- https://www.mathworks.com/help/deeplearning/ug/train-network-with-multiple-outputs.html
- https://www.mathworks.com/help/deeplearning/ug/multiple-input-and-multiple-output-networks.html
Prediction Time series Data with LSTM Network and multiple Inputs
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Hello Together,
i am currently trying to use an LSTM Network to predict Time Series data.
So far the Training has worked out ok and now i am trying to predict data for every Input variable (12). I tried to modify and use the code which was given in the Examples, https://de.mathworks.com/help/deeplearning/ug/time-series-forecasting-using-deep-learning.html but it did not work out.
Is there anybody who has worked with this Type of Network and could help me out ? I am by no means an expert in matlab but have managed to come this far, which ist alread for my standards an achievment.
My goals for my project:
- I want to predict the Temperature and efficiency of electric motors by using an neural Network model in Simulink
- My Simulink model should contain an Neural network Block with an already Trained network based on real Trainingsdata of an electric Motor
- It should be able to predict the 12 Parameters, i will calculate the effiiciency of the Motor of the Predicted data
- It should be able to do the Predictions for any Operating point of the electrical machine
- i want to give the Simulation 3+1 inputs, so that it can calculate the rest itself
- Torque and RPM to determin the operating Point
- Time( time Steps) to determin the Operating Time of each Point
- Initial Tempreature value to let the system know in which condition its starts
I have made a small PDF with my Idea which is also attached.
i will shorty summarize what i did so far in my code that i attached
- Collecting Data in a test Rig, the longest data Set is 24 hours long
- Narrowed the input Parameters of the Network to 12 Inputs and 12 Outputs
- Load in 3 different dat sets
- Norming the Data with ist own max values
- Transformed my table in to a matrix
- created an numeric array with same sequence length of all 3 data sets
- separated the data into Training and Test data
- Created predictors and Responses with the Training Data
- created for each an Datastore
- Combined the Datastore
- Define The Network and Training Opts
- Trained the Network
- Seperated the Test data in predictors and response
- Tried to predict something with the predict function
- tried closed loop prediction with the predict and update state function
I Hope i was bale to summarize what i did. I have no idea how i should keep going to make the Prediction part work.
I would like to give you the Datasets, but they are too big to upload them here. Do you know how i can provide thme to you?
Thank You for your Help!
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Udit
2023-10-6
Hi,
I understand that you want to want to train an LSTM network with 12 inputs given to the model and the trained model should predict 12 outputs. You can train a multi-output LSTM network using a custom training loop. You can refer to the following MathWorks documentations to understand more about how to train a deep learning model having multiple inputs and multiple outputs.
I hope this helps.
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