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毕业论文网 > 毕业论文 > 物流管理与工程类 > 物流管理 > 正文

基于灰色理论的农产品冷链物流需求与关键因素预测研究毕业论文

 2021-11-06 08:11  

摘 要

Abstract 5

第1章 绪论 6

1.1研究背景及意义 6

1.1.1研究背景 6

1.1.2研究意义 7

1.2国内外研究现状 7

1.2.1依托于电商的农产品冷链物流研究 7

1.2.2物流需求预测方法的研究现状 8

1.3研究内容及技术路线 9

1.3.1研究内容 9

1.3.2研究方法 9

1.3.3技术路线 10

第2章 农产品冷链物流需求概述 11

2.1冷链物流 11

2.1.1冷链物流的概念 11

2.1.2冷链物流的特点 11

2.2物流需求 12

2.2.1物流需求量 12

2.2.2物流需求预测 12

2.3生鲜电商 12

第3章 农产品冷链物流研究理论基础 14

3.1问题描述 14

3.2灰色 GM(1,1)预测模型 14

3.3灰色 GM(1,1)预测模型的检验 15

3.3.1预测模型的有效性检测 15

3.3.2 精度检验 16

3.3.3灰色 GM(1,1)预测模型精度检验各等级参照标准 16

3.4灰色关联度分析模型 17

第4章 冷链物流需求影响因素的灰色关联分析 18

4.1灰色关联模型的建立 18

4.1.1指标选取原则 18

4.1.2指标选取 19

4.2灰色关联度计算 21

4.3结果分析 21

第5章 冷链物流需求趋势预测分析 23

5.1冷链物流需求及各指标的预测 23

5.2冷链物流需求的趋势分析 24

第6章 总结及展望 26

6.1全文总结 26

6.2研究展望 26

致谢 28

参考文献 29

摘要

在中国经济不断市场化发展的当下时代中,人们的生活水平和要求变得更加多样和丰富,有时候千里之外的食材也并非不切实际了。在此情况的要求下,为了保持食材的新鲜运输,冷链物流的发展就尤为重要。影响其发展的相关因素的研究和对江西省的农产品冷链物流的需求的预测,在一定程度上帮助了企业政府在未来的一段时期内提供决策依据,重点发展控制关联度较大的影响因素指标。

首先,本文通过搜集、整理有关冷链物流以及灰色理论的国内外文献资料,了解到当前农产品冷链物流和预测方法、指标的研究现状,使得对农产品冷链物流需求预测的问题有了整体认识。

其次,本文基于灰色理论,运用灰色关联度分析法构建了影响因素相关度模型和灰色 GM(1,1)需求预测模型,其中灰色 GM(1,1)预测模型还包括了有效性和灵敏度检验的研究。

再次,通过查阅江西省相关的报告年鉴,收集相关的数据,并对数据进行预处理筛选,基于相应原则和数据可得性,据剔除不明显指标数据,后带入模型进行运算求解,再对结果进行有效性和灵敏性分析研究和相关性比较。

最后,根据影响因素的相关性和预测结果提出相应的分析和建议。总结全文的不足和改进想法。

关键词:农产品,冷链物流,灰色关联度分析,灰色 GM(1,1)模型,需求预测

Abstract

In the current era of continuous market-oriented development of China's economy, people's living standards and requirements become more diverse and rich, and sometimes the ingredients thousands of miles away are not unrealistic. In this case, in order to maintain fresh transportation of food materials, the development of cold chain logistics is particularly important. To some extent, the research on the relevant factors affecting its development and the prediction of the demand for cold chain logistics of agricultural products in Jiangxi Province will help the enterprise government to provide the decision-making basis in the future period, and focus on the development and control of the influential factors with a large degree of relevance.

First of all, through collecting and sorting out the domestic and foreign literature about cold chain logistics and grey theory, this paper understands the current research status of cold chain logistics and forecasting methods and indicators of agricultural products, which makes a comprehensive understanding of the demand forecasting of cold chain logistics of agricultural products.

Secondly, based on the grey theory, this paper uses the grey correlation degree analysis method to build the correlation degree model of influencing factors and the grey GM (1,1) demand prediction model, in which the grey GM (1,1) prediction model also includes the research of validity and sensitivity test.

Thirdly, by consulting the relevant report yearbook of Jiangxi Province, collecting the relevant data, and pre-processing and screening the data, based on the corresponding principles and data availability, according to the elimination of the non obvious index data, then into the model for calculation, and then the effectiveness and sensitivity of the results are analyzed and compared.

Finally, according to the correlation of influencing factors and prediction results, the corresponding analysis and suggestions are put forward. Summarize the shortcomings and improvement ideas of the whole paper.

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