为提高光伏发电功率预测精度,提出一种基于外生因素及季节性的差分自回归移动平均SARIMAX(seasonal autoregressive integrated moving average with exogenous factors)并结合优化支持向量回归SVR(support vector regression)的光伏发...为提高光伏发电功率预测精度,提出一种基于外生因素及季节性的差分自回归移动平均SARIMAX(seasonal autoregressive integrated moving average with exogenous factors)并结合优化支持向量回归SVR(support vector regression)的光伏发电功率预测方法。首先,采用相关性特征法聚类气象条件中关键气象因子,以消除数据冗余并降低ARIMAX模型的复杂性;其次,在ARIMAX模型中引入季节性因素,构建SARIMAX模型来捕捉数据的季节性变化;最后,使用SARIMAX模型的拟合残差其作为SVR模型的输入,进一步拟合数据的非线性。通过仿真算例分析表明,所提方法可显著提高光伏发电功率预测精度。展开更多
The study aims to reveal phylogenetic and evolutionary relationship between aerobic anoxygenic phototrophic bacteria（AAnPB） and their relatives,anaerobic anoxygenic phototrophic bacteria（AnAnPB） and nonphototrophi...The study aims to reveal phylogenetic and evolutionary relationship between aerobic anoxygenic phototrophic bacteria（AAnPB） and their relatives,anaerobic anoxygenic phototrophic bacteria（AnAnPB） and nonphototrophic bacteria（NPB,which had high homology of 16S rDNA gene with AAnPB and fell into the same genus）,and validate reliability and usefulness of farnesyl pyrophosphate synthase（FPPS） gene for the phylogenetic determination.FPPS genes with our modified primers and 16S rDNA genes with general primers,were amplified and sequenced or retrieved from GenBank database.In contrast to 16S rDNA gene phylogenetic tree,AAnPB were grouped into two clusters and one branch alone with no intermingling with NPB and AnAnPB in the tree constructed on FPPS.One branch of AAnPB,in both trees,was located closer to outgroup species than AnAnPB,which implicated that some AAnPB would be diverged earlier in FPPS evolutionary history than AnAnPB and NPB.Some AAnPB and NPB were closer located in both trees and this suggested that they were the closer relatives than AnAnPB.Combination codon usage in FPPS with phylogenetic analysis,the results indicates that FPPS gene and 16S rRNA gene have similar evolutionary pattern but the former seems to be more reliable and useful in determining the phylogenic and evolutionary relationship between AAnPB and their relatives.This is the first attempt to use a molecular marker beside 16S rRNA gene for studying the phylogeny of AAnPB,and the study may also be helpful in understanding the evolutionary relationship among phototrophic microbes and the trends of photosynthetic genes transfer.展开更多
The bacterial diversity and abundance in the snow of East Rongbuk glacier, Mt. Everest were examined through 16S rRNA gene clone library and flow cytometry approaches. In total, 35 16S rRNA gene sequences were obtaine...The bacterial diversity and abundance in the snow of East Rongbuk glacier, Mt. Everest were examined through 16S rRNA gene clone library and flow cytometry approaches. In total, 35 16S rRNA gene sequences were obtained, which belong to α, β, γ-Proteobacteria, Actinobacteria, Firmicutes, CFB, Cyanobacteria, Eukaryotic chloroplast, and TM7 candidate phylum respectively. γ-Proteobacteria was the dominant bacterial group in this region, while the genera Acinetobacter and Leclercia were domi- nant on the genus level. The community structure varied seasonally. The bacterial abundance in sum- mer snow was higher than that in winter. Moreover, the snow bacterial community structures in both seasons were diverse, with not only common species but season-specific species. The common species most likely originated from the Tibet Plateau. Bacteria in summer snow are affiliated with marine environ- ment, whereas bacteria in winter snow are closely related to more diverse environments and show the feature of resistance to cold. Seasonal variations of abundance and bacterial diversity were most proba- bly due to the seasonal characteristics of climate and atmospheric circulation in Mt. Everest.展开更多
Bacterial abundance in surface snow between 6600 and 8000 m a.s.l. on the northern slope of Mt. Ev- erest was investigated by flow cytometry. Bacterial diversity in serac ice at 6000 m a.s.l., glacier melt- water at 6...Bacterial abundance in surface snow between 6600 and 8000 m a.s.l. on the northern slope of Mt. Ev- erest was investigated by flow cytometry. Bacterial diversity in serac ice at 6000 m a.s.l., glacier melt- water at 6350 m, and surface snow at 6600 m a.s.l. was examined by constructing a 16S rRNA gene clone library. Bacterial abundance in snow was higher than that in the Antarctic but similar to other mountain regions in the world. Bacterial abundance in surface snow increased with altitude but showed no correlation with chemical parameters. Bacteria in the cryosphere on Mt. Everest were closely related to those isolated from soil, aquatic environments, plants, animals, humans and other frozen environ- ments. Bacterial community structures in major habitats above 6000 m were variable. The Cyto- phaga-Flavobacterium-Bacteroides (CFB) group absolutely dominated in glacial meltwater, while β-Proteobacteria and the CFB group dominated in serac ice, and β-Proteobacteria and Actinobacteria dominated in surface snow. The remarkable differences among the habitats were most likely due to the bacterial post-deposition changes during acclimation processes.展开更多
文摘为提高光伏发电功率预测精度,提出一种基于外生因素及季节性的差分自回归移动平均SARIMAX(seasonal autoregressive integrated moving average with exogenous factors)并结合优化支持向量回归SVR(support vector regression)的光伏发电功率预测方法。首先,采用相关性特征法聚类气象条件中关键气象因子,以消除数据冗余并降低ARIMAX模型的复杂性;其次,在ARIMAX模型中引入季节性因素,构建SARIMAX模型来捕捉数据的季节性变化;最后,使用SARIMAX模型的拟合残差其作为SVR模型的输入,进一步拟合数据的非线性。通过仿真算例分析表明,所提方法可显著提高光伏发电功率预测精度。
基金The National Natural Science Foundation of China under contract Nos 40232021 and 40576063
文摘The study aims to reveal phylogenetic and evolutionary relationship between aerobic anoxygenic phototrophic bacteria（AAnPB） and their relatives,anaerobic anoxygenic phototrophic bacteria（AnAnPB） and nonphototrophic bacteria（NPB,which had high homology of 16S rDNA gene with AAnPB and fell into the same genus）,and validate reliability and usefulness of farnesyl pyrophosphate synthase（FPPS） gene for the phylogenetic determination.FPPS genes with our modified primers and 16S rDNA genes with general primers,were amplified and sequenced or retrieved from GenBank database.In contrast to 16S rDNA gene phylogenetic tree,AAnPB were grouped into two clusters and one branch alone with no intermingling with NPB and AnAnPB in the tree constructed on FPPS.One branch of AAnPB,in both trees,was located closer to outgroup species than AnAnPB,which implicated that some AAnPB would be diverged earlier in FPPS evolutionary history than AnAnPB and NPB.Some AAnPB and NPB were closer located in both trees and this suggested that they were the closer relatives than AnAnPB.Combination codon usage in FPPS with phylogenetic analysis,the results indicates that FPPS gene and 16S rRNA gene have similar evolutionary pattern but the former seems to be more reliable and useful in determining the phylogenic and evolutionary relationship between AAnPB and their relatives.This is the first attempt to use a molecular marker beside 16S rRNA gene for studying the phylogeny of AAnPB,and the study may also be helpful in understanding the evolutionary relationship among phototrophic microbes and the trends of photosynthetic genes transfer.
基金This work was supported by the Ministry of Science and Technology of the People's Republic of China(Grant No.2005CB422004)the National Natural Science Foundation of China(Grant Nos.40121101&40401054)the Innovation Program of the Chinese Academy of Sciences(Grant No.KZCX3-SW-339).
文摘The bacterial diversity and abundance in the snow of East Rongbuk glacier, Mt. Everest were examined through 16S rRNA gene clone library and flow cytometry approaches. In total, 35 16S rRNA gene sequences were obtained, which belong to α, β, γ-Proteobacteria, Actinobacteria, Firmicutes, CFB, Cyanobacteria, Eukaryotic chloroplast, and TM7 candidate phylum respectively. γ-Proteobacteria was the dominant bacterial group in this region, while the genera Acinetobacter and Leclercia were domi- nant on the genus level. The community structure varied seasonally. The bacterial abundance in sum- mer snow was higher than that in winter. Moreover, the snow bacterial community structures in both seasons were diverse, with not only common species but season-specific species. The common species most likely originated from the Tibet Plateau. Bacteria in summer snow are affiliated with marine environ- ment, whereas bacteria in winter snow are closely related to more diverse environments and show the feature of resistance to cold. Seasonal variations of abundance and bacterial diversity were most proba- bly due to the seasonal characteristics of climate and atmospheric circulation in Mt. Everest.
基金Supported by the Ministry of Science and Technology of China (Grant No. 2005CB422004)the National Natural Science Foundation of China (Grant Nos. 40121101 and 40401054)+1 种基金the Innovation Program (Grant No. KZCX3-SW-339)the "Talent Project" of the Chinese Academy of Sciences, the Social Commonweal Research Project of Ministry of Science and Technology of China (2005DIA3J106)
文摘Bacterial abundance in surface snow between 6600 and 8000 m a.s.l. on the northern slope of Mt. Ev- erest was investigated by flow cytometry. Bacterial diversity in serac ice at 6000 m a.s.l., glacier melt- water at 6350 m, and surface snow at 6600 m a.s.l. was examined by constructing a 16S rRNA gene clone library. Bacterial abundance in snow was higher than that in the Antarctic but similar to other mountain regions in the world. Bacterial abundance in surface snow increased with altitude but showed no correlation with chemical parameters. Bacteria in the cryosphere on Mt. Everest were closely related to those isolated from soil, aquatic environments, plants, animals, humans and other frozen environ- ments. Bacterial community structures in major habitats above 6000 m were variable. The Cyto- phaga-Flavobacterium-Bacteroides (CFB) group absolutely dominated in glacial meltwater, while β-Proteobacteria and the CFB group dominated in serac ice, and β-Proteobacteria and Actinobacteria dominated in surface snow. The remarkable differences among the habitats were most likely due to the bacterial post-deposition changes during acclimation processes.
