We proposed an enhanced image binarization method.The proposed solution incorporates Monte-Carlo simulation into the local thresholding method to address the essential issues with respect to complex background,spatial...We proposed an enhanced image binarization method.The proposed solution incorporates Monte-Carlo simulation into the local thresholding method to address the essential issues with respect to complex background,spatially-changed illumination,and uncertainties of block size in traditional method.The proposed method first partitions the image into square blocks that reflect local characteristics of the image.After image partitioning,each block is binarized using Otsu’s thresholding method.To minimize the influence of the block size and the boundary effect,we incorporate Monte-Carlo simulation into the binarization algorithm.Iterative calculation with varying block sizes during Monte-Carlo simulation generates a probability map,which illustrates the probability of each pixel classified as foreground.By setting a probability threshold,and separating foreground and background of the source image,the final binary image can be obtained.The described method has been tested by benchmark tests.Results demonstrate that the proposed method performs well in dealing with the complex background and illumination condition.展开更多
An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited i...An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.展开更多
The present research relies on a cascade control approach through the Monte-Carlo based method in the presence of uncertainties to evaluate the performance of the real overactuated space systems.A number of potential ...The present research relies on a cascade control approach through the Monte-Carlo based method in the presence of uncertainties to evaluate the performance of the real overactuated space systems.A number of potential investigations in this area are first considered to prepare an idea with respect to state-of-the-art.The insight proposed here is organized to present attitude cascade control approach including the low thrust in connection with the high thrust to be implemented,while the aforementioned Monte-Carlo based method is carried out to guarantee the approach performance.It is noted that the investigated outcomes are efficient to handle a class of space systems presented via the center of mass and the moments of inertial.And also a number of profiles for the thrust vector and the misalignments as the disturbances all vary in its span of nominal variations.The acquired results are finally analyzed in line with some well-known benchmarks to verify the approach efficiency.The key core of finding in the research is to propose a novel 3-axis control approach to deal with all the mentioned uncertainties of space systems under control,in a synchronous manner,as long as the appropriate models in the low-high thrusts are realized.展开更多
A modified discontinuous deformation analysis (DDA) algorithm was proposed to simulate the failure behavior of jointed rock. In the proposed algorithm, by using the Monte-Carlo technique, random joint network was gene...A modified discontinuous deformation analysis (DDA) algorithm was proposed to simulate the failure behavior of jointed rock. In the proposed algorithm, by using the Monte-Carlo technique, random joint network was generated in the domain of interest. Based on the joint network, the triangular DDA block system was automatically generated by adopting the advanced front method. In the process of generating blocks, numerous artificial joints came into being, and once the stress states at some artificial joints satisfy the failure criterion given beforehand, artificial joints will turn into real joints. In this way, the whole fragmentation process of rock mass can be replicated. The algorithm logic was described in detail, and several numerical examples were carried out to obtain some insight into the failure behavior of rock mass containing random joints. From the numerical results, it can be found that the crack initiates from the crack tip, the growth direction of the crack depends upon the loading and constraint conditions, and the proposed method can reproduce some complicated phenomena in the whole process of rock failure.展开更多
基金Project(2018YFC1505401)supported by the National Key R&D Program of ChinaProject(41702310)supported by the National Natural Science Foundation of China+1 种基金Project(SKLGP2017K014)supported by the Foundation of State Key Laboratory of Geohazard Prevention and Geo-environment Protection,ChinaProject(2018JJ3644)supported by the Natural Science Foundation of Hunan Province,China
文摘We proposed an enhanced image binarization method.The proposed solution incorporates Monte-Carlo simulation into the local thresholding method to address the essential issues with respect to complex background,spatially-changed illumination,and uncertainties of block size in traditional method.The proposed method first partitions the image into square blocks that reflect local characteristics of the image.After image partitioning,each block is binarized using Otsu’s thresholding method.To minimize the influence of the block size and the boundary effect,we incorporate Monte-Carlo simulation into the binarization algorithm.Iterative calculation with varying block sizes during Monte-Carlo simulation generates a probability map,which illustrates the probability of each pixel classified as foreground.By setting a probability threshold,and separating foreground and background of the source image,the final binary image can be obtained.The described method has been tested by benchmark tests.Results demonstrate that the proposed method performs well in dealing with the complex background and illumination condition.
基金Project(51606225) supported by the National Natural Science Foundation of ChinaProject(2016JJ2144) supported by Hunan Provincial Natural Science Foundation of ChinaProject(502221703) supported by Graduate Independent Explorative Innovation Foundation of Central South University,China
文摘An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.
文摘The present research relies on a cascade control approach through the Monte-Carlo based method in the presence of uncertainties to evaluate the performance of the real overactuated space systems.A number of potential investigations in this area are first considered to prepare an idea with respect to state-of-the-art.The insight proposed here is organized to present attitude cascade control approach including the low thrust in connection with the high thrust to be implemented,while the aforementioned Monte-Carlo based method is carried out to guarantee the approach performance.It is noted that the investigated outcomes are efficient to handle a class of space systems presented via the center of mass and the moments of inertial.And also a number of profiles for the thrust vector and the misalignments as the disturbances all vary in its span of nominal variations.The acquired results are finally analyzed in line with some well-known benchmarks to verify the approach efficiency.The key core of finding in the research is to propose a novel 3-axis control approach to deal with all the mentioned uncertainties of space systems under control,in a synchronous manner,as long as the appropriate models in the low-high thrusts are realized.
基金Projects(50479071, 40672191) supported by the National Natural Science Foundation of ChinaProject(SKLZ0801) supported by the Independent Research Key Project of State Key Laboratory of Geomechanics and Geotechnical EngineeringProject(SKLQ001) supported by the Independent Research Frontier Exploring Project of State Key Laboratory of Geomechanics and Geotechnical Engineering
文摘A modified discontinuous deformation analysis (DDA) algorithm was proposed to simulate the failure behavior of jointed rock. In the proposed algorithm, by using the Monte-Carlo technique, random joint network was generated in the domain of interest. Based on the joint network, the triangular DDA block system was automatically generated by adopting the advanced front method. In the process of generating blocks, numerous artificial joints came into being, and once the stress states at some artificial joints satisfy the failure criterion given beforehand, artificial joints will turn into real joints. In this way, the whole fragmentation process of rock mass can be replicated. The algorithm logic was described in detail, and several numerical examples were carried out to obtain some insight into the failure behavior of rock mass containing random joints. From the numerical results, it can be found that the crack initiates from the crack tip, the growth direction of the crack depends upon the loading and constraint conditions, and the proposed method can reproduce some complicated phenomena in the whole process of rock failure.
