This work aims to extend the technique of Model Based Testing to assign priorities to test cases, so generated from various UML (2.0) diagrams,according to their significance or probability of ...

Model-based models use data-driven algorithms to adapt and generalize, making them powerful for complex problems. However, they can demand significant data, computational resources, and may lack ...

As OEMs and machine builders continue to search for advantages in the digital age, the use of model-based design - an approach involving, at it's core, the ...

This algorithm is based on the combination of the nonsmooth optimization method and an incremental approach, which involves the auxiliary SSC problem. The algorithm constructs clusters incrementally ...

Abstract: In this paper, three model-based fault diagnosis algorithms for robotic systems are designed, compared, simulated, and implemented. The first algorithm is based on a nonlinear adaptive ...

It is very simple for an algorithm to produce a model with a 90% accuracy level. It can be very difficult to train this algorithm to increase the accuracy to 95% or higher. When making decisions based ...