In order to improve the risk evaluation and management in fresh grape supply chain and enhance the sustainable level of the supply chain, this study applied neural network to evaluate the risk of fresh grape supply chain from the perspective of sustainable development. Firstly, the possible risk factors in the supply chain were identified and the risk evaluation index system were proposed; then risk evaluation models based on single BP and optimized BP (GABP and PSO-BP) neural network were established; and then the models were trained, tested and evaluated using data set from supply chain survey. The survey and analysis results showed that the risk of fresh grape supply chain was at a low level but the risk in each link was discrepant, the biggest risk was the risks among the links in the chain (R0), and the high risk dimensions were the economic risk, social risk and cooperation risk; most risky events were located in the second quadrant (small probability & high damage risk events). The results of models training and testing indicated that the optimized model was superior to single BP neural network for risk assessment in grape sustainable supply chain, and the PSO-BP model was more accurate and suitable with less evaluation errors and a bigger R2. The results also extracted the risk factors that contributed most to the overall risk of grape sustainable supply chain. This paper enriches the method of supply chain risk assessment theoretically, and provides practical suggestions for risk prevention, stable operation and sustainability improvement of fresh grape supply chain.

为了提高鲜食葡萄供应链的风险评估和管理水平，提高供应链的可持续水平，本研究运用神经网络从可持续发展的角度评估鲜食葡萄供应链的风险。首先，确定了供应链中可能存在的风险因素，并提出了风险评估指标体系。然后建立了基于单一BP和优化BP（GABP和PSO-BP）神经网络的风险评估模型。然后使用供应链调查中的数据集对模型进行训练，测试和评估。调查分析结果表明，新鲜葡萄供应链的风险水平较低，但各个环节的风险差异较大，最大的风险是该环节中的各个环节之间的风险（R0），高风险维度是经济风险，社会风险和合作风险；最危险的事件位于第二象限（小概率和高损害风险事件）。模型训练和测试的结果表明，优化后的模型在葡萄可持续供应链中的风险评估优于单一BP神经网络，而PSO-BP模型更准确，更合适，评估误差更小，R2更大。结果还提取了对葡萄可持续供应链总体风险影响最大的风险因素。本文从理论上丰富了供应链风险评估的方法，为鲜葡萄供应链的风险防范，稳定运行和可持续性改善提供了实用建议。最危险的事件位于第二象限（小概率和高损害风险事件）。模型训练和测试的结果表明，优化后的模型在葡萄可持续供应链中的风险评估优于单一BP神经网络，而PSO-BP模型更准确，更合适，评估误差更小，R2更大。结果还提取了对葡萄可持续供应链总体风险影响最大的风险因素。本文从理论上丰富了供应链风险评估的方法，为鲜葡萄供应链的风险防范，稳定运行和可持续性改善提供了实用建议。最危险的事件位于第二象限（小概率和高损害风险事件）。模型训练和测试的结果表明，优化后的模型在葡萄可持续供应链中的风险评估优于单一BP神经网络，而PSO-BP模型更准确，更合适，评估误差更小，R2更大。结果还提取了对葡萄可持续供应链总体风险影响最大的风险因素。本文从理论上丰富了供应链风险评估的方法，为鲜葡萄供应链的风险防范，稳定运行和可持续性改善提供了实用建议。模型训练和测试的结果表明，优化后的模型在葡萄可持续供应链中的风险评估优于单一BP神经网络，而PSO-BP模型更准确，更合适，评估误差更小，R2更大。结果还提取了对葡萄可持续供应链总体风险影响最大的风险因素。本文从理论上丰富了供应链风险评估的方法，为鲜葡萄供应链的风险防范，稳定运行和可持续性改善提供了实用建议。模型训练和测试的结果表明，优化后的模型在葡萄可持续供应链中的风险评估优于单一BP神经网络，而PSO-BP模型更准确，更合适，评估误差更小，R2更大。结果还提取了对葡萄可持续供应链总体风险影响最大的风险因素。本文从理论上丰富了供应链风险评估的方法，为鲜葡萄供应链的风险防范，稳定运行和可持续性改善提供了实用建议。结果还提取了对葡萄可持续供应链总体风险影响最大的风险因素。本文从理论上丰富了供应链风险评估的方法，为鲜葡萄供应链的风险防范，稳定运行和可持续性改善提供了实用建议。结果还提取了对葡萄可持续供应链总体风险影响最大的风险因素。本文从理论上丰富了供应链风险评估的方法，为鲜葡萄供应链的风险防范，稳定运行和可持续性改善提供了实用建议。