This paper presents an interval effective independence method for optimal sensor placement, which contains uncertain structural information. To overcome the lack of insufficient statistic description of uncertain para...This paper presents an interval effective independence method for optimal sensor placement, which contains uncertain structural information. To overcome the lack of insufficient statistic description of uncertain parameters, this paper treats uncertainties as non-probability intervals. Based on the iterative process of classical effective independence method, the proposed study considers the eliminating steps with uncertain cases. Therefore, this method with Fisher information matrix is extended to interval numbers, which could conform to actual engineering. As long as we know the bounds of uncertainties, the interval Fisher information matrix could be obtained conveniently by interval analysis technology. Moreover, due to the definition and calculation of the interval relationship, the possibilities of eliminating candidate sensors in each iterative process and the final layout of sensor placement are both presented in this paper. Finally, two numerical examples, including a five-storey shear structure and a truss structure are proposed respectively in this paper. Compared with Monte Carlo simulation, both of them can indicate the veracity of the interval effective independence method.展开更多
It seems that an effective way of how to make the right choice of Various investment projects is based on the theory of average internal income rate, or the theory of weight-added internal income rate. With several ex...It seems that an effective way of how to make the right choice of Various investment projects is based on the theory of average internal income rate, or the theory of weight-added internal income rate. With several examples of numerical value, this paper proves that this method is not as effective as expected, but indirectly testifies that only with the principle of maximization of NPV that independent projects can be the best combination of projects with limited investment that is achieved.展开更多
The wheat canopy reflectance spectrum is affected by many internal and external factors such as diseases and growth stage. Separating the effects of disease stress on the crop from the observed mixed signals is crucia...The wheat canopy reflectance spectrum is affected by many internal and external factors such as diseases and growth stage. Separating the effects of disease stress on the crop from the observed mixed signals is crucial for increasing the precision of remote sensing monitoring of wheat stripe rust. The canopy spectrum of winter wheat infected by stripe rust was processed with the difference-in-differences(DID) algorithm used in econometrics. The monitoring accuracies of wheat stripe rust before and after processing with the DID algorithm were compared in the presence of various external factors, disease severity, and several simulated satellite sensors. The correlation between the normalized difference vegetation index processed by the DID algorithm(NDVI-DID) and the disease severity level(SL) increased in comparison with the NDVI before processing. The increase in precision in the natural disease area in the field in the presence of large differences in growth stage, growth, planting, and management of the crop was greater than that in the controlled experiment. For low disease levels(SL < 20%), the R2 of the regression of NDVI-DIDon SL was 38.8% higher than that of the NDVI and the root mean square error(RMSE) was reduced by 11.1%. The increase in precision was greater than that for the severe level(SL > 40%).According to the measured hyperspectral data, the spectral reflectance of three satellite sensor levels was simulated. The wide-band NDVI was calculated. Compared with the wide-band NDVI and vegetation indexes(VI) before DID processing, there were increases in the correlation between SL and the various types of VIS-DID, as well as in the correlation between SL and NDVI-DID. It is feasible to apply the DID algorithm to multispectral satellite data and diverse types of VISfor monitoring wheat stripe rust. Our results improve the quantification of independent effects of stripe rust infection on canopy reflectance spectrum,increase the precision of remote sensing monitoring of wheat stripe rust, and provide a reference for remote sensing monitoring of other crop diseases.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11502278)
文摘This paper presents an interval effective independence method for optimal sensor placement, which contains uncertain structural information. To overcome the lack of insufficient statistic description of uncertain parameters, this paper treats uncertainties as non-probability intervals. Based on the iterative process of classical effective independence method, the proposed study considers the eliminating steps with uncertain cases. Therefore, this method with Fisher information matrix is extended to interval numbers, which could conform to actual engineering. As long as we know the bounds of uncertainties, the interval Fisher information matrix could be obtained conveniently by interval analysis technology. Moreover, due to the definition and calculation of the interval relationship, the possibilities of eliminating candidate sensors in each iterative process and the final layout of sensor placement are both presented in this paper. Finally, two numerical examples, including a five-storey shear structure and a truss structure are proposed respectively in this paper. Compared with Monte Carlo simulation, both of them can indicate the veracity of the interval effective independence method.
文摘It seems that an effective way of how to make the right choice of Various investment projects is based on the theory of average internal income rate, or the theory of weight-added internal income rate. With several examples of numerical value, this paper proves that this method is not as effective as expected, but indirectly testifies that only with the principle of maximization of NPV that independent projects can be the best combination of projects with limited investment that is achieved.
基金supported by the National Natural Science Foundation of China (42171394, 41601467)。
文摘The wheat canopy reflectance spectrum is affected by many internal and external factors such as diseases and growth stage. Separating the effects of disease stress on the crop from the observed mixed signals is crucial for increasing the precision of remote sensing monitoring of wheat stripe rust. The canopy spectrum of winter wheat infected by stripe rust was processed with the difference-in-differences(DID) algorithm used in econometrics. The monitoring accuracies of wheat stripe rust before and after processing with the DID algorithm were compared in the presence of various external factors, disease severity, and several simulated satellite sensors. The correlation between the normalized difference vegetation index processed by the DID algorithm(NDVI-DID) and the disease severity level(SL) increased in comparison with the NDVI before processing. The increase in precision in the natural disease area in the field in the presence of large differences in growth stage, growth, planting, and management of the crop was greater than that in the controlled experiment. For low disease levels(SL < 20%), the R2 of the regression of NDVI-DIDon SL was 38.8% higher than that of the NDVI and the root mean square error(RMSE) was reduced by 11.1%. The increase in precision was greater than that for the severe level(SL > 40%).According to the measured hyperspectral data, the spectral reflectance of three satellite sensor levels was simulated. The wide-band NDVI was calculated. Compared with the wide-band NDVI and vegetation indexes(VI) before DID processing, there were increases in the correlation between SL and the various types of VIS-DID, as well as in the correlation between SL and NDVI-DID. It is feasible to apply the DID algorithm to multispectral satellite data and diverse types of VISfor monitoring wheat stripe rust. Our results improve the quantification of independent effects of stripe rust infection on canopy reflectance spectrum,increase the precision of remote sensing monitoring of wheat stripe rust, and provide a reference for remote sensing monitoring of other crop diseases.
