{"title":"Local Fractional Strong Metric Dimension of Certain Complex Networks","authors":"Faiza Jamil, Agha Kashif, Sohail Zafar, M. Ojiema","doi":"10.1155/2023/3635342","DOIUrl":null,"url":null,"abstract":"<jats:p>Fractional variants of distance-based parameters have application in the fields of sensor networking, robot navigation, and integer programming problems. Complex networks are exceptional networks which exhibit significant topological features and have become quintessential research area in the field of computer science, biology, and mathematics. Owing to the possibility that many real-world systems can be intelligently modeled and represented as complex networks to examine, administer and comprehend the useful information from these real-world networks. In this paper, local fractional strong metric dimension of certain complex networks is computed. Building blocks of complex networks are considered as the symmetric networks such as cyclic networks <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\">\n <msub>\n <mrow>\n <mi>C</mi>\n </mrow>\n <mrow>\n <mi>n</mi>\n </mrow>\n </msub>\n </math>\n </jats:inline-formula>, circulant networks <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\">\n <msub>\n <mrow>\n <mi>C</mi>\n </mrow>\n <mrow>\n <mi>n</mi>\n </mrow>\n </msub>\n <mfenced open=\"(\" close=\")\" separators=\"|\">\n <mrow>\n <mn>1,2</mn>\n </mrow>\n </mfenced>\n </math>\n </jats:inline-formula>, mobious ladder networks <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\">\n <msub>\n <mrow>\n <mi>M</mi>\n </mrow>\n <mrow>\n <mn>2</mn>\n <mi>n</mi>\n </mrow>\n </msub>\n </math>\n </jats:inline-formula>, and generalized prism networks <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M4\">\n <msubsup>\n <mrow>\n <mi>G</mi>\n </mrow>\n <mrow>\n <mi>m</mi>\n </mrow>\n <mrow>\n <mi>n</mi>\n </mrow>\n </msubsup>\n </math>\n </jats:inline-formula>. In this regard, it is shown that LSFMD of <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M5\">\n <msub>\n <mrow>\n <mi>C</mi>\n </mrow>\n <mrow>\n <mi>n</mi>\n </mrow>\n </msub>\n <mfenced open=\"(\" close=\")\" separators=\"|\">\n <mrow>\n <mi>n</mi>\n <mo>≥</mo>\n <mn>3</mn>\n </mrow>\n </mfenced>\n </math>\n </jats:inline-formula> and <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M6\">\n <msubsup>\n <mrow>\n <mi>G</mi>\n </mrow>\n <mrow>\n <mi>m</mi>\n </mrow>\n <mrow>\n <mi>n</mi>\n </mrow>\n </msubsup>\n <mfenced open=\"(\" close=\")\" separators=\"|\">\n <mrow>\n <mi>n</mi>\n <mo>≥</mo>\n <mn>6</mn>\n </mrow>\n </mfenced>\n </math>\n </jats:inline-formula> is 1 when <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M7\">\n <mi>n</mi>\n </math>\n </jats:inline-formula> is even and <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M8\">\n <mi>n</mi>\n <mo>/</mo>\n <mi>n</mi>\n <mo>−</mo>\n <mn>1</mn>\n </math>\n </jats:inline-formula> when <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M9\">\n <mi>n</mi>\n </math>\n </jats:inline-formula> is odd, whereas LSFMD of <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M10\">\n <msub>\n <mrow>\n <mi>M</mi>\n </mrow>\n <mrow>\n <mn>2</mn>\n <mi>n</mi>\n </mrow>\n </msub>\n </math>\n </jats:inline-formula> is 1 when <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M11\">\n <mi>n</mi>\n </math>\n </jats:inline-formula> is odd and <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M12\">\n <mi>n</mi>\n <mo>/</mo>\n <mi>n</mi>\n <mo>−</mo>\n <mn>1</mn>\n </math>\n </jats:inline-formula> when <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M13\">\n <mi>n</mi>\n </math>\n </jats:inline-formula> is even. Also, LSFMD of <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M14\">\n <msub>\n <mrow>\n <mi>C</mi>\n </mrow>\n <mrow>\n <mi>n</mi>\n </mrow>\n </msub>\n <mfenced open=\"(\" close=\")\" separators=\"|\">\n <mrow>\n <mn>1,2</mn>\n </mrow>\n </mfenced>\n </math>\n </jats:inline-formula> is <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M15\">\n <mi>n</mi>\n <mo>/</mo>\n <mn>2</mn>\n <mrow>\n <mfenced open=\"(\" close=\")\" separators=\"|\">\n <mrow>\n <mo>⌈</mo>\n <mrow>\n <mrow>\n <mi>m</mi>\n <mo>+</mo>\n <mn>1</mn>\n </mrow>\n <mo>/</mo>\n <mn>2</mn>\n </mrow>\n <mo>⌉</mo>\n </mrow>\n </mfenced>\n </mrow>\n </math>\n </jats:inline-formula> where <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M16\">\n <mi>n</mi>\n <mo>≥</mo>\n <mn>6</mn>\n </math>\n </jats:inline-formula> and <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M17\">\n <mi>m</mi>\n <mo>=</mo>\n <mo>⌈</mo>\n <mrow>\n <mrow>\n <mi>n</mi>\n <mo>−</mo>\n <mn>5</mn>\n </mrow>\n <mo>/</mo>\n <mn>4</mn>\n </mrow>\n <mo>⌉</mo>\n </math>\n </jats:inline-formula>.</jats:p>","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"68 1","pages":"3635342:1-3635342:8"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Complex psychiatry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2023/3635342","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Fractional variants of distance-based parameters have application in the fields of sensor networking, robot navigation, and integer programming problems. Complex networks are exceptional networks which exhibit significant topological features and have become quintessential research area in the field of computer science, biology, and mathematics. Owing to the possibility that many real-world systems can be intelligently modeled and represented as complex networks to examine, administer and comprehend the useful information from these real-world networks. In this paper, local fractional strong metric dimension of certain complex networks is computed. Building blocks of complex networks are considered as the symmetric networks such as cyclic networks , circulant networks , mobious ladder networks , and generalized prism networks . In this regard, it is shown that LSFMD of and is 1 when is even and when is odd, whereas LSFMD of is 1 when is odd and when is even. Also, LSFMD of is where and .
基于距离的参数的分数变量在传感器网络、机器人导航和整数规划问题等领域都有应用。复杂网络是一种表现出显著拓扑特征的特殊网络,已成为计算机科学、生物学和数学领域的典型研究领域。由于许多现实世界的系统可以被智能地建模和表示为复杂的网络,以检查、管理和理解来自这些现实世界网络的有用信息。本文计算了一类复杂网络的局部分数阶强度量维数。复杂网络的构建块被认为是对称网络,如循环网络C n,循环网络C n 1,2,水陆梯网m2n;广义棱镜网络G m n。在这方面,表明C n n的LSFMD≥3G m n n≥6n为偶数时为1 n为奇数时为n / n - 1,而m2n的LSFMD在n为奇数和n时为1当n为偶数时,为/ n−1。 同时,c1(1,2)的LSFMD等于n /2 (m + 1 / 2其中,n≥6,m =≤n−5 / 4;