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基于统计聚类与时序分析的风电场短期风速预测模型 被引量:2
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作者 陈勤勤 陈国初 《上海电机学院学报》 2014年第2期76-82,共7页
在时间序列预测法的基础上,运用统计聚类分析的方法对历史风速数据进行预处理,综合考虑了气象因素对风速的影响。根据预测日的平均风速、最大和最小风速、风向及温度等特征参数,按照相似性最大的原则,选择合适的风速数据作为预测建模用... 在时间序列预测法的基础上,运用统计聚类分析的方法对历史风速数据进行预处理,综合考虑了气象因素对风速的影响。根据预测日的平均风速、最大和最小风速、风向及温度等特征参数,按照相似性最大的原则,选择合适的风速数据作为预测建模用的训练样本。与未经预处理的数据所建立的模型相比,预测精度得到了显著提高,并验证了采用统计聚类分析来预处理数据的正确性,为更精确地预测风电功率提供了条件。 展开更多
关键词 风速预测 时间序列分析 统计聚类分析 相似性原则 预测精度
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基于作物生长模型及CAST分类的华北夏玉米生产力区划研究 被引量:5
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作者 邬定荣 刘建栋 +2 位作者 刘玲 姜朝阳 于强 《气象科学》 北大核心 2015年第1期66-70,共5页
利用试验数据校正并验证了机理性的作物生长模型WOFOST,随后模拟了华北42个站点1961—2006年夏玉米的光温和气候生产潜力。并首次运用新型统计检验聚类方法(CAST),对夏玉米光温及气候生产潜力的要素场分别进行了定量化分区。结果表明,... 利用试验数据校正并验证了机理性的作物生长模型WOFOST,随后模拟了华北42个站点1961—2006年夏玉米的光温和气候生产潜力。并首次运用新型统计检验聚类方法(CAST),对夏玉米光温及气候生产潜力的要素场分别进行了定量化分区。结果表明,华北夏玉米光温及气候生产潜力均分为5个不同荷载中心的区域。与农业气象传统等值线分区方法相比,将作物模型与CAST相结合进行的生产潜力区划可以更客观地反映以荷载中心台站为代表的产量的时空分布特征。这对于指导区域农业气候区划,实现区域农业可持续发展具有重要的理论及现实意义。 展开更多
关键词 气候生产潜力 夏玉米 统计检验聚类分析 产量区划
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Application of Two-Order Difference to Gap Statistic
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作者 岳士弘 王秀秀 魏苗苗 《Transactions of Tianjin University》 EI CAS 2008年第3期217-221,共5页
Gap statistic is a well-known index of clustering validity, but its realization is difficult to be comprehended and accurately determined. A direct method is presented to improve the performance of the Gap statistic, ... Gap statistic is a well-known index of clustering validity, but its realization is difficult to be comprehended and accurately determined. A direct method is presented to improve the performance of the Gap statistic, which applies the two-order difference of within-cluster dispersion to replace the constructed null reference distribution in the Gap statistic. Hence, the realization of the Gap statistic becomes easy and is reformulated, and its uncertainty in applications is reduced. Also, the limitation of the Gap statistic is analyzed by two typical examples, that is, the Gap statistic is difficult to be applied to the dataset that contains strong-overlap or uneven-density clusters. Experiments verify the usefulness of the proposed method. 展开更多
关键词 clustering validity Gap statistic data structure
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Comprehensive Research on Focal Mechanism Solutions in the Capital Circle Area of China
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作者 Wu Minjie Wu Anxu +4 位作者 Xu Ping Lin Xiangdong Dong Hongyan Xin Xuexia Li Layue 《Earthquake Research in China》 2014年第1期79-90,共12页
Comprehensive statistical analysis was performed on the basic features of focal mechanisms of 619 ML≥2. 0 earthquakes which occurred in the capital circle area from January 2002 to June 2010. By dividing the capital ... Comprehensive statistical analysis was performed on the basic features of focal mechanisms of 619 ML≥2. 0 earthquakes which occurred in the capital circle area from January 2002 to June 2010. By dividing the capital area into three studying regions based on regional tectonic characteristics,cluster analysis was conducted on the focal mechanisms of all subregions using the longest distance method in the statistical cluster analysis to study the characteristics of tectonic stress tensors. The result shows that dominant P-axis azimuth distribution is NNE-NEE and that of T-axis is NNW-NWW,most of the focal areas are controlled by a horizontal stress field and rupture is mainly of horizontal strike-slip. The maximum principal compression stress orientation is NE75° in the west,NE62° in the middle,and near EW in the east of the capital area. The regional tectonic stress field is characterized by horizontal compression. 展开更多
关键词 Focal mechanism solution Systematic cluster Stress tensor Capital circlearea
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Related factors and regional differences in energy consumption in China
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作者 QU Xiao-e ZHU Qing YANG Yang 《Chinese Business Review》 2010年第7期27-36,共10页
This article used the Cluster analysis of statistical method to separate China's 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985... This article used the Cluster analysis of statistical method to separate China's 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985 to 2007. The categories were high, moderate and low energy consumption areas and they had significant differences in energy consumption. Based on this classification, the authors analyzed the influencing factors of energy consumption in the three areas by means of panel data econometric model. The results showed that the influencing factors were obviously different. In order to support national goal of energy conservation and emission reduction, the energy measures and policies should be distinctly taken. 展开更多
关键词 energy consumption Cluster analysis panel model econometric analysis
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