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To adjust the models to the constraints imposed by the electrophysiological data, we optimised the model parameters by means of an optimisation method.
The parameters studied were optimized using Taguchi Optimisation Method.
This study presents an optimisation method for improving greenhouse design.
The polynomial robust H∞ optimisation method is used in design.
The analytical optimisation method comprises of three steps.
A simple test with gradient descent optimisation run from randomly selected initial positions in the search space shows that a more powerful optimisation method is required.
The Cross Entropy optimisation method has been adapted here to address this calibration problem.
A two-step optimisation method was developed to determine the position and dimension of each riser.
The model parameters were identified from the experimental data using a hybrid optimisation method.
Comparing the obtained optimal results with other articles justifies the proposed optimisation method.
The optimisation method is based on a genetic algorithm supported by an elitist strategy.
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