针对J2EE服务端组件的自动化测试方案

针对J2EE服务端组件难于进行自动化测试的现状,提出了一种将Cactus框架与Ant工具结合以实现容器内自动化单元测试的解决方案,能利用其辅助XP的持续集成实践。     

基于蚁群智能和支持向量机的人脸性别分类方法

蚁群优化算法是根据自然界中蚂蚁能够将食物以最短路径搬回蚁巢这一智能行为而提出的一种新颖的进化算法,该算法不仅具有很好的鲁棒性,良好的正反馈特性,而且具有并行分布计算的特点。同时,支持向量机又是一种基于结构风险最小化原理的机器学习技术,具有很强的学习泛化能力,为此,文章提出了基于蚁群优化算法和支持向量机的人脸性别分类的方法。首先,通过KL变换降低人脸性别特征的维数,并根据特征值按照从大到小的顺序进行排列,然后采用10-交叉确认技术,用蚁群优化算法对人脸性别特征面进行选择,以对支持向量机进行学习、训练和测试。实验表明,与其他分类算法相比较,这种方法不仅图像处理简单,实用性强,而且正确识别率特别高。     

具有调和特性的蚁群改进算法

蚁群算法是一种仿生类算法,该文首先介绍了蚁群算法及发展,并分析它易于收敛于局部最优解及收敛速度比较慢的原因。然后给出了一个基于调和特性的改进蚁群算法,通过对蚁群结果的变异和调和过程的操作来克服蚁群算法的缺点。最后通过实例得到满意的结果。     

制造系统通用作业计划与蚁群算法优化

分析了基本作业方式的“通用-特例”关系,提出了全面研究上述基本作业方式的通用作业计划的概念,建立了通用作业计划非连接图模型及基于蚁群算法的优化方法。算例研究假定一制造系统包含开放作业、异顺序作业、混杂流水作业三种作业方式,将其按照通用作业计划方式采用蚁群算法进行优化,所得的近优加工流程时间显著优于采用穷举法对三种作业方式分别优化所得的最优解。     

医院病房空调环境中细菌密度的监测分析

通过对某综合性医院使用房间空调器的病房和非空调病房中细菌密度的监测分析,证明医院病房不宜采用局部式空调方式。     

Changes in the Cuticular Hydrocarbon Profile of the Slave-Maker Ant Queen, Polyergus breviceps Emery, After Killing a Formica Host Queen (Hymenoptera: Formicidae)

Queens of the slave-maker ant, Polyergus breviceps, take over nests of their Formica host species by fatally attacking the resident queen. As workers only begin grooming the P. breviceps queen once she has ceased her attack, we investigated whether a change in parasite queen chemistry may account for the change in worker behavior. Cuticular hydrocarbon profiles of newly mated P. breviceps queens and of queens of their two Formica host species were found to be species-specific. Profiles of newly mated P. breviceps queens that had attacked a Formica queen, however, were virtually identical to the queen profile of the species killed. Mass spectral analysis revealed that the hydrocarbons on the cuticles of newly mated P. breviceps changed from primarily normal alkanes to methyl and di-methyl branched alkanes after attacks. The results suggest that cuticular compounds from the host queen were transferred to the parasite queen during their aggressive interaction.     

一种仿Dijkstra的蚂蚁算法

为了快捷可靠地寻找到满足多媒体QoS保证的路由,结合Dijkstra算法和蚂蚁算法,从源节点开始,在所有满足QoS要求的邻接链路上泛滥寻路蚂蚁,所有中间节点依据一个设定的QoS路由优劣综合评价函数,在到达的所有寻路蚂蚁中选择其最优者复制并继续泛滥,直到最后到达目的节点为止。这样,通过约束条件下的穷举搜索,最后一定可以找到源节点和目的节点间的满足QoS要求的路由。实验证明,该算法具有思路直观、运算量小、强收敛、能自适应网络变动优点。     

改进型蚁群算法求解单任务Agent联盟

联盟是多Agent之间一种重要的合作方法,如何生成面向某个任务的最优联盟是一个复杂的组合优化问题．首次引入蚁群算法来解决这一问题,在求解过程中蚂蚁倾向于选择曾经合作过并且合作效果比较好的Agent组成联盟,充分实现了熟人机制;创新地引入“第2种信息素”对蚁群算法进行改进,不再易于陷入局部极小．对比实验结果表明,本算法在解的性能和收敛速度上均优于相关算法．     

平面布局的蚁群算法

To increase the optimization result and efficiency in floorplan, ant colony algorithm was used as optimization algorithm of floorplan. In this algorithm, the B*-tree structure was defined to describe the structure of layout, the utilization efficiency of modules was defined to be pheromone which strenthened the dependency relationship of partial modules that occupy less area, and mutation scheme was employed to improve the efficiency of convergence. Through experiments, ant colony algorithm can get better result and efficiency than simulate annealing algorithm in the flooplan of hard modules.     

Colony: An Artificial Life Model for Active Autonomous Objects

Appropriate aids on top of the primitive object-oriented model will help promote better understanding of the semantics of applications and allow us to focus better on the various aspects of given problems. This study focuses on the exploration of a design model and the corresponding programming framework for the modelling and implementation of applications involving active autonomous objects based on the object technology. The proposed design model is an artificial life model based on the colony phenomenon in nature. This model can naturally be mapped onto an object-oriented implementation. The colony model favours a predicate-based object communication/coordination pattern as opposed to the navigational message-passing paradigm seen in programming languages such as C+ +. The proposed model is particularly appealing to us, for it presents a unifying conceptual design model and programming framework for a wide class of applications including neural networks, genetic algorithms and fuzzy expert systems. The ideas presented are illustrated through a genetic algorithm problem.