To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization （QPSO） alg...To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization （QPSO） algorithm. By a precedence ordering coding, the diagnostic sequence optimization can be translated into a precedence ordering problem in the multidimensional space of swarm. It can get the optimizing order quickly by using the powerful and quick search capability of QPSO algorithm, and the order is the diagnostic sequence for the system. The realization of the method is simpler than other methods, and the results are more excellent than others, and it has been applied in the engineering practice.展开更多
In this paper, a new partial transmit sequence（PTS）scheme with low computational complexity is proposed for the problems of high computational complexity in the conventional PTS method. By analyzing the relationship...In this paper, a new partial transmit sequence（PTS）scheme with low computational complexity is proposed for the problems of high computational complexity in the conventional PTS method. By analyzing the relationship of candidate sequences in the PTS method under the interleaved partition method, it has been discovered that some candidate sequences generated by phase factor sequences have the same peak average power ratio（PAPR）. Hence, phase factor sequences can be optimized to reduce their searching times. Then, the computational process of generating candidate sequences can be simplified by improving the utilization of data and minimizing the calculations of complex multiplication. The performance analysis shows that, compared with the conventional PTS scheme, the proposed approach significantly decreases the computational complexity and has no loss of PAPR performance.展开更多
In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a le...In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a less or rougher concept. With different translation sequences, the problem of information loss is varied. To get the translation sequence, in which the jth agent taking part in rough communication gets maximum information, a simulated annealing algorithm is used. Analysis and simulation of this algorithm demonstrate its effectiveness.展开更多
In rough communication, because each agent has a different language and can not provide precise communication to each other, the concept translated among multi-agents will loss some information, and this results in a ...In rough communication, because each agent has a different language and can not provide precise communication to each other, the concept translated among multi-agents will loss some information, and this results in a less or rougher concept. With different translation sequences the amount of the missed knowledge is varied. The λ-optimal translation sequence of rough communication, which concerns both every agent and the last agent taking part in rough communication to get information as much as he （or she） can, is given. In order to get the λ-optimal translation sequence, a genetic algorithm is used. Analysis and simulation of the algorithm demonstrate the effectiveness of the approach.展开更多
This paper proposes a hybrid approach for recognizing human activities from trajectories. First, an improved hidden Markov model （HMM） parameter learning algorithm, HMM-PSO, is proposed, which achieves a better bala...This paper proposes a hybrid approach for recognizing human activities from trajectories. First, an improved hidden Markov model （HMM） parameter learning algorithm, HMM-PSO, is proposed, which achieves a better balance between the global and local exploitation by the nonlinear update strategy and repulsion operation. Then, the event probability sequence （EPS） which consists of a series of events is computed to describe the unique characteristic of human activities. The anatysis on EPS indicates that it is robust to the changes in viewing direction and contributes to improving the recognition rate. Finally, the effectiveness of the proposed approach is evaluated by data experiments on current popular datasets.展开更多
提升航空器运行效率,获取航空运输利益最大化,是中国民航一直以来追求的目标。研究表明,EoR进近(Established on RNP AR)在提升近距平行跑道运行效率方面具有不可替代的优势,因此受到业界广泛关注。将EoR进近与排序策略结合,以航班延误...提升航空器运行效率,获取航空运输利益最大化,是中国民航一直以来追求的目标。研究表明,EoR进近(Established on RNP AR)在提升近距平行跑道运行效率方面具有不可替代的优势,因此受到业界广泛关注。将EoR进近与排序策略结合,以航班延误时间最小为目标函数,建立基于EoR的排序模型。对比分析基于EoR的独立运行与相关运行对航班延误时间的影响。针对大规模航班排序计算时解空间较大且要求时效性的特点,提出一种基于S形函数的自适应粒子群优化算法(S-shaped function based adaptive particle swarm optimization,SA-PSO)对模型进行求解。以昆明长水国际机场终端区为例进行实例验证,尾流安全间隔上,采用中国民航航空器尾流重新分类(RECAT-CN)运行标准。结果表明:EoR独立运行较相关运行减少总延误约38%、EoR独立运行模式下,本文算法较先到先服务(first come first served,FCFS)算法减少总延误约15.3%。展开更多
基金supported by the National Natural Science Foundation of China(60771063).
文摘To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization （QPSO） algorithm. By a precedence ordering coding, the diagnostic sequence optimization can be translated into a precedence ordering problem in the multidimensional space of swarm. It can get the optimizing order quickly by using the powerful and quick search capability of QPSO algorithm, and the order is the diagnostic sequence for the system. The realization of the method is simpler than other methods, and the results are more excellent than others, and it has been applied in the engineering practice.
基金supported by the National Natural Science Foundation of China(6167309361370152)the Science and Technology Project of Shenyang(F16-205-1-01)
文摘In this paper, a new partial transmit sequence（PTS）scheme with low computational complexity is proposed for the problems of high computational complexity in the conventional PTS method. By analyzing the relationship of candidate sequences in the PTS method under the interleaved partition method, it has been discovered that some candidate sequences generated by phase factor sequences have the same peak average power ratio（PAPR）. Hence, phase factor sequences can be optimized to reduce their searching times. Then, the computational process of generating candidate sequences can be simplified by improving the utilization of data and minimizing the calculations of complex multiplication. The performance analysis shows that, compared with the conventional PTS scheme, the proposed approach significantly decreases the computational complexity and has no loss of PAPR performance.
基金the Natural Science Foundation of Shandong Province (Y2006A12)the Scientific ResearchDevelopment Project of Shandong Provincial Education Department(J06P01)the Doctoral Foundation of University of Jinan(B0633).
文摘In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a less or rougher concept. With different translation sequences, the problem of information loss is varied. To get the translation sequence, in which the jth agent taking part in rough communication gets maximum information, a simulated annealing algorithm is used. Analysis and simulation of this algorithm demonstrate its effectiveness.
基金supported by the National Natural Science Foundation of China(61070241)the Natural Science Foundation of Shandong Province(ZR2010FM035)+1 种基金the Science and Technology Foundation of University of Jinan(XKY1031XKY0808)
文摘In rough communication, because each agent has a different language and can not provide precise communication to each other, the concept translated among multi-agents will loss some information, and this results in a less or rougher concept. With different translation sequences the amount of the missed knowledge is varied. The λ-optimal translation sequence of rough communication, which concerns both every agent and the last agent taking part in rough communication to get information as much as he （or she） can, is given. In order to get the λ-optimal translation sequence, a genetic algorithm is used. Analysis and simulation of the algorithm demonstrate the effectiveness of the approach.
基金supported by the National Natural Science Foundation of China(60573159)the Guangdong High Technique Project(201100000514)
文摘This paper proposes a hybrid approach for recognizing human activities from trajectories. First, an improved hidden Markov model （HMM） parameter learning algorithm, HMM-PSO, is proposed, which achieves a better balance between the global and local exploitation by the nonlinear update strategy and repulsion operation. Then, the event probability sequence （EPS） which consists of a series of events is computed to describe the unique characteristic of human activities. The anatysis on EPS indicates that it is robust to the changes in viewing direction and contributes to improving the recognition rate. Finally, the effectiveness of the proposed approach is evaluated by data experiments on current popular datasets.
文摘提升航空器运行效率,获取航空运输利益最大化,是中国民航一直以来追求的目标。研究表明,EoR进近(Established on RNP AR)在提升近距平行跑道运行效率方面具有不可替代的优势,因此受到业界广泛关注。将EoR进近与排序策略结合,以航班延误时间最小为目标函数,建立基于EoR的排序模型。对比分析基于EoR的独立运行与相关运行对航班延误时间的影响。针对大规模航班排序计算时解空间较大且要求时效性的特点,提出一种基于S形函数的自适应粒子群优化算法(S-shaped function based adaptive particle swarm optimization,SA-PSO)对模型进行求解。以昆明长水国际机场终端区为例进行实例验证,尾流安全间隔上,采用中国民航航空器尾流重新分类(RECAT-CN)运行标准。结果表明:EoR独立运行较相关运行减少总延误约38%、EoR独立运行模式下,本文算法较先到先服务(first come first served,FCFS)算法减少总延误约15.3%。
