Overview of Neural Networks with Simulation Modeling
Artificial intelligence has gone from being a buzzword to an integral part of the application of digital transformation processes within the industrial sector. Today, digital transformative solutions leverage the use of AI subsets such as Neural Networks to manage repetitive tasks and simplify complex computing processes.
The Overview of Neural Network video provides a demonstration of how Simio discrete event simulation and digital twin software expand the use of feed-forward regression NN models to solve complex design and operational problems. Simio’s extensive tools for utilizing and training NN, as well as, creating training data sets of neural networks empower developers with a powerful solution to leverage both simulation modeling and neural networks to solve real-world problems.
A defining feature of Simio’s support for neural networks is providing you with the option to import NN algorithms in the ONNX format to evaluate NN models. This supportive feature ensures you can develop NN networks externally and deploy them within accurate virtual representations of your facilities to evaluate their decision-making capabilities in the real-world.
Another defining feature Simio Software offers is the no-code neural network development process. The no-code process empowers developers to create NN models without having to encounter complex coding challenges. Once created, you have the option to train and evaluate your NN models directly using the Simio Trainer feature. You can also choose to export the developed model as an ONNX file to a third-party platform.
The ability to generate curated training data sets from Simio simulation models eliminates the challenges of generating the clean data every NN model requires to optimize its decision-making capabilities. Training data sets from Simio can be used to train your Neural Network within Simio and any other third-party application.Simio enables the import of ONNX NN models and the export of training data and NN models to support the research and evaluation projects of everyone taking advantage of the convergence of simulation modeling and artificial intelligence.