Abstract Monthly mean sea ice motion vectors and monthly mean sea level pressure （SLP） for the period of 1979-2006 are investigated to understand the spatial and temporal changes of Arctic sea-ice drift. According t...Abstract Monthly mean sea ice motion vectors and monthly mean sea level pressure （SLP） for the period of 1979-2006 are investigated to understand the spatial and temporal changes of Arctic sea-ice drift. According to the distinct differences in monthly mean ice velocity field as well as in the distribution of SLP, there are four primary types in the Arctic Ocean： Beaufort Gyre＋Transpolar Drift, Anticyclonic Drift, Cyclonic Drift and Double Gyre Drift. These four types account for 81% of the total, and reveal distinct seasonal variations. The Cyclonic Drift with a large-scale anticlockwise ice motion pattern trends to prevail in summer while the Anticyclonic Drift with an opposite pattern trends to prevail in winter and spring. The prevailing seasons for the Beaufort Gyre＋Transpolar Drift are spring and autumn, while the Double Gyre Drift trends to prevail in winter, especially in Feb- ruary. The annual occurring times of the Anticyclonic Drift and the Cyclonic Drift are closely correlated with the yearly mean Arc- tic Oscillation （AO） index, with a correlation coefficient of -0.54 and 0.54 （both significant with the confident level of 99%）, re- spectively. When the AO index stays in a high positive （negative） condition, the sea-ice motion in the Arctic Ocean demonstrates a more anticlockwise （clockwise） drifting pattern as a whole. When the AO index stays in a neutral condition, the sea-ice motion becomes much more complicated and more transitional types trend to take place.展开更多
提出了一种基于闭合频繁模式的半随机森林数据流分类算法(Semi-Random Forest based on Closed Frequent Pattern,SRFCFP),以解决数据流中噪声和概念漂移问题。SRFCFP利用闭合频繁模式对数据流进行表示,去除冗余信息和噪声,突出数据特...提出了一种基于闭合频繁模式的半随机森林数据流分类算法(Semi-Random Forest based on Closed Frequent Pattern,SRFCFP),以解决数据流中噪声和概念漂移问题。SRFCFP利用闭合频繁模式对数据流进行表示,去除冗余信息和噪声,突出数据特征。采用半随机森林建立分类模型,并通过基于时间衰减的模式集更新机制适应数据流的无限性。为了检测概念漂移并及时适应,引入了一种模式集差异性度量方式,用于测量数据分布变化。实验结果表明,在MOA平台下使用真实和合成数据集,SRFCFP在平均精度上超越了相关对比算法,并能有效处理数据流中的概念漂移和噪声问题。展开更多
Environmental variations and ontogeny may affect plant morphological traits and biomass allocation patterns that are related to the adjustments of plant ecological strategies. We selected 2-, 3-and 4-year-old Fritilla...Environmental variations and ontogeny may affect plant morphological traits and biomass allocation patterns that are related to the adjustments of plant ecological strategies. We selected 2-, 3-and 4-year-old Fritillaria unibracteata plants to explore the ontogenetic and altitudinal changes that impact their morphological traits(i.e., plant height, single leaf area,and specific leaf area) and biomass allocations [i.e.,biomass allocations of roots, bulbs, leaves, stems, and flowers] at relatively low altitudinal ranges(3400 m to 3600 m asl) and high altitudinal ranges(3600 m to4000 m asl). Our results indicated that plant height,root biomass allocation, and stem biomass allocation significantly increased during the process of individual growth and development, but single leaf area, specific leaf area, bulb biomass allocation, and leaf biomass allocation showed opposite trends.Furthermore, the impacts of altitudinal changes on morphological traits and biomass allocations had no significant differences at low altitude, except for single leaf area of 2-year-old plants. At high altitude,significantly reduced plant height, single leaf area and leaf biomass allocation for the 2-year-old plants,specific leaf area for the 2-and 4-year-old plants, and stem biomass allocation were found along altitudinal gradients. Significantly increased sexual reproductive allocation and relatively stable single leaf area and leaf biomass allocation were also observed for the 3-and 4-year-old plants. In addition, stable specific leaf area for the 3-year-old plants and root biomass allocation were recorded. These results suggested that the adaptive adjustments of alpine plants, in particular F. unibracteata were simultaneously influenced by altitudinal gradients and ontogeny.展开更多
提出类别属性数据流数据离群度量——加权频繁模式离群因子(weighted frequent pattern outlier factor,简称WFPOF),并在此基础上给出一种快速数据流离群点检测算法FODFP-Stream(fast outlier detection for high dimensional categoric...提出类别属性数据流数据离群度量——加权频繁模式离群因子(weighted frequent pattern outlier factor,简称WFPOF),并在此基础上给出一种快速数据流离群点检测算法FODFP-Stream(fast outlier detection for high dimensional categorical data streams based on frequent pattern).该算法通过动态发现和维护频繁模式来计算离群度,能够有效地处理高维类别属性数据流,并可进一步扩展到数值属性和混合属性数据流.对仿真数据集和真实数据集的实验检测均验证该算法具有良好的适用性和有效性.展开更多
基金the National Natural Science Foundation of China (Grant no. 40631006)the National Major Science Project of China for Global Change Research (Grant no. 2010CB951403)
文摘Abstract Monthly mean sea ice motion vectors and monthly mean sea level pressure （SLP） for the period of 1979-2006 are investigated to understand the spatial and temporal changes of Arctic sea-ice drift. According to the distinct differences in monthly mean ice velocity field as well as in the distribution of SLP, there are four primary types in the Arctic Ocean： Beaufort Gyre＋Transpolar Drift, Anticyclonic Drift, Cyclonic Drift and Double Gyre Drift. These four types account for 81% of the total, and reveal distinct seasonal variations. The Cyclonic Drift with a large-scale anticlockwise ice motion pattern trends to prevail in summer while the Anticyclonic Drift with an opposite pattern trends to prevail in winter and spring. The prevailing seasons for the Beaufort Gyre＋Transpolar Drift are spring and autumn, while the Double Gyre Drift trends to prevail in winter, especially in Feb- ruary. The annual occurring times of the Anticyclonic Drift and the Cyclonic Drift are closely correlated with the yearly mean Arc- tic Oscillation （AO） index, with a correlation coefficient of -0.54 and 0.54 （both significant with the confident level of 99%）, re- spectively. When the AO index stays in a high positive （negative） condition, the sea-ice motion in the Arctic Ocean demonstrates a more anticlockwise （clockwise） drifting pattern as a whole. When the AO index stays in a neutral condition, the sea-ice motion becomes much more complicated and more transitional types trend to take place.
文摘提出了一种基于闭合频繁模式的半随机森林数据流分类算法(Semi-Random Forest based on Closed Frequent Pattern,SRFCFP),以解决数据流中噪声和概念漂移问题。SRFCFP利用闭合频繁模式对数据流进行表示,去除冗余信息和噪声,突出数据特征。采用半随机森林建立分类模型,并通过基于时间衰减的模式集更新机制适应数据流的无限性。为了检测概念漂移并及时适应,引入了一种模式集差异性度量方式,用于测量数据分布变化。实验结果表明,在MOA平台下使用真实和合成数据集,SRFCFP在平均精度上超越了相关对比算法,并能有效处理数据流中的概念漂移和噪声问题。
基金funded by the Natural Science Foundation Project of Sichuan Science and Technology Department (2018JY0305)Key Projects of the Natural Science Foundation of Sichuan Education Department (18ZA0002)
文摘Environmental variations and ontogeny may affect plant morphological traits and biomass allocation patterns that are related to the adjustments of plant ecological strategies. We selected 2-, 3-and 4-year-old Fritillaria unibracteata plants to explore the ontogenetic and altitudinal changes that impact their morphological traits(i.e., plant height, single leaf area,and specific leaf area) and biomass allocations [i.e.,biomass allocations of roots, bulbs, leaves, stems, and flowers] at relatively low altitudinal ranges(3400 m to 3600 m asl) and high altitudinal ranges(3600 m to4000 m asl). Our results indicated that plant height,root biomass allocation, and stem biomass allocation significantly increased during the process of individual growth and development, but single leaf area, specific leaf area, bulb biomass allocation, and leaf biomass allocation showed opposite trends.Furthermore, the impacts of altitudinal changes on morphological traits and biomass allocations had no significant differences at low altitude, except for single leaf area of 2-year-old plants. At high altitude,significantly reduced plant height, single leaf area and leaf biomass allocation for the 2-year-old plants,specific leaf area for the 2-and 4-year-old plants, and stem biomass allocation were found along altitudinal gradients. Significantly increased sexual reproductive allocation and relatively stable single leaf area and leaf biomass allocation were also observed for the 3-and 4-year-old plants. In addition, stable specific leaf area for the 3-year-old plants and root biomass allocation were recorded. These results suggested that the adaptive adjustments of alpine plants, in particular F. unibracteata were simultaneously influenced by altitudinal gradients and ontogeny.
基金Supported by The National Natural Science Foundation of China(Grant Nos.11301350,11472124,and 11271158)the Dr.Start-up fund in Liaoning Province,China(Grant No.20141050)
文摘提出类别属性数据流数据离群度量——加权频繁模式离群因子(weighted frequent pattern outlier factor,简称WFPOF),并在此基础上给出一种快速数据流离群点检测算法FODFP-Stream(fast outlier detection for high dimensional categorical data streams based on frequent pattern).该算法通过动态发现和维护频繁模式来计算离群度,能够有效地处理高维类别属性数据流,并可进一步扩展到数值属性和混合属性数据流.对仿真数据集和真实数据集的实验检测均验证该算法具有良好的适用性和有效性.
