In this paper, we propose an efficient algorithm, called FFP-Growth (shortfor fast FP-Growth) , to mine frequent itemsets. Similar to FP-Growth, FFP-Growth searches theFP-tree in the bottom-up order, but need not cons...In this paper, we propose an efficient algorithm, called FFP-Growth (shortfor fast FP-Growth) , to mine frequent itemsets. Similar to FP-Growth, FFP-Growth searches theFP-tree in the bottom-up order, but need not construct conditional pattern bases and sub-FP-trees,thus, saving a substantial amount of time and space, and the FP-tree created by it is much smallerthan that created by TD-FP-Growth, hence improving efficiency. At the same time, FFP-Growth can beeasily extended for reducing the search space as TD-FP-Growth (M) and TD-FP-Growth (C). Experimentalresults show that the algorithm of this paper is effective and efficient.展开更多
A new algorithm based on an FC-tree （frequent closed pattern tree） and a max-FCIA （maximal frequent closed itemsets algorithm） is presented, which is used to mine the frequent closed itemsets for solving memory an...A new algorithm based on an FC-tree （frequent closed pattern tree） and a max-FCIA （maximal frequent closed itemsets algorithm） is presented, which is used to mine the frequent closed itemsets for solving memory and time consuming problems. This algorithm maps the transaction database by using a Hash table,gets the support of all frequent itemsets through operating the Hash table and forms a lexicographic subset tree including the frequent itemsets.Efficient pruning methods are used to get the FC-tree including all the minimum frequent closed itemsets through processing the lexicographic subset tree.Finally,frequent closed itemsets are generated from minimum frequent closed itemsets.The experimental results show that the mapping transaction database is introduced in the algorithm to reduce time consumption and to improve the efficiency of the program.Furthermore,the effective pruning strategy restrains the number of candidates,which saves space.The results show that the algorithm is effective.展开更多
The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system perf...The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.展开更多
The presently existing decision making method for problem of goal type, i.e. the goal programming, is popular to some extent. In this paper we analyzed the features of the problem and the method,based on which we foun...The presently existing decision making method for problem of goal type, i.e. the goal programming, is popular to some extent. In this paper we analyzed the features of the problem and the method,based on which we found some defects of the method and pointed out these defects. To overcome these defects we absorbed the spirit and exploited concepts of evaluation criterion and the fault measure of evaluation criterion. We proposed and applied a method with an evaluation criterion, after which we also p...展开更多
A class of interactive multi objective decision making method by means of evaluation criterion is proposed for problems with linear value function,in which case,the decision maker(DM) usually has only unwhole infor...A class of interactive multi objective decision making method by means of evaluation criterion is proposed for problems with linear value function,in which case,the decision maker(DM) usually has only unwhole information of weights for objectives. The concept of fault measure of the evaluation criterion is proposed to measure the deviation of the evaluation criterion from the DMs preference structure.The approach to obtain an upper boundary of fault measure of an evaluation criterion,and the approach to modify the evaluation criterion to be one with smaller fault measure,and the approach to obtain a pre optimized objective set by evaluation criterion with certain fault measure are also proposed.展开更多
Seismic imaging quality is critical to describing reservoirs. There are many methods that can improve imaging quality; some rely on advanced processing means, whereas others rely on changing the field acquisition meth...Seismic imaging quality is critical to describing reservoirs. There are many methods that can improve imaging quality; some rely on advanced processing means, whereas others rely on changing the field acquisition methods. However, most of the acquisition methods focus on improving imaging by using infill shots without considering the target-layer illumination energy. Moreover, total infill shooting greatly increases the acquisition cost. In this paper, we present a new method for maximizing the contribution to the target shadow area illumination by automatic local infill shooting. Thus, we designed 2D and 3D models and obtained the depth migration section by forward modeling, infill shots, depth migration, etc. The model results also show that by choosing the most appropriate number of shot points, we can enhance the shadow area energy and improve the target-layer imaging quality at low cost.展开更多
In this paper,we propose a hybrid algorithm for finding a set of non dominated solutions of a multi objective optimization problem.In the proposed algorithm,a local search procedure is applied to each solution gener...In this paper,we propose a hybrid algorithm for finding a set of non dominated solutions of a multi objective optimization problem.In the proposed algorithm,a local search procedure is applied to each solution generated by genetic operations.The aim of the proposed algorithm is not to determine a single final solution but to try to find all the non dominated solutions of a multi objective optimization problem.The choice of the final solution is left to the decision makers preference.High search ability of the proposed algorithm is demonstrated by computer simulation.展开更多
In recent years,the number of incidents involved with unmanned aerial vehicles(UAVs)has increased conspicuously,resulting in an increasingly urgent demand for developing anti-UAV systems. The vast requirements of high...In recent years,the number of incidents involved with unmanned aerial vehicles(UAVs)has increased conspicuously,resulting in an increasingly urgent demand for developing anti-UAV systems. The vast requirements of high detection accuracy with respect to low altitude UAVs are put forward. In addition,the methods of UAV detection based on deep learning are of great potential in low altitude UAV detection. However,such methods need high-quality datasets to cope with the problem of high false alarm rate(FAR)and high missing alarm rate(MAR)in low altitude UAV detection,special high-quality low altitude UAV detection dataset is still lacking. A handful of known datasets for UAV detection have been rejected by their proposers for authorization and are of poor quality. In this paper,a comprehensive enhanced dataset containing UAVs and jamming objects is proposed. A large number of high-definition UAV images are obtained through real world shooting, web crawler, and data enhancement.Moreover,to cope with the challenge of low altitude UAV detection in complex backgrounds and long distance,as well as the puzzle caused by jamming objects,the noise with jamming characteristics is added to the dataset. Finally,the dataset is trained,validated,and tested by four mainstream deep learning models. The results indicate that by using data enhancement,adding noise contained jamming objects and images of UAV with complex backgrounds and long distance,the accuracy of UAV detection can be significantly improved. This work will promote the development of anti-UAV systems deeply,and more convincing evaluation criteria are provided for models optimization for UAV detection.展开更多
In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objectiv...In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation （GOSR） and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm （IOGA） and its process are described. Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload.展开更多
A design and optimization approach of dynamic and control performance for a two-DOF planar manipulator was proposed.After the kinematic and dynamic analysis,several advantages of the mechanism were illustrated,which m...A design and optimization approach of dynamic and control performance for a two-DOF planar manipulator was proposed.After the kinematic and dynamic analysis,several advantages of the mechanism were illustrated,which made it possible to obtain good dynamic and control performances just through mechanism optimization.Based on the idea of design for control(DFC),a novel kind of multi-objective optimization model was proposed.There were three optimization objectives:the index of inertia,the index describing the dynamic coupling effects and the global condition number.Other indexes to characterize the designing requirements such as the velocity of end-effector,the workspace size,and the first mode natural frequency were regarded as the constraints.The cross-section area and length of the linkages were chosen as the design variables.NSGA-II algorithm was introduced to solve this complex multi-objective optimization problem.Additional criteria from engineering experience were incorporated into the selecting of final parameters among the obtained Pareto solution sets.Finally,experiments were performed to validate the linear dynamic structure and control performances of the optimized mechanisms.A new expression for measuring the dynamic coupling degree with clear physical meaning was proposed.The results show that the optimized mechanism has an approximate decoupled dynamics structure,and each active joint can be regarded as a linear SISO system.The control performances of the linear and nonlinear controllers were also compared.It can be concluded that the optimized mechanism can achieve good control performance only using a linear controller.展开更多
文摘In this paper, we propose an efficient algorithm, called FFP-Growth (shortfor fast FP-Growth) , to mine frequent itemsets. Similar to FP-Growth, FFP-Growth searches theFP-tree in the bottom-up order, but need not construct conditional pattern bases and sub-FP-trees,thus, saving a substantial amount of time and space, and the FP-tree created by it is much smallerthan that created by TD-FP-Growth, hence improving efficiency. At the same time, FFP-Growth can beeasily extended for reducing the search space as TD-FP-Growth (M) and TD-FP-Growth (C). Experimentalresults show that the algorithm of this paper is effective and efficient.
基金The National Natural Science Foundation of China(No.60603047)the Natural Science Foundation of Liaoning ProvinceLiaoning Higher Education Research Foundation(No.2008341)
文摘A new algorithm based on an FC-tree （frequent closed pattern tree） and a max-FCIA （maximal frequent closed itemsets algorithm） is presented, which is used to mine the frequent closed itemsets for solving memory and time consuming problems. This algorithm maps the transaction database by using a Hash table,gets the support of all frequent itemsets through operating the Hash table and forms a lexicographic subset tree including the frequent itemsets.Efficient pruning methods are used to get the FC-tree including all the minimum frequent closed itemsets through processing the lexicographic subset tree.Finally,frequent closed itemsets are generated from minimum frequent closed itemsets.The experimental results show that the mapping transaction database is introduced in the algorithm to reduce time consumption and to improve the efficiency of the program.Furthermore,the effective pruning strategy restrains the number of candidates,which saves space.The results show that the algorithm is effective.
文摘The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.
文摘The presently existing decision making method for problem of goal type, i.e. the goal programming, is popular to some extent. In this paper we analyzed the features of the problem and the method,based on which we found some defects of the method and pointed out these defects. To overcome these defects we absorbed the spirit and exploited concepts of evaluation criterion and the fault measure of evaluation criterion. We proposed and applied a method with an evaluation criterion, after which we also p...
文摘A class of interactive multi objective decision making method by means of evaluation criterion is proposed for problems with linear value function,in which case,the decision maker(DM) usually has only unwhole information of weights for objectives. The concept of fault measure of the evaluation criterion is proposed to measure the deviation of the evaluation criterion from the DMs preference structure.The approach to obtain an upper boundary of fault measure of an evaluation criterion,and the approach to modify the evaluation criterion to be one with smaller fault measure,and the approach to obtain a pre optimized objective set by evaluation criterion with certain fault measure are also proposed.
基金funded by the Science and technology Program (No:13ZB0191)the Natural Gas Geology Innovation Team (No:13TD0024) of Sichuan Province Education Departmentthe Sichuan Province University Key Laboratory of Natural Gas Geology,the Sichuan Province key Disciplines Construction Program (Earth Exploration and Information Technology)
文摘Seismic imaging quality is critical to describing reservoirs. There are many methods that can improve imaging quality; some rely on advanced processing means, whereas others rely on changing the field acquisition methods. However, most of the acquisition methods focus on improving imaging by using infill shots without considering the target-layer illumination energy. Moreover, total infill shooting greatly increases the acquisition cost. In this paper, we present a new method for maximizing the contribution to the target shadow area illumination by automatic local infill shooting. Thus, we designed 2D and 3D models and obtained the depth migration section by forward modeling, infill shots, depth migration, etc. The model results also show that by choosing the most appropriate number of shot points, we can enhance the shadow area energy and improve the target-layer imaging quality at low cost.
文摘In this paper,we propose a hybrid algorithm for finding a set of non dominated solutions of a multi objective optimization problem.In the proposed algorithm,a local search procedure is applied to each solution generated by genetic operations.The aim of the proposed algorithm is not to determine a single final solution but to try to find all the non dominated solutions of a multi objective optimization problem.The choice of the final solution is left to the decision makers preference.High search ability of the proposed algorithm is demonstrated by computer simulation.
基金supported by the National Natural Science Foundation of China(No. 62173237)the National Key R&D Program of China(No.2018AAA0100804)+7 种基金the Zhejiang Key laboratory of General Aviation Operation technology(No.JDGA2020-7)the Talent Project of Revitalization Liaoning(No. XLYC1907022)the Key R & D Projects of Liaoning Province (No. 2020JH2/10100045)the Natural Science Foundation of Liaoning Province(No. 2019-MS-251)the Scientific Research Project of Liaoning Provincial Department of Education(No.JYT2020142)the High-Level Innovation Talent Project of Shenyang (No.RC190030)the Science and Technology Project of Beijing Municipal Commission of Education (No. KM201811417005)the Academic Research Projects of Beijing Union University(No.ZB10202005)。
文摘In recent years,the number of incidents involved with unmanned aerial vehicles(UAVs)has increased conspicuously,resulting in an increasingly urgent demand for developing anti-UAV systems. The vast requirements of high detection accuracy with respect to low altitude UAVs are put forward. In addition,the methods of UAV detection based on deep learning are of great potential in low altitude UAV detection. However,such methods need high-quality datasets to cope with the problem of high false alarm rate(FAR)and high missing alarm rate(MAR)in low altitude UAV detection,special high-quality low altitude UAV detection dataset is still lacking. A handful of known datasets for UAV detection have been rejected by their proposers for authorization and are of poor quality. In this paper,a comprehensive enhanced dataset containing UAVs and jamming objects is proposed. A large number of high-definition UAV images are obtained through real world shooting, web crawler, and data enhancement.Moreover,to cope with the challenge of low altitude UAV detection in complex backgrounds and long distance,as well as the puzzle caused by jamming objects,the noise with jamming characteristics is added to the dataset. Finally,the dataset is trained,validated,and tested by four mainstream deep learning models. The results indicate that by using data enhancement,adding noise contained jamming objects and images of UAV with complex backgrounds and long distance,the accuracy of UAV detection can be significantly improved. This work will promote the development of anti-UAV systems deeply,and more convincing evaluation criteria are provided for models optimization for UAV detection.
文摘In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation （GOSR） and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm （IOGA） and its process are described. Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload.
基金Project(2009AA04Z216) supported in part by the National High Technology Research and Development Program of ChinaProject(2009ZX04013-011) supported by the National Science and Technology Major Program of ChinaProject(20092302120068) supported by the Doctoral Program of Higher Education of China
文摘A design and optimization approach of dynamic and control performance for a two-DOF planar manipulator was proposed.After the kinematic and dynamic analysis,several advantages of the mechanism were illustrated,which made it possible to obtain good dynamic and control performances just through mechanism optimization.Based on the idea of design for control(DFC),a novel kind of multi-objective optimization model was proposed.There were three optimization objectives:the index of inertia,the index describing the dynamic coupling effects and the global condition number.Other indexes to characterize the designing requirements such as the velocity of end-effector,the workspace size,and the first mode natural frequency were regarded as the constraints.The cross-section area and length of the linkages were chosen as the design variables.NSGA-II algorithm was introduced to solve this complex multi-objective optimization problem.Additional criteria from engineering experience were incorporated into the selecting of final parameters among the obtained Pareto solution sets.Finally,experiments were performed to validate the linear dynamic structure and control performances of the optimized mechanisms.A new expression for measuring the dynamic coupling degree with clear physical meaning was proposed.The results show that the optimized mechanism has an approximate decoupled dynamics structure,and each active joint can be regarded as a linear SISO system.The control performances of the linear and nonlinear controllers were also compared.It can be concluded that the optimized mechanism can achieve good control performance only using a linear controller.
