Name
Title | ||
|---|---|---|
The Fluorescence Spectroscopy Recognition of the Mineral Oil Based on the Multiresolution Orthogonal Multiwavelet Neural Network |
Abstract | ||
|---|---|---|
The singular value eigenvectors of the different kinds of the mineral oil stylebooks are obtained by parameterizing the three-dimensional fluorescence spectroscopy. They are complicated and not easy to be recognized by the simple formula. The multiwavelet neural network is introduced to realize the identification of the different kinds of the mineral oil. It was layered. It had the feature of the part study. The prompting function of the network is constructed by the multiscale function and multiwavelet function. The experiment indicates that the network has all the virtue of the wavelet neural network (WNN). It also has the much better approach property than the WNN. It can effectively recognize the fine distinction between the different spectrums and realize the identification of the oil by much fewer train times than the WNN. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CSSE.2008.999 | CSSE (4) |
Keywords | Field | DocType |
singular value,singular value decomposition,petroleum industry,convergence,spectroscopy,fluorescence,neural nets,artificial neural networks,wavelet transforms,petroleum,three dimensional,spectrum,neural network,eigenvectors,fluorescence spectroscopy | Convergence (routing),Singular value decomposition,Mineral oil,Singular value,Pattern recognition,Computer science,Fluorescence spectroscopy,Artificial intelligence,Artificial neural network,Eigenvalues and eigenvectors,Wavelet transform | Conference |
Volume | Issue | ISSN |
4 | null | null |
ISBN | Citations | PageRank |
978-0-7695-3336-0 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lv Jiangtao | 1 | 0 | 0.34 |
| Yutian Wang | 2 | 0 | 4.06 |
| Pan Zhao | 3 | 0 | 2.37 |