Use neural network model in function for optimizing some variables in Python

Question

1.00/5 (1 vote)

See more:

, +

I have a neural network model (model.predict in code) which fitted our data, and now we want optimized some variables that exist in the model. my code are attached below,

def objective_function(X):
  wob   = X[0]
  torque= X[1]
  RPM   = X[2]
  pump  = X[3]
  input = pd.DataFrame(wob,torque,RPM, 0.00017,0.027,pump,0,0.5,0.386,0.026,0.0119,0.33,0.83,0.48)
  obj= model.predict(input)
  return obj

I want to know my function code is correct or not?

What I have tried:

you can see the code, I attached the code. I'm not expert in python, unfortunately.

Posted 9-Feb-22 23:22pm

Member 15530401

Updated 9-Feb-22 23:23pm

v2

Add a Solution

Comments

Richard MacCutchan 10-Feb-22 5:47am

"I want to know my function code is correct or not?"
What results does it produce?

Member 15530401 10-Feb-22 8:17am

I want to use this function as a function of the simulated annealing algorithm for optimization 4 variables (wob, torque, RPM, pump). Describing function is my first stage for using the SA algorithm. I want to know, describing functions like the above code, is correct or not. for example, I introduce input in dataframe format for the entrance of neural network (model. predict), I want to know, all of these are correct or have a problem somewhere.

Add your solution here

Treat my content as plain text, not as HTML

Preview 0

…

Existing Members

Sign in to your account

...or Join us

Download, Vote, Comment, Publish.

Your Email
Password
Forgot your password?

Your Email
This email is in use. Do you need your password?
Optional Password

I have read and agree to the Terms of Service and Privacy Policy
Please subscribe me to the CodeProject newsletters

When answering a question please:

Read the question carefully.
Understand that English isn't everyone's first language so be lenient of bad spelling and grammar.
If a question is poorly phrased then either ask for clarification, ignore it, or edit the question and fix the problem. Insults are not welcome.
Don't tell someone to read the manual. Chances are they have and don't get it. Provide an answer or move on to the next question.

Let's work to help developers, not make them feel stupid.

This content, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)