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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:205/60  |  提交时间:2021/02/22 Feature engineering sensor data analysis Internet of things (IoT) analytics interpretable learning automation. |
| Development of STEP AP224 Extractor for Interfacing Feature Based CAPP to STEP-NC (AP238) 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 655-670 作者: Deepanshu Srivastava; Venkateswara Rao Komma Adobe PDF(3913Kb)  |  收藏  |  浏览/下载:121/38  |  提交时间:2021/02/22 Reduced-order observer discrete-time systems Lipschitz systems H∞ ARDUINO MEGA 2560 device. |
| Convergence Analysis of a New MaxMin-SOMO Algorithm 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 534-542 作者: Atlas Khan; Yan-Peng Qu 浏览  |  Adobe PDF(1429Kb)  |  收藏  |  浏览/下载:155/53  |  提交时间:2021/02/22 Optimization self organizing map (SOM) SOM-based optimization (SOMO) algorithm particle swarm optimization (PSO) genetic algorithms (GAs). |
| 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:141/46  |  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. |
| Deep Learning Based Single Image Super-resolution: A Survey 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 413-426 作者: Viet Khanh Ha; Jin-Chang Ren; Xin-Ying Xu; Sophia Zhao; Gang Xie; Valentin Masero; Amir Hussain 浏览  |  Adobe PDF(1389Kb)  |  收藏  |  浏览/下载:131/33  |  提交时间:2021/02/22 Image super-resolution convolutional neural network high-resolution image low-resolution image deep learning. |
| 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:177/57  |  提交时间:2021/02/22 Emergency supply chain Rough set House of quality management indicators attribute reduction. |
| A Survey of the Research Status of Pedestrian Dead Reckoning Systems Based on Inertial Sensors 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 65-83 作者: Yuan Wu; Hai-Bing Zhu; Qing-Xiu Du; Shu-Ming Tang 浏览  |  Adobe PDF(1248Kb)  |  收藏  |  浏览/下载:267/80  |  提交时间:2021/02/22 Inertial measurement unit (IMU) pedestrian dead-reckoning indoor navigation technical route general framework. |
| Optimization RFID-enabled Retail Store Management with Complex Event Processing 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 52-64 作者: Shang-Lian Peng; Ci-Jian Liu; Jia He; Hong-Nian Yu; Fan Li 浏览  |  Adobe PDF(1080Kb)  |  收藏  |  浏览/下载:182/51  |  提交时间:2021/02/22 Complex event processing (CEP) radio frequency identification (RFID) Internet of things data stream supply chain retail store. |
| Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 27-39 作者: Yu Hao; Zhi-Jie Xu; Ying Liu; Jing Wang; Jiu-Lun Fan 浏览  |  Adobe PDF(1521Kb)  |  收藏  |  浏览/下载:220/59  |  提交时间:2021/02/22 Crowd behavior spatial-temporal texture gray level co-occurrence matrix information entropy. |
| Key Crowdsourcing Technologies for Product Design and Development 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 1-15 作者: Xiao-Jing Niu; Sheng-Feng Qin; John Vines; Rose Wong; Hui Lu 浏览  |  Adobe PDF(997Kb)  |  收藏  |  浏览/下载:197/55  |  提交时间:2021/02/22 Crowdsourcing technologies product design and development (PDD) communication information sharing design evaluation feedback. |