基于模糊综合评判和BP神经网络的通机产品售后质量损失评估及预警方法

In view of the after-sale quality loss is affected by multiple factors and it's difficult to evaluate and early warning the after-sale quality loss for universal gasoline engines. An after-sale quality loss evaluation and early warning method for universal gasoline engines was put forward, which is based on fuzzy comprehensive evaluation and BP neural networks. Meanwhile, the evaluation indicators for after-sale quality loss was founded. Subsequently, some of the key technologies were studied, including fuzzy comprehensive evaluation, three layers BP neural networks forecasting for the after-sale quality loss. Finally, the method was successfully applied for after-sale quality loss evaluation and early warning in a universal gasoline engines manufacturer in Chongqing, and good results were obtained.