Dykes are a special kind of intrusive rocks which were formed by deep magma intruded into the existing brittle fractures in the crust.Dykes swarms in different tectonic environments are very significant to re-construc...Dykes are a special kind of intrusive rocks which were formed by deep magma intruded into the existing brittle fractures in the crust.Dykes swarms in different tectonic environments are very significant to re-construct the展开更多
In this paper, we present a model of stochastic swarm system and prove the stability of this kind of systems. We establish the stable aggregating behavior for the group using a coordination control scheme. This indivi...In this paper, we present a model of stochastic swarm system and prove the stability of this kind of systems. We establish the stable aggregating behavior for the group using a coordination control scheme. This individual-based control scheme is a combination of attractive and repulsive interactions among the individuals in the group, which ensures the cohesion of the group and collision avoidance among the individuals. The dynamics of each individual depends on the relative positions between the individuals and the influences of the random disturbances. Under the influences of the noises, this position-based control strategy still generates the stable aggregating behavior harmoniously for the group and the self-organized swarm pattern is formed.展开更多
This paper considers an anisotropic swarm model with a class of attraction and repulsion functions. It is shown that the members of the swarm will aggregate and eventually form a cohesive cluster of finite size around...This paper considers an anisotropic swarm model with a class of attraction and repulsion functions. It is shown that the members of the swarm will aggregate and eventually form a cohesive cluster of finite size around the swarm center. Moreover, It is also proved that under certain conditions, the swarm system can be completely stable, i.e., every solution converges to the equilibrium points of the system. The model and results of this paper extend a recent work on isotropic swarms to more general cases and provide further insight into the effect of the interaction pattern on self-organized motion in a swarm system. Keywords Biological systems - Multiagent systems - Pattern formation - Stability - Swarms This work was supported by the National Natural Science Foundation of China (No. 60274001 and No. 10372002) and the National Key Basic Research and Development Program (No.2002CB312200).展开更多
Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic fie...Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic field computation （MFC） model consists of a field simulator, a non-derivative optimization algo- rithm and an auxiliary data processing unit. The mathematical model is deduced and proved that the MFC model is equivalent to a quadratic discriminant function. Furthermore, the finite element prototype is derived, and the simulator is developed, combining with particle swarm optimizer for the field configuration. Two benchmark classification experiments are studied in the numerical experiment, and one notable advantage is demonstrated that less training samples are required and a better generalization can be achieved.展开更多
针对特征权重难以准确量化的问题,提出一种基于灰狼优化(grey wolf optimizer, GWO)算法和鸟群算法(bird swarm algorithm, BSA)的混合算法,用于特征权重的寻优。首先,将Chebyshev映射、反向学习与精英策略用于混合算法的初始种群生成;...针对特征权重难以准确量化的问题,提出一种基于灰狼优化(grey wolf optimizer, GWO)算法和鸟群算法(bird swarm algorithm, BSA)的混合算法,用于特征权重的寻优。首先,将Chebyshev映射、反向学习与精英策略用于混合算法的初始种群生成;其次,将改进后的GWO算法位置更新策略融入BSA的觅食行为中,得到一种新的局部搜索策略;然后,将BSA的警觉行为与飞行行为用作混合算法的全局搜索平衡策略,从而得到一种收敛的灰狼-鸟群算法(grey wolf and bird swarm algorithm, GWBSA),通过GWBSA的迭代寻优可获得各特征的权重值。利用标准测试函数和标准分类数据集进行了对比实验,与遗传算法、蚁狮算法等方法相比,GWBSA具有较快的收敛速度且不易陷入局部最优,可以提高模式分类问题的求解质量。展开更多
基金co-supported by National Natural Science Foundation of China (Project number 41502201)"Western Light" project of Chinese Academy of Sciences (XBBS201301)
文摘Dykes are a special kind of intrusive rocks which were formed by deep magma intruded into the existing brittle fractures in the crust.Dykes swarms in different tectonic environments are very significant to re-construct the
基金Supported by the National Natural Science Foundation of China (60574088, 60274014)
文摘In this paper, we present a model of stochastic swarm system and prove the stability of this kind of systems. We establish the stable aggregating behavior for the group using a coordination control scheme. This individual-based control scheme is a combination of attractive and repulsive interactions among the individuals in the group, which ensures the cohesion of the group and collision avoidance among the individuals. The dynamics of each individual depends on the relative positions between the individuals and the influences of the random disturbances. Under the influences of the noises, this position-based control strategy still generates the stable aggregating behavior harmoniously for the group and the self-organized swarm pattern is formed.
文摘This paper considers an anisotropic swarm model with a class of attraction and repulsion functions. It is shown that the members of the swarm will aggregate and eventually form a cohesive cluster of finite size around the swarm center. Moreover, It is also proved that under certain conditions, the swarm system can be completely stable, i.e., every solution converges to the equilibrium points of the system. The model and results of this paper extend a recent work on isotropic swarms to more general cases and provide further insight into the effect of the interaction pattern on self-organized motion in a swarm system. Keywords Biological systems - Multiagent systems - Pattern formation - Stability - Swarms This work was supported by the National Natural Science Foundation of China (No. 60274001 and No. 10372002) and the National Key Basic Research and Development Program (No.2002CB312200).
基金supported by the National Natural Science Foundation of China(60903005)the National Basic Research Program of China(973 Program)(2012CB821206)
文摘Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic field computation （MFC） model consists of a field simulator, a non-derivative optimization algo- rithm and an auxiliary data processing unit. The mathematical model is deduced and proved that the MFC model is equivalent to a quadratic discriminant function. Furthermore, the finite element prototype is derived, and the simulator is developed, combining with particle swarm optimizer for the field configuration. Two benchmark classification experiments are studied in the numerical experiment, and one notable advantage is demonstrated that less training samples are required and a better generalization can be achieved.
文摘针对特征权重难以准确量化的问题,提出一种基于灰狼优化(grey wolf optimizer, GWO)算法和鸟群算法(bird swarm algorithm, BSA)的混合算法,用于特征权重的寻优。首先,将Chebyshev映射、反向学习与精英策略用于混合算法的初始种群生成;其次,将改进后的GWO算法位置更新策略融入BSA的觅食行为中,得到一种新的局部搜索策略;然后,将BSA的警觉行为与飞行行为用作混合算法的全局搜索平衡策略,从而得到一种收敛的灰狼-鸟群算法(grey wolf and bird swarm algorithm, GWBSA),通过GWBSA的迭代寻优可获得各特征的权重值。利用标准测试函数和标准分类数据集进行了对比实验,与遗传算法、蚁狮算法等方法相比,GWBSA具有较快的收敛速度且不易陷入局部最优,可以提高模式分类问题的求解质量。
