An improved swarm optimization for parameter estimation and biological model selection.
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incor...
Saved in:
Main Authors: | Afnizanfaizal Abdullah, Safaai Deris, Mohd Saberi Mohamad, Sohail Anwar |
---|---|
Format: | article |
Language: | EN |
Published: |
Public Library of Science (PLoS)
2013
|
Subjects: | |
Online Access: | https://doaj.org/article/de9f0fbcefc84d808b9b0493e0153a3f |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Differential Bees Flux Balance Analysis with OptKnock for in silico microbial strains optimization.
by: Yee Wen Choon, et al.
Published: (2014) -
Development of an Artificial Neural Network Utilizing Particle Swarm Optimization for Modeling the Spray Drying of Coconut Milk
by: Jesse Lee Kar Ming, et al.
Published: (2021) -
Parameter identification of sound absorption model of porous materials based on modified particle swarm optimization algorithm.
by: Xiaomei Xu, et al.
Published: (2021) -
Particle Swarm Optimization (PSO) Model for Hydroponics pH Control System
by: Mohammad Farid Saaid, et al.
Published: (2021) -
Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization
by: Yukai Chen, et al.
Published: (2021)