Simulation of the Effect of Texture on Anisotropy in SLM-Produced IN 718 Microstructures
Explore the source record for details and available documents.
Engineering topics
Publications and source records attributed to Jacob Dean Hochhalter.
Explore the source record for details and available documents.
In this paper, we introduce Bingo, a flexible and customizable yet performant Python framework for symbolic regression with genetic programming. Bingo maintains a modular code structure for simple abstraction and easily swappable components. Fitness functions, selection methods, and constant optimization methods allow for easy problem-specific customization. Bingo also maintains several features for increased efficiency such as parallelism, equation simplification, and a C++ backend. We compare Bingo’s performance to other genetic programming for symbolic regression (GPSR) methods to show that it is both competitive and flexible.