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
Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencie...Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencies in ABC regarding its local search ability and global search efficiency. Aiming at these deficiencies,an ABC variant named hybrid ABC(HABC) algorithm is proposed.Firstly, the variable neighborhood search factor is added to the solution search equation, which can enhance the local search ability and increase the population diversity. Secondly, inspired by the neuroscience investigation of real honeybees, the memory mechanism is put forward, which assumes the artificial bees can remember their past successful experiences and further guide the subsequent foraging behavior. The proposed memory mechanism is used to improve the global search efficiency. Finally, the results of comparison on a set of ten benchmark functions demonstrate the superiority of HABC.展开更多
A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely no...A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely not all jobs can be scheduled within specified scheduling horizons due to the limited machine capacity. The objective is thus to maximize the overall profits of processed jobs while respecting machine constraints. A first-in- first-out heuristic is applied to find an initial solution, and then a large neighborhood search procedure is employed to relax and re- optimize cumbersome solutions. A machine learning mechanism is also introduced to converge on the most efficient neighborhoods for the problem. Extensive computational results are presented based on data from an application involving the daily observation scheduling of a fleet of earth observing satellites. The method rapidly solves most problem instances to optimal or near optimal and shows a robust performance in sensitive analysis.展开更多
This paper presents a neighborhood optimal trajectory online correction algorithm considering terminal time variation,and investigates its application range.Firstly,the motion model of midcourse guidance is establishe...This paper presents a neighborhood optimal trajectory online correction algorithm considering terminal time variation,and investigates its application range.Firstly,the motion model of midcourse guidance is established,and the online trajectory correction-regenerating strategy is introduced.Secondly,based on the neighborhood optimal control theory,a neighborhood optimal trajectory online correction algorithm considering the terminal time variation is proposed by adding the consideration of terminal time variation to the traditional neighborhood optimal trajectory correction method.Thirdly,the Monte Carlo simulation method is used to analyze the application range of the algorithm,which provides a basis for the division of application domain of the online correction algorithm and the online regeneration algorithm of midcourse guidance trajectory.Finally,the simulation results show that the algorithm has high real-time performance,and the online correction trajectory can meet the requirements of terminal constraint change.The application range of the algorithm is obtained through Monte Carlo simulation.展开更多
The neighborhood center provides an implementation case for centralizing community service facilities and organizing service provision effectively,and has achieved community service improvement,which provides innovati...The neighborhood center provides an implementation case for centralizing community service facilities and organizing service provision effectively,and has achieved community service improvement,which provides innovative methods for governance innovation.This paper summarizes the development process of neighborhood center planning in China,and analyzes related planning cases in Suzhou,Tianjin,Hangzhou,and Chengdu focusing on planning characteristics and operating mechanisms.Based on the case of Chongqing,it gives answer to key issues of the local application of neighborhood center planning concept.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supported by the National Natural Science Foundation of China(7177121671701209)
文摘Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencies in ABC regarding its local search ability and global search efficiency. Aiming at these deficiencies,an ABC variant named hybrid ABC(HABC) algorithm is proposed.Firstly, the variable neighborhood search factor is added to the solution search equation, which can enhance the local search ability and increase the population diversity. Secondly, inspired by the neuroscience investigation of real honeybees, the memory mechanism is put forward, which assumes the artificial bees can remember their past successful experiences and further guide the subsequent foraging behavior. The proposed memory mechanism is used to improve the global search efficiency. Finally, the results of comparison on a set of ten benchmark functions demonstrate the superiority of HABC.
基金supported by the National Natural Science Foundation of China (7060103570801062)
文摘A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely not all jobs can be scheduled within specified scheduling horizons due to the limited machine capacity. The objective is thus to maximize the overall profits of processed jobs while respecting machine constraints. A first-in- first-out heuristic is applied to find an initial solution, and then a large neighborhood search procedure is employed to relax and re- optimize cumbersome solutions. A machine learning mechanism is also introduced to converge on the most efficient neighborhoods for the problem. Extensive computational results are presented based on data from an application involving the daily observation scheduling of a fleet of earth observing satellites. The method rapidly solves most problem instances to optimal or near optimal and shows a robust performance in sensitive analysis.
基金supported by the National Natural Science Foundation of China(61873278,62173339)。
文摘This paper presents a neighborhood optimal trajectory online correction algorithm considering terminal time variation,and investigates its application range.Firstly,the motion model of midcourse guidance is established,and the online trajectory correction-regenerating strategy is introduced.Secondly,based on the neighborhood optimal control theory,a neighborhood optimal trajectory online correction algorithm considering the terminal time variation is proposed by adding the consideration of terminal time variation to the traditional neighborhood optimal trajectory correction method.Thirdly,the Monte Carlo simulation method is used to analyze the application range of the algorithm,which provides a basis for the division of application domain of the online correction algorithm and the online regeneration algorithm of midcourse guidance trajectory.Finally,the simulation results show that the algorithm has high real-time performance,and the online correction trajectory can meet the requirements of terminal constraint change.The application range of the algorithm is obtained through Monte Carlo simulation.
基金based on the project of“The Study of Neighborhood Center Planning in Cuiyun District,Yubei District,Chongqing(2018)”,whose research work is undertaken by Chongqing Universitysupported by the National Natural Science Foundation of China(Grant No.51778078)
文摘The neighborhood center provides an implementation case for centralizing community service facilities and organizing service provision effectively,and has achieved community service improvement,which provides innovative methods for governance innovation.This paper summarizes the development process of neighborhood center planning in China,and analyzes related planning cases in Suzhou,Tianjin,Hangzhou,and Chengdu focusing on planning characteristics and operating mechanisms.Based on the case of Chongqing,it gives answer to key issues of the local application of neighborhood center planning concept.
