within the mining industry using the Fuzzy Analytic Network Process (FANP) method. It focuses on five key dimensions of sustainable development: economic, social, environmental, operational, and stakeholder perspectives. By applying the FANP method, a detailed prioritized ranking is created, covering both the main dimensions and specific subfields within each. This comprehensive approach offers an in-depth, balanced assessment of sustainability performance, providing valuable insights to inform decision-making. The method’s applicability extends beyond the mining sector, offering a flexible model that can be adapted to various industries and research fields. This versatility is achieved by integrating machine learning, particularly a multilayer perceptron, which accurately assesses a company’s overall performance across multiple dimensions. The research fills a gap in integrated studies within the Moroccan mining industry, offering actionable insights to improve management practices and promote sustainable development. This contribution benefits the industry and the broader research community.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrating Artificial Neural Networks and Fuzzy Analytic Network Process for Comprehensive Sustainable Performance Assessment in Morocco’s Mining Sector

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Chayma Farchi,
  • Fadwa Farchi,
  • Badr Touzi,
  • Ahmed Mousrij

摘要

This article explores the evaluation of sustainable performance within the mining industry using the Fuzzy Analytic Network Process (FANP) method. It focuses on five key dimensions of sustainable development: economic, social, environmental, operational, and stakeholder perspectives. By applying the FANP method, a detailed prioritized ranking is created, covering both the main dimensions and specific subfields within each. This comprehensive approach offers an in-depth, balanced assessment of sustainability performance, providing valuable insights to inform decision-making. The method’s applicability extends beyond the mining sector, offering a flexible model that can be adapted to various industries and research fields. This versatility is achieved by integrating machine learning, particularly a multilayer perceptron, which accurately assesses a company’s overall performance across multiple dimensions. The research fills a gap in integrated studies within the Moroccan mining industry, offering actionable insights to improve management practices and promote sustainable development. This contribution benefits the industry and the broader research community.