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Research on IFHI prediction effect based on grey relational analysis and BP neural network
| Content Provider | Scilit |
|---|---|
| Author | Wang, Yiqi Chen, Lei |
| Copyright Year | 2021 |
| Description | Journal: Iop Conference Series: Earth and Environmental Science IFHI (Fire Risk Index) is a key indicator of the fire risk capability of polymer materials.[1] In view of the complexity, uncertainty and nonlinearity of IFHI prediction, this paper adopts the grey relational analysis method proposed by Deng Yulong et al to carry out dimensionality reduction analysis of parameters. Four parameters of SEA, MLR, TTI and CO yield, which are highly correlated with IFHI value, were selected to construct BP neural network prediction model. The predicted value is compared with the actual value, and the mean square error MSE =0.01308. It is proved that this model has a good prediction effect and can provide scientific basis for IFHI prediction. |
| Related Links | https://iopscience.iop.org/article/10.1088/1755-1315/692/2/022107/pdf |
| ISSN | 17551307 |
| e-ISSN | 17551315 |
| DOI | 10.1088/1755-1315/692/2/022107 |
| Journal | Iop Conference Series: Earth and Environmental Science |
| Issue Number | 2 |
| Volume Number | 692 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2021-03-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Earth and Environmental Science Fire Risk Ifhi Prediction Prediction Effect |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences Physics and Astronomy Environmental Science |
