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  • 袁晓杰,杨子江,李欣,张溢卓.我国水产品消费量预测及政策性建议[J].海洋开发与管理,2024,41(3):153-162    
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我国水产品消费量预测及政策性建议
袁晓杰,杨子江,李欣,张溢卓
上海海洋大学经济管理学院;中国水产科学研究院
摘要:
为了顺应我国居民水产品消费结构变化,通过研判我国未来水产品消费趋势,以期为我国水产品消费市场统筹规划与科学布局起到学术支撑作用。文章选取人口结构、进出口水平、发展水平和消费水平四大重要因素中的9个典型指标进行主成分分析,构建BP神经网络模型来预测我国2023—2035年的水产品消费趋势。结果表明,“十四五”“十五五”及更长一段时间,我国水产品表观消费量具有较大提升空间,水产品消费量在2035年有望增至9 044.40万t。为保障水产品有效供给,满足水产品消费升级需求,提出深度挖掘水产品资源、完善水产品消费促进政策、加强冷链物流基础设施建设及政府主导产业发展等建议,以进一步满足居民对美好生活的需求。
关键词:  水产品消费  预测  BP神经网络模型
DOI:10.20016/j.cnki.hykfygl.20230822.001
投稿时间:2023-06-19修订日期:2024-02-23
基金项目:中国水产科学研究院院级基本科研业务费专项资金项目“我国水产品消费现状与趋势研究”(2022XT0801).
Forecast and Policy Suggestion of Consumption of Aquatic Products in China
YUAN Xiaojie,YANG Zijiang,LI Xin,ZHANG Yizhuo
School of Economics and Management, Shanghai Ocean University;Chinese Academy of Fishery Sciences
Abstract:
In order to adapt to the changes in the consumption structure of aquatic products in our country, the future consumption trend of aquatic products is studied and judged, in order to play an academic supporting role for the overall planning and scientific layout of aquatic products consumption market in China. In this paper, 9 typical indicators of population structure, import and export level, development level and consumption level are selected for principal component analysis, and BP neural network model is constructed to predict the consumption trend of aquatic products in China from 2023 to 2035. The results show that in the “14th Five-Year Plan”, “15th Five-Year Plan” and an even longer period of time, the apparent consumption of aquatic products in China has a large room for improvement, which is expected to increase to 90 444 000 tons in 2035. In order to ensure the effective supply of aquatic products and meet the needs of aquatic product consumption upgrading, suggestions were put forward to further explore aquatic product resources, improve aquatic product consumption promotion policies, strengthen the construction of cold chain logistics infrastructure and the development of government-led industries, so as to further meet the needs of residents for a better life.
Key words:  Consumption of aquatic products, Forecast, Influencing factors, BP neural network model