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Accurate Classification of EEG Signals Using Neural Networks Trained by Hybrid Population-physic-based Algorithm 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 1, 页码: 108-122
作者:  Sajjad Afrakhteh;  Mohammad-Reza Mosavi;  Mohammad Khishe;  Ahmad Ayatollahi
浏览  |  Adobe PDF(1536Kb)  |  收藏  |  浏览/下载：169/66  |  提交时间：2021/02/22
Brain-computer interface (BCI)  classification  electroencephalography (EEG)  gravitational search algorithm (GSA)  multi-layer perceptron neural network (MLP-NN)  particle swarm optimization.  
Electronic Nose and Its Applications: A Survey 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 179-209
作者:  Diclehan Karakaya;  Oguzhan Ulucan;  Mehmet Turkan
浏览  |  Adobe PDF(1365Kb)  |  收藏  |  浏览/下载：200/39  |  提交时间：2021/02/22
Artificial intelligence  machine learning  pattern recognition  electronic nose (EN)  sensors technology.  
Optimization of Grasping Efficiency of a Robot Used for Sorting Construction and Demolition Waste 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 5, 页码: 691-700
作者:  Yue-Dong Ku;  Jian-Hong Yang;  Huai-Ying Fang;  Wen Xiao;  Jiang-Teng Zhuang
浏览  |  Adobe PDF(1122Kb)  |  收藏  |  浏览/下载：111/36  |  提交时间：2021/02/22
Construction and demolition waste  sorting robot  grasping strategy  mathematical models  robot kinematics parameters.  
Ground-level Ozone Prediction Using Machine Learning Techniques: A Case Study in Amman, Jordan 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 5, 页码: 667-677
作者:  Maryam Aljanabi;  Mohammad Shkoukani;  Mohammad Hijjawi
浏览  |  Adobe PDF(1159Kb)  |  收藏  |  浏览/下载：92/28  |  提交时间：2021/02/22
Ozone prediction  machine learning  neural networks  supervised learning  regression.  
Robust Object Tracking via Information Theoretic Measures 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 5, 页码: 652-666
作者:  Wei-Ning Wang;  Qi Li;  Liang Wang
Adobe PDF(1855Kb)  |  收藏  |  浏览/下载：176/25  |  提交时间：2021/02/22
Object tracking  information theoretic measures  correntropy  template update  robust to complex noises.  
Robust Object Tracking via Information Theoretic Measures 期刊论文
International Journal of Automation and Computing, 2020, 期号: 17, 页码: 1
作者:  Wang, Weining;  Li, Qi;  Wang, Liang
浏览  |  Adobe PDF(9045Kb)  |  收藏  |  浏览/下载：205/57  |  提交时间：2020/09/03
Object tracking, information theoretic measures, correntropy, template update, robust to complex noises