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...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2016-08-01
|
| Series: | Protein & Cell |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1007/s13238-016-0302-5 |