| 王晓平，闫 飞.基于神经网络分析的北京城镇农产品冷链物流需求预测[J].广东农业科学,2018,45(6):120-128 |
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基于神经网络分析的北京城镇农产品冷链物流需求预测 |
| Forecast of cold chain logistics demand for agricultural products in Beijing based on neural network |
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| DOI：10.16768/j.issn.1004-874X.2018.06.020 |
| 中文关键词: 农产品冷链物流 需求量预测 灰色模型 神经网络模型 主成分分析 |
| 英文关键词: cold chain logistics of agricultural products demand forecast grey model neural network model principal component analys |
| 基金项目:北京市社会科学基金研究基地项目（15JDJGB054） |
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| 摘要点击次数: 1773 |
| 全文下载次数: 605 |
| 中文摘要: |
| 为了预测由居民消费所引起的农产品冷链物流需求，从农产品供给、社会经济、冷链发展、人
文发展、物流需求规模5 个角度构建影响指标体系，利用BP 神经网络和RBF 神经网络在需求预测中的优
势，建立基于主成分分析和神经网络组合模型的需求预测模型，并以北京为例，对两种模型的预测结果进
行对比分析。结果表明：通过灰色关联度分析各个影响指标，发现北京市城镇人口数量、第一产业增加值、
第三产业占GDP 比重等因素对农产品冷链物流需求量的影响最大；预测到2020 年北京城镇居民农产品冷
链物流需求将达到642.27 万t；所建立的模型对冷链物流需求及其影响因素的非线性关系方面有较高的精
度和应用价值，能够为农产品冷链物流规划者及政府提供定量决策依据。 |
| 英文摘要: |
| In order to forecast the demand of agricultural products cold chain logistics caused by the
consumption，this paper constructs an impact index system from six aspects of agricultural products supply，social
economy，cold chain development，humanities，logistics demand scale，and uses the advantages of BP neural
network and RBF neural network in demand forecasting，establishes a demand forecasting model based on principal
component analysis and neural network combination model. This paper takes Bei Jing as an example，and compares
and analyzes the forecasting results of the two models. The results show that：through the grey relational analysis of
various impact indicators，it is found that the number of urban population，the added value of the primary industry，
the proportion of the tertiary industry to GDP and other factors have the greatest impact on the demand of agricultural
products cold chain logistics；Forecast by 2020 Beijing urban residents agricultural products cold chain logistics
demand will reach 6.642 million tons；The model established in this paper has high precision and application value
in the non-linear relationship between cold chain logistics demand and its influencing factors，and can provide
quantitative decision-making basis for agricultural cold chain logistics planners and governments. |
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