Graph-Theoretic Techniques for the Study of Structures or Networks in Engineering
1Anhui Jianzhu University, Hefei, China
2Louisiana College, Pineville, USA
3University of Management and Technology, Lahore, Pakistan
Graph-Theoretic Techniques for the Study of Structures or Networks in Engineering
Description
Graph-theoretic techniques based on the properties of distance and valency of destinations, atoms, nodes, or vertices in the form of equations, polynomials, or matrices play a vital role in the studies of the physical and chemical properties of structures or networks in computer, bio, chemical and pharmaceutical industrial engineering.
Some of the familiar techniques are topological indices, metric bases, labelling, pebbling, energy, entropy, domination, and spectrum, which are used to find the accessibility, centrality, clustering, complexity, connectivity, modularity, robustness, vulnerability, stability, and solubility of computer-based networks in computer engineering. These are also used to discover drugs in pharmaceutical industrial engineering and predict the density, heat of evaporation, melting (boiling or freezing) point, surface tension, critical temperature, recognition, diffusion, and formation of chemical compounds involved in the chemical structures related to bio and chemical engineering.
The aim of this Special Issue is to attract original research contributions and comprehensive reviews on graph-theoretic techniques for various engineering-based structures or networks, for example, chemical entropy, security, irrigation, robotic, vehicle tracking, automated street lighting, temperature/humidity detection, communication and neural networks. We encourage submissions of theoretical as well as applied investigations.
Potential topics include but are not limited to the following:
- Computation of spectrum of networks
- Evaluation of energy and entropy of networks
- Calculation of degree and distance-based topological indices of networks
- Coding, decoding, domination, and labeling of networks
- Computational analysis of metric dimensions of networks