Hi,
I'm a software engineering undergraduate.
I have a dataset which includes the numerical values of variables x,y,z and output r.
I want to create an algorithm which basically uses a prediction algorithm using neural networks and finds the relationship between x,y,z and predict r, such that when i give a new set of inputs it should predict z, this is a reactive approach.
Therefore to make it proactive, i want to look at the past data of x,y,z and r and forecast future values of z.
Can i combine two models like this and make a hybrid algorithm because sometimes we can't just use past behavior to determine? are there any usecases or papers which have used prediction and forecasting together?
Also any idea how long will it take to train both models?
Thank you.
Please have a look
https://towardsdatascience.com/an-overview-of-time-series-forecasting-models-a2fa7a358fcb
Have a look at:: Conference Paper A Prediction Model Based on Time Series Data in Intelligent ...
https://ieeexplore.ieee.org/abstract/document/4840324
https://towardsdatascience.com/the-complete-guide-to-time-series-analysis-and-forecasting-70d476bfe775
Please have a look
https://towardsdatascience.com/an-overview-of-time-series-forecasting-models-a2fa7a358fcb
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