Novel moderate transformation of fuzzy membership function into basic belief assignment

In information fusion, the uncertain information from different sources might be modeled with different theoretical frameworks. When one needs to fuse the uncertain information represented by different uncertainty theories, constructing the transformation between different frameworks is crucial. Various transformations of a Fuzzy Membership Function (FMF) into a Basic Belief Assignment (BBA) have been proposed, where the transformations based on uncertainty maximization and minimization can determine the BBA without preselecting the focal elements. However, these two transformations that based on uncertainty optimization emphasize the extreme cases of uncertainty. To avoid extreme attitudinal bias, a trade-off or moderate BBA with the uncertainty degree between the minimal and maximal ones is more preferred. In this paper, two moderate transformations of an FMF into a trade-off BBA are proposed. One is the weighted average based transformation and the other is the optimization-based transformation with weighting mechanism, where the weighting factor can be user-specified or determined with some prior information. The rationality and effectiveness of our transformations are verified through numerical examples and classification examples.     

基于改进狼群算法的多无人机协同多目标分配CSCD

针对现代空战多无人机协同多目标任务分配问题,结合标准狼群算法,提出了一种改进狼群算法的多目标任务分配方法。根据狼群的不同分工以及搜索属性,建立了基于自主游走机制的头狼产生规则、基于多策略知识库的探狼游走机制和基于自适应步长的猛狼奔袭及围攻方式,从而对传统狼群算法的随机性进行智能化约束与控制,以解决多无人机协同多目标任务分配问题。数值仿真结果表明,该方法能够快速有效获得任务分配方案,避免陷入局部最优。     

大气环境监测卫星地方时控制策略优化

针对大气环境监测卫星地方时的控制和优化问题，从太阳同步轨道卫星的地方时漂移规律入手，建立了地方时漂移估计模型，给出了通过改变倾角来调节地方时漂移的控制策略。在此基础上，采用遗传算法对控制策略进行了优化，讨论了相关算子的选择，最终得到了燃料有限情况下的最优控制曲线。优化结果表明:不限燃料情况下，大气环境监测卫星可通过寿命内一次倾角控制实现小于6.6 min的地方时偏差。此外，为了保证地方时偏差小于15 min的指标要求，卫星至少需要进行一次0.07°的倾角控制。