数据挖掘与数据融合相结合的异类信息融合*

针对组网系统中的信息样式多、模糊性强等特点,介绍了分布式异类传感器组网系统及其特点,将数据挖掘中的知识发现理论与数据融合的知识应用理论相结合,建立了异类信息综合处理的集成模型。并提出了基于模糊神经网络的数据挖掘算法,增强了集成模型的自学习性能。模型有效地提高了异类传感器组网系统的智能化、自动化能力。     

基于CMAC的模糊神经网络方法

结合模糊神经网络和小脑模型连接控制CMAC理论,提出训练时间短、精度高的CMAC模糊神经网络方法,给出了网络结构、算法,并通过一个维修经费预测实例讲述了这种算法.     

军校教员业绩的模糊综合评估方法研究

根据模糊综合评估理论,建立了军校教员业绩的模糊综合评估模型,对军校教员业绩的模糊综合测评方法进行了研究,并给出了一种新的确定评估指标权重的方法,使得模糊综合测评更加公正、全面、合理、准确.最后给出了测评实例,取得了比较好的效果.     

多种武器攻击下舰船电力系统生命力的模糊综合评判

应用模糊数学理论对舰船电力系统生命力进行了模糊综合评判,讨论了舰船电力系统在多种武器攻击下的模糊评估模型,并以某型舰艇的电力系统为例,通过对其子系统的模糊评估分析,得出整个电力系统的生命力指标.评估的结果说明了根据加权模糊综合评判模型,可以把模糊性很强的舰船生命力指标定量化,为电力系统设计方案选优提供依据.     

电传动坦克模糊控制器仿真研究

将一种基于参数自调整的模糊控制器应用于坦克电传动系统中,并在MATLAB\SIMULINK中设计了参数自调整的模糊控制器。仿真和实验结果证明了该方案能克服原有电传动系统中常规控制不能适应大范围工况变化的弊端,具有调速范围大,鲁棒性强等特点。     

Clustering in defence-related procurement: the case of a Belgian naval construction cluster

ABSTRACT

This paper examines the importance of closer co-operation in defence-related procurement. Led by the decision that Belgium will lead the procurement of 12 Mine CounterMeasures Vessels (MCMV), the case of a potential Belgian naval construction cluster is discussed. The feasibility of a potential cluster is investigated by looking at key elements of a successful naval construction cluster, the Dutch naval construction cluster, and comparing those key elements to the current Belgian situation. Forming a sustainable Belgian naval construction cluster will be difficult. Most of the procurement process of the MCMVs is set on a European tender. In the long run, due to the absence of both a launching customer and leader firms, no party is able to carry the cluster with investments and knowledge spill-overs. In order to keep public support for large defence-related investments, clustering around the MCMV integration system and proactive cluster support is recommended.