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| A Wide Learning Approach for Interpretable Feature Recommendation for 1-D Sensor Data in IoT Analytics 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 800-811
作者: Snehasis Banerjee; Tanushyam Chattopadhyay; Utpal Garain
 浏览 |  Adobe PDF(891Kb) |  收藏 | 浏览/下载：185/56 | 提交时间：2021/02/22
Feature engineering sensor data analysis Internet of things (IoT) analytics interpretable learning automation. |
| Predictive Control Based on Fuzzy Supervisor for PWARX Hybrid Model 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 683-695
作者: Olfa Yahya; Zeineb Lassoued; Kamel Abderrahim
浏览 | Adobe PDF(2179Kb) | 收藏 | 浏览/下载：83/50 | 提交时间：2021/02/22
Nonlinear control hybrid systems mixed logical dynamic (MLD) model predictive control fuzzy supervisor. |
| Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 511-533
作者: Khaled M. Goher; Sulaiman O. Fadlallah
浏览 | Adobe PDF(2563Kb) | 收藏 | 浏览/下载：128/43 | 提交时间：2021/02/22
Two-wheeled inverted pendulum (IP) with two direction handling Lagrangian formulation proportional-integral-derivative (PID) fuzzy logic control (FLC) under-actuated systems. |
| Experimental Evaluation of Certain Pursuit and Evasion Schemes for Wheeled Mobile Robots 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 491-510
作者: Amit Kumar; Aparajita Ojha
浏览 | Adobe PDF(1548Kb) | 收藏 | 浏览/下载：116/44 | 提交时间：2021/02/22
Pursuit-evasion wheeled mobile robot proportional navigation trajectory planning target interception. |
| 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
浏览 | Adobe PDF(1576Kb) | 收藏 | 浏览/下载：126/41 | 提交时间：2021/02/22
Non-stationary signals sparse S-transform (SST) scaling method fuzzy decision tree pattern classification. |
| H∞ State Estimation for Stochastic Markovian Jumping Neural Network with Time-varying Delay and Leakage Delay 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 329-340
作者: Ya-Jun Li; Zhao-Wen Huang; Jing-Zhao Li
浏览 | Adobe PDF(696Kb) | 收藏 | 浏览/下载：170/47 | 提交时间：2021/02/22
H∞ filtering state estimation Markovian jump exponential stability linear matrix inequality (LMI) neural networks time-varying delay leakage delay. |
| Emergency Supply Chain Management Based on Rough Set – House of Quality 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 297-309
作者: Yuan He ; Xue-Dong Liang; Fu-Min Deng; Zhi Li
浏览 | Adobe PDF(932Kb) | 收藏 | 浏览/下载：166/54 | 提交时间：2021/02/22
Emergency supply chain Rough set House of quality management indicators attribute reduction. |
| Dual-modal Physiological Feature Fusion-based Sleep Recognition Using CFS and RF Algorithm 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 286-296
作者: Bing-Tao Zhang; Xiao-Peng Wang; Yu Shen
浏览 | Adobe PDF(847Kb) | 收藏 | 浏览/下载：169/42 | 提交时间：2021/02/22
Feature fusion mild difficulty in falling asleep (MDFA) decision support tool sleep issues optimal feature set. |
| Function Projective Lag Synchronization of Chaotic Systems with Certain Parameters via Adaptive-impulsive Control 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 238-247
作者: Xiu-Li Chai; Zhi-Hua Gan
浏览 | Adobe PDF(2522Kb) | 收藏 | 浏览/下载：89/37 | 提交时间：2021/02/22
Function projective lag synchronization (FPLS) adaptive-impulsive chaotic systems numerical simulation Lyapunov stability theory. |
| Performance Evaluation and Improvement of Chipset Assembly & Test Production Line Based on Variability 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 186-198
作者: Chang-Jun Li; Zong-Shi Xie; Xin-Ran Peng; Bo Li
浏览 | Adobe PDF(1239Kb) | 收藏 | 浏览/下载：126/41 | 提交时间：2021/02/22
Performance evaluation and improvement chipset assembly & test production line (CATPL) parameters Little′s law variability. |
