Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

CAD, or computer-aided design, has transformed design in many fields, allowing simulation and numerical data modeling in industries such as architecture, engineering, construction, product design and ...

This course explores computational design methodologies, focusing on parametric modelling and generative algorithms powered by AI for construction design projects. Students will be exposed to the use ...

Using the computer to design objects by modeling their components with real-world behaviors and attributes. Typically specialized for either mechanical design or building design, a parametric modeler ...

Many phase-averaged parametric nearshore wave models are based on the energy balance concept and use linear wave theory to calculate wave parameters (e.g., wave energy, wave height, wave setup). For a ...

This is a preview. Log in through your library . Abstract Since longitudinal and survival data are often obtained together in applications, studies on joint modelling that reveal the relationship ...

We all know and love OpenSCAD for its sweet sweet parametrical goodness. However, it’s possible to get some of that same goodness out of Fusion 360. To do this we will be making a mathematical model ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...