A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positio...A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positions, and the calculation of the prior probability distribution of each beam position is discussed. And then, two search algorithms based on information gain are proposed using Shannon entropy and Kullback-Leibler entropy, respectively. With the proposed strategy, the information gain of each beam position is predicted before the radar detection, and the observation is made in the beam position with the maximal information gain. Compared with the conventional method of sequential search and confirm search, simulation results show that the proposed search strategy can distinctly improve the search performance and save radar time resources with the same given detection probability.展开更多
The artificial bee colony （ABC） algorithm is a sim- ple and effective global optimization algorithm which has been successfully applied in practical optimization problems of various fields. However, the algorithm is...The artificial bee colony （ABC） algorithm is a sim- ple and effective global optimization algorithm which has been successfully applied in practical optimization problems of various fields. However, the algorithm is still insufficient in balancing ex- ploration and exploitation. To solve this problem, we put forward an improved algorithm with a comprehensive search mechanism. The search mechanism contains three main strategies. Firstly, the heuristic Gaussian search strategy composed of three different search equations is proposed for the employed bees, which fully utilizes and balances the exploration and exploitation of the three different search equations by introducing the selectivity probability P,. Secondly, in order to improve the search accuracy, we propose the Gbest-guided neighborhood search strategy for onlooker bees to improve the exploitation performance of ABC. Thirdly, the self- adaptive population perturbation strategy for the current colony is used by random perturbation or Gaussian perturbation to en- hance the diversity of the population. In addition, to improve the quality of the initial population, we introduce the chaotic opposition- based learning method for initialization. The experimental results and Wilcoxon signed ranks test based on 27 benchmark func- tions show that the proposed algorithm, especially for solving high dimensional and complex function optimization problems, has a higher convergence speed and search precision than ABC and three other current ABC-based algorithms.展开更多
In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this stud...In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects： one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county＇s distribution network showed that the improved ACOA was practicable.展开更多
Since 1980s,with the deepening of the cultural communication between China and western countries,more and more works on China written by modern foreign scholars are translated into Chinese,and most of the versions are...Since 1980s,with the deepening of the cultural communication between China and western countries,more and more works on China written by modern foreign scholars are translated into Chinese,and most of the versions are of high quality. But there also exist some common deficiencies,the most representative of which lie in the versions reflecting the Chinese elements,that is,the versions are ( 1) less formal; ( 2) less idiomatical and ( 3) unable to correct the errors of the original. However,translation practice shows that back translation is an effective way to solve the problems above. Based on the discussion of the back translation theory and his experience from translating Chinese Characteristics,the author presents some corresponding strategies about back translation.展开更多
为探究在集散式控制系统(distributed control system,DCS)危险排除过程中控制员不同信息搜索策略对排险任务绩效的影响及认知负荷的中介效应,基于虚拟现实技术、皮肤电采样和眼动追踪技术构建模拟DCS工控平台,招募20名相关专业被试参...为探究在集散式控制系统(distributed control system,DCS)危险排除过程中控制员不同信息搜索策略对排险任务绩效的影响及认知负荷的中介效应,基于虚拟现实技术、皮肤电采样和眼动追踪技术构建模拟DCS工控平台,招募20名相关专业被试参与模拟排险实验并对其认知负荷及排险绩效进行量化,使用眼动轨迹匹配法判断被试的信息搜索模式,研究认知负荷的中介效应及中介机理。研究结果表明:不同信息搜索策略会显著影响任务绩效;认知负荷对该影响的中介效应高达89.66%,表明信息搜索策略主要通过影响认知负荷来间接作用于排险任务绩效,认知负荷越高,任务绩效越低;逻辑系统搜索策略能通过高效图式匹配减少认知资源消耗,显著抑制认知负荷增长,任务绩效表现最佳;空间系统搜索较难抑制认知负荷,任务绩效较差;随机搜索被试认知负荷显著高于其他组,绩效表现最差;此外,不同认知负荷水平下被试的信息搜索策略没有明显转变倾向。研究结果可为DCS控制人员的考核和培训提供理论支撑。展开更多
基金the High Technology Research and Development Programme of China (2003AA134030)
文摘A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positions, and the calculation of the prior probability distribution of each beam position is discussed. And then, two search algorithms based on information gain are proposed using Shannon entropy and Kullback-Leibler entropy, respectively. With the proposed strategy, the information gain of each beam position is predicted before the radar detection, and the observation is made in the beam position with the maximal information gain. Compared with the conventional method of sequential search and confirm search, simulation results show that the proposed search strategy can distinctly improve the search performance and save radar time resources with the same given detection probability.
基金supported by the Aviation Science Foundation of China(20105196016)the Postdoctoral Science Foundation of China(2012M521807)
文摘The artificial bee colony （ABC） algorithm is a sim- ple and effective global optimization algorithm which has been successfully applied in practical optimization problems of various fields. However, the algorithm is still insufficient in balancing ex- ploration and exploitation. To solve this problem, we put forward an improved algorithm with a comprehensive search mechanism. The search mechanism contains three main strategies. Firstly, the heuristic Gaussian search strategy composed of three different search equations is proposed for the employed bees, which fully utilizes and balances the exploration and exploitation of the three different search equations by introducing the selectivity probability P,. Secondly, in order to improve the search accuracy, we propose the Gbest-guided neighborhood search strategy for onlooker bees to improve the exploitation performance of ABC. Thirdly, the self- adaptive population perturbation strategy for the current colony is used by random perturbation or Gaussian perturbation to en- hance the diversity of the population. In addition, to improve the quality of the initial population, we introduce the chaotic opposition- based learning method for initialization. The experimental results and Wilcoxon signed ranks test based on 27 benchmark func- tions show that the proposed algorithm, especially for solving high dimensional and complex function optimization problems, has a higher convergence speed and search precision than ABC and three other current ABC-based algorithms.
基金Supported by China Postdoctoral Science Foundation(20090460873)
文摘In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects： one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county＇s distribution network showed that the improved ACOA was practicable.
文摘Since 1980s,with the deepening of the cultural communication between China and western countries,more and more works on China written by modern foreign scholars are translated into Chinese,and most of the versions are of high quality. But there also exist some common deficiencies,the most representative of which lie in the versions reflecting the Chinese elements,that is,the versions are ( 1) less formal; ( 2) less idiomatical and ( 3) unable to correct the errors of the original. However,translation practice shows that back translation is an effective way to solve the problems above. Based on the discussion of the back translation theory and his experience from translating Chinese Characteristics,the author presents some corresponding strategies about back translation.
文摘为探究在集散式控制系统(distributed control system,DCS)危险排除过程中控制员不同信息搜索策略对排险任务绩效的影响及认知负荷的中介效应,基于虚拟现实技术、皮肤电采样和眼动追踪技术构建模拟DCS工控平台,招募20名相关专业被试参与模拟排险实验并对其认知负荷及排险绩效进行量化,使用眼动轨迹匹配法判断被试的信息搜索模式,研究认知负荷的中介效应及中介机理。研究结果表明:不同信息搜索策略会显著影响任务绩效;认知负荷对该影响的中介效应高达89.66%,表明信息搜索策略主要通过影响认知负荷来间接作用于排险任务绩效,认知负荷越高,任务绩效越低;逻辑系统搜索策略能通过高效图式匹配减少认知资源消耗,显著抑制认知负荷增长,任务绩效表现最佳;空间系统搜索较难抑制认知负荷,任务绩效较差;随机搜索被试认知负荷显著高于其他组,绩效表现最差;此外,不同认知负荷水平下被试的信息搜索策略没有明显转变倾向。研究结果可为DCS控制人员的考核和培训提供理论支撑。
