利用TIGGE资料中欧洲中期天气预报中心（ECMWF,the European Centre for Medium-Range Weather Forecasts）、日本气象厅（JMA,the Japan Meteorological Agency）、美国国家环境预报中心（NCEP,the National Centers for Environmental...利用TIGGE资料中欧洲中期天气预报中心（ECMWF,the European Centre for Medium-Range Weather Forecasts）、日本气象厅（JMA,the Japan Meteorological Agency）、美国国家环境预报中心（NCEP,the National Centers for Environmental Prediction）以及英国气象局（UKMO,the UK Met Office）4个中心1~7 d预报的日降水量集合预报资料,并以中国降水融合产品作为＂观测值＂,对我国地面降水量预报进行统计降尺度处理。采用空间滑动窗口增加中雨和大雨雨量样本,建立分级雨量的回归方程,并与未分级雨量的统计降尺度预报进行对比。结果表明,对于不同模式、不同预报时效以及不同降水量级,统计降尺度的预报技巧改进程度不尽相同。统计降尺度的预报技巧依赖于模式本身的预报效果。相比雨量未分级回归,雨量分级回归的统计降尺度预报与观测值的距平相关系数更高,均方根误差更小,不同量级降水的ETS评分明显提高。对雨量分级回归统计降尺度预报结果进行二次订正,可大大减少小雨的空报。展开更多
The contribution of this paper is comparing three popular machine learning methods for software fault prediction. They are classification tree, neural network and case-based reasoning. First, three different classifie...The contribution of this paper is comparing three popular machine learning methods for software fault prediction. They are classification tree, neural network and case-based reasoning. First, three different classifiers are built based on these three different approaches. Second, the three different classifiers utilize the same product metrics as predictor variables to identify the fault-prone components. Third, the predicting results are compared on two aspects, how good prediction capabilities these models are, and how the models support understanding a process represented by the data.展开更多
This study analyzed the effects of ecological factors on secondary metabolites of Scutellaria baicalensis using two sources:92individual roots of S.baicalensis from all over China,and secondary metabolites,medicinal m...This study analyzed the effects of ecological factors on secondary metabolites of Scutellaria baicalensis using two sources:92individual roots of S.baicalensis from all over China,and secondary metabolites,medicinal materials and inorganic element contents obtained from the testing of 92 S.baicalensis rhizosphere soil samples.The study used environmental data from the Genuine Medicinal Material Spatial Analysis Database.Most of the chemical constituents of S.baicalensis were negatively correlated to latitude and positively correlated to temperature;generally,the contents of 21 chemical constituents were higher at low latitudes than that at high latitudes.By gradual regression analysis,it was found that the content of baicalin in S.baicalensis was negatively correlated to latitude and generally the content of inorganic elements in soil was excessively high(excluding Mg and Ca),which has a negative effect on the accumulation of chemical constituents in S.baicalensis.Based on the cluster analysis of 21 constituents,S.baicalensis from different places of origin was divided into two groups,and S.baicalensis was not genuine only in a specific small region.Within the zone from Chifeng,Inner Mongolia to Taibai,Shaanxi is suitable for accumulation of secondary metabolites of S.baicalensis and such a zone represents a suitable distribution and potential genuine producing area.展开更多
文摘利用TIGGE资料中欧洲中期天气预报中心（ECMWF,the European Centre for Medium-Range Weather Forecasts）、日本气象厅（JMA,the Japan Meteorological Agency）、美国国家环境预报中心（NCEP,the National Centers for Environmental Prediction）以及英国气象局（UKMO,the UK Met Office）4个中心1~7 d预报的日降水量集合预报资料,并以中国降水融合产品作为＂观测值＂,对我国地面降水量预报进行统计降尺度处理。采用空间滑动窗口增加中雨和大雨雨量样本,建立分级雨量的回归方程,并与未分级雨量的统计降尺度预报进行对比。结果表明,对于不同模式、不同预报时效以及不同降水量级,统计降尺度的预报技巧改进程度不尽相同。统计降尺度的预报技巧依赖于模式本身的预报效果。相比雨量未分级回归,雨量分级回归的统计降尺度预报与观测值的距平相关系数更高,均方根误差更小,不同量级降水的ETS评分明显提高。对雨量分级回归统计降尺度预报结果进行二次订正,可大大减少小雨的空报。
文摘The contribution of this paper is comparing three popular machine learning methods for software fault prediction. They are classification tree, neural network and case-based reasoning. First, three different classifiers are built based on these three different approaches. Second, the three different classifiers utilize the same product metrics as predictor variables to identify the fault-prone components. Third, the predicting results are compared on two aspects, how good prediction capabilities these models are, and how the models support understanding a process represented by the data.
基金supported by the National Natural Science Foundation of China(81130070,81072989)the National Key Technology Research and Development Program of China(2012BAI29B02)
文摘This study analyzed the effects of ecological factors on secondary metabolites of Scutellaria baicalensis using two sources:92individual roots of S.baicalensis from all over China,and secondary metabolites,medicinal materials and inorganic element contents obtained from the testing of 92 S.baicalensis rhizosphere soil samples.The study used environmental data from the Genuine Medicinal Material Spatial Analysis Database.Most of the chemical constituents of S.baicalensis were negatively correlated to latitude and positively correlated to temperature;generally,the contents of 21 chemical constituents were higher at low latitudes than that at high latitudes.By gradual regression analysis,it was found that the content of baicalin in S.baicalensis was negatively correlated to latitude and generally the content of inorganic elements in soil was excessively high(excluding Mg and Ca),which has a negative effect on the accumulation of chemical constituents in S.baicalensis.Based on the cluster analysis of 21 constituents,S.baicalensis from different places of origin was divided into two groups,and S.baicalensis was not genuine only in a specific small region.Within the zone from Chifeng,Inner Mongolia to Taibai,Shaanxi is suitable for accumulation of secondary metabolites of S.baicalensis and such a zone represents a suitable distribution and potential genuine producing area.
