Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mi...

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Detalles Bibliográficos
Autores principales: MotieGhader, Habib, Gharaghani, Sajjad, Masoudi-Sobhanzadeh, Yosef, Masoudi-Nejad, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shaheed Beheshti University of Medical Sciences 2017
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5603862/
https://www.ncbi.nlm.nih.gov/pubmed/28979308

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5603862/
https://www.ncbi.nlm.nih.gov/pubmed/28979308

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