文章摘要
何宜超1,孙鹏1,焦志强1,张杰勇1,王衡2.语义驱动的作战资源服务聚类方法[J].空军工程大学学报:自然科学版,2020,21(4):101-107
语义驱动的作战资源服务聚类方法
Semantic Driven Clustering Method of Combat Resource Service
  
DOI:
中文关键词: 作战资源服务化  服务聚类  OWL-S  K-means  遗传算法
英文关键词: servitization of combat resources  service clustering  OWL-S  K-means  genetic algorithm
基金项目:国家自然科学基金(61573017, 61703425)
作者单位
何宜超1,孙鹏1,焦志强1,张杰勇1,王衡2 1.空军工程大学信息与导航学院 西安 710077 2.空装合肥第一军代室 合肥 230000 
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中文摘要:
      针对SOA架构下指挥信息系统中作战资源服务池规模大、服务组织效率不高的特点,进行了服务组织聚类的研究。首先对作战资源进行属性分析,基于OWL-S描述规范对其进行服务化建模,形成作战资源原子级服务本体模型,实现云服务化;然后构建了作战资源服务聚类模型,并在遗传算法中将模拟退火方法和K-means方法相结合,提出了一种作战资源服务聚类方法;最后通过仿真与GS和GK算法进行了对比。实验结果表明,所提算法能够在可接受的时间内找到适应度值更高的聚类方案,且方案结果适应度值的标准差较低。该方法相比于GS与GK算法具有更好的寻优性与稳定性。
英文摘要:
      Aiming at the characteristics of large-scale combat resource service pools and low service organization efficiency in the command information system under the SOA architecture, a clustering study of service organizations is conducted. Firstly, the attributes of combat resources are analyzed, based on the OWL-S description specification, service oriented modeling of combat resources is formed, and an atomic level service ontology model of combat resources is formed to realize the cloud service of combat resources. Then a clustering model of combat resource service is constructed, and the simulated annealing method and the K-means method are combined in the genetic algorithm, and a clustering method of combat resource service is proposed. Finally, the simulation is compared with the GS and GK algorithms. The experimental results show that the proposed algorithm can find a clustering scheme with a higher fitness value within an acceptable time, and the standard deviation of the fitness value of the solution results is lower. Compared with GS and GK algorithms, this method has better optimization and stability.
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