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First wetland mapping at 10-m spatial resolution in South America using multi-source and multi-feature remote sensing data

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Science China Earth Sciences 2024年第10期67卷 3252-3269页

作者： Weiwei SUN Gang YANG Yuling HUANG Dehua MAO Ke HUANG Lin ZHU Xiangchao MENG Tian FENG Chao CHEN Yong GE Department of Geography and Spatial Information Techniques Ningbo UniversityNingbo 315211China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences&Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Natural Resources and Planning Bureau Shanghai Pudong New DistrictShanghai 200100China Key Laboratory of Wetland Ecology and Environment Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun 130102China Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China School of Geography Science and Geomatics Engineering Suzhou University of Science and TechnologySuzhou 215009China

Wetland degradation has been accelerating in recent years globally. Accurate information on the geographic distribution and categories of wetlands is essential for their conservation and management. Despite being the world′s fourth largest continent, South America has limited research on wetland mapping, and there is currently no available map that provides comprehensive information on wetland distribution and categories in the region. To address this issue, we used Sentinel-1, Sentinel-2 and SRTM data, developed a sample collection method and a wetland mapping method with a collection of multi-source features such as optical features, polarization features and shape features for South American wetlands. We produced a 10-m resolution wetland map based on the Google Earth Engine(GEE) platform. Our Level-1 wetland cover map accurately captured six wetland sub-categories with an overall accuracy of 96.24% and a kappa coefficient of 0.8649, while our Level-2 water cover map included five sub-categories with an overall accuracy of 97.23% and a kappa coefficient of0.9368. The results show that the total area of existing wetlands in South America is approximately 1,737,000 km~2, which is6.8% of the total land area. Among the ten wetland categories, shallow sea had the largest area(960,527.4 km~2), while aquaculture ponds had the smallest area 1513.6 km~2. Swamp had the second largest area(306,240.1 km~2). Brazil, Argentina,Venezuela, Bolivia, and Colombia were found to have the largest wetland areas, with Brazil and Colombia having the most diverse wetland categories. This product can serve as baseline data for subsequent monitoring, management, and conservation of South American wetlands.

关键词： Wetland mapping Google Earth Engine Sentinel imagery South America

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FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models 38

FIRE: A Dataset for Feedback Integration and Refinement Eval...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Li, Pengxiang Gao, Zhi Zhang, Bofei Yuan, Tao Wu, Yuwei Harandi, Mehrtash Jia, Yunde Zhu, Song-Chun Li, Qing Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology China State Key Laboratory of General Artificial Intelligence BIGAI China State Key Laboratory of General Artificial Intelligence Peking University China Department of Electrical and Computer System Engineering Monash University Australia Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University China Department of Automation Tsinghua University China

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinement dataset, consisting of 1.1M multi-turn conversations that are derived from 27 source datasets, empowering VLMs to spontaneously refine their responses based on user feedback across diverse tasks. To scale up the data collection, FIRE is collected in two components: FIRE-100K and FIRE-1M, where FIRE-100K is generated by GPT-4V, and FIRE-1M is freely generated via models trained on FIRE-100K. Then, we build FIRE-Bench, a benchmark to comprehensively evaluate the feedback-refining capability of VLMs, which contains 11K feedback-refinement conversations as the test data, two evaluation settings, and a model to provide feedback for VLMs. We develop the FIRE-LLaVA model by fine-tuning LLaVA on FIRE-100K and FIRE-1M, which shows remarkable feedback-refining capability on FIRE-Bench and outperforms untrained VLMs by 50%, making more efficient user-agent interactions and underscoring the significance of the FIRE dataset. © 2024 Neural information processing systems foundation. All rights reserved.

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Micro reactors for measurement and analysis of thermochemical gas-solid reactions

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Resources Chemicals and Materials 2022年第2期1卷 152-166页

作者： Zhennan Han Junrong Yue Chao Wang Xi Zeng Jian Yu Fang Wang Yu Guan Xuejing Liu Fu Ding Liangliang Fu Xin Jia Xingfei Song Dingrong Bai Guangwen Xu Key Laboratory on Resources Chemicals and Material of Ministry of Education Shenyang University of Chemical TechnologyShenyang 110142China The State Key Laboratory of Multi-phase Complex System Institute of Process EngineeringChinese Academy of ScienceBeijing 100190China School of Ecology and Environment Beijing Technology and Business UniversityBeijing 100048China

Micro reactors are the essential part of thermal analysis techniques for characterizing gas-solid thermochemical reactions. The dynamic and diversified needs for investigating various complex materials and gas-solid reactions have led to the development of a variety of different microreactors over the years. Solid particles in microreactors are normally heated by furnaces from outside, resistive elements from inside, direct contact with bed particles, or other non-resistively methods. Solid particles can be fixed or fluidized in reactors where gas-solid contacts vary from diffusion-dominated to nearly diffusion-free conditions. Based on these characteristics, in this article we presented a broad classification for microreactors used for thermal analysis of gas-solid reactions. For each of the most popularly used microreactors, their features and limitations are briefly reviewed. By addressing the diversity of the microreactors used in the field of thermal analysis, the review aims at providing general guidance for the selection and operation of the microreactor to satisfy one's practical specific needs.

关键词： Microreactors Thermal analysis Gas-solid reaction Kinetics Mechanism

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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YOLO-based multi-class target detection for SAR images

YOLO-based multi-class target detection for SAR images

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IEEE Information Technology and Mechatronics engineering Conference (ITOEC)

作者： Linlin Qiu Weigang Zhu Yonggang Li Lei Qiu Fanyin Ma Graduate School Space Engineering University Beijing China Key Laboratory of Complex Electronic System Simulation Department of Electronics and Optical Engineering Space Engineering University Beijing China

The current SAR image target detection mainly focuses on single category target detection problem in single task scenario, and no research has been conducted on multi-category target detection in different scenarios. YOLO is widely used in target detection tasks because of its speed and accuracy. In this paper, the YOLOv3, YOLOv5 and YOLOv8 algorithms, which have better detection performance and are more widely used, are used to perform target detection on the SAR image multi-category target detection dataset MSAR-1.0, and the detection results are analyzed from both the SAR image multi-category target detection dataset and the YOLO algorithm.

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Conversion of infrared ocean target images to visible images driven by energy information

Conversion of infrared ocean target images to visible images...

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作者： Chen, Changlin Chao, Xuewei State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China College of Mechanical and Electrical Engineering Shihezi University Xinjiang China

Infrared images are full of energy information, which can intuitively reflect the difference between objects and scenes. Visible images are full of color information, which can intuitively reflect the details of objects and scenes. To achieve the comprehensive utilization of infrared energy information when transforming infrared images to visible images, this paper proposes a method called infrared-energy-to-color (IETC) based on Cycle-Consistent Generative Adversarial Networks (CycleGAN). We compare some state-of-the-art methods in image transformation;the results show that the proposed model can generate visible images of ocean objects and scenes in the visual expression. Furthermore, in the quantitative evaluation, the proposed method performs better than others. In addition, the classic object detection algorithms also show that the proposed IETC method can achieve more robust results. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Image classification

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Short Circuit Fault Characteristics of Low Frequency AC Transmission system Based on Modular Multilevel Matrix Converter

Short Circuit Fault Characteristics of Low Frequency AC Tran...

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2023 International Conference on Power Energy systems and Applications, ICoPESA 2023

作者： Zhao, Zexin Han, Bin Zhao, Guoliang Xu, Yunfei Lu, Zhengang Xiang, Nianwen Wang, Shulai China Electric Power Research Institute Power System Department Beijing China State Grid Smart Grid Research Institute State Key Laboratory of Advanced Power Transmission Technology Beijing China Hefei University of Technology School of Electrical Engineering and Automation Hefei China

ISBN: (纸本)9798350345605

Compared with power frequency AC transmission and DC transmission, low frequency AC transmission has its unique advantages, which is suitable for long distance transmission, large scale renewable generation and regulation of regional power grid. The fault characteristics affect the system design and operation, which is necessary to study. From the perspective of system topology and converter control, the characteristics of three-phase short circuit fault are analyzed and a simulation model is built on PSCAD for verification in this paper. After a fault occurs, it can be divided into two stages before and after the control responses. Before the control responses, the overvoltage is generated between the terminals of branch reactors and modular capacitors discharges. After the control responses, system characteristics are related to fault location and control strategy. The control and modulation of the converter can make the low frequency and power frequency systems interact with each other. This study can provide a reference for the parameters of equipment and converter control, as well as fault protection in low frequency systems. © 2023 IEEE.

关键词： Timing circuits

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Modal Analysis of a Renewable Power Generation Station Based on the Equivalent Decoupling 8

Modal Analysis of a Renewable Power Generation Station Based...

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8th Asia Conference on Power and Electrical engineering, ACPEE 2023

作者： Wang, Xiao Dong, Wenkai Sun, Yamin Su, Tianyu Xie, Xiaorong North China Electric Power Research Institute Co. Ltd State Grid Jibei Electric Power Co. Ltd. Research Institute Beijing China Tsinghua University State Key Laboratory of Power System Department of Electrical Engineering Beijing China

ISBN: (纸本)9798350345520

In this paper, a single-unit-based modal analyzing method for the renewable power generation station (RPGS) is proposed and the characteristics of the mode shapes (MSs) and participation factors (PFs) are analytically studied. First, under the condition that the units are of similar dynamic models, expressions for the MS and PF matrices of the station with respect to the MS and PF matrices of a single unit and the network parameters are derived. Then, it is found that for each of the modes, the MSs and PFs can be formed by the MSs and PFs of a single unit and the eigenvalues and eigenvectors of the network reactance matrix. Therefore, a single-unit-based modal analysis method is proposed. Second, it is further revealed that under the condition of similar dynamic models, the activities and participations of the same state variable of each of the units to a single mode are mainly determined by the network topology. In addition, the condition and mechanism for the phenomenon that participations of each of the units to the dominant mode are nearly identical are also analytically demonstrated. Finally, effectiveness of the method proposed and conclusions drawn is verified via study cases. © 2023 IEEE.

关键词： Modal analysis

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Decision Dependent Uncertainty Modelling Methodology for Renewable-dominant Power systems 23

Decision Dependent Uncertainty Modelling Methodology for Ren...

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23rd Wind and Solar Integration Workshop, WIW 2024

作者： Wang, Weisheng Wang, Zheng Feng, Shuanglei Liu, Feng Hou, Yunhe Hu, Bo State Key Laboratory of Renewable Energy Grid-Integration China Electric Power Research Institute Haidian District Beijing100192 China Department of Electrical Engineering Tsinghua University Beijing100084 China Department of Electrical and Electronic Engineering The University of Hong Kong 999077 Hong Kong State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9781837242689

In renewable-dominant power systems, renewable energy sources such as wind power and photovoltaics become the main contributors to electric power and power generation. Due to the wind and solar resources across different time and spatial contexts, as well as the different types of load response resources, their uncertainties differ significantly. Compared to traditional power systems, renewable-dominant power systems not only experience a notable increase in uncertainty on the power supply side, but also exhibit significant changes in the characteristics of uncertainty on both supply and demand sides. Focusing on the uncertainty on both supply and demand sides of renewable-dominant power systems, this paper finds the decision dependent uncertainty on both supply and demand sides, reveals the mechanism of the decision dependent uncertainty on both supply and demand sides, puts forward a quantitative characterization method of the decision dependent uncertainty by using mathematical modelling method and joint probability distribution theory, and realizes the optimal solution. According to the example simulation results, the proposed method and constructed model can effectively quantify and characterize the decision dependent uncertainty on both supply and demand sides of renewable-dominant power systems. Moreover, the computational results show a high degree of agreement with actual conditions, thereby validating the rationality and correctness of the research methods employed. © Energynautics GmbH.

关键词： DECISION DEPENDENT UNCERTAINTY MODELLING ENDOGENOUS UNCERTAINTY EXOGENOUS UNCERTAINTY OPTIMIZATION SOLUTION RENEWABLE-DOMINANT POWER system

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Zero-Order Optimization in Security Constrained Power system Scheduling 4

Zero-Order Optimization in Security Constrained Power System...

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4th IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024

作者： An, Qi Wang, Jianxiao Wu, Shengyu Ren, Weikai Huang, Ruanming Li, Gengyin North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China Peking University National Engineering Laboratory for Big Data Analysis and Applications Beijing China State Grid Energy Research Institute CO. LTD. Beijing China Institute of Energy Peking University Beijing China Planning Center State Grid Shanghai Electric Power Company Shanghai China

ISBN: (纸本)9798350395914

The security and resilience of power systems are gradually challenged. As a typical index measuring the security and resilience of power systems, the frequency stability issue is becoming prominent. Due to the increase in the complexity of power systems, the frequency stability boundary is gradually becoming fuzzy, leading to traditional analytical-modeling algorithms hardly applicable for frequency stability constrained dispatch. Existing data-driven methods for characterizing frequency stability boundary typically requires massive simulation calculations, leading to unnecessary computing power consumption. To this end, zeroth-order (ZO) optimization, which aims to solve optimization problems embedding non-analytic functions, is adopted for solving the frequency stability constrained dispatch in this paper. In contrast to traditional data-driven methods, we directly embed frequency stability simulation check into power system dispatch. The gradient of frequency stability simulation check is estimated through ZO optimization, thereby realizing the interaction optimization between power system dispatch and real-time simulation. In this way, the solution for the frequency stability constrained dispatch is modified towards the optimal point along the gradient descent direction. Cases studies based on IEEE-9 bus system verifies that, compared with traditional data-driven methods, the solution approach we propose could reduce the system cost while significantly improving the calculation efficiency. © 2024 IEEE.

关键词： Frequency stability

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