Research on New Energy Vehicle Sales Problem Based on Improved Gray Correlation and BP Neural Network

Junhao Wu, Wanyang Zuo
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Abstract

New energy vehicles are an important development direction for the global automotive industry in the 21st century, and their sales are closely related to China's sustainable development strategy. However, compared with traditional cars, consumers still have some doubts about new energy vehicles, and their marketing needs scientific decisions. Thus, it is essential to establish a customer mining model for new energy vehicles. This paper takes three newly launched brands of new energy vehicles as research objects and establishes a customer mining model for new energy vehicles based on improved gray correlation and BP neural network with the customer satisfaction scores of each performance of the three new energy vehicles as indicators. The experimental results show that the coefficients of determination for the three models are 0.99488, 0.99317 and 0.99525,respectively, which reach the expected accuracy. This model can provide some reference and practical significance for the sales strategy of new energy vehicles.
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基于改进灰色关联和BP神经网络的新能源汽车销售问题研究
新能源汽车是21世纪全球汽车产业的重要发展方向,其销售与中国的可持续发展战略密切相关。然而,与传统汽车相比,消费者对新能源汽车仍有一些疑虑,其营销需要科学决策。因此,建立新能源汽车客户挖掘模型至关重要。本文以新推出的三个新能源汽车品牌为研究对象,以三款新能源汽车各性能的客户满意度得分为指标,基于改进的灰色关联和BP神经网络,建立了新能源汽车客户挖掘模型。实验结果表明,三种模型的决定系数分别为0.99488、0.99317和0.99525,均达到了预期的精度。该模型可以为新能源汽车的销售策略提供一定的参考和现实意义。
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