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Xuerui Zhang - IEEE Xplore Author Profile
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Xuerui Zhang

Publications
10
Citations
7
Publications by Year
20162024
Co-Authors:
Show All Co-Authors (25)
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Xuerui Zhang

Affiliation

College of Intelligent Science and Engineering
Harbin Engineering University
Harbin, China

Publication Topics

Biography

Xuerui Zhang received the B.S. degree in mathematics and applied mathematics from the Henan Normal University in 2016, and the M.S. degree in fundamental mathematics from the Dalian University of Technology in 2019. She is a Ph.D. candidate in control theory and control engineering with the School of Control Science and Engineering, Dalian University of Technology. Her research interests include industrial artificial intelligence, intelligent optimization, and machine learning.(Based on document published on 1 April 2024).
Publications
10
Citations
7
Publications by Year
20162024
Co-Authors:
Show All Co-Authors (25)
Author's Published Works

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Research on INS/GNSS Integrated Navigation Positioning Based on an Improved Pre-Integration Algorithm

Yinhao Xiong;Yanhui Wei;Xi Wang;Xuerui Zhang

OCEANS 2024 - Singapore
Year: 2024 | Conference Paper |
To solve the problem that the Markov property of the extended Kalman filter (EKF) hypothesis cannot trace the historical information and the optimal state estimation cannot be obtained only by using the first-order Taylor expansion, an improved pre-integration algorithm is introduced in this paper. Based on the theory of pre-integration, this paper refers to the high-precision strapdown inertial n...Show More

Research on INS/GNSS Integrated Navigation Positioning Based on an Improved Pre-Integration Algorithm

Yinhao Xiong;Yanhui Wei;Xi Wang;Xuerui Zhang

Year: 2024 | Conference Paper |

Ingredient Planning for Copper Industry: A Deep Reinforcement Learning-Based \epsilon-Constrained Multi-Objective Optimization Framework

Xuerui Zhang;Zhongyang Han;Zhiyuan Wang;Jun Zhao;Wei Wang

2024 IEEE Congress on Evolutionary Computation (CEC)
Year: 2024 | Conference Paper |
Effective ingredient plan plays a crucial role in the copper industry as it directly impacts both economic interest and resource utilization of the enterprise. Aims at minimizing both production cost and loss simultaneously, a multi-objective ingredient optimization model considering practical constraints is established in this study. In order to effectively address the model, a deep reinforcement...Show More

Ingredient Planning for Copper Industry: A Deep Reinforcement Learning-Based $\epsilon$-Constrained Multi-Objective Optimization Framework

Xuerui Zhang;Zhongyang Han;Zhiyuan Wang;Jun Zhao;Wei Wang

Year: 2024 | Conference Paper |

Multi-scale target detection for airfield visual navigation of taxiing aircraft

Qijun Luo;Jiagang Chen;Xuerui Zhang;Tao Zhang

2024 4th International Conference on Neural Networks, Information and Communication Engineering (NNICE)
Year: 2024 | Conference Paper |
In the context of visual navigation-based civil aircraft assistance systems, the scene target scales captured by onboard cameras exhibit significant variations, and the computational power of airborne platforms is limited. To promptly and accurately identify threat targets in airborne scenic images, a lightweight multi-scale object detection algorithm based on improved YOLOv5s is proposed. Firstly...Show More

Multi-scale target detection for airfield visual navigation of taxiing aircraft

Qijun Luo;Jiagang Chen;Xuerui Zhang;Tao Zhang

Year: 2024 | Conference Paper |

A Multi-Stage Differential-Multifactorial Evolutionary Algorithm for Ingredient Optimization in the Copper Industry

Xuerui Zhang;Zhongyang Han;Jun Zhao

IEEE/CAA Journal of Automatica Sinica
Year: 2024 | Volume: 11, Issue: 10 | Journal Article |
Cited by: Papers (1)
Ingredient optimization plays a pivotal role in the copper industry, for which it is closely related to the concentrate utilization rate, stability of furnace conditions, and the quality of copper production. To acquire a practical ingredient plan, which should exhibit long duration time with sufficient utilization and feeding stability for real applications, an ingredient plan optimization model ...Show More

A Multi-Stage Differential-Multifactorial Evolutionary Algorithm for Ingredient Optimization in the Copper Industry

Xuerui Zhang;Zhongyang Han;Jun Zhao

Year: 2024 | Volume: 11, Issue: 10 | Journal Article |

Multi-View Fusion Networks for Multimodal Fake News Detection

Wei Cui;Pu Li;Xuerui Zhang

2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
Year: 2023 | Conference Paper |
The proliferation of multimedia fake news misleads social opinion, damages social harmony, and seriously challenges the authority of news media. Current multimodal fake news detection methods focus on extracting better unimodal features using pre-trained models and developing complex networks for visual and textual feature fusion, mostly ignoring social contextual information. In the text, we pres...Show More

Multi-View Fusion Networks for Multimodal Fake News Detection

Wei Cui;Pu Li;Xuerui Zhang

Year: 2023 | Volume: 11 | Conference Paper |

A Recommender System Based on Model Regularization Wasserstein Generative Adversarial Network

Qingxian Wang;Qing Huang;Kangkang Ma;Xuerui Zhang

2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
A recommender system (RS) commonly adopts a High-dimensional and sparse (HiDS) matrix to describe user-item preferences. Collaborative Filtering (CF)-based models have been widely adopted to address such an HiDS matrix. However, a CF-based model is unable to learn the property distribution characteristic of user’s preference from an HiDS matrix, thereby its representation ability is limited. To ad...Show More

A Recommender System Based on Model Regularization Wasserstein Generative Adversarial Network

Qingxian Wang;Qing Huang;Kangkang Ma;Xuerui Zhang

Year: 2021 | Conference Paper |

Prune Strategy to YOLO-Based Model

Boyu Zhao;Zhicheng Dong;Xuerui Zhang;Jie Li

2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI)
Year: 2020 | Conference Paper |
One-stage networks have been widely used in target detection systems that need to learn from the big data. Most of them have good real-time performance and accuracy. However, due to their convolution structure, in actual applications, they still require more memory space and stronger computing power, thereby we choose to apply a pruning strategy on the target detection network to reduce the size o...Show More

Prune Strategy to YOLO-Based Model

Boyu Zhao;Zhicheng Dong;Xuerui Zhang;Jie Li

Year: 2020 | Conference Paper |

Application of Face Data Augmentation Based on Rotate-and-Render-DCGAN in Campus Security

Kai Wu;Ynanchao Yu;Xuerui Zhang;Jie Li;Qian Zhang

2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
Targeting at solving the problem of low accuracy of existing recognition methods caused by the imbalance of face data sets in the university security system, an unbalanced Data Augmentation method based on Rotate-and-Render-DCGAN is proposed to improve face recognition accuracy campus. Our goal is to correct the angled faces in the data set through Rotate-and-Render and generate artificial images ...Show More

Application of Face Data Augmentation Based on Rotate-and-Render-DCGAN in Campus Security

Kai Wu;Ynanchao Yu;Xuerui Zhang;Jie Li;Qian Zhang

Year: 2020 | Conference Paper |

Prediction of Chlorophyll-a content using hybrid model of least squares support vector regression and radial basis function neural networks

Xu Wang;Guoyin Wang;Xuerui Zhang

2016 Sixth International Conference on Information Science and Technology (ICIST)
Year: 2016 | Conference Paper |
Cited by: Papers (4)
Eutrophication has become a serious environment problem in many parts of the world and Chlorophyll-a concentration is one of the important parameters for the characterization of water quality, which reflects the degree of eutrophication and algae content in the water body. So establishing a forecasting model to predict the chlorophyll-a concentration in evaluation of eutrophication become more urg...Show More

Prediction of Chlorophyll-a content using hybrid model of least squares support vector regression and radial basis function neural networks

Xu Wang;Guoyin Wang;Xuerui Zhang

Year: 2016 | Conference Paper |

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