Construction of Mining Industry Esg Information Disclosure Evaluation Index System Based on BP Neural Network

ESG (Environmental, Social, and Governance) disclosure has garnered significant global attention, particularly within the mining industry. Its importance extends beyond its impact on corporate sustainability, delving into the core issues of global resource management and social responsibility. Against this backdrop, scholars are actively researching how to leverage artificial intelligence technologies, notably by developing a framework for evaluating ESG disclosures in the mining sector based on Backpropagation Neural Networks (BP Neural Networks). Against this backdrop, this paper employs a BP neural network to construct an evaluation indicator system for ESG information disclosure in the mining industry. Firstly, by incorporating international mainstream indicator systems, we select indicators that align with the characteristics of China and the mining industry. This process results in the construction of our ESG rating system. Subsequently, we systematically construct a BP neural network model for evaluating ESG information disclosure in the mining industry. The results indicate that the BP neural network method possesses high-speed self-learning and adaptability, enabling objective evaluation and analysis.