In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the tempor...In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the temporal correlation, spatial correlation and historical correlation, a basic DTTS model is built. And a three-stage approach is put forward for the simplification and calibration of the basic DTTS model. Through critical sections pre-selection and critical time pre-selection, the first stage reduces the variable number of the basic DTTS model. In the second stage, variable coefficient calibration is implemented based on basic model simplification and stepwise regression analysis. Aimed at dynamic noise estimation, the characteristics of noise are summarized and an extreme learning machine is presented in the third stage. A case study based on a real-world road network in Beijing, China, is carried out to test the efficiency and applicability of proposed DTTS model and the three-stage approach.展开更多
随着互联电网运行方式的愈加复杂多变以及广域量测系统部署的越来越完善,以广域测量系统(wide area measurement system,WAMS)量测大数据为基础的实时稳定分析成为必然要求。与此同时,如何对全网多节点毫秒级海量WAMS大数据进行时空同...随着互联电网运行方式的愈加复杂多变以及广域量测系统部署的越来越完善,以广域测量系统(wide area measurement system,WAMS)量测大数据为基础的实时稳定分析成为必然要求。与此同时,如何对全网多节点毫秒级海量WAMS大数据进行时空同步处理和异常数据检测,成为阻碍其发挥更大作用的关键问题。因此,该文提出基于高维随机矩阵描述的WAMS量测大数据建模与分析方法。首先在对WAMS量测数据时空特性分析的基础上,根据高维随机矩阵理论,进行了WAMS量测大数据的高维随机矩阵模型构建,然后推导了其异常数据检测理论和方法,最后在仿真算例上模拟实测量测数据,通过对比不同异常时刻量测数据的Trace检测和谱分布,验证了该量测大数据的建模方法的有效性与适用性。展开更多
基于MODIS影像数据反演的2009年2月份至12月份太湖梅梁湾水域表面叶绿素a、悬浮物浓度以及水温数据,结合初级生产力垂向归纳模型(Vertically Generalized Production Model:VGPM)估算获得梅梁湾2009年逐月平均日初级生产力时空分布。结...基于MODIS影像数据反演的2009年2月份至12月份太湖梅梁湾水域表面叶绿素a、悬浮物浓度以及水温数据,结合初级生产力垂向归纳模型(Vertically Generalized Production Model:VGPM)估算获得梅梁湾2009年逐月平均日初级生产力时空分布。结果表明,梅梁湾2009年年平均日初级生产力及逐月平均日初级生产力空间分布差异显著,呈现从湾内向湾口逐渐递减的趋势。时间序列分析显示,梅梁湾初级生产力季节差异显著,夏季>秋季>春季>冬季,全年初级生产力主要集中在夏季,占47.4%。通过分析VGPM模型中几个输入参数对初级生产力的影响,发现悬浮物浓度与标准化初级生产力存在显著负冥函数关系,反映沉积物再悬浮引起的悬浮物浓度增加能降低水体初级生产力。温度对初级生产力也有一定的调控与制约,与初级生产力呈现正相关趋势,在低于21℃的温度范围内与最大光合作用速率呈现正相关。展开更多
基金Project(2014BAG01B0403)supported by the National High-Tech Research and Development Program of China
文摘In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the temporal correlation, spatial correlation and historical correlation, a basic DTTS model is built. And a three-stage approach is put forward for the simplification and calibration of the basic DTTS model. Through critical sections pre-selection and critical time pre-selection, the first stage reduces the variable number of the basic DTTS model. In the second stage, variable coefficient calibration is implemented based on basic model simplification and stepwise regression analysis. Aimed at dynamic noise estimation, the characteristics of noise are summarized and an extreme learning machine is presented in the third stage. A case study based on a real-world road network in Beijing, China, is carried out to test the efficiency and applicability of proposed DTTS model and the three-stage approach.
文摘随着互联电网运行方式的愈加复杂多变以及广域量测系统部署的越来越完善,以广域测量系统(wide area measurement system,WAMS)量测大数据为基础的实时稳定分析成为必然要求。与此同时,如何对全网多节点毫秒级海量WAMS大数据进行时空同步处理和异常数据检测,成为阻碍其发挥更大作用的关键问题。因此,该文提出基于高维随机矩阵描述的WAMS量测大数据建模与分析方法。首先在对WAMS量测数据时空特性分析的基础上,根据高维随机矩阵理论,进行了WAMS量测大数据的高维随机矩阵模型构建,然后推导了其异常数据检测理论和方法,最后在仿真算例上模拟实测量测数据,通过对比不同异常时刻量测数据的Trace检测和谱分布,验证了该量测大数据的建模方法的有效性与适用性。
文摘基于MODIS影像数据反演的2009年2月份至12月份太湖梅梁湾水域表面叶绿素a、悬浮物浓度以及水温数据,结合初级生产力垂向归纳模型(Vertically Generalized Production Model:VGPM)估算获得梅梁湾2009年逐月平均日初级生产力时空分布。结果表明,梅梁湾2009年年平均日初级生产力及逐月平均日初级生产力空间分布差异显著,呈现从湾内向湾口逐渐递减的趋势。时间序列分析显示,梅梁湾初级生产力季节差异显著,夏季>秋季>春季>冬季,全年初级生产力主要集中在夏季,占47.4%。通过分析VGPM模型中几个输入参数对初级生产力的影响,发现悬浮物浓度与标准化初级生产力存在显著负冥函数关系,反映沉积物再悬浮引起的悬浮物浓度增加能降低水体初级生产力。温度对初级生产力也有一定的调控与制约,与初级生产力呈现正相关趋势,在低于21℃的温度范围内与最大光合作用速率呈现正相关。
