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Towards Fault-Tolerant Systems based on Adaptive Cellular Genetic Algorithms

机译:朝基于自适应蜂窝遗传算法的容错系统

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This paper presents an adaptive cellular Genetic Algorithm (cGA) which aims at realizing a fault tolerant platform that determines the attitude parameters of a vehicle, based on Global Positioning System (GPS) technology. This research work investigates the inherent ability of cGAs to deal with Single Hardware Errors (SHEs) that could permanently affect the operation of a system. The proposed approach is based on measuring the genetic diversity behaviour during the evolutionary process and thus to control the exploitation/exploration tradeoff via the grid to neighbourhood ratio, a parameter specific to cGAs topologies. By appropriately controlling this parameter, the complex search space associated to the attitude determination problem is conveniently explored in terms of efficiency and efficacy.
机译:本文介绍了一种自适应蜂窝遗传算法(CGA),其目的在于实现基于全球定位系统(GPS)技术确定车辆姿态参数的容错平台。本研究工作调查了CGA处理的固有能力,处理可以永久影响系统操作的单一硬件错误(SHES)。所提出的方法是基于测量进化过程中的遗传多样性行为,从而通过网格控制开发/勘探概论,对CGA拓扑的参数。通过适当地控制该参数,在效率和功效方面,方便地探讨了与姿态确定问题相关的复杂搜索空间。

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