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[1]苏怀　张劲军.天然气管网大数据分析方法及发展建议[J].油气储运,2020,39(10):1-15.
　SU Huai,ZHANG Jinjun.Approach of big data analysis and suggestions on development ofnatural gas pipeline network[J].Oil & Gas Storage and Transportation,2020,39(10):1-15.
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天然气管网大数据分析方法及发展建议

《油气储运》[ISSN:1000-8241/CN:13-1093/TE] 卷: 39 期数: 2020年10 页码: 1-15 栏目: 出版日期: 2020-11-25
Title:
Approach of big data analysis and suggestions on development of
natural gas pipeline network
作者:

苏怀　张劲军

Author(s):

SU Huai;  ZHANG Jinjun

关键词:

天然气管网; 大数据; 分析; 应用; 方法论

Keywords:

natural gas pipeline network;  big data;  analysis;  application;  methodology

分类号:
TE88
文献标志码:
A
摘要:
天然气管网数据具有海量、多源异构、类型多样、价值密度差异大等特点，数据分析与应用难
度大。借鉴电网、供应链、互联网等领域大数据研究成果，提出了基于数据处理、数据挖掘、多元数据
综合分析的天然气管网大数据分析方法框架。从数据清洗、特征筛选、特征重构3 个方面阐述了管
网数据处理的方法与功能；结合具体业务和场景，明确了预测预警、模式识别、规则学习与推理是构
成管网数据挖掘方法的基础；讨论了运用多元化管网数据的综合方法，指出发展多模态学习和联邦
学习是打破管网数据壁垒、形成数据智慧的关键路径。天然气管网大数据分析应该不断完善管网的
大数据“生态”、深入研究融合领域知识的机器学习方法，发展跨领域、可解释、可控制的管网大数据
分析方法体系，为智慧管网技术提供理论基础。

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更新日期/Last Update: 2020-09-17