When running an experiment, inhomogeneity of the experimental units may result in poor estimations of treatment effects. Thus, it is desirable to select a good blocked design before running the experiment. Mostly, a s...When running an experiment, inhomogeneity of the experimental units may result in poor estimations of treatment effects. Thus, it is desirable to select a good blocked design before running the experiment. Mostly, a single block variable was used in the literature to treat the inhomogeneity for simplicity. However, in practice, the inhomogeneity often comes from multi block variables. Recently, a new criterion called B2-GMC was proposed for two-level regular designs with multi block variables. This paper proposes a systematic theory on constructing some B^2-GMC designs for the first time. Experimenters can easily obtain the B^2-GMC designs according to the construction method. Pros of B^2-GMC designs are highlighted in Section 4, and the designs with small run sizes are tabulated in Appendix B for practical use.展开更多
Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture.It helps the farmers in the optimal use of fertilizers.It reduces the cost of food production and also the n...Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture.It helps the farmers in the optimal use of fertilizers.It reduces the cost of food production and also the negative environmentalimpacts on atmosphere and water bodies due to indiscriminate dosageof fertilizers.The traditional chemical-based laboratory soil analysis methodsdo not serve the purpose as they are hardly suitable for site specific soil management.Moreover,the spectral range used in the chemical-based laboratory soil analysismay be of 350-2500 nm,which leads to redundancy and confusion.Developing sensors based on the discovery of spectral wavebands that respondto soil macronutrient concentrations,on the other hand,is an innovative and successfultechnology since the results are dependable and timely.The goal of thisarticle is to use a supervised neuro-fuzzy based dimensionality reduction approachin the sensor development process to determine sensitive wavebands of soilmacronutrients.Accordingly,the spectral signatures of the soil are collected inan outdoor environment and mapped with its macronutrient concentrations.In thisspectral analysis,the spectral reflectance of 424 wavelengths has been obtainedand these wavelengths are evaluated through combined and individual modesas well.Appropriate wavelengths are selected in each case by minimizing the fuzzy reflectance assessment index.The effectiveness of these selected wavelengthsin each mode is validated by modeling the relation between the reduced reflectancespace and each macronutrient concentration using Partial Least Squares Multi Variable Regression(PLS-MVR)method.Set of optimal wavebands areidentified and the results are compared with the existing systems.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos.11271205,11371223,11431006 and 11601244the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20130031110002+1 种基金the“131”Talents Program of Tianjinthe Program for Scientific Research Innovation Team in Applied Probability and Statistics of Qufu Normal University under Grant No.0230518
文摘When running an experiment, inhomogeneity of the experimental units may result in poor estimations of treatment effects. Thus, it is desirable to select a good blocked design before running the experiment. Mostly, a single block variable was used in the literature to treat the inhomogeneity for simplicity. However, in practice, the inhomogeneity often comes from multi block variables. Recently, a new criterion called B2-GMC was proposed for two-level regular designs with multi block variables. This paper proposes a systematic theory on constructing some B^2-GMC designs for the first time. Experimenters can easily obtain the B^2-GMC designs according to the construction method. Pros of B^2-GMC designs are highlighted in Section 4, and the designs with small run sizes are tabulated in Appendix B for practical use.
文摘Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture.It helps the farmers in the optimal use of fertilizers.It reduces the cost of food production and also the negative environmentalimpacts on atmosphere and water bodies due to indiscriminate dosageof fertilizers.The traditional chemical-based laboratory soil analysis methodsdo not serve the purpose as they are hardly suitable for site specific soil management.Moreover,the spectral range used in the chemical-based laboratory soil analysismay be of 350-2500 nm,which leads to redundancy and confusion.Developing sensors based on the discovery of spectral wavebands that respondto soil macronutrient concentrations,on the other hand,is an innovative and successfultechnology since the results are dependable and timely.The goal of thisarticle is to use a supervised neuro-fuzzy based dimensionality reduction approachin the sensor development process to determine sensitive wavebands of soilmacronutrients.Accordingly,the spectral signatures of the soil are collected inan outdoor environment and mapped with its macronutrient concentrations.In thisspectral analysis,the spectral reflectance of 424 wavelengths has been obtainedand these wavelengths are evaluated through combined and individual modesas well.Appropriate wavelengths are selected in each case by minimizing the fuzzy reflectance assessment index.The effectiveness of these selected wavelengthsin each mode is validated by modeling the relation between the reduced reflectancespace and each macronutrient concentration using Partial Least Squares Multi Variable Regression(PLS-MVR)method.Set of optimal wavebands areidentified and the results are compared with the existing systems.
