Computer Science – Neural and Evolutionary Computing
Scientific paper
2009-06-26
Computer Science
Neural and Evolutionary Computing
21 pages; 10 figures; 14 tables
Scientific paper
The design and the implementation of a genetic algorithm are described. The applicability domain is on structure-activity relationships expressed as multiple linear regressions and predictor variables are from families of structure-based molecular descriptors. An experiment to compare different selection and survival strategies was designed and realized. The genetic algorithm was run using the designed experiment on a set of 206 polychlorinated biphenyls searching on structure-activity relationships having known the measured octanol-water partition coefficients and a family of molecular descriptors. The experiment shows that different selection and survival strategies create different partitions on the entire population of all possible genotypes.
No associations
LandOfFree
A genetic algorithm for structure-activity relationships: software implementation does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A genetic algorithm for structure-activity relationships: software implementation, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A genetic algorithm for structure-activity relationships: software implementation will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-670447