A dandelion algorithm(DA) is a recently developed intelligent optimization algorithm for function optimization problems. Many of its parameters need to be set by experience in DA,which might not be appropriate for all...A dandelion algorithm(DA) is a recently developed intelligent optimization algorithm for function optimization problems. Many of its parameters need to be set by experience in DA,which might not be appropriate for all optimization problems. A self-adapting and efficient dandelion algorithm is proposed in this work to lower the number of DA's parameters and simplify DA's structure. Only the normal sowing operator is retained;while the other operators are discarded. An adaptive seeding radius strategy is designed for the core dandelion. The results show that the proposed algorithm achieves better performance on the standard test functions with less time consumption than its competitive peers. In addition, the proposed algorithm is applied to feature selection for credit card fraud detection(CCFD), and the results indicate that it can obtain higher classification and detection performance than the-state-of-the-art methods.展开更多
传统蜂窝网络采用固定的频谱资源分配方式,导致频谱利用率低且无法满足用户高速和高质量通信需求。针对这种局限性提出了一种将分布式天线系统(Distributed Antenna System,DAS)与终端直通(Device to Device,D2D)通信技术相结合的策略...传统蜂窝网络采用固定的频谱资源分配方式,导致频谱利用率低且无法满足用户高速和高质量通信需求。针对这种局限性提出了一种将分布式天线系统(Distributed Antenna System,DAS)与终端直通(Device to Device,D2D)通信技术相结合的策略。首先,该方案提出协同上下行链路(Uplink and Downlink Collaboration,UADC)的资源分配算法,并构建了以最大化系统总效率为目标的非线性规划问题。然后,将该问题分为最佳功率选择和信道分配2个子问题,同时利用匈牙利算法为D2D对选择最佳信道。最后,在MATLAB仿真平台进行实验。仿真结果表明,相比于仅复用上行链路的和仅使用DAS系统的方法,所提方案的频谱效率更高。展开更多
This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is ...This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic.展开更多
基金supported by the Institutional Fund Projects(IFPIP-1481-611-1443)the Key Projects of Natural Science Research in Anhui Higher Education Institutions(2022AH051909)+1 种基金the Provincial Quality Project of Colleges and Universities in Anhui Province(2022sdxx020,2022xqhz044)Bengbu University 2021 High-Level Scientific Research and Cultivation Project(2021pyxm04)。
文摘A dandelion algorithm(DA) is a recently developed intelligent optimization algorithm for function optimization problems. Many of its parameters need to be set by experience in DA,which might not be appropriate for all optimization problems. A self-adapting and efficient dandelion algorithm is proposed in this work to lower the number of DA's parameters and simplify DA's structure. Only the normal sowing operator is retained;while the other operators are discarded. An adaptive seeding radius strategy is designed for the core dandelion. The results show that the proposed algorithm achieves better performance on the standard test functions with less time consumption than its competitive peers. In addition, the proposed algorithm is applied to feature selection for credit card fraud detection(CCFD), and the results indicate that it can obtain higher classification and detection performance than the-state-of-the-art methods.
文摘传统蜂窝网络采用固定的频谱资源分配方式,导致频谱利用率低且无法满足用户高速和高质量通信需求。针对这种局限性提出了一种将分布式天线系统(Distributed Antenna System,DAS)与终端直通(Device to Device,D2D)通信技术相结合的策略。首先,该方案提出协同上下行链路(Uplink and Downlink Collaboration,UADC)的资源分配算法,并构建了以最大化系统总效率为目标的非线性规划问题。然后,将该问题分为最佳功率选择和信道分配2个子问题,同时利用匈牙利算法为D2D对选择最佳信道。最后,在MATLAB仿真平台进行实验。仿真结果表明,相比于仅复用上行链路的和仅使用DAS系统的方法,所提方案的频谱效率更高。
基金funded by the Joint Funds of the National Natural Science Foundation of China (61079001)
文摘This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic.
