湖北农业科学 ›› 2022, Vol. 61 ›› Issue (22): 174-177.doi: 10.14088/j.cnki.issn0439-8114.2022.22.031

• 信息工程 • 上一篇    下一篇

深度学习环境下香料种植推荐模型的设计研究

孙吉红1, 钱晔2,3, 周正1, 张剑波1   

  1. 1.云南省科学技术院,昆明 650000;
    2.云南农业大学大数据学院(信息工程学院),昆明 650201;
    3.云南省高校农业信息技术重点实验室,昆明 650201
  • 收稿日期:2021-11-08 出版日期:2022-11-25 发布日期:2023-01-11
  • 通讯作者: 张剑波(1984-),男,云南昆明人,副研究员,硕士,主要从事科技管理、科技传播、科技成果转移转化研究,(电话)15208718470(电子信箱)ibizacandance@126.com。
  • 作者简介:孙吉红(1983-),男,云南建水人,副研究员,硕士,主要从事人工智能、农业信息化研究,(电话)18788442310(电子信箱)81972331@qq.com
  • 基金资助:
    云南省省级“放管服”科研项目; 云南主要天然香料植物资源的研究及产业化(2019-1-N-25318000002120)

Design and research on recommendation model of spice cultivation in deep learning environment

SUN Ji-hong1, QIAN Ye2,3, ZHOU Zheng1, ZHANG Jian-bo1   

  1. 1. Yunnan Provincial Academy of Science and Technology, Kunming 650051,China;
    2. School of Big Data (Information Engineering) ,Yunnan Agricultural University, Kunming 650201,China;
    3. Key Laboratory of Agricultural Information Technology in Yunnan, Kunming 650201,China
  • Received:2021-11-08 Online:2022-11-25 Published:2023-01-11

摘要: 为进一步利用人工智能技术服务云南省,促进云南省草果产业不断壮大发展,减少资源和劳动力的浪费,选取最具有代表性的云南省怒江草果种植基地,构建草果病虫害预测模型、草果价格预测模型等多个智能模型,搭建草果产业智能推荐模型群。采用云计算技术搭建草果产业智能推荐平台,助推农户致富、企业发展壮大、科研人员获得显著的研究成果,为种植户、种植企业、销售企业、加工企业、科研人员5类人群提供优质、高效的智能化服务模式,并且在运营的过程中不断壮大平台的规模和影响力,助推云南省乃至全国草果行业的发展。

关键词: 香料种植, 推荐模型, 设计, 深度学习

Abstract: In order to further use artificial intelligence technology to serve Yunnan Province, promote the continuous growth and development of the fructus tsaoko industry in Yunnan Province, and reduce the waste of resources and labor, the most representative fructus tsaoko planting base in Nujiang,Yunnan Province was selected to construct multiple intelligent models such as fructus tsaoko pest prediction model and fructus tsaoko price prediction model, and build an intelligent recommendation model group for fructus tsaoko industry. The use of cloud computing technology to build an intelligent recommendation platform for the grass and fruit industry would help farmers get rich, enterprises grow and develop, and scientific researchers obtain significant research results. It would provide high-quality and efficient intelligent service models for five groups of farmers, planting enterprises, sales enterprises, processing enterprises, and scientific researchers. In the process of operation, the scale and influence of the platform would continue to grow, and the development of the fructus tsaoko industry in Yunnan Province and even the whole country would be promoted.

Key words: spice planting, recommended model, design, deep learning

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