The superior fault tolerance of artificial neural network training with a fault/noise injection-based genetic algorithm

The superior fault tolerance of artificial neural network training with a fault/noise injection-based genetic algorithm

Abstract Artificial neural networks (ANNs) are powerful computational tools that are designed to replicate the human brain and adopted to solve a variety of problems in many different fields. Fault tolerance (FT), an important property of ANNs, ensures their reliability when significant portions of...

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Bibliographic Details
Main Authors: Feng Su, Peijiang Yuan, Yangzhen Wang, Chen Zhang
Format: Article
Language:English
Published: SpringerOpen 2016-08-01
Series:Protein & Cell
Subjects:
artificial neural networks
fault tolerance
genetic algorithm
Online Access:http://link.springer.com/article/10.1007/s13238-016-0302-5

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