机器学习技术在农业气象中的应用  

Application of Machine Learning Techniques in Agrometeorology

作　　者：赵思琪 吕晓宇 王智勇 秦志伟 李玉香[1] ZHAO Siqi;LYU Xiaoyu;WANG Zhiyong;QIN Zhiwei;LI Yuxiang(Hebei Normal University of Science and Technology Qinhuangdao,Hebei 066004)

机构地区：[1]河北科技师范学院,河北秦皇岛066004

出　　处：《现代农业研究》2023年第8期136-139,共4页Modern Agriculture Research

基　　金：2018年教育部产学合作协同育人项目“基于Python的数据分析与智能开发人才培养实践”(项目编号:201801037002);2018年教育部产学合作协同育人项目“Python全栈开发人才培养实践”(项目编号:201802057003)。

摘　　要：本文介绍了机器学习技术在农业气象领域的应用,涵盖了机器学习在农业气象数据处理、预测模型、制图与区划等方面的应用。机器学习技术可以帮助农业工作者更加精准地了解气象变化趋势和规律,制定科学的作物种植和管理方案,提高农业生产效率和收益。同时,本文也指出了机器学习在农业气象领域面临的挑战,包括数据质量和数据量、模型准确性和泛化能力、跨学科融合和技术创新等方面的问题。最后,本文展望了机器学习在农业气象领域的未来发展趋势和前景,预计机器学习将进一步结合多种数据来源,提高模型的准确性和可靠性,同时加强数据质量和标注、增强模型的泛化能力、推动跨学科融合等方面的发展。This paper introduces the application of machine learning technology in the field of agricultural meteorology,covering the application of machine learning in agrometeorology data processing,prediction model,mapping and regionalization,etc.Machine learning technology can help agricultural workers to more accurately understand the trends and laws of meteorological changes,develop scientific crop planting and management programs,and improve the efficiency and benefits of agricultural production.At the same time,this paper also highlights the challenges of machine learning in agrometeorology,including data quality and data quantity,model accuracy and generalization ability,interdisciplinary integration,and technological innovation.Finally,this paper looks forward to the future development trend and prospects of machine learning in the field of agricultural meteorology.It is expected that machine learning will further combine various data sources to improve the accuracy and reliability of models,while strengthening the data quality and annotation,enhance the generalization ability of models,and promote the development of interdisciplinary integration.

关 键 词：机器学习 农业气象 气象数据 无人机技术 物联网技术 

分 类 号：S163[农业科学—农业气象学]