Research Article
An Innovative Thinking-Based Intelligent Information Fusion Algorithm
Table 3
The parameters settings of each algorithm.
| | Algorithm | Parameter setting |
| | ITIIF | = 50, = 10000, = 1,
= 1 |
| | GA | Populations = 80, iterations number = 50,
crossover probability = 0.9,
mutation probability = 0.1 |
| | EDAs | Populations = 300, iterations number = 50,
selective probability = 0.2 |
| | ACO | Information heuristic factor = 0.8,
expected heuristic factor = 0.6,
pheromone evaporation rate = 0.5 |
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