检索结果-内蒙古大学图书馆

2024 China Automation Congress, CAC 2024

作者： Zhou, Aoran Qiu, Lipeng Wu, Yali Department of Information and Control Engineering Xi'an University of Technology Shaan'xi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co Ltd Xi'an710016 China

ISBN: (纸本)9798350368604

In view of the problems of high energy consumption, long inventory time and low production efficiency in the production process of traditional aluminum extrusion machine, this paper establishes an efficient two-stage parallel scheduling optimization model based on the integration of flexible job shop scheduling and assembly sequence planning (IFJSS-ASP). On this basis, an evolutionary algorithm combining strong dominance relationship and simple grouping method (SDREA-SGM) is proposed. The algorithm utilizes a two-stage hybrid chromosome encoding and decoding method to establish a rational mapping from the decision space to the solution space. Furthermore, in order to prevent the model from easily falling into local optima, an adaptive intra-class and inter-class pairing selection strategy has been adopted by the algorithm. This enhances global search and improves local search ***, the feasibility and effectiveness of the algorithm are verified by solving problems of different scales. © 2024 IEEE.

关键词： Job shop scheduling

来源：评论

学校读者我要写书评

暂无评论

Fault diagnosis for small samples based on VMR

Fault diagnosis for small samples based on VMR

引用

2024 China Automation Congress, CAC 2024

作者： Wu, Xuejin Wu, Yali Hu, Yanghu Department of Information and Control Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratoiy of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd Xi'an710016 China

ISBN: (纸本)9798350368604

The scarcity of fault samples presents a significant challenge for fault diagnosis in industrial processes. Conventional methods often fail to deliver satisfactory results when dealing with small sample sizes. In addressing the issue of small sample fault diagnosis in industrial processes, this paper utilizes the Variational Mode Reconstruction(VMR) algorithm to screen the best components decomposed by the Variational Mode Decomposition(VMD) through the envelope entropy then random weighting them and signal reconstruction to achieve data enhancement, to enrich the sample size and to prevent the model overfitting phenomenon due to the scarcity of samples. Meanwhile, this paper integrates Convolutional Neural Network (CNN) and Long Short-term Memory Neural Network (LSTM) to propose a network model of spatio-temporal feature fusion for feature extraction and classification. The experiments demonstrate that this model not only enhances data diversity but also ensures consistency before and after enhancement, effectively mitigating overfitting. Furthermore, it guarantees high recognition and generalization rates in fault diagnosis. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Two-Stage OD Flow Prediction for Emergency in Urban Rail Transit

引用

IEEE Transactions on Intelligent Transportation systems 2024年第1期25卷 920-928页

作者： Zhu, Guangyu Ding, Jiacun Wei, Yun Yi, Yang Xu, Sendren Sheng-Dong Wu, Edmond Q. Beijing Jiaotong University Key Lab. of Transport Industry of Big Data Application Technologies for Comprehensive Transport The Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing100044 China Beijing Mass Transit Railway Operation Corporation Ltd. Beijing100014 China Yangzhou University College of Information Engineering Yangzhou225127 China National Taiwan University of Science and Technology Automation and Control Center The Graduate Institute of Automation and Control Taipei106335 Taiwan Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

Urban rail transit (URT) is vulnerable to natural disasters and social emergencies including fire, storm and epidemic (such as COVID-19), and real-time origin-destination (OD) flow prediction provides URT operators with important information to ensure the safety of URT system. However, hindered by the high dimensionality of OD flow and the lack of supportive information reflecting the real-time passenger flow changes, study in this area is at the beginning stage. A novel model consisting of two stages is proposed for OD flow prediction. The first stage predicts the inflows of all stations by Long Short-Term Memory (LSTM) in real time, where the dimension is reduced compared with predicting OD flows directly. In the second stage, the notion of separation rate, namely, the proportion of inbound passengers bounding for another station, is estimated. Finally, The OD flow is predicted by multiplying the inflow and separation rate. Experiments based on Hangzhou Metro dataset show the proposed model outperforms the contrast model in weighted mean average error (WMAE) and weighted mean square error (WMSE). Results also suggest that the proposed prediction model performs better on weekdays than on weekends, and with greater accuracy on larger OD flows. © 2000-2011 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

research on workflow recognition for liver rupture repair surgery

引用

Mathematical Biosciences and engineering 2024年第2期21卷 1844-1856页

作者： Men, Yutao Zhao, Zixian Chen, Wei Wu, Hang Zhang, Guang Luo, Feng Yu, Ming Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Medical Support Technology Research Department Systems Engineering Institute Academy of Military Sciences People’s Liberation Army Tianjin300161 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

Liver rupture repair surgery serves as one tool to treat liver rupture, especially beneficial for cases of mild liver rupture hemorrhage. Liver rupture can catalyze critical conditions such as hemorrhage and shock. Surgical workflow recognition in liver rupture repair surgery videos presents a significant task aimed at reducing surgical mistakes and enhancing the quality of surgeries conducted by surgeons. A liver rupture repair simulation surgical dataset is proposed in this paper which consists of 45 videos collaboratively completed by nine surgeons. Furthermore, an end-to-end SA-RLNet, a self attention-based recurrent convolutional neural network, is introduced in this paper. The self-attention mechanism is used to automatically identify the importance of input features in various instances and associate the relationships between input features. The accuracy of the surgical phase classification of the SA-RLNet approach is 90.6%. The present study demonstrates that the SA-RLNet approach shows strong generalization capabilities on the dataset. SA-RLNet has proved to be advantageous in capturing subtle variations between surgical phases. The application of surgical workflow recognition has promising feasibility in liver rupture repair surgery. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

引用

China Communications 2024年第5期21卷 297-313页

作者： Ma Shuai Yang Lei Ding Wanying Li Hang Zhang Zhongdan Xu Jing Li Zongyan Xu Gang Li Shiyin Department of Strategic and Advanced Interdisciplinary Research Peng Cheng LaboratoryShenzhen 518055China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Data-driven Intelligent Information System Laboratory Shenzhen Research Institute of Big DataShenzhen 518172China Ocean College Zhejiang UniversityZhoushan 316021China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication *** other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental *** on such a platform,we first construct a real signal dataset with ten modulation ***,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature *** also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated ***,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other *** also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

关键词： AdaBoost DBN machine learning signal demodulation

来源：评论

学校读者我要写书评

暂无评论

Deciphering decadal urban ozone trends from historical records since 1980

引用

National Science Review 2024年第11期11卷 117-129页

作者： Haolin Wang Xiao Lu Paul I.Palmer Lin Zhang Keding Lu Ke Li Tatsuya Nagashima Ja-Ho Koo Hiroshi Tanimoto Haichao Wang Meng Gao Cheng He Kai Wu Shaojia Fan Yuanhang Zhang School of Atmospheric Sciences Sun Yat-sen University and Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Education Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) School of Geo Sciences University of Edinburgh National Centre for Earth Observation University of Edinburgh Laboratory for Climate and Ocean-Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking University State Key Joint Laboratory of Environmental Simulation and Pollution Control The State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution ControlCollege of Environmental Sciences and Engineering Peking University Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science &Technology National Institute for Environmental Studies Department of Atmospheric Sciences Yonsei University Department of Geography Hong Kong Baptist University Department of Civil and Environmental Engineering University of California

Ozone pollution is a major environmental threat to human health. Timely assessment of ozone trends is crucial for informing environmental policy. Here we show that for the most recent decade（2013–2022） in the northern hemisphere, warm-season（April–September） mean daily 8-h average maximum ozone increases much faster in urban regions with top ozone levels(mainly in the North China Plain, 1.2 ± 1.3 ppbv year-1) than in other, low-ozone regions(0.2 ± 0.9 ppbv year-1). These trends widen the ozone differences across urban regions, and increase extreme pollution levels and health threats from a global perspective. Comparison of historical trends in different urban regions reveals that ozone increases in China during 2013–2022 differ in magnitude and mechanisms to historical periods in other regions since *** reflects a unique chemical environment characterized by exceptionally high nitrogen oxides and aerosol concentrations, where reducing ozone precursor emissions leads to substantial ozone *** increase in China has slowed down in 2018–2022 compared to 2013–2017, driven by ongoing emission reductions, but with ozone-favorable weather conditions. Historical ozone evolution in Japan and South Korea indicates that ozone increases should be suppressed with continuous emission *** temperature and associated wildfires have also reversed ozone decreases in the USA and Europe,with anthropogenic ozone control slowing down in recent decades.

关键词： air quality surface ozone trends

来源：评论

学校读者我要写书评

暂无评论

An Efficient Stability Criterion for Near-Fundamental-Frequency Oscillation Risk Assessment of Wind Power Integrated systems via MMC-HVDC 19th

An Efficient Stability Criterion for Near-Fundamental-Freque...

引用

19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wu, Linlin Dong, Wenkai Ren, Yina Wang, Xiao Xie, Xiaorong State Grid Jibei Electric Power Co. Ltd. Research Institute North China Electric Power Research Institute Co. Ltd. Beijing100045 China State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China

ISBN: (纸本)9789819613823

Recently, near-fundamental-frequency oscillations (NFFOs) have been observed in practical wind power integrated systems via MMC-HVDC (WISM). However, a practical WISM is often high-order, causing the oscillation risk assessment to be computationally heavy. Therefore, in this paper, an efficient stability criterion is proposed, which gives the critical stability conditions considering the impact of number of generators and network topology. Then NFFO risk of a WISM under different numbers of generators and network topologies can be quickly judged. The stability criterion can be obtained via the Nyquist-based stability analysis on a single generator integrated system via MMC-HVDC and hence is simple in application. In addition, derivations of the stability criterion also give an analytical explanation to the NFFO risk induced by the integration of wind power. Finally, effectiveness of the proposed method and conclusions drawn is verified based on a typical WISM. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

A Method of Magnetometer Relative Reference Calibration for Micro-Nano Satellite and Its Application in Orbit

A Method of Magnetometer Relative Reference Calibration for ...

引用

IEEE International Conference of Intelligent Robotic and control engineering (IRCE)

作者： Mingqun Li Xiang Liu Shangshang Chen Kun Ma Qinghua Jiang Research and Development Center Beijing Institute of Control Engineering Beijing China System Design Department Beijing Institute of Control Engineering Beijing China

For a low-cost micro-nano satellite that uses magnetometer as the core sensor of attitude determination system, a calibration method of relative reference between multiple magnetometer is proposed. The influence of satellite magnetic environment on magnetic field intensity measurement is studied. After considering remanence, induction and installation deviation, an accurate measurement model of magnetometer is proposed. Without introducing other high-performance attitude sensors, the relative relationship between the measurement data of different magnetometer is derived, and a magnetometer relative reference calibration method based on the least square method is proposed. Mathematical simulation shows that the proposed method reduces the relative measurement error of the magnetometer from 2000 nT to 50 nT, and then uses the telemetry data of the satellite in orbit to calibrate several magnetometer of the satellite. After injecting new parameters, the attitude difference of satellites with different magnetometer as the reference decreases from 16 degrees to less than 2 degrees, indicating that the consistency of the magnetometer reference has been significantly improved, which verifies the effectiveness and practicality of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Biochar technology cannot offset land carbon emissions in Guangdong province, China

引用

Carbon research 2024年第1期3卷 1-14页

作者： Wang, Funing Zhou, Wenneng Wang, Xili Zhao, Qing Han, Mengjie State Key Lab of Clean Energy Utilization Institute of Carbon Neutrality State Environmental Protection Engineering Center for Coal-Fired Air Pollution Control Zhejiang University Hangzhou310027 China Jiaxing Research Institute Zhejiang University Jiaxing314000 China Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds School of Ecology Environment and Resources Guangdong University of Technology Guangzhou510006 China Economic & amp Information center Zhejiang310006 China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing100084 China Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management Institute of Eco-environmental and Soil Sciences Guangdong Academy of Sciences Guangzhou510650 China National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China Guangzhou510650 China

As a highly developed region, Guangdong province has substantial industrial emissions. Its subtropical monsoon climate, characterized by abundant hydrothermal conditions, contributes to a substantial biomass potential. The adoption of potential biomass-based carbon dioxide removal (CDR) technologies, such as biochar, presents an opportunity to mitigate emissions and work towards carbon neutrality in the future. However, the current state of the land carbon balance and the CDR potential of biochar in Guangdong province remains unclear. We first calculated the land carbon balance based on inventory data. Then we estimated the CDR potential of biochar derived from agricultural residues, forestry residues, and bioenergy crops cultivated on marginal lands in Guangdong province using life cycle analysis (LCA). Results show that Guangdong province has not yet achieved carbon neutrality, with a net emission (carbon emissions remaining after offsetting by carbon sinks) of 925.63 Tg CO2e (CO2 equivalent, 1Tg = 106 t) in 2021. Emissions from energy consumption account for the highest proportion, contributing 83.8% of total emissions. In the highest biomass utilization scenario, the maximum CDR potential of biochar derived from all biomass types reaches 84.30 Tg CO2e yr-1, which could offset 9.11% of net carbon emissions in Guangdong province. Our findings provide crucial guidance for setting emission reduction targets and implementing effective mitigation strategies in Guangdong province under temperature warming. Graphical Abstract: (Figure presented.) © The Author(s) 2024.

关键词： Carbon capture and utilization

来源：评论

学校读者我要写书评

暂无评论

A Low-complexity Decision Variables Classification Brainstorm Optimization Algorithm

A Low-complexity Decision Variables Classification Brainstor...

引用

2024 International Conference on Applied Mathematics, Modelling and Statistics Application, AMMSA 2024

作者： Li, Qiyue Qiu, Lipeng Zhou, Aoran Wu, Yali Wang, Ziren Department of Information and Control Engineering Xi'An University of Technolog Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd. Xi'an710016 China

In the complex optimization scenarios of real life, we often need to not only weigh the conflicts between multi-objectives but also face the challenges brought by large-scale decision variables. When the scale of decision variables increases sharply, the search space will expand exponentially, which makes it difficult for the algorithm to traverse the whole search space under limited resources, so that the number of local optimal solutions increases sharply. The so-called 'dimension disaster' appears. To effectively deal with this problem, this paper proposes a large-scale multi-objective brainstorm optimization algorithm (LMaOBSO) based on low complexity decision variable classification method and improved penalty boundary intersection strategy. The algorithm uses a low-complexity tree sorting variable classification method to divide the decision variables into converges and diversity variables quickly. At the same time, the convergent variables are optimized by the improved penalty boundary crossover strategy to solve the problems existing in large-scale optimization problems. © Published under licence by IOP Publishing Ltd.

关键词： Disasters

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：