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Fuzzy system reliability computation of the convoy of unmanned intelligent vehicles

机译:无人智能车车队的模糊系统可靠性计算

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Unmanned intelligent ground vehicles play significant role in wide range of applications. They are of great significance in military applications as well as other commercial applications. In order to assure the performance of unmanned intelligent vehicles, it is important to predict the reliability of the system. Reliability can be calculated using different approaches as seen in the literature, but we propose a Graph theoretic approach supported by Fuzzy and Neuro-Fuzzy approaches for predicting the node and branch reliability of the system. We portray the convoy of unmanned vehicles as a communication network where the nodes represent the station of the convoy of unmanned intelligent vehicles and the branches would represent the path between two stations. The node and branch reliability is calculated using the Fuzzy and Neuro Fuzzy approaches. The terminal and system reliability would be calculated using Boolean algebra. Thus the overall system reliability of a convoy of vehicles is the result of Fuzzy, Neuro-Fuzzy and Boolean approaches. A spanning tree based algorithm is proposed for computation of the system reliability of a convoy of vehicles. We also propose to simulate the overall system reliability with some existing data of factors that contribute in computation of node and branch reliability.
机译:无人驾驶智能地面车辆在广泛的应用中起着重要作用。它们在军事应用以及其他商业应用中都具有重要意义。为了确保无人驾驶智能车辆的性能,重要的是预测系统的可靠性。可以使用文献中看到的不同方法来计算可靠性,但是我们提出了一种由Fuzzy和Neuro-Fuzzy方法支持的图论方法来预测系统的节点和分支可靠性。我们将无人驾驶车队描绘成一个通信网络,其中节点代表无人驾驶智能车车队的站点,而分支则代表两个站点之间的路径。使用模糊和神经模糊方法计算节点和分支的可靠性。终端和系统可靠性将使用布尔代数来计算。因此,车队的整体系统可靠性是模糊,神经模糊和布尔方法的结果。提出了一种基于生成树的算法来计算车队的系统可靠性。我们还建议使用一些有助于节点和分支可靠性计算的因素的现有数据来模拟总体系统可靠性。

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