Genetic programming (GP) has emerged as a potent evolutionary methodology for autonomously designing image classifiers and extracting relevant features. Its capacity to evolve interpretable models by ...

Practical examples and exercises help learners apply concepts to real-world projects Updated 2025 editions ensure relevance for modern science, engineering, and research tasks MATLAB is used ...

Abstract: Genetic programming (GP) and fuzzy logic are used to automatically segment mammography images. GP allows the evolution of optimized segmentation models, guided by a fuzzy logic-based fitness ...

Standard Genetic Programming: Traditional GP with tree-based evolution Structure-Based Genetic Programming: Enhanced GP that considers structural similarity during evolution The implementation is ...

The goal of gpsr is to solve symbolic regression problem using genetic programming technique. Genetic programming is a widely used machine learning method in a variety of tasks: optimization, ...

Abstract: Genetic programming (GP) has been widely applied to evolve scheduling heuristics for dynamic flexible job shop scheduling (DFJSS). However, the evaluation of GP individuals is ...