Abstract:

Agricultural-related enterprises shoulder the vital mission of ensuring food security and stabilizing the supply of agricultural products. The implementation of the rural revitalization strategy and the vigorous development of new agricultural productivity have brought new opportunities for the transformation and upgrading of agricultural-related enterprises. However, the financial situation of agricultural-related enterprises in China is relatively fragile, and the construction of a scientific financial risk early warning model for agricultural-related enterprises is of great significance. Based on the financial data of 131 agricultural-related listed companies from 2018 to 2023, this article constructs a financial risk early warning model for agricultural enterprises based on BP neural network, and takes Beidahuang Agriculture Co., Ltd. as an example to verify the prediction results of the model. The research results show that the BP neural network financial risk early warning model for agricultural-related enterprises constructed in this study has relatively high prediction accuracy and can accurately identify the financial risk situation of agricultural-related enterprises. In the future, agricultural-related enterprises should promote the in-depth integration of intelligent financial early warning and digital management, continuously optimize the indicator system, and constantly enhance their technological innovation capabilities, risk prevention and control levels, and capital management capabilities, to drive the improvement of quality and efficiency and the transformation and upgrading of the enterprises.

Key words: rural revitalization, BP neural network, financial risk early warning, agriculture-related enterprises, agricultural new quality productive forces

摘要：

涉农企业承担着保障粮食安全、稳定农产品供给等重大使命。随着乡村振兴战略的深入实施和农业新质生产力的大力发展，涉农企业迎来了转型升级的重大机遇。目前我国涉农企业财务状况普遍较为脆弱，因而构建科学的财务风险预警模型具有重要的现实意义。文章基于131家涉农上市公司2018—2023年财务数据，构建了基于BP神经网络的涉农企业财务风险预警模型，并以北大荒股份有限公司为例对模型预测结果进行验证。研究结果表明，BP神经网络财务风险预警模型预测准确率较高，可以准确识别涉农企业财务风险状况。今后，涉农企业应推动智能化财务预警与数字化管理深度融合，持续优化指标体系，不断提升科技创新能力、风险防控水平与资本管理水平，驱动企业提质增效与转型升级。

关键词: 乡村振兴, BP神经网络, 财务风险预警, 涉农企业, 农业新质生产力