Metric dimension is one of the distance-based parameters which are used to find the position of the robot in a network space by utilizing lesser number of notes and minimum consumption of time. It is also used to characterize the chemical compounds. The metric dimension has a wide range of applications in the field of computer science such as integer programming, radar tracking, pattern recognition, robot navigation, and image processing. A vertex in a network resolves the adjacent pair of vertices if attains an unequal distance from end points of . A local resolving neighbourhood set is a set of vertices of which resolve . A mapping is called local resolving function of if for any adjacent pair of vertices of of and the minimal value of for all local resolving functions of is called local fractional metric dimension of . In this paper, we have studied the local fractional metric dimension of wheel-related networks such as web-wheel network, subdivision of wheel network, line network of subdivision of wheel network, and double-wheel network and also examined their boundedness.

中文翻译：

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某些轮网络的基于距离的分数维数

度量维度是基于距离的参数之一，用于利用较少数量的音符和最少的时间消耗来找到机器人在网络空间中的位置。它还用于表征化合物。度量维度在整数规划、雷达跟踪、模式识别、机器人导航和图像处理等计算机科学领域有着广泛的应用。如果网络中的顶点到 的端点的距离不相等，则它会解析相邻的顶点对。局部解析邻域集是解析的顶点的集合。一个映射称为if的局部解析函数对于 的任何相邻顶点对以及的所有局部解析函数的最小值称为的局部分数度量维数。在本文中，我们研究了轮相关网络的局部分数度量维数，例如网轮网络、轮网络细分、轮网络细分线网络和双轮网络，并检验了它们的有界性。