In this paper, we introduce the A, weights into the tent space, many important results in the tent space are generalized. Also, new relations between the A, weights and Carleson measures are obtained.
To reduce the dependence of EM inversion on the choice of initial model and to obtain the global minimum, we apply transdimensional Bayesian inversion to time-domain airborne electromagnetic data. The transdimensional...To reduce the dependence of EM inversion on the choice of initial model and to obtain the global minimum, we apply transdimensional Bayesian inversion to time-domain airborne electromagnetic data. The transdimensional Bayesian inversion uses the Monte Carlo method to search the model space and yields models that simultaneously satisfy the acceptance probability and data fitting requirements. Finally, we obtain the probability distribution and uncertainty of the model parameters as well as the maximum probability. Because it is difficult to know the height of the transmitting source during flight, we consider a fixed and a variable flight height. Furthermore, we introduce weights into the prior probability density function of the resistivity and adjust the constraint strength in the inversion model by changing the weighing coefficients. This effectively solves the problem of unsatisfactory inversion results in the middle high-resistivity layer. We validate the proposed method by inverting synthetic data with 3% Gaussian noise and field survey data.展开更多
Both opportunities and challenges are currently faced by government management innovation in the age of ＂big data＂. Traditionally, relative studies view the management of governments as the effective means to improv...Both opportunities and challenges are currently faced by government management innovation in the age of ＂big data＂. Traditionally, relative studies view the management of governments as the effective means to improve governmental services, without really understanding the structural influence of big data and network technology on governmental mode of thinking. Against such backdrop, this paper tries to conduct critical analysis based upon traditional outcomes in this regard, trying to make full use of the function of big data technology. With these efforts, this paper contributes to the building of an interaction theory that could promote transparency of information and customization and segmentation of the policies. By constructing a mode in which management could be carried out based on the law of big data, by building an information management system in which balance could be achieved between responsibility and freedom, by promoting the rebalancing among public power, online civil society and civil rights, the innovation of governmental management would be achieved.展开更多
文摘In this paper, we introduce the A, weights into the tent space, many important results in the tent space are generalized. Also, new relations between the A, weights and Carleson measures are obtained.
基金This paper was financially supported by the Key National Research Project of China （Nos. 2017YFC0601900 and 2016YFC0303100）, and the Key Program of National Natural Science Foundation of China （No. 41530320） and Surface Project （No. 41774125）.
文摘To reduce the dependence of EM inversion on the choice of initial model and to obtain the global minimum, we apply transdimensional Bayesian inversion to time-domain airborne electromagnetic data. The transdimensional Bayesian inversion uses the Monte Carlo method to search the model space and yields models that simultaneously satisfy the acceptance probability and data fitting requirements. Finally, we obtain the probability distribution and uncertainty of the model parameters as well as the maximum probability. Because it is difficult to know the height of the transmitting source during flight, we consider a fixed and a variable flight height. Furthermore, we introduce weights into the prior probability density function of the resistivity and adjust the constraint strength in the inversion model by changing the weighing coefficients. This effectively solves the problem of unsatisfactory inversion results in the middle high-resistivity layer. We validate the proposed method by inverting synthetic data with 3% Gaussian noise and field survey data.
文摘Both opportunities and challenges are currently faced by government management innovation in the age of ＂big data＂. Traditionally, relative studies view the management of governments as the effective means to improve governmental services, without really understanding the structural influence of big data and network technology on governmental mode of thinking. Against such backdrop, this paper tries to conduct critical analysis based upon traditional outcomes in this regard, trying to make full use of the function of big data technology. With these efforts, this paper contributes to the building of an interaction theory that could promote transparency of information and customization and segmentation of the policies. By constructing a mode in which management could be carried out based on the law of big data, by building an information management system in which balance could be achieved between responsibility and freedom, by promoting the rebalancing among public power, online civil society and civil rights, the innovation of governmental management would be achieved.
