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Independent principal component analysis for simulation of soil water content and bulk density in a Canadian Watershed
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作者 Alaba Boluwade Chandra A.Madramootoo 《International Soil and Water Conservation Research》 SCIE CSCD 2016年第3期151-158,共8页
Accurate characterization of soil properties such as soil water content(SWC)and bulk density(BD)is vital for hydrologic processes and thus,it is importance to estimateθ(water content)andρ(soil bulk density)among oth... Accurate characterization of soil properties such as soil water content(SWC)and bulk density(BD)is vital for hydrologic processes and thus,it is importance to estimateθ(water content)andρ(soil bulk density)among other soil surface parameters involved in water retention and infiltration,runoff generation and water erosion,etc.The spatial estimation of these soil properties are important in guiding agricultural management decisions.These soil properties vary both in space and time and are correlated.Therefore,it is important to find an efficient and robust technique to simulate spatially correlated variables.Methods such as principal component analysis(PCA)and independent component analysis(ICA)can be used for the joint simulations of spatially correlated variables,but they are not without their flaws.This study applied a variant of PCA called independent principal component analysis(IPCA)that combines the strengths of both PCA and ICA for spatial simulation of SWC and BD using the soil data set from an 11 km^(2) Castor watershed in southern Quebec,Canada.Diagnostic checks using the histograms and cumulative distribution function(cdf)both raw and back transformed simulations show good agreement.Therefore,the results from this study has potential in characterization of water content variability and bulk density variation for precision agriculture. 展开更多
关键词 Spatial variability Soil properties Agricultural decision-making independent principal component analysis
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Preliminary application of turn-by-turn data analysis to the SSRF storage ring
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作者 陈建辉 赵振堂 《Chinese Physics C》 SCIE CAS CSCD 2009年第7期590-593,共4页
There is growing interest in utilizing the beam position monitor turn-by-turn(TBT) data to debug accelerators. TBT data can be used to determine the linear optics,coupled optics and nonlinear behaviors of the storag... There is growing interest in utilizing the beam position monitor turn-by-turn(TBT) data to debug accelerators. TBT data can be used to determine the linear optics,coupled optics and nonlinear behaviors of the storage ring lattice. This is not only a useful complement to other methods of determining the linear optics such as LOCO,but also provides a possibility to uncover more hidden phenomena. In this paper,a preliminary application of a β function measurement to the SSRF storage ring is presented. 展开更多
关键词 beam position monitor turn-by-turn model independent analysis principal component analysis independent component analysis
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