The Oil Layer Recognition Based on Multi-kernel Function Relevance Vector Machines
In the oil layer recognition, Relevance vector machines (RVM) have a good effect. But the single kernel function RVM has some limitations, a kind of multi-kernel function RVM based on particle swarm optimization (PSO) is proposed, which includes the model parameter estimation, model optimization on...
Saved in:
Main Authors: | Zhao, Qianqian (Author), Xia, Xinyuan (Author), Xia, Kewen (Author), Hu, Zhaozheng (Author) |
---|---|
Format: | EJournal Article |
Published: |
Institute of Advanced Engineering and Science,
2014-02-01.
|
Subjects: | |
Online Access: | Get fulltext |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Quadratic tuned kernel parameter in Non-linear support vector machine (SVM) for agarwood oil compounds quality classification
by: Bin Mohd Raif, Muhamad Addin Akmal, et al.
Published: (2020) -
Performance of Support Vector Machine in Classifying EEG Signal of Dyslexic Children using RBF Kernel
by: Zainuddin, AZA, et al.
Published: (2018) -
Channel Estimation on 60GHz Wireless System Based on Subspace Pursuit
by: Zu, Baokai, et al.
Published: (2014) -
Support Vector Machines
by: CALTECH -
Fast pornographic image recognition using compact holistic features and multi-layer neural network
by: Wijaya, I Gede Pasek Suta, et al.
Published: (2019)