Introduction In the aerospace industry, there are two ways to collecting data: ModSim (modeling and simulation) or physical experiments. As discussed in previous articles, it can be very expensive in time and resources to design and execute a large experiment; to...
In a previous discussion on optimization, we touched on the importance of optimization within complex systems. To tackle such these non-intuitive problems, we were introduced to man-made and nature-inspired techniques. Topping the list of nature-inspired algorithms...
In our last discussion, we took a look at linear regressions using a marketing example centered around monthly sales. In addition to being able to fit our previous data sales, we’d also backed out a linear fit (with [math] r^2 = 0.965 [/math] that we could use...
Intro. to Linear Regressions One of the first concepts that people often learn in artificial intelligence (AI) and machine learning (ML) is the concept of linear regressions. This is largely due to the fact that many AI and ML algorithms optimize for a...
Introduction Our blog post on synthetic scene generation discussed the power of modeling realistic objects like terrain and vehicles, applying material attribution, using the objects within a scene to simulate physics of a highly specific scenario. A second blog...
