How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image re...How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.展开更多
Compared to 3D object detection using a single camera,multiple cameras can overcome some limitations on field-of-view,occlusion,and low detection confidence.This study employs multiple surveillance cameras and develop...Compared to 3D object detection using a single camera,multiple cameras can overcome some limitations on field-of-view,occlusion,and low detection confidence.This study employs multiple surveillance cameras and develops a cooperative 3D object detection and tracking framework by incorporating temporal and spatial information.The framework consists of a 3D vehicle detection model,cooperatively spatial-temporal relation scheme,and heuristic camera constellation method.Specifically,the proposed cross-camera association scheme combines the geometric relationship between multiple cameras and objects in corresponding detections.The spatial-temporal method is designed to associate vehicles between different points of view at a single timestamp and fulfill vehicle tracking in the time aspect.The proposed framework is evaluated based on a synthetic cooperative dataset and shows high reliability,where the cooperative perception can recall more than 66%of the trajectory instead of 11%for single-point sensing.This could contribute to full-range surveillance for intelligent transportation systems.展开更多
The problem of interval correlation results in interval extension is discussed by the relationship of interval-valued functions and real-valued functions. The methods of reducing interval extension are given. Based on...The problem of interval correlation results in interval extension is discussed by the relationship of interval-valued functions and real-valued functions. The methods of reducing interval extension are given. Based on the ideas of the paper, the formulas of sub-interval perturbed finite element method based on the elements are given. The sub-interval amount is discussed and the approximate computation formula is given. At the same time, the computational precision is discussed and some measures of improving computational efficiency are given. Finally, based on sub-interval perturbed finite element method and anti-slide stability analysis method, the formula for computing the bounds of stability factor is given. It provides a basis for estimating and evaluating reasonably anti-slide stability of structures.展开更多
Scenario forecasting methods have been widely studied in recent years to cope with the wind power uncertainty problem. The main difficulty of this problem is to accurately and comprehensively reflect the time-series c...Scenario forecasting methods have been widely studied in recent years to cope with the wind power uncertainty problem. The main difficulty of this problem is to accurately and comprehensively reflect the time-series characteristics and spatial-temporal correlation of wind power generation. In this paper, the marginal distribution model and the dependence structure are combined to describe these complex characteristics. On this basis, a scenario generation method for multiple wind farms is proposed. For the marginal distribution model, the autoregressive integrated moving average-generalized autoregressive conditional heteroskedasticity-t (ARIMA-GARCH-t) model is proposed to capture the time-series characteristics of wind power generation. For the dependence structure, a time-varying regular vine mixed Copula (TRVMC) model is established to capture the spatial-temporal correlation of multiple wind farms. Based on the data from 8 wind farms in Northwest China, sufficient scenarios are generated. The effectiveness of the scenarios is evaluated in 3 aspects. The results show that the generated scenarios have similar fluctuation characteristics, autocorrelation, and crosscorrelation with the actual wind power sequences.展开更多
丰富的历史风速数据是开展海岛微电网规划工作的前提。为此,针对待规划海岛无历史风速数据的问题,提出了一种利用周边海岛风速时空相关性估计目标海岛长期风速序列的方法。首先,结合滑动窗和云模型,自适应划分周边海岛风速序列的时序区...丰富的历史风速数据是开展海岛微电网规划工作的前提。为此,针对待规划海岛无历史风速数据的问题,提出了一种利用周边海岛风速时空相关性估计目标海岛长期风速序列的方法。首先,结合滑动窗和云模型,自适应划分周边海岛风速序列的时序区间;其次,根据各时序区间内风速云模型数字特征的余弦相似度,匹配周边海岛各分段风速序列间的相似性转移关系(similarity transfer relationship,STR);最后,考虑STR与海岛空间位置关系,以权重表示各STR对目标海岛风速序列估计的影响,进而依据各STR及其权重估计目标海岛的长期风速序列。研究结果表明:相较于利用皮尔逊相关系数(Pearson correlation coefficient,PCC)计算各天风速序列间的相关性,进而估计海岛长期风速序列的方法,使用所提方法得到的估计结果与实际序列间的平均绝对误差、均方根误差和PCC分别约改善了7.31%、17.98%和0.46%,所提方法能够实现较高准确度的海岛长期风速序列估计。论文研究可为历史风速数据缺失情况下开展海岛风速预测工作提供参考。展开更多
In order to relate the design and analysis of an optical pattern recognition system with the structural parameters, only by introducing the prolate spheroidal wave function (PSWF) can the amount of information be comp...In order to relate the design and analysis of an optical pattern recognition system with the structural parameters, only by introducing the prolate spheroidal wave function (PSWF) can the amount of information be computed. Combining the imaging wave function set {ψi(x)} and distorted wave function set {b_i(p)} and two integral equations they satisfy derives the expression of the amount of information. The design method of matched filter connected with its amount of information is studied, and their amounts of information belonging to different pattern recognition systems are illustrated. It can be seen that the difference of the amounts of information for various systems is obvious.展开更多
The influence of vessel attitude on spatial-temporal correlation of sea-bottom re- verberation is discussed. The theoretical correlation function is deduced in consideration of the attitude of vessel. The relationship...The influence of vessel attitude on spatial-temporal correlation of sea-bottom re- verberation is discussed. The theoretical correlation function is deduced in consideration of the attitude of vessel. The relationship of the spatial-temporal correlation and the vessel attitude is obtained： The greater the sway of the vessel on some direction is, the faster the correlation coefficient decreases on the direction. The theoretical correlation function agrees well with the simulation result when sea-bottom has no large-scale relief but has isotropic roughness. The actual sea-bottom usually has large-scale relief and anisotropic roughness, so the vessel attitude and the large-scale relief cannot determine the shape of the correlation function, but trial data has proved their combined influence. In addition, the influence of the vessel attitude on the measurement of vertical velocity is discussed.展开更多
文摘How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.
基金the National Natural Science Foundation of China(No.61873167)the Automotive Industry Science and Technology Development Foundation of Shanghai(No.1904)。
文摘Compared to 3D object detection using a single camera,multiple cameras can overcome some limitations on field-of-view,occlusion,and low detection confidence.This study employs multiple surveillance cameras and develops a cooperative 3D object detection and tracking framework by incorporating temporal and spatial information.The framework consists of a 3D vehicle detection model,cooperatively spatial-temporal relation scheme,and heuristic camera constellation method.Specifically,the proposed cross-camera association scheme combines the geometric relationship between multiple cameras and objects in corresponding detections.The spatial-temporal method is designed to associate vehicles between different points of view at a single timestamp and fulfill vehicle tracking in the time aspect.The proposed framework is evaluated based on a synthetic cooperative dataset and shows high reliability,where the cooperative perception can recall more than 66%of the trajectory instead of 11%for single-point sensing.This could contribute to full-range surveillance for intelligent transportation systems.
文摘The problem of interval correlation results in interval extension is discussed by the relationship of interval-valued functions and real-valued functions. The methods of reducing interval extension are given. Based on the ideas of the paper, the formulas of sub-interval perturbed finite element method based on the elements are given. The sub-interval amount is discussed and the approximate computation formula is given. At the same time, the computational precision is discussed and some measures of improving computational efficiency are given. Finally, based on sub-interval perturbed finite element method and anti-slide stability analysis method, the formula for computing the bounds of stability factor is given. It provides a basis for estimating and evaluating reasonably anti-slide stability of structures.
基金This work was supported by the National Key Research and Development Program of China(No.2017YFB0902600).
文摘Scenario forecasting methods have been widely studied in recent years to cope with the wind power uncertainty problem. The main difficulty of this problem is to accurately and comprehensively reflect the time-series characteristics and spatial-temporal correlation of wind power generation. In this paper, the marginal distribution model and the dependence structure are combined to describe these complex characteristics. On this basis, a scenario generation method for multiple wind farms is proposed. For the marginal distribution model, the autoregressive integrated moving average-generalized autoregressive conditional heteroskedasticity-t (ARIMA-GARCH-t) model is proposed to capture the time-series characteristics of wind power generation. For the dependence structure, a time-varying regular vine mixed Copula (TRVMC) model is established to capture the spatial-temporal correlation of multiple wind farms. Based on the data from 8 wind farms in Northwest China, sufficient scenarios are generated. The effectiveness of the scenarios is evaluated in 3 aspects. The results show that the generated scenarios have similar fluctuation characteristics, autocorrelation, and crosscorrelation with the actual wind power sequences.
文摘丰富的历史风速数据是开展海岛微电网规划工作的前提。为此,针对待规划海岛无历史风速数据的问题,提出了一种利用周边海岛风速时空相关性估计目标海岛长期风速序列的方法。首先,结合滑动窗和云模型,自适应划分周边海岛风速序列的时序区间;其次,根据各时序区间内风速云模型数字特征的余弦相似度,匹配周边海岛各分段风速序列间的相似性转移关系(similarity transfer relationship,STR);最后,考虑STR与海岛空间位置关系,以权重表示各STR对目标海岛风速序列估计的影响,进而依据各STR及其权重估计目标海岛的长期风速序列。研究结果表明:相较于利用皮尔逊相关系数(Pearson correlation coefficient,PCC)计算各天风速序列间的相关性,进而估计海岛长期风速序列的方法,使用所提方法得到的估计结果与实际序列间的平均绝对误差、均方根误差和PCC分别约改善了7.31%、17.98%和0.46%,所提方法能够实现较高准确度的海岛长期风速序列估计。论文研究可为历史风速数据缺失情况下开展海岛风速预测工作提供参考。
基金Project supported by the National Natural Science Foundation of China.
文摘In order to relate the design and analysis of an optical pattern recognition system with the structural parameters, only by introducing the prolate spheroidal wave function (PSWF) can the amount of information be computed. Combining the imaging wave function set {ψi(x)} and distorted wave function set {b_i(p)} and two integral equations they satisfy derives the expression of the amount of information. The design method of matched filter connected with its amount of information is studied, and their amounts of information belonging to different pattern recognition systems are illustrated. It can be seen that the difference of the amounts of information for various systems is obvious.
文摘The influence of vessel attitude on spatial-temporal correlation of sea-bottom re- verberation is discussed. The theoretical correlation function is deduced in consideration of the attitude of vessel. The relationship of the spatial-temporal correlation and the vessel attitude is obtained： The greater the sway of the vessel on some direction is, the faster the correlation coefficient decreases on the direction. The theoretical correlation function agrees well with the simulation result when sea-bottom has no large-scale relief but has isotropic roughness. The actual sea-bottom usually has large-scale relief and anisotropic roughness, so the vessel attitude and the large-scale relief cannot determine the shape of the correlation function, but trial data has proved their combined influence. In addition, the influence of the vessel attitude on the measurement of vertical velocity is discussed.
