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About Graph Theory Recent Applications
<p>This volume is a small yet unique contribution to graph theory applications and modeling with graphs. The subjects discussed include information hiding using graphs, dynamic graph-based systems to model and control cyber-physical systems, graph reconstruction, average distance neighborhood graphs, and pure and mixed-integer linear programming formulations to cluster networks.</p><p>Graph theory, being a rigorously investigated field of combinatorial mathematics, is adopted by a wide variety of disciplines addressing a plethora of real-world applications. Advances in graph algorithms and software implementations have made graph theory accessible to a larger community of interest. Ever-increasing interest in machine learning and model deployments for network data demands a coherent selection of topics rewarding a fresh, up-to-date summary of the theory and fruitful applications to probe further.</p><p>Contents<br>1. Graph Models in Information Hiding<br>2. A Dynamic Graph-Based Systems Framework for Modeling, and Control of Cyber-Physical Systems Typified by Buildings<br>3. Reconstruction of Graphs<br>4. On Average Distance of Neighborhood Graphs and Its Applications<br>5. Clustering Network Data Using Mixed Integer Linear Programming</p>
Detailed Information
| Author: | ,,, |
|---|---|
| Publication Year: | 2022 |
| ISBN: | 1839695277 |
| Pages: | 87 |
| Language: | other |
| File Size: | 6.3415 |
| Format: | |
| Price: | FREE |
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