Introducing our Latest 2022 Release – Machine Learning.
Machine learning – Build the logic of your simulation directly from your data – no need for Visual Logic! Incorporate Machine Learning algorithms directly into your simulation for routing, timing and anywhere you use a distribution.
Simul8 is already the fastest tool on the market, with the addition of machine learning we’ve just taken this to a whole new level! No more having to interrogate process owners and data sets to find the unique routing or timing rules, train your Machine Learning algorithm and let Simul8 do the rest!
We are the only simulation tool on the market to offer integrated machine learning functionality. Everyone lets you train data sets, or optimize end results. We let you use machine learning directly inside your simulation. Just call out to your preferred R or Python machine learning library to process your data set, and it’ll tell Simul8 what it should do next.
So, what is Machine Learning?
Generally speaking, Machine Learning is a group of techniques which learn from data to imitate a human being, in order to predict an outcome.
What are the benefits of Machine Learning?
Improve accuracy: ML will improve accuracy as there will be no misjudgment. The data being needed tell the story of how your process works, including any niche rules that make your process work.
Easily Maintained: Any changes to your process will be reflected in the data, you won’t need to rebuild your simulation, just a quick update to the machine learning algorithm with the new data is all that is required.
Saves time: As processes become more complex and data is becoming more and more vast, it is taking longer to analyse and understand the rules of the process. By definition, machine learning is an imitation of the data so in other words is an imitation of the rules in your process. You don’t need to spend the time doing the analysis.
Combine ML with our other killer USP Process Mining, and you have the ability to build continuously up to date, real time digital twins.