首页|Research Study Findings from University of Management and Tech- nology Update Understanding of Robotics (Computing dominant metric dimensions of certain connected networks)
Research Study Findings from University of Management and Tech- nology Update Understanding of Robotics (Computing dominant metric dimensions of certain connected networks)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Elsevier
Research findings on robotics are discussed in a new report. According to news reporting originating from Lahore, Pakistan, by NewsRx correspondents, research stated, "In the studies of the connected networks, metric dimension being a distance-based parameter got much more attention of the researches due to its wide range of applications in different areas of chemistry and computer science." The news journalists obtained a quote from the research from University of Management and Tech- nology: "At present its various types such as local metric dimension, mixed metric dimension, solid metric dimension, and dominant metric dimension have been used to solve the problems related to drug discov- eries, embedding of biological sequence data, classification of chemical compounds, linear optimization, robot navigation, differentiating the interconnected networks, detecting network motifs, image processing, source localization and sensor networking. Dominant resolving sets are better than resolving sets because they carry the property of domination. In this paper, we obtain the dominant metric dimension of wheel, gear and anti-web wheel network in the form of integral numbers. We observe that the aforesaid networks have bounded dominant metric dimension as the order of the network increases."
University of Management and TechnologyLahorePakistanAsiaEmerging TechnologiesMachine LearningRobotRobotics
NETL
NSTL
Elsevier
