The second option allows the optimization of the FIS elements: MF bound location for fuzzy inputs and outputs, rule conclusions. The Solis and Wetts method is available. It is a mono agent evolutionist strategy. The reference [7] gives the detailed algorithms. It is available in two forms:
In any case the optimization procedure does not find the absolute best solution, but one among the solutions corresponding to the given criteria.
Possible constraints
Whatever the FIS element to optimize, the optimization is based on the FIS performance improvement.
The algorithm can be sumitted to some user defined constraints. The solutions found will onlu=y be retained if they satisfy the constraints.
Parameters:
A higher value will increase the success rate of the procedure.
Impose a minimum distance between the centers of two adjacent MFs. The value is between 0 and 1, and represents a fraction of the total range.
The default value is 0.000001 and corresponds to no constraint.
With this constraint, MF bounds are not allowed to move away from their initial values further than
, where nmf is the number of fuzzy sets within the partition.
Opens a popup window allowing to set some parameters to control the algorithm.
Initialize the random generator.
Raise this number if needed to increase the chances for the search algorithm to find a valid solution.
The solutions found by the algorithm are kept only if the constraints are respected.
Check the checkboxes to choose the FIS elements to optimize.
This checkbox preselects/unselects all MFs for all inputs.
If this checkbox is checked, the partitions are standardized fuzzy partitions, which guarantees the respect of the semantic [4] and the rule interpretability.
For each input, each MF is listed with a checkbox to select/unselect it.
For the output:
For a fuzzy output, check/uncheck Standard (for Standard Fuzzy Partition) and select the MFs to optimize, as for inputs.
For each rule, checkbox to select/unselect it. The selected rules will have their conclusion optimized.
If the output is crisp, the Limited vocabulary in FIS option restraints the conclusion values to a permutation of the initial values given in the FIS configuration. Otherwise, the conclusions can take any value.
Displays the key for a copy/paste operation, to reuse it as an argument of the fisopt program.
Result
In case of success, the procedure creates a new optimized FIS, which is opened in a new window. Otherwise, a warning is displayed.
Advice for users
The optimization procedure does not find the absolute best solution, but one solution corresponding to the given criteria.
It is advisable to proceed with successive steps, rather than to optimize everything at once. It is always possible to iterate the optimization procedure, by reusing the FIS created at the previous optimization step.