Dear sir/Madam
I am trying the foolowing idea:
Data_Driven multi-objective optimization:
https://gekko.readthedocs.io/en/latest/ml.html
Machine Learning
Gekko specializes in optimization, dynamic simulation, and control.
The ML module in GEKKO interfaces compatible machine learning algorithms into the optimization suite
to be used for data-based optimization. Trained models from scikit-learn, gpflow, nonconformist,
and tensorflow are imported into Gekko for design optimization, model predictive control,
and physics-informed hybrid modeling.
"""
My main Target is I have 4 decison variable data and two column objective function data.
and I want to train first and then interfacing with GEKKO OptimiZation suite with following link ML models
link: https://gekko.readthedocs.io/en/latest/ml.html
Please help me fro problem of data-driven Multi-objective optimization using GEKKO and ML model trainings.
I can attach the code if someone willing to help me.
with best regards
Siye Kahsay I'd be delighted to assist you with any data-driven multi-objective optimization issue utilizing GEKKO and machine learning models.
The initial stage would be to train a machine learning model using the data from your choice variables and goal functions. You can use any GEKKO-compatible machine learning library, such as scikit-learn, gpflow, nonconformist, or tensorflow.
After training the model, you may import it into GEKKO using the ML module. The model may then be used to create predictions and optimize the decision variables in order to minimize the objective functions.
I would be better positioned to offer a more extensive and precise answer if you could share additional specifics about your unique use case and any code you have produced so far.
To perform data-driven multi-objective optimization using GEKKO and ML model training, you can follow these steps:
I would like to connect with you to expand my research network. It would be great to exchange knowledge and collaborate on potential projects in the future. Let me know if you're interested in connecting, and I look forward to hearing from you!
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