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94 results on '"Bi, Zhongqin"'

4. A Multi-behavior Recommendation Algorithm Based on Personalized Federated Learning

Author

Bi, Zhongqin, Duan, Yutang, Zhang, Weina, Shan, Meijing, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Wang, Xinheng, editor, and Voros, Nikolaos, editor

Published
2024
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5. Fast Fault Location Technology for Distribution Network Based on Quantum Ant Colony Algorithm

Author

BI Zhongqin, YU Xiaowan, WANG Baonan, HUANG Wentao, ZHANG Dan, DONG Zhen

Subjects
location of fault section in distribution network, quantum ant colony algorithm (qaca), information self-correction method, hierarchical location model network, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

Integration of distributed generations into distribution networks has become one of the important features of new power systems. The integration of distributed generation and the uncertainty of power generation make the power flow in distribution networks complex and variable, which poses higher technical requirements for rapid fault location in distribution networks. However, existing intelligent optimization algorithms may encounter problems such as slow convergence speed and susceptibility to local optimization when solving the problem of fault section location in distribution networks. To address these challenges and problems, a rapid fault section location technology based on quantum ant colony algorithm (QACA) is proposed. First, a location mathematical model is constructed based on the state approximation idea and the minimum fault set theory. Then, an information self-correction method is proposed for the missing information uploaded by feeder terminal unit, and a hierarchical location model is proposed to shorten the location time. Afterwards, three improvement techniques are proposed to improve the QACA. The update mechanism of the quantum rotary gate is improved, the rotation angle is dynamically adjusted in the form of function control, and the elite strategy is introduced to accelerate the convergence speed of the algorithm. Finally, after the key parameters are determined, the effectiveness of the improved technique, the information self-correction method, and the hierarchical positioning model is verified. A comparison with 7 different algorithms indicates that the improved QACA can effectively locate the fault section, and has a fast convergence speed, great accuracy, and fault tolerance.

Published
2024
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7. YOLO-RFB: An Improved Traffic Sign Detection Model

Author

Bi, Zhongqin, Xu, Fuqiang, Shan, Meijing, Yu, Ling, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Deng, Shuiguang, editor, Zomaya, Albert, editor, and Li, Ning, editor

Published
2022
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8. An Improved Spectral Clustering Algorithm Using Fast Dynamic Time Warping for Power Load Curve Analysis

Author

Bi, Zhongqin, Leng, Yabin, Liu, Zhe, Li, Yongbin, Fuentes, Stelios, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Liu, Jing, editor, Gao, Honghao, editor, Yin, Yuyu, editor, and Bi, Zhongqin, editor

Published
2020
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10. An Approach for Item Recommendation Using Deep Neural Network Combined with the Bayesian Personalized Ranking

Author

Bi, Zhongqin, Zhou, Siming, Yang, Xiaoxian, Zhou, Ping, Wu, Jiale, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Xiaohua, Jia, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Wang, Xinheng, editor, Gao, Honghao, editor, Iqbal, Muddesar, editor, and Min, Geyong, editor

Published
2019
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11. Covering Diversification and Fairness for Better Recommendation (Short Paper)

Author

Yang, Qing, Han, Li, Zhou, Ya, Liu, Shaobing, Zhang, Jingwei, Bi, Zhongqin, Pan, Fang, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Xiaohua, Jia, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Wang, Xinheng, editor, Gao, Honghao, editor, Iqbal, Muddesar, editor, and Min, Geyong, editor

Published
2019
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12. Recommending More Suitable Music Based on Users’ Real Context

Author

Yang, Qing, Zhan, Le, Han, Li, Zhang, Jingwei, Bi, Zhongqin, Akan, Ozgur, Series Editor, Bellavista, Paolo, Series Editor, Cao, Jiannong, Series Editor, Coulson, Geoffrey, Series Editor, Dressler, Falko, Series Editor, Ferrari, Domenico, Series Editor, Gerla, Mario, Series Editor, Kobayashi, Hisashi, Series Editor, Palazzo, Sergio, Series Editor, Sahni, Sartaj, Series Editor, Shen, Xuemin (Sherman), Series Editor, Stan, Mircea, Series Editor, Xiaohua, Jia, Series Editor, Zomaya, Albert Y., Series Editor, Gao, Honghao, editor, Wang, Xinheng, editor, Yin, Yuyu, editor, and Iqbal, Muddesar, editor

Published
2019
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13. From Landscape to Portrait: A New Approach for Outlier Detection in Load Curve Data

Author

Tang, Guoming, Wu, Kui, Lei, Jingsheng, Bi, Zhongqin, and Tang, Jiuyang

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Data Structures and Algorithms
Abstract

In power systems, load curve data is one of the most important datasets that are collected and retained by utilities. The quality of load curve data, however, is hard to guarantee since the data is subject to communication losses, meter malfunctions, and many other impacts. In this paper, a new approach to analyzing load curve data is presented. The method adopts a new view, termed \textit{portrait}, on the load curve data by analyzing the periodic patterns in the data and re-organizing the data for ease of analysis. Furthermore, we introduce algorithms to build the virtual portrait load curve data, and demonstrate its application on load curve data cleansing. Compared to existing regression-based methods, our method is much faster and more accurate for both small-scale and large-scale real-world datasets., Comment: 10 pages, 9 figures

Published
2013

14. An Efficient and Provably Secure Pairing-Free Certificateless Signature Scheme Based on Variant of RSA

Author

Wang, Liangliang, Wen, Mi, Chen, Kefei, Bi, Zhongqin, Long, Yu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Wen, Sheng, editor, Wu, Wei, editor, and Castiglione, Aniello, editor

Published
2017
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15. Segmentation-based Decision Networks for Steel Surface Defect Detection

Author

Zhongqin Bi Zhongqin Bi, Qiancong Wu Zhongqin Bi, Meijing Shan Qiancong Wu, and Wei Zhong Meijing Shan

Subjects
Computer Networks and Communications, Software
Abstract

With the advent of the Industrial 4.0 era, deep learning has been continuously applied to the task of surface defect detection, and effective progress has been made. However, the limited number of training samples and high labelling costs are considerable obstacles to the vigorous development of this task. Thus, we explore the use of different numbers of labels with various accuracies during training to achieve the maximum detection accuracy with the lowest cost. Our proposed method includes improved segmentation and decision networks. An attention mechanism is integrated into the segmentation subnetwork. Moreover, atrous convolutions are used in the segmentation and decision subnetworks. In addition, the original loss function is improved. Several experiments are carried out on the Severstal Steel Defect dataset collected in Germany, and the results show that each component improves the detection accuracy by 1% to 2%. Finally, when we add an appropriate number of pixel-level labels in the weakly supervised learning mode, the detection accuracy reaches that of the fully supervised mode with a significantly reduced annotation cost. &nbsp

Published
2022

19. Approximate Reduction for the Interval-Valued Decision Table

Author

Xu, Feifei, Bi, Zhongqin, Lei, Jingsheng, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Miao, Duoqian, editor, Pedrycz, Witold, editor, Ślȩzak, Dominik, editor, Peters, Georg, editor, Hu, Qinghua, editor, and Wang, Ruizhi, editor

Published
2014
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21. Termination of Loop Programs with Polynomial Guards

Author

Wu, Bin, Shen, Liyong, Bi, Zhongqin, Zeng, Zhenbing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Taniar, David, editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Pardede, Eric, editor, and Apduhan, Bernady O., editor

Published
2010
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34. Research on wireless robot path planning under edge computing considering multistep searching and inflection points.

Author

Bi, Zhongqin, Ma, Yuanyuan, Yang, Xiaoxian, and Zhou, Ping

Subjects
ROBOTIC path planning, ANT algorithms, EDGE computing, WIRELESS communications, INFLECTION (Grammar)
Abstract

The wireless robot path planning is a hot research topic in the fields of automatic control and wireless communication. With the help of the edge computing model, the robot can implement location‐aware and positioning to effectively explore the direction and avoid barriers with less computation time. In this paper, an improved ant colony optimization algorithm is proposed to wireless robot path planning. First, the grid method to build a formal map for the robot environment is introduced, by which we can accurately simulate the barriers and paths environment. Second, the multistep path‐planning method is proposed to optimize the path length of robot walking and improve the quality of the solution. Third, to make the wireless robot route smoother, the inflection point parameter is integrated into the probability formula. All these related data are collected and processed at the edge node with cooperative communication. The way of edge computing makes root robustness and stability. Besides, the pheromone strength coefficient Q is reduced to increase the convergence speed of the proposed algorithm. Finally, the experiment results show that our method can obtain a better path planning for the wireless robot, compared with the traditional algorithms. [ABSTRACT FROM AUTHOR]

Published
2021
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