Application of back-propagation networks in debris flow prediction
β Scribed by Tung-Chueng Chang; Ru-Jen Chao
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 588 KB
- Volume
- 85
- Category
- Article
- ISSN
- 0013-7952
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
In this research, the authors developed back-propagation neural networks (BNNs) to predict the fatigue life of spot welds subjected to various geometric factors and loading conditions. This paper described the developing procedures of the BNNs in detail for the spot weld fatigue. Then, the BNNs deve
## Abstract This paper proposes a speed improvement of the error back propagation algorithm, which is employed widely in the multilayered neural network, by introducing the prediction. The idea is to realize a larger acceleration by introducing the differential factor for the moment terms in the er
Debris flow frequency and magnitude were determined for 33 basins in southwest British Columbia. Basins were first classified as either weathering-limited or transport-limited using a discriminant function based on debris-contributing area, an area-weighted terrain stability number, and drainage den