- Setting a maximum number of generations: This involves specifying a predetermined limit on the number of generations the GA will run before terminating.
- Defining a convergence criterion: This criterion is based on a tolerance limit, where the GA is terminated when the optimal solution undergoes changes smaller than the specified tolerance value.
optimization criteria for my neural network using Genetic Algorithm
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hello all! I developed a neural network using Genetic Algorithm(GA). the fitness function of GA will be the neural network performance. I mean the less the error my GA is works well. But the Question arises when I can stop my GA hw i will define the stopping criteria for the same. please give me some suggestions.
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Umang Pandey
2023-9-21
Hi Chandrima,
From what I understand, you can fetch the fitness function values correctly from your neural network and want to determine a stopping criterion for the GA.
When it comes to defining a stopping criterion for a GA, there are several approaches that can be considered, depending on the specific optimization problem at hand. Among these approaches, two popular ones are:
These are just a couple of examples, and the choice of stopping criterion depends on the nature of the optimization problem.
For further information refer the documentation:
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