中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共5条，第1-5条 帮助

限定条件        
已选(0)清除 条数/页：   排序方式：
An Advanced Analysis System for Identifying Alcoholic Brain State Through EEG Signals 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 737-747
作者:  Siuly Siuly;  Varun Bajaj;  Abdulkadir Sengur;  Yanchun Zhang
Adobe PDF(4171Kb)  |  收藏  |  浏览/下载：176/57  |  提交时间：2021/02/22
Electroencephalogram (EEG)  alcoholism  optimum allocation technique  feature extraction  decision table.  
A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and Pattern Recognition 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 398-412
作者:  N. R. Nayak;  P. K. Dash;  R. Bisoi
Adobe PDF(1576Kb)  |  收藏  |  浏览/下载：163/53  |  提交时间：2021/02/22
Non-stationary signals  sparse S-transform (SST)  scaling method  fuzzy decision tree  pattern classification.  
Sequential Fault Diagnosis Using an Inertial Velocity Differential Evolution Algorithm 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 389-397
作者:  Xiao-Hong Qiu;  Yu-Ting Hu;  Bo Li
浏览  |  Adobe PDF(792Kb)  |  收藏  |  浏览/下载：182/65  |  提交时间：2021/02/22
Differential evolution (DE)  evolutionary computation  fault isolation rate (FIR)  testability  fault diagnosis.  
An Approach to Reducing Input Parameter Volume for Fault Classifiers 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 199-212
作者:  Ann Smith;  Fengshou Gu;  Andrew D. Ball
浏览  |  Adobe PDF(1085Kb)  |  收藏  |  浏览/下载：163/70  |  提交时间：2021/02/22
Fault diagnosis  classification  variable clustering  data compression  big data.  
Potential Bands of Sentinel-2A Satellite for Classification Problems in Precision Agriculture 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 16-26
作者:  Tian-Xiang Zhang;  Jin-Ya Su;  Cun-Jia Liu;  Wen-Hua Chen
浏览  |  Adobe PDF(1123Kb)  |  收藏  |  浏览/下载：202/59  |  提交时间：2021/02/22
Sentinel-2A  remote sensing  image classification  supervised learning  precision agriculture.