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Selecting of global phenological field observations for validating coarse AVHRR-derived forest phenology products based on spatial heterogeneity and temporal consistency

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Ecological Informatics 2025年 90卷

作者： Shao, Qi Huang, Chao Xiao, Yuanjun Liu, Li Liu, Weiwei Huang, Ran Zhou, Chang Weng, Wei Huang, Jingfeng Key Laboratory of Environmental Remediation and Ecological Health Ministry of Education Zhejiang University Hangzhou 310058 China State Key Laboratory of Soil Pollution Control and Safety Zhejiang University Hangzhou 310058 China Institute of Applied Remote Sensing and Information Technology Zhejiang University Hangzhou 310058 China Key Laboratory of Agricultural Remote Sensing and Information Systems Hangzhou 310058 China Key Laboratory of National Forestry and Grassland Administration on Forest Ecosystem Protection and Restoration of Poyang Lake Watershed College of Forestry Jiangxi Agricultural University Nanchang 330045 China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering College of Computer and Information Technology China Three Gorges University Yichang 443002 China Department of Geography and Spatial Information Techniques Ningbo University Ningbo 315211 China School of Automation Hangzhou Dianzi University Xiasha Higher Education Zone Hangzhou 310058 China

Global phenological field observations play a crucial role in validating remote sensing products and algorithms. However, due to the spatial mismatch and scale effect between the field observations and the pixels of remote sensing phenology products, a direct comparison often leads to scale errors and increased uncertainty. Therefore, evaluating the spatial representativeness of field observations for remote sensing product validation is essential. This study developed a novel “bottom-up” evaluation framework named MSPT (Main land cover type, Spatial heterogeneity, Point-area consistency and Temporal consistency), which comprehensively assesses the spatial representativeness of forest phenological field observations within the coarse spatial scale. Based on MSPT method, the capability of global forest phenological field observations to support coarse-scale remote sensing validation was evaluated. Compared with the general method, MSPT significantly improved validation performance. For the start of the growing season (SOS), the root mean square error (RMSE) decreased from 49.70 to 33.75 days, and the percent bias (PBIAS) changed from −0.14 to 0.03. For the end of the growing season (EOS), the RMSE was reduced from 83.42 to 42.53 days, and the PBIAS decreased from 0.15 to 0.08. These findings demonstrate that MSPT enhances the reliability of validation datasets and effectively reducing uncertainty in the evaluation of coarse AVHRR-derived forest phenology products. The framework offers new insights into resolving the scale mismatch between field observations and the pixels of remote sensing products. © 2025

关键词： Field observations Forest phenology Satellite product Spatial mismatch Spatial representativeness

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Off-Policy Q-Learning for Anti-Interference control of Multi-Player Systems ⁎

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IFAC-PapersOnLine 2020年第2期53卷 9189-9194页

作者： Jinna Li Zhenfei Xiao Tianyou Chai Frank. L. Lewis Sarangapani Jagannathan School of Information and Control Engineering Liaoning Shihua University Fushun 113001 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China UTA Research Institute the University of Texas at Arlington Arlington TX 76118 USA Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 USA

This paper develops a novel off-policy game Q-learning algorithm to solve the anti-interference control problem for discrete-time linear multi-player systems using only data without requiring system matrices to be known. The primary contribution of this paper lies in that the Q-learning strategy employed in the proposed algorithm is implemented in an off-policy policy iteration approach other than on-policy learning due to the well-known advantages of off-policy Q-learning over on-policy Q-learning. All of the players work hard together for the goal of minimizing their common performance index meanwhile defeating the disturbance that tries to maximize the specific performance index, and finally they reach the Nash equilibrium of the game resulting in satisfying disturbance attenuation condition. In order to find the solution to the Nash equilibrium, the anti-interference control problem is first transformed into an optimal control problem. Then an off-policy Q-learning algorithm is proposed in the framework of typical adaptive dynamic programming (ADP) and game architecture, such that control policies of all players can be learned using only measured data. Comparative simulation results are provided to verify the effectiveness of the proposed method.

关键词： H ∞ control off-policy Q-learning game theory Nash equilibrium

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How to Teach control System Optimization (A Practical Decompisition Approach for the Optimization of TDOF control Systems)

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IFAC-PapersOnLine 2019年第9期52卷 115-120页

作者： Cs. Bányász L. Keviczky R. Bars Institute for Computer Science and Control of the Hungarian Academy of Sciences Department of Automation and Applied Informatics Budapest University of Technology and Economics H-1111 Budapest Kende u 13-17 Hungary

The optimality in a generic two-degree of freedom control system can be decomposed into three major steps, because the control error has three major parts: design-, realizability- and modeling-loss. The second term can be made zero for inverse stable processes only. This decomposition opens new ways for practical optimization of two-degree-of-freedom ( TDOF ) systems and helps the construction of new algorithms for robust identification and control. It is more reasonable to teach the optimization of control systems using these components.

关键词： two-degree-of-freedom control systems performance robustness optimality

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Bebop 2 Quadrotor as a Platform for Research and Education in Robotics and control Engineering

Bebop 2 Quadrotor as a Platform for Research and Education i...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Wojciech Giernacki Piotr Kozierski Jacek Michalski Marek Retinger Rafal Madonski Pascual Campoy Institute of Robotics and Machine Intelligence Faculty of Control Robotics and Electrical Engineering of Poznan University of Technology Poznań Poland Institute of Computing Science (Faculty of Computing and Telecommunications) and with the Institute of Robotics and Machine Intelligence (Faculty of Control Robotics and Electrical Engineering) Poznan University of Technology Poznań Poland International Energy College Energy Electricity Research Center Jinan University Zhuhai China Computer Vision and Aerial Robotics (CVAR) Centre for Automation and Robotics Technical University of Madrid (UPM) Madrid Spain

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

In conducting research and teaching in fields related to unmanned aerial vehicles (UAVs), it is particularly important to select a universal, safe, open research platform and tools for rapid prototyping. Ready-to-use, low-cost micro-class UAVs such as Bebop 2 are successfully used in that regard. This article presents how to use the potential of this flying robot with Robot Operating System (ROS). The most important software solutions for the developed experimental testbed FlyBebop are characterized here. Their capabilities in research and education are exemplified using three distinct cases: 1) research results on the method of optimal, in-flight, iterative self-tuning of UAV position controller parameters (based only on current measurements), 2) the use of the reinforcement learning method in the autonomous landing of a single drone on a moving vehicle, 3) planning the movement of UAVs for autonomous video recording along the planned path in the arrangement: "cameraman drone" and "lighting technician drones".

关键词： Drones Robots Education Cameras Sensors Tools

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Switched-capacitor finite impulse response rotator filter

Switched-capacitor finite impulse response rotator filter

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Paweł Pawłowski Rafał Długosz Adam Dąbrowski Division of Signal Processing and Electronic Systems Jana Pawł a II 24 Poznan University of Technology Faculty of Control Robotics and Electrical Engineering and Institute of Automation and Robotics Poznań Poland Faculty of Telecommunication Computer Science and Electrical Engineering Kaliskiego 7 UTP University of Science and Technology Bydgoszcz Poland

ISBN: (数字)9788362065394

ISBN: (纸本)9781728177465

Design of the topology and layout for an analog finite impulse response (FIR) filter realized in the CMOS technology using the switched capacitor (SC) technique, is presented. The filter is based on the so called “rotator structure” supplemented with the programmable capacitor array. This array makes the on-line adjusting of the frequency response of the filter possible in a very wide range, thus, enlarges the area of applications of this circuit, e.g., to multi-standard wireless communication, software-defined radio, adaptive systems, etc. The presented circuit realizes filters of orders up to 15 (16 filter coefficients). The maximum frequency range approaches ca. 2 MHz. The circuit dissipates ca. 8 mW from the power supply.

关键词： Finite impulse response filters Capacitors IIR filters Clocks Operational amplifiers Switches Capacitance

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Improved K-medoids clustering based on gray association rule

Improved K-medoids clustering based on gray association rule

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International Conference on Intelligent Computing, Communication and Devices, ICCD 2017

作者： Gao, Shiying Zhou, Xiaofeng Li, Shuai Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Network Control System Chinese Academy of Sciences Shenyang110016 China School of Computer Science and Engineering Northeastern University Shenyang110000 China

ISBN: (纸本)9789811089435

This paper presents a new K-Medoids clustering algorithm based on gray relational degree. Analyze the gray incidence of each attribute and convert them into the weights of the attributes, and then apply these weights to the distance measure of the cluster;based on this measure, this paper proposed an improved clustering algorithm: Gray-K-Medoids clustering algorithm and applied it to the analysis of the aluminum electrolysis data. The paper introduces the gray relational degree and the basic principle based on the gray relational degree clustering and introduced the improved algorithm in detail. In order to test the effect of improving the algorithm, it was used to the production data of an aluminum plant, and the results show the effectiveness of the algorithm, has a certain promotional value. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Clustering algorithms

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Extensions of the open-source framework Aerostack 3.0 for the development of more interactive flights between UAVs

Extensions of the open-source framework Aerostack 3.0 for th...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Wojciech Giernacki Jacek Cieślak Martin Molina Pascual Campoy Institute of Robotics and Machine Intelligence Faculty of Control Robotics and Electrical Engineering Poznan University of Technology Poznań Poland Department of Artificial Intelligence Technical University of Madrid (UPM) Madrid Spain Computer Vision and Aerial Robotics (CVAR) Centre for Automation and Robotics Technical University of Madrid (UPM) Madrid Spain

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

The basis for properly verified R&D works is to provide reliable prototyping tools at three most important stages: computer simulation, laboratory tests and real-world experiments. In the laboratory-limited conditions, particular importance is attributed to the first two stages, especially in the context of the safety development of autonomous flights of unmanned aerial vehicle (UAV) groups in various missions. The open-source framework Aerostack support those needs and its effectiveness has been proven in the International Micro Air Vehicle Indoor Competitions (IMAV 2013, 2016, 2017) and Mohammed Bin Zayed International Robotics Challenge (MBZIRC 2020). In the paper, the exemplary functionalities for the new version of Aerostack Version 3.0 Distribution Sirocco (Aerial robotics framework for the industry), extended additionally with a library of new behaviors, are presented. The mission of UAVs can be developed fast and effectively in order to conduct test flights with real drones in lab, before one will decide to fly autonomously outdoor. The representative results obtained for low-cost *** 2.0 UAV models in two missions, are presented. The first mission is autonomous patrolling the area by a pair of UAVs, the second - intercepting the intruder in guarded area by the guard UAV.

关键词： Robots Trajectory Drones Libraries Software computer architecture

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Smart train operation algorithms based on expert knowledge and reinforcement learning

arXiv

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arXiv 2020年

作者： Zhou, Rui Song, Shiji Xue, Anke You, Keyou Wu, Hu Department of Computer Science University of Oxford OxfordOX1 1LE United Kingdom Department of Automation Tsinghua University Beijing100084 China Key Laboratory for IOT and Information Fusion Technology of Zhejiang Institute of Information and Control Hangzhou Dianzi University Hangzhou310018 China

During recent decades, the automatic train operation (ATO) system has been gradually adopted in many subway systems. On the one hand, it is more intelligent than traditional manual driving;on the other hand, it increases the energy consumption and decreases the riding comfort of the subway system. This paper proposes two smart train operation algorithms based on the combination of expert knowledge and reinforcement learning algorithms. Compared with previous works, smart train operation algorithms can realize the control of continuous action for the subway system and satisfy multiple objectives (the safety, the punctuality, the energy efficiency, and the riding comfort) without using an offline optimized speed profile. Firstly, through analyzing historical data of experienced subway drivers, we summarize the expert knowledge rules and build inference methods to guarantee the riding comfort, the punctuality and the safety of the subway system. Then we develop two algorithms to realize the control of continuous action and to ensure the energy efficiency of train operation. Among them, one is the smart train operation (STO) algorithm based on deep deterministic policy gradient named (STOD) and another is the smart train operation algorithm based on normalized advantage function (STON). Finally, we verify the performance of proposed algorithms via some numerical simulations with the real field data collected from the Yizhuang Line of the Beijing Subway and their performance will be compared with existing ATO algorithms. The results of numerical simulations show that the developed smart train operation systems are better than manual driving and existing ATO algorithms in respect of energy efficiency. In addition, STOD and STON have the ability to adapt to different trip times and different resistance conditions. Copyright © 2020, The Authors. All rights reserved.

关键词： Reinforcement learning

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The Method of Neural Network control over the Process of Manufacturing Foil Solar Panels 2

The Method of Neural Network Control over the Process of Man...

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2nd IEEE International Conference on System Analysis and Intelligent Computing, SAIC 2020

作者： Sachenko, Anatoliy Ivakhiv, Orest Vyshnia, Volodymyr Grzeszczyk, Konrad Osolinskyi, Oleksandr Novosad, Stanislav Kochan, Volodymyr Nakonechnyi, Markiyan Kochan, Orest Kopania, Lukasz Kazimierz Pulaski University of Technology and Humanities in Radom Department of Informatics Radom Poland Lviv Polytechnic National University Department of Intelligent Mechatronics and Robotics Lviv Ukraine Dnipropetrovsk State University of Internal Affairs Department of Economic and Information Security Dnipro Ukraine International Vision Machinery VISORT Sp. J Radom Poland Ternopil National Economic University Department for Information Computer Systems and Control Ternopil Ukraine Ternopil National Economic University Research Institute for Intelligent Computer Systems Ternopil Ukraine Lviv Polytechnic National University Department of Computerized Automation Systems Lviv Ukraine Lviv Polytechnic National University Department of Measuring Information Technologies Lviv Ukraine

ISBN: (纸本)9781728190822

Authors have developed a method of control over one of the main technological processes of manufacturing foil solar panels, i.e., burning tracks in the layers of semiconductor material and insulation. The proposed method is based on neural networks trained directly on the control object. This eliminates the laborious process of identifying the parameters of the control object mathematical model and the impact of its error on the training outcomes. To clarify the conditions for optimizing a certain law for generating the control action by neural networks various laws of control have been simulated. It's established that laws of control can be changed according to the current situation of the control object. Simulation outcomes proofed that the most efficient is the system with the PI- controller. © 2020 IEEE.

关键词： Process control

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Capsule Network-Based Text Sentiment Classification

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IFAC-PapersOnLine 2020年第5期53卷 698-703页

作者： Bingyang Chen Zhidong Xu Xiao Wang Long Xu Weishan Zhang School of Computer Science and Technology China University of Petroleum Qingdao 266580 China School of security National Defence University PLA China Beijing 100091 China Beijing 100091 China Qingdao Academy of Intelligent Industries Shandong Qingdao 266109 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

To improve text sentiments classification issues, such as information loss and insensitivity to spatial information, this paper proposes a text sentiment classification model based on the capsule network (T-Caps), which uses the Transformer to extract low-level text features. The method iteratively updates capsule network parameters through optimized dynamic routing algorithms and global parameter sharing, and it obtains the relationship between local features of the text and the overall emotional polarity to save the information integrity of text features. By comparing with multiple models, we find that the Transformer has the strongest feature extraction capability. The experimental results show that our model is capable of extracting more discriminative semantic features and yields a significant performance gain compared to other baseline methods.

关键词： Sentiment classification Capsule network Transformer Deep learning Attention

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