基于机器学习的行道树落叶指数助力城市环境保障的研究  

Research on the Help of Roadside Tree Defoliation Index to Urban Environmental Protection Based on Machine Learning

作　　者：范翠英 Fan Cuiying(Shanghai Jing'an Urban Development Group Co.,Ltd.,Shanghai,China)

机构地区：[1]上海静安城市发展(集团)有限公司,上海

出　　处：《科学技术创新》2024年第20期56-59,共4页Scientific and Technological Innovation

摘　　要：党的十九大以来,习总书记强调超大城市的发展要更多运用新一代信息技术手段,提高城市科学化、精细化、智能化管理水平。二十大报告中,再次提出建设数字中国,提高城市治理水平,实现城市数字化转型。以上海静安城市发展(集团)有限公司自主研发的“落叶指数”为例,依托机器学习算法技术,研究行道树脱落的影响因子,通过构建预测模型精准预测落叶信息,使得道路保洁排班、调配更加科学,实现管理方式向数据管理转变、向定量管理转变、向精细化管理转变。Since the 19th CPC National Congress,General Secretary Xi has emphasized that the development of megacities should make more use of the new generation of information technology,and improve the level of scientific,refined and intelligent management of cities.In the report of the 20th CPC National Congress,it is once again proposed to build Digital China,improve the level of urban governance,and realize the digital transformation of cities.This paper takes the"Deciduous Leaf Index"independently developed by Shanghai Jing'an Urban Development(Group)Co.,Ltd.as an example.Relying on machine learning algorithm technology,the paper studies the influencing factors of roadside tree shedding.By building a prediction model,the paper accurately predicts the information of deciduous leaves,so as to make the road cleaning scheduling and deployment more scientific,and realize the transformation of management mode to data management,quantitative management and refined management.

关 键 词：数字中国 城市治理 数字化转型 行道树 落叶指数 

分 类 号：S718[农业科学—林学]