Prediction model of low cycle fatigue life of 304 stainless steel based on genetic algorithm optimized BP neural network
The low cycle fatigue life of 304 stainless steel is an essential basis for safety assessment. Usually, there is a complex nonlinear relationship between fatigue life and influencing factors, which is difficult to be predicted by traditional fatigue life models. Based on this, the BP algorithm and g...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2022-01-01
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| Series: | Materials Research Express |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2053-1591/ac7cc0 |