Drought research requires data on precipitation and actual soil moisture of fields because precipitation is variable among years and the soil textures differ with crop fields. Measurement of soil water content in the ...Drought research requires data on precipitation and actual soil moisture of fields because precipitation is variable among years and the soil textures differ with crop fields. Measurement of soil water content in the field is simple but labor-intensive. A prototype of an automatic field data monitoring system has been recently developed to collect data more efficiently. Using this system, data of soil water contents was successfully transmitted onto the personal computer approximately 700 m away from wheat field plots, for the period from March to May which was critical for soil drying and wheat growth. In addition, sample data of soil water content and grain yield was obtained from field plots of three bread wheat genotypes.展开更多
Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. I...Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.展开更多
文摘Drought research requires data on precipitation and actual soil moisture of fields because precipitation is variable among years and the soil textures differ with crop fields. Measurement of soil water content in the field is simple but labor-intensive. A prototype of an automatic field data monitoring system has been recently developed to collect data more efficiently. Using this system, data of soil water contents was successfully transmitted onto the personal computer approximately 700 m away from wheat field plots, for the period from March to May which was critical for soil drying and wheat growth. In addition, sample data of soil water content and grain yield was obtained from field plots of three bread wheat genotypes.
基金the National Natural Science Foundation of China (Nos. 60772007 and 60672008)China Postdoctoral Sci-ence Foundation (No. 20070410258)
文摘Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.
