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daa seminar[1].pptx_SQL _UNIT_DBMS_PRESENTSTATION
- 1. Graph Algorithms: A Visual Guide A visual journey through key graph algorithms. Explore examples and applications for easy understanding. We'll simplify complex concepts for clear insights. By, Komeshdharun Mahendran(RA2311003012109)
- 2. Introduction to Graph Theory Graphs Composed of nodes (vertices) and connections (edges). Real-World Applications • Networks • Maps • Relationships Graphs are fundamental structures for representing relationships.
- 3. Types of Graphs Directed One-way connections. Undirected Two-way connections. Weighted Edges with values. Unweighted Edges without values. Different types of graphs cater to various relationship types.
- 4. Graph Coloring: What is it? Node Assignment Assign colors to nodes. Constraint No adjacent nodes share the same color. Applications • Map coloring • Scheduling • Register allocation Graph coloring optimizes resource allocation and minimizes conflicts.
- 5. Applications of Graph Coloring Map Coloring Minimize colors and ensure clear boundaries. Scheduling Assign tasks efficiently and allocate resources. Register Allocation Optimize compiler performance. Graph coloring plays a vital role in resource optimization.
- 6. Greedy Coloring Algorithm Approach Simple, intuitive method. Process Assign the first available color. Greedy coloring provides a fast, effective coloring solution.
- 7. Greedy Coloring Example 1 Nodes & Edges Example graph with nodes and edges. 2 Color Assignment Walkthrough of color assignment. 3 Result Colored graph: no adjacent nodes share color. Visualizing the Greedy algorithm ensures effective coloring.
- 8. Depth First Search (DFS): Overview Traversal Algorithm for traversing a graph. 1 Exploration Explores as far as possible along each branch. 2 Mechanism Uses a stack (implicit recursion). 3 DFS efficiently explores graph structures recursively.
- 14. Complexity of Depth First Search The time complexity of the DFS algorithm is represented in the form of O(V + E), where V is the number of nodes and E is the number of edges. The space complexity of the algorithm is O(V).
- 15. DFS Step-by-Step 1 Start Node Mark as visited. 2 Explore Unvisited neighbors recursively. DFS traverses graphs by diving deep into each branch.
- 16. Summary and Conclusion 3 Algorithms Covered key graph algorithms. DFS Algorithms Graph coloring, Greedy coloring, DFS. Real-World Relevance Applications and real-world relevance. These algorithms solve real-world optimization problems.