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30th International Conference on Neural Information processing, ICONIP 2023

作者： Ma, ShiLun Kang, Wei Xue, Yun Wen, YiMin Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China School of Municipal and Surveying Engineering Hunan City University Yiyang413000 China

ISBN: (纸本)9789819981830

In this article, we consider the problem of semi-supervised data stream classification. The main difficulties of data stream semi-supervised classification include how to jointly utilize labeled and unlabeled samples to adress concept drift detection and how to use unlabeled to update trained classifier. Existing algorithms like the CPSSDS method constantly retrain a new classifier when concept drift is detected, it is very consuming and wasteful. In this paper, the algorithm of data stream semi-supervised classification with recurring concept drift named as CPSSDS-R is proposed. First, the labeled samples in the first data block are used to initialize a classifier, which is added into a pool and actived for classification. While a new data block arrives, concept drift is detected by computing conformal prediction results. If no concept drift is detected, the pseudo-labeled samples in the previous data block are added with the labeled samples in the current data block to incrementally train the active classifier. If a new concept is detected, a new classifier is trained on the labeled samples of the current data block and added into the pool and actived for classification, else if a recurring concept is detected, the pseudo-labeled samples and labeled samples in the current data block are used to incrementally update the classifier corresponding to the recurring concept in the pool and actived for classification. The proposed algorithm is tested on multiple synthetic and real datasets, and its cumulative accuracy and block accuracy at different labeling ratios demonstrate the effectiveness of the proposed algorithm. The code for the proposed algorithm is available on https://***/ymw12345/cpssds-r. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Tight Formulations of Unit Commitment with General Start-Up Ramp Rate Constraints

Tight Formulations of Unit Commitment with General Start-Up ...

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2021 IEEE Sustainable Power and Energy Conference, iSPEC 2021

作者： Gao, Yijie Zhang, Xuan Yu, Yaowen Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan China Hitachi Abb Power Grid San JoseCA United States

ISBN: (纸本)9781665414395

Unit commitment (UC) is a central market clearing process in wholesale electricity markets. With the increasing size and complexity of market-clearing models, UC problems become more and more complicated. To improve the computation efficiency, this paper tightens UC formulations with the general start-up ramp rate. Through analyzing their parameters over three periods, units are categorized into several categories for constructing corresponding tight formulations, and three of the categories are beyond existing works. By applying a recent systematic formulation tightening approach on top of these categories, new tight constraints of the general start-up ramp rate have been obtained. Numeral testing results illustrate the tightening process and demonstrate the improvement of computational efficiency when using our tightened formulations. © 2021 IEEE.

关键词： Computational efficiency

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Online Identification of Boost Converter Components with Multiple Updating RLS Algorithm

Online Identification of Boost Converter Components with Mul...

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第42届中国控制会议

作者： Tong Zhou Zhicheng Zhang Zhiqiang Zuo Yijing Wang Peng Li Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information EngineeringTianjin University Key Laboratory of System Control and Information Processing Ministry of Education

In this paper,component parameters of the boost converter are identified online using a multiple updating recursive least squares(MURLS) *** component parameters,such as resistance,inductor inductance and capacitor capacitance,are obtained directly through the identification procedure rather than transfer function *** MURLS algorithm is applied to improve the rapidity of system identification compared to the traditional recursive least squares(RLS) algorithm,which is verified by a comparative simulation between MURLS and RLS and the simulation of a load-switching scenario.

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BokehMe: When Neural Rendering Meets Classical Rendering

arXiv

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arXiv 2022年

作者： Peng, Juewen Cao, Zhiguo Luo, Xianrui Lu, Hao Xian, Ke Zhang, Jianming Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Adobe Research

We propose BokehMe, a hybrid bokeh rendering framework that marries a neural renderer with a classical physically motivated renderer. Given a single image and a potentially imperfect disparity map, BokehMe generates high-resolution photo-realistic bokeh effects with adjustable blur size, focal plane, and aperture shape. To this end, we analyze the errors from the classical scattering-based method and derive a formulation to calculate an error map. Based on this formulation, we implement the classical renderer by a scattering-based method and propose a two-stage neural renderer to fix the erroneous areas from the classical renderer. The neural renderer employs a dynamic multi-scale scheme to efficiently handle arbitrary blur sizes, and it is trained to handle imperfect disparity input. Experiments show that our method compares favorably against previous methods on both synthetic image data and real image data with predicted disparity. A user study is further conducted to validate the advantage of our method. Copyright © 2022, The Authors. All rights reserved.

关键词： Rendering (computer graphics)

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Two-stage Train Components Defect Detection Based on Prior Knowledge

Two-stage Train Components Defect Detection Based on Prior K...

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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： Gang Peng Zhiyong Li Shaowei Wan Zhang Deng Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Wuhan Lisai Technology Co. Ltd. Wuhan China

The existing method of detecting defects in train components, which relies on visual identification, requires extensive involvement from inspectors and presents certain limitations. In this study, a two-stage defect detection based on prior knowledge was developed, which first detects the types and positions of components, and then conducts targeted detection of possible existing defect types. The algorithm introduces the prior knowledge of the relative spatial position relationship of components and optimizes the detection of sub-components by cascaded convolutional neural networks and local scale-up. In this study, three methods were used, including deep learning, template matching, and quantitative evaluation based on prior knowledge, to perform targeted detection of defect types that may occur in components. Experiments have verified the adaptability and accuracy of the method, demonstrating its high value for engineering applications.

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Chinese Summary Generation Algorithm Based on Contrastive Attention Mechanism 4

Chinese Summary Generation Algorithm Based on Contrastive At...

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4th International Symposium on Computer Engineering and intelligent Communications, ISCEIC 2023

作者： Guo, Liupeng Xiao, Yannan Wen, Yayuan Wen, Peizhi Guilin University of Electronic Technology School of Computer and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China Guilin University of Electronic Technology School of Computer and Information Security Guilin China Guangxi Normal University School of Electronic and Information Engineering School of Integrated Circuits Guilin China

ISBN: (纸本)9798350306323

Generative summarization based on the seq2seq model has gained widespread adoption due to the advancements and efficacy of the sequence-to-sequence framework. However, these models encounter challenges in handling out-of-vocabulary words and may produce summaries with factual inaccuracies. This paper addresses these issues by proposing a summarization generation model, MBC, which is built upon the Transformer as the baseline model. Additionally, it incorporates the BERT pre-trained model, pointer generation network, contrastive attention mechanism, and coverage loss. The model employs a pointer generation network to augment its vocabulary coverage capabilities by generating new terms. To enhance the representation of key information from the source text, a contrastive attention mechanism is employed during summary generation. In addition, by introducing coverage loss, the model can reduce repetitive content in the summary. To assess the model's performance, this paper employs ROUGE values as evaluation metrics and conducts comparative experiments with other models using the LCSTS dataset. The experimental results demonstrate that, in comparison with other models, this model is more adept at attending to salient information within the source text and generating summaries of greater accuracy. © 2023 IEEE.

关键词： BERT pre-training model contrastive attention mechanism coverage loss pointer generation network seq2seq model

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Switched High-Gain Based Interval Observer Design for Harmonic Oscillator System 42

Switched High-Gain Based Interval Observer Design for Harmon...

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42nd Chinese control Conference, CCC 2023

作者： Ming, Tianhang Wang, Xiaoling Liu, Bo Su, Housheng College of Automation & Ai Nanjing University of Posts and Telecommunications Nanjing210023 China Nanjing210023 China College of Information Engineering Minzu University of China Beijing100081 China Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligence Control of Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturbance and measurement noise, a high-gain interval observer is firstly defined and constructed for the harmonic oscillator system to realize the interval estimation on the state and the robust control of the system. Then, a switched high-gain interval observer is proposed to reduce the influence of the measurement noise for a tighter interval width on the state estimation. Finally, some numerical simulations are given to verify the theoretical results. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Robust control

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Topic Embedded Representation Enhanced Variational Wasserstein Autoencoder for Text Modeling 5

Topic Embedded Representation Enhanced Variational Wasserste...

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5th IEEE International Conference on Electronics Technology, ICET 2022

作者： Xiang, Zheng Liu, Xiaoming Yang, Guan Liu, Yang Zhongyuan University of Technology School of Computer Science Zhengzhou China Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China Key Laboratory of text processing and image understanding Zhengzhou China Xidian University State Key Laboratory of Integrated Services Networks Xi'an China Shandong University Key Lab of Cryptologic Technology and Information Security Ministry of Education Xi'an China

ISBN: (纸本)9781665485081

Variational Autoencoder (VAE) is now popular in modeling and language generation tasks, which need to pay attention to the diversity of generation results. The existing models are insufficient in capturing the built-in relationships between topic representation and sequential words. At the same time, there is a massive contradiction between the commonly used simple Gaussian prior and the actual complex distribution of languages. To address the above problems, we introduce a hybrid Wasserstein Autoencoder (WAE) with Topic Embedded Representation (TER) for modeling. TER is obtained through an embedding-based topic model and can capture the dependencies and semantic similarities between topics and words. In this case, the learned latent variable has rich semantic knowledge with the help of TER and is easier to explain and control. Our experiments show that our method is competitive with other VAEs in modeling. © 2022 IEEE.

关键词： Semantics

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Prescribed Performance control of Mobile Wheeled Inverted Pendulum Systems Under Arbitrary Initial Conditions

Prescribed Performance Control of Mobile Wheeled Inverted Pe...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Mengshi Zhang Yu Cao Bo Yang Jian Huang Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute ShenZhen China

Mobile wheeled inverted pendulum (MWIP) is a typical naturally unstable underactuated system and it is very necessary to constrain its transient response to improve the overall safety. Prescribed performance control (PPC) is an effective method, however the system initial conditions are usually required to be known and constraint, otherwise it can lead to singularity problems. In practical systems, it is often difficult to obtain the exact initial state leading to limitations in the application of PPC. To overcome this issue, this paper presented a composite error transformation function to address the problem of initial condition dependence. A continuous bounded function was designed to compress the arbitrary initial error into the predefined bound to avoid singularities. After a set time, it was degraded to an original system error. Based on this composite transformation, a state feedback controller was proposed for the underactuated MWIP system to achieve the constraint outputs. Then, by employing the Lyapunov theorem, it was guaranteed that the closed-loop system would remain stable. Various numerical simulations under different initial conditions were carried out to prove the validity of the proposed controller.

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Edge-Assisted Flexible Platooning of Connected and Automated Vehicles Under Traffic Anomaly

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IEEE Transactions on Vehicular Technology 2025年

作者： Gao, Fengkun Yang, Bo Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

The platooning of connected and automated vehicles (CAVs) has the great potential to significantly improve travel experience in terms of safety, comfortableness, and energy efficiency. However, constrained by sensing range and prediction accuracy, the performance of CAV platoon can not be guaranteed in the scenario of mixed traffic consisting of CAVs and human-driven vehicles (HDVs). This is not only due to the uncertainty of HDVs but also related to the occurrence of various traffic anomalies, such as emergency braking and accidents. In this paper, we aim to investigate an efficient control strategy to guarantee the operation of the platoon in mixed traffic, especially in the case of traffic anomalies. To tackle the problem, an edge-assisted platoon control strategy, called E-CACC, is proposed. First, an error-aware flexible tracking policy is designed to adapt to HDV uncertainties and speed prediction errors. Based on the tracking policy, a zone model predictive control (ZMPC) method is then designed to guarantee travel safety and avoid undesired acceleration. Further, a coordination strategy of CAV platoon and roadside unit (RSU) is proposed to prevent the platoon from potential collision in the case of traffic anomalies, where an event-based communication trigger is designed to determine whether and when the platoon establishes communication links with RSU to acquire exogenous sensing data of anomaly segment. Finally, the evaluation results illustrate the effectiveness of the proposed method in improving travel safety and comfortableness. © 1967-2012 IEEE.

关键词： Braking performance

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