| 我国新能源汽车月度销售量预测模型研究 |
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| 引用本文： | 周彦福,王红蕾.我国新能源汽车月度销售量预测模型研究[J].教育技术导刊,2019,18(8):149-153. |
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| 作者姓名： | 周彦福 王红蕾 |
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| 作者单位： | 贵州大学 管理学院，贵州 贵阳 550003 |
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| 基金项目： | 南方电网资助项目（066601（2016）030101XT198） |
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| 摘 要： | 在新能源汽车可缓解未来一系列环境、资源问题的重要背景下，对新能源汽车销售量准确预测有助于加速新能源汽车市场推广，降低相关生产研发企业运营成本。提取8个关键影响因素，应用灰色关联分析（GRA）验证各因素影响能力，然后构建基于果蝇算法优化灰色神经网络（FOA-GNN）预测模型的新能源汽车月度销售量预测模型。通过预测结果对比检验，验证该预测模型在预测新能源汽车销售量上有较高的预测精度。应用该模型对我国新能源汽车2019年月度销售量进行预测，结果表明，我国新能源汽车发展在2019年度依然可保持良好的增长态势。
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| 关 键 词： | 新能源汽车 销售量 果蝇算法 灰色神经网络 销售量预测 |
| 收稿时间： | 2019-05-06 |
Research on Monthly Sales Forecasting Model of New Energy Vehicles in China |
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| ZHOU Yan-fu,WANG Hong-lei.Research on Monthly Sales Forecasting Model of New Energy Vehicles in China[J].Introduction of Educational Technology,2019,18(8):149-153. |
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| Authors: | ZHOU Yan-fu WANG Hong-lei |
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| Institution: | School of Management， Guizhou University， Guiyang 550003， China |
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| Abstract: | Under the background of important measures to alleviate a series of environmental and resource problems in the future， the accurate forecast of new energy vehicle sales can accelerate the promotion of new energy vehicles and reduce the operating costs of production and research-related enterprises. This paper extracts eight key influencing factors， and uses gray relevance analysis （GRA） to verify the influencing ability of each factor， and then constructs a new energy vehicle monthly sales forecasting model based on FOA-GNN prediction model. Through the comparison test of prediction results， it is verified that the prediction model has higher prediction accuracy in predicting the sales volume of new energy vehicles. Finally， the model is used to forecast the monthly sales volume of new energy vehicles in China in 2019. The results show that the development of new energy vehicles in China still maintains a good growth trend in 2019. |
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| Keywords: | new energy vehicle sales volume fruit fly algorithm grey neural network sales volume prediction |
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