二手汽车网
10.16638/jki.1671-7988.2020.04.020
因素研究*
毛攀,蔡云,万雄,王文迪
(西华大学汽车与交通学院,四川成都610039)
摘要:为了高效客观准确评估二手车价格,以影响二手车价格评估的因素为研究对象,采用文献法分析筛选出二
手车评估价格的11个影响因素并建立了BP神经网络二手车价格评估模型。通过BP神经网络二手车价格评估模型
的计算结果显示模型预测价格与实际价格相关系数达到0.96,根据所建模型的连接权值得出了二手车价格评估影响
权重值较大的7个因素。最后将影响二手车价格评估的7个主要因素作为输入重构了价格评估模型并重新计算二手
车价格得出BP-11模型与BP-7模型计算结果基本一致且Pearson 相关性度到0.83。因此本文的研究结果表明:二
手车价格评估主要受综合油耗、车辆售后满意度、车龄、车辆可靠性、舒适性、外观、当前里程数的影响,BP神
经网络二手车价格评估模型可由这7个因素描述。
关键词:二手车评估价格;影响因素;BP神经网络;权重
中图分类号:F045.3 文献标识码:B 文章编号:1671-7988(2020)04-59-06
Research on Influencing Factors of used car price evaluation based
on BP neural network*
Mao Pan, Cai Yun, Wan Xiong, Wang Wendi
(School of Automotive &Transportation Engineering, Xihua University, Sichuan Chengdu 610039)
Abstract: In order to evaluate the second-hand car price efficiently, objectively and accurately, this paper takes the factors that affect the second-hand car evaluation price as the research object, selects 11 influencing factors of the second-hand car evaluation price by literature analysis, and establishes the BP neural network second-hand car price evaluation model. Through the calculation results of BP neural network used car price evaluation model, it shows that the correlation coefficient between the predicted evaluation price and the actual price of the model is 0.96. According to the connection weight of the model, seven factors that have great influence on the weight value of used car price evaluation are given. Finally, seven main factors that affect the second-hand car price evaluation are used as input to reconstruct the price evaluation model and recalculate the second-hand car price. The results of bp-11 model and bp-7 model are basically the same, and the Pearson correlation degree is 0.83. Therefore, the research results of this paper show that: the second-hand car price evaluation is mainly affected by comprehensive fuel consumption, vehicle after-sales satisfaction, vehicle age, vehicle reliability, comfort, appearance and current mileage. The BP neural network second-hand car price evaluation model can be described by these seven factors.
Keywords: Used carevaluation price; Influencing factors; BP neural network; Weight
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