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中国建筑能耗时间序列变化趋势及其影响因素 被引量:28
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作者 王霞 任宏 +2 位作者 蔡伟光 武涌 陈明曼 《暖通空调》 北大核心 2017年第11期21-26,93,共7页
分析了我国建筑能耗时间序列变化趋势,运用LMDI分解方法对我国2001—2014年的建筑能耗进行因素分解,定量分析了这些因素对建筑能耗的影响程度和影响规律。结果表明:我国建筑能耗呈现持续增长趋势,但年均增速在"十一五"和"... 分析了我国建筑能耗时间序列变化趋势,运用LMDI分解方法对我国2001—2014年的建筑能耗进行因素分解,定量分析了这些因素对建筑能耗的影响程度和影响规律。结果表明:我国建筑能耗呈现持续增长趋势,但年均增速在"十一五"和"十二五"期间明显放缓,人口规模因素、城镇化因素、建筑面积因素、行为因素对其增长均具有显著的正向驱动作用,促使建筑能耗累计增长5.05亿t标准煤;建筑能效则对建筑能耗增长具有抑制作用,促使其增幅降低97%,共节约4.88亿t标准煤。 展开更多
关键词 建筑能耗 时间序列变化趋势 LMDI分解法 驱动因素 建筑节能
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荔浦河快速预警及洪水演变特点分析
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作者 刘胜娅 粟忠 滕培宋 《广西水利水电》 2017年第3期22-24,共3页
以广西荔浦河"2016.05"暴雨洪水为例,对荔浦河暴雨洪水相关关系以及洪水时间序列变化趋势进行分析,研究其暴雨洪水特点及规律,为荔浦河快速预警服务及洪水演变特点分析提供科学依据,为提升中小河流水文情报服务水平、推动水... 以广西荔浦河"2016.05"暴雨洪水为例,对荔浦河暴雨洪水相关关系以及洪水时间序列变化趋势进行分析,研究其暴雨洪水特点及规律,为荔浦河快速预警服务及洪水演变特点分析提供科学依据,为提升中小河流水文情报服务水平、推动水文供给侧结构性改革提供技术支撑。 展开更多
关键词 中小河流 暴雨洪水 快速预警 洪水时间序列变化趋势 水文情报服务
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Change Point Detection and Trend Analysis for Time Series
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作者 Hong Zhang Stephen Jeffrey John Carter 《Chinese Journal of Chemical Physics》 SCIE EI CAS CSCD 2022年第2期399-406,I0004,共9页
Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whe... Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whereas trend can be defined as estimation of gradual departure from past norms.We analyze the time series data in the presence of trend,using Cox-Stuart methods together with the change point algorithms.We applied the methods to the nearsurface wind speed time series for Australia as an example.The trends in near-surface wind speeds for Australia have been investigated based upon our newly developed wind speed datasets,which were constructed by blending observational data collected at various heights using local surface roughness information.The trend in wind speed at 10 m is generally increasing while at 2 m it tends to be decreasing.Significance testing,change point analysis and manual inspection of records indicate several factors may be contributing to the discrepancy,such as systematic biases accompanying instrument changes,random data errors(e.g.accumulation day error)and data sampling issues.Homogenization technique and multiple-period trend analysis based upon change point detections have thus been employed to clarify the source of the inconsistencies in wind speed trends. 展开更多
关键词 Time series Change point detection Trend analysis Wind speed HOMOGENIZATION
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