Genetic algorithms for modelling and optimisation

By J. Mccall. 2005

974 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Immunology

View Paper: https://www.semanticscholar.org/paper/7b9fc37fd3430c2bf2d3b1eb2049226df13a55e4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Goran Oreski
2. Stjepan Oreski

In Immunology

1. Goran Oreski
2. Stjepan Oreski

Citations in the corpus

• Genetic algorithm-based heuristic for feature selection in credit risk assessment (2014, background): “Genetic algorithms (GAs) can be described as a heuristic search and optimisation technique that is inspired by natural evolution (McCall, 2005), which transposes the notions of natural evolution to the world of computers and imitates natural evolution.”