摘要
燃气低压管网的合理高效规范化管理是燃气普及、管线巡查、实时预警和应急响应的基本保障。我国燃气管网发展虽然迅速,但终端用户的低压管网仍存在很多规划和管理上的不足。互联网大数据时代的兴起为燃气行业终端用户的智能管理提供了潜在机会。本文基于GIS空间分析功能,把燃气管网系统扩展深入到街道级管理模式,分析区域管理中低压管网的空间分布及影响因素,采用协同克里金插值预测城郊和乡镇区域低压管网空间分布态势,并对预测结果进行了精度评价。实验区验证结果表明,预测模型较好,其平均误差、均方根误差、标准化均方根误差均在容错范围内。该研究可为燃气管网规划和市场开发等工作提供决策依据,为智慧燃气服务民生提供思路和方案。
The efficient and standardization management of low-pressure gas pipe network is a basic guarantee for its prevalence rate,routine safety inspection,real-time alarm and timely emergency response.Though the gas pipe network has been developed rapidly,there are still more efforts required on the planning and management of low pressure pipe network.The big data era developing up on the internet provides a potential chance of intelligent management for end-users in the gas industry.In this article,we extend the gas pipe network into street level in terms of GIS spatial analysis functions,investigate the spatial distribution of low pressure gas pipe network and related influencing factor from the regional management,then adopt the Cokriging method to predict its distribution over rural towns and suburb of local cities,followed by an accuracy assessment.Our results show that the validation over the study region receives a good prediction with tolerant standard mean error,root mean square error,and the normalized root mean square error.This work may contribute to the gas pipe planning and market development,and as well the construction of smart gas services.
作者
王重阳
曲烨
帅艳民
WANG Chongyang;QU Ye;SHUAI Yanmin(Limited Corporation of Shenyang Gas,Shenyang 110000,China;College of Surveying and Geographical Science,Liaoning Technical University,Fuxin 123000,China;Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,State Key Laboratory of Desert and Oasis Ecology,Urumqi 830011,China;Research Center for Ecology and Environment of Central Asia,Chinese Academy of Sciences,Urumqi 830011,China)
出处
《测绘与空间地理信息》
2022年第3期28-32,共5页
Geomatics & Spatial Information Technology
基金
辽宁省“兴辽英才计划”项目(XLYC1802027)
中国科学院百人计划(Y938091)
湖南自然科学基金(2018JJ2116)资助。
