200 likes | 297 Views
This study presents an iterative algorithm for data processing enhancement, showcasing the effectiveness of distinct cutting and cycling rules. By analyzing iterations and rules, explore methods to optimize data handling for improved outcomes.
E N D
3 2 1 6 4 5 8 7 MST Instance
Iteration 1: Blue Rule 3 2 1 Cut = {1, 2} 6 4 5 8 7
Iteration 1: Blue Rule 3 2 1 Cut = {1, 2} 6 4 5 8 7
Iteration 2: Blue Rule 3 2 Cut = {3} 1 6 4 5 8 7
Iteration 2: Blue Rule 3 2 Cut = {3} 1 6 4 5 8 7
Iteration 3: Red Rule 3 2 1 Cycle = {3, 4, 5} 6 4 5 8 7
Iteration 3: Red Rule 3 2 1 Cycle = {3, 4, 5} 6 4 5 8 7
Iteration 4: Red Rule 3 2 1 Cycle = 1-2-3-6 6 4 5 8 7
Iteration 4: Red Rule 3 2 1 Cycle = 1-2-3-6 6 4 5 8 7
Iteration 5: Blue Rule 3 2 1 Cut = 1-2-6 6 4 5 8 7
Iteration 5: Blue Rule 3 2 1 Cut = 1-2-6 6 4 5 8 7
Iteration 6: Blue Rule 3 2 1 Cut = 1-2-5-6-7 6 4 5 8 7
Iteration 6: Blue Rule 3 2 1 Cut = 1-2-5-6-7 6 4 5 8 7
Iteration 7: Red Rule 3 2 1 Cycle = 1-2-3-4-5-6-1 6 4 5 8 7
Iteration 7: Red Rule 3 2 1 Cycle = 1-2-3-4-5-6-1 6 4 5 8 7
Iteration 8: Blue Rule 3 2 1 Cut = {2, 7} 6 4 5 8 7
Iteration 8: Blue Rule 3 2 1 Cut = {2, 7} 6 4 5 8 7
After Iteration 14 3 2 1 6 4 5 8 7
MST 3 2 1 6 4 5 8 7