Organisms modeling: The question of radial basis function networks
2014
Massardier, Lauriane | Coquillard, Patrick
There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of systems-theory and artificial neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evaluation of an usual machine learning technique (radial basis function(RBF) networks) in the context of systems and biological reactive organisms
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书目信息
ACTIMS 2014 - ACTIVITY-BASED MODELING & SIMULATION 2014. (3)2014; Activity-Based Modeling and Simulation Workshop (ACTIMS), Zurich, CHE, 2014-01-16-2014-01-18, 9 p.
出版者
EDP Sciences
其它主题
Autre (sciences du vivant); Connaissance scientifique
语言
英语
类型
Conference Paper; Conference Part
团体作者
Muzy, Alexandre
2016-06-15
AGRIS AP
