scholarly journals Radio Reciprocal Membership Function on Cycle Related Graphs

2019 ◽  
Vol 8 (4) ◽  
pp. 626-628
Keyword(s):  
Membership Function ◽  
Graph Labeling ◽  
New Approach ◽  
Wheel Graph ◽  
Fan Graph ◽  
Radio Labeling

Radio labeling is graph labeling which deals with nodes of a graph. A new approach fuzzy radio reciprocal labeling proposed. Fuzzy radio reciprocal labeling deals with membership function [0,1] for every vertex and edge for making flexible which is stand for by -1 FRL .Fuzzy radio reciprocal labeling is determined for fan graph and wheel graph

Research on a New Type of Integral Sum Graph with the Sequence Label Method

2013 ◽  
Vol 340 ◽  
pp. 542-545
Author(s):  
Duan Yin Shi ◽  
Xiao Peng Zhang ◽  
Wen Yu Li
Keyword(s):  
Data Structure ◽  
Point Of View ◽  
Graph Labeling ◽  
Practical Point ◽  
Label Method ◽  
Alternative Method ◽  
New Type ◽  
Fan Graph

Integral sum graph was introduced by Harary. This theory is a labeling of graph. From a practical point of view, integral sum graph labeling can be used as a compressed representation of a graph, a data structure for representing the graph, and an alternative method for defining and storing graphs. In this paper, to give an integral sum labeling of fan graph, and to prove that all multiple composite fan graph are integral sum graphs with the sequence label method.

scholarly journals Applications of mathematical programming in graceful labeling of graphs

2004 ◽  
Vol 2004 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Kourosh Eshghi ◽  
Parham Azimi
Keyword(s):  
Mathematical Programming ◽  
Graph Labeling ◽  
Computational Results ◽  
Programming Technique ◽  
New Approach ◽  
Graceful Labeling ◽  
Applications Of Mathematical Programming ◽  
The Subject ◽  
Mathematical Programming Technique ◽  
Special Classes

Graceful labeling is one of the best known labeling methods of graphs. Despite the large number of papers published on the subject of graph labeling, there are few particular techniques to be used by researchers to gracefully label graphs. In this paper, first a new approach based on the mathematical programming technique is presented to model the graceful labeling problem. Then a “branching method” is developed to solve the problem for special classes of graphs. Computational results show the efficiency of the proposed algorithm for different classes of graphs. One of the interesting results of our model is in the class of trees. The largest tree known to be graceful has at most 27 vertices but our model can easily solve the graceful labeling for trees with 40 vertices.

scholarly journals Super cyclic antimagic covering for some families of graphs

2021 ◽  
Vol 5 (1) ◽  
pp. 27-33
Author(s):  
Muhammad Numan ◽  
◽  
Saad Ihsan Butt ◽  
Amir Taimur ◽  
◽  
...  
Keyword(s):  
Coding Theory ◽  
Necessary Conditions ◽  
Graph Labeling ◽  
Computer Networking ◽  
Wheel Graph ◽  
Scheme Theory

Graph labeling plays an important role in different branches of sciences. It gives useable information in the study of radar, missile and rocket theory. In scheme theory, coding theory and computer networking graph labeling is widely employed. In the present paper, we find necessary conditions for the octagonal planner map and multiple wheel graph to be super cyclic antimagic cover and then discuss their super cyclic antimagic covering.

A Study on Radio Labeling of Diameter N-2 and Caterpillar Graphs

2018 ◽  
Vol 6 (8) ◽  
pp. 30
Author(s):  
M. Shakila ◽  
N. Rajakumari
Keyword(s):  
Chromatic Number ◽  
Basic Type ◽  
Graph Labeling ◽  
Vertex Coloring ◽  
Not Given ◽  
Minimum Value ◽  
Caterpillar Graphs ◽  
Radio Labeling

Radio labeling of graphs is a specific type of graph labeling. The basic type of graph labeling is vertex coloring; this is where the vertices of a graph G are assigned different colors so that adjacent vertices are not given the same color. A k-coloring of a graph G is a coloring that uses k colors. The chromatic number of a graph G is the minimum value for k such that a k-coloring exists for G [2].

scholarly journals On the local metric dimension of t-fold wheel, Pn o Km, and generalized fan

2018 ◽  
Vol 2 (2) ◽  
pp. 88
Author(s):  
Rokhana Ayu Solekhah ◽  
Tri Atmojo Kusmayadi
Keyword(s):  
Connected Graph ◽  
Ordered Set ◽  
Metric Dimension ◽  
Minimum Cardinality ◽  
Wheel Graph ◽  
Metric Set ◽  
Metric Basis ◽  
Fan Graph

<p>Let <span class="math"><em>G</em></span> be a connected graph and let <span class="math"><em>u</em>, <em>v</em></span> <span class="math"> ∈ </span> <span class="math"><em>V</em>(<em>G</em>)</span>. For an ordered set <span class="math"><em>W</em> = {<em>w</em><sub>1</sub>, <em>w</em><sub>2</sub>, ..., <em>w</em><sub><em>n</em></sub>}</span> of <span class="math"><em>n</em></span> distinct vertices in <span class="math"><em>G</em></span>, the representation of a vertex <span class="math"><em>v</em></span> of <span class="math"><em>G</em></span> with respect to <span class="math"><em>W</em></span> is the <span class="math"><em>n</em></span>-vector <span class="math"><em>r</em>(<em>v</em>∣<em>W</em>) = (<em>d</em>(<em>v</em>, <em>w</em><sub>1</sub>), <em>d</em>(<em>v</em>, <em>w</em><sub>2</sub>), ..., </span> <span class="math"><em>d</em>(<em>v</em>, <em>w</em><sub><em>n</em></sub>))</span>, where <span class="math"><em>d</em>(<em>v</em>, <em>w</em><sub><em>i</em></sub>)</span> is the distance between <span class="math"><em>v</em></span> and <span class="math"><em>w</em><sub><em>i</em></sub></span> for <span class="math">1 ≤ <em>i</em> ≤ <em>n</em></span>. The set <span class="math"><em>W</em></span> is a local metric set of <span class="math"><em>G</em></span> if <span class="math"><em>r</em>(<em>u</em> ∣ <em>W</em>) ≠ <em>r</em>(<em>v</em> ∣ <em>W</em>)</span> for every pair <span class="math"><em>u</em>, <em>v</em></span> of adjacent vertices of <span class="math"><em>G</em></span>. The local metric set of <span class="math"><em>G</em></span> with minimum cardinality is called a local metric basis for <span class="math"><em>G</em></span> and its cardinality is called a local metric dimension, denoted by <span class="math"><em>l</em><em>m</em><em>d</em>(<em>G</em>)</span>. In this paper we determine the local metric dimension of a <span class="math"><em>t</em></span>-fold wheel graph, <span class="math"><em>P</em><sub><em>n</em></sub></span> <span class="math"> ⊙ </span> <span class="math"><em>K</em><sub><em>m</em></sub></span> graph, and generalized fan graph.</p>

A Robust Operator Functional State Fuzzy Modeling Approach Based on EEG Data

2014 ◽  
Vol 556-562 ◽  
pp. 4065-4068
Author(s):  
Shao Zeng Yang ◽  
Jian Hua Zhang
Keyword(s):  
Membership Function ◽  
Functional State ◽  
Fuzzy Model ◽  
Fuzzy Modeling ◽  
Crossover Point ◽  
New Approach ◽  
Fuzzy Models ◽  
Eeg Data ◽  
Operator Functional State ◽  
Machine Systems

Operator functional state (OFS) is defined as the time-variable ability that an operator completes his/her assigned tasks. To evaluate the OFS in safety-critical human-machine systems, it is modeled by using the Wang-Mendel-based fuzzy system paradigm in this paper. The fuzzy model is constructed to correlate three EEG features (as model inputs) to the human-machine system performance (as model output). To derive a fuzzy model for real-time OFS assessment, the Gaussian membership function membership crossover point membership gradeδis found to be an essential parameter that controls the robustness of data-driven fuzzy models. The fuzzy models with differentδare applied to the OFS fuzzy modeling. The results have demonstrated that an appropriate value ofδcan be selected to derive robust fuzzy models. Compare with the results obtained by fuzzy models based on symmetric Gaussian membership functions, the new approach based on asymmetric Gaussian membership function leads to considerably improved robustness performance.

scholarly journals Wiener Index of Gear Fan Graph and Gear Wheel Graph

2014 ◽  
Vol 26 (11) ◽  
pp. 3397-3400 ◽  
Author(s):  
Wei Gao ◽  
Li Shi
Keyword(s):  
Gear Wheel ◽  
Wiener Index ◽  
Wheel Graph ◽  
Fan Graph
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