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640 results on '"Zhang, Ximing"'

3. Demand Response Method Considering Multiple Types of Flexible Loads in Industrial Parks

Author

Cui, Jia, Gao, Mingze, Zhou, Xiaoming, Li, Yang, Liu, Wei, Tian, Jiazheng, and Zhang, Ximing

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Machine Learning
Abstract

With the rapid development of the energy internet, the proportion of flexible loads in smart grid is getting much higher than before. It is highly important to model flexible loads based on demand response. Therefore, a new demand response method considering multiple flexible loads is proposed in this paper to character the integrated demand response (IDR) resources. Firstly, a physical process analytical deduction (PPAD) model is proposed to improve the classification of flexible loads in industrial parks. Scenario generation, data point augmentation, and smooth curves under various operating conditions are considered to enhance the applicability of the model. Secondly, in view of the strong volatility and poor modeling effect of Wasserstein-generative adversarial networks (WGAN), an improved WGAN-gradient penalty (IWGAN-GP) model is developed to get a faster convergence speed than traditional WGAN and generate a higher quality samples. Finally, the PPAD and IWGAN-GP models are jointly implemented to reveal the degree of correlation between flexible loads. Meanwhile, an intelligent offline database is built to deal with the impact of nonlinear factors in different response scenarios. Numerical examples have been performed with the results proving that the proposed method is significantly better than the existing technologies in reducing load modeling deviation and improving the responsiveness of park loads., Comment: Submitted to Expert Systems with Applications

Published
2022
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12. Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task Learning

Author

Zhang, Ximing, Zhang, Qian-Wen, Yan, Zhao, Liu, Ruifang, and Cao, Yunbo

Subjects
Computer Science - Computation and Language
Abstract

In multi-label text classification (MLTC), each given document is associated with a set of correlated labels. To capture label correlations, previous classifier-chain and sequence-to-sequence models transform MLTC to a sequence prediction task. However, they tend to suffer from label order dependency, label combination over-fitting and error propagation problems. To address these problems, we introduce a novel approach with multi-task learning to enhance label correlation feedback. We first utilize a joint embedding (JE) mechanism to obtain the text and label representation simultaneously. In MLTC task, a document-label cross attention (CA) mechanism is adopted to generate a more discriminative document representation. Furthermore, we propose two auxiliary label co-occurrence prediction tasks to enhance label correlation learning: 1) Pairwise Label Co-occurrence Prediction (PLCP), and 2) Conditional Label Co-occurrence Prediction (CLCP). Experimental results on AAPD and RCV1-V2 datasets show that our method outperforms competitive baselines by a large margin. We analyze low-frequency label performance, label dependency, label combination diversity and coverage speed to show the effectiveness of our proposed method on label correlation learning., Comment: Accepted by ACL 2021 (Finding)

Published
2021

13. The Fatigue Failure Prediction of a Vari-Speed Drive with Different Rollers

Author

Liu, Jing, Zhang, Ximing, Shang, Jingtao, Li, Jin, Ding, Shizhao, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Zhang, Hao, editor, Feng, Guojin, editor, Wang, Hongjun, editor, Gu, Fengshou, editor, and Sinha, Jyoti K., editor

Published
2023
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40. Jointly Learning Salience and Redundancy by Adaptive Sentence Reranking for Extractive Summarization

Author

Zhang, Ximing, Liu, Ruifang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Li, Sheng, editor, Sun, Maosong, editor, Liu, Yang, editor, Wu, Hua, editor, Kang, Liu, editor, Che, Wanxiang, editor, He, Shizhu, editor, and Rao, Gaoqi, editor

Published
2021
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43. Development and commissioning of a broadband online X‐ray spectrometer for the SXFEL Facility.

Author

Yang, Zhicheng, Zhang, Ximing, Geng, Heping, Chen, Jiahua, Feng, Chao, Liu, Bo, and Li, Bin

Subjects
*SPECTROMETERS, *PHOTONS, *LASERS, *ELECTRONS, *SEEDS
Abstract

A broadband online X‐ray spectrometer has been designed and commissioned at the SUD beamline of the Shanghai Soft X‐ray Free‐Electron Laser Facility, which can deliver both SASE and seeded FEL pulses to user experiments, spanning the photon energy range of 50–620 eV. The resolving powers of the spectrometer calibrated via online measurement at 92 eV and 249 eV are ∼20000 and ∼15000, respectively, and the absolute photon energy is characterized by an electron time‐of‐flight spectrometer. The high energy resolution provided by the spectrometer can differentiate the fine structure in the FEL spectrum, to determine its pulse length. [ABSTRACT FROM AUTHOR]

Published
2024
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50. A Mobile Device Multitasking Model with Multiple Mobile Edge Computing Servers

Author

Deng, Tao, Zhao, Yunkai, Zhang, Ximing, Xu, Bin, Qi, Jin, Ma, Yuntao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sun, Xingming, editor, and Wang, Jinwei, editor

Published
2020
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