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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data 49

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Cheng, Haibo He, Yunpeng Zeng, Peng Li, Shichao Vyatkin, Valeriy Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350331820

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction. © 2023 IEEE.

关键词： Forecasting

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Multi-Quasi-Proportional-Resonant Control for Capacitive-Coupling Grid-Connect Inverter (CGCI) with Accurate Active Power Injection Technique 49

Multi-Quasi-Proportional-Resonant Control for Capacitive-Cou...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Chan, Pak-Ian Sou, Wai-Kit Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal Vlsi China Institute of Microelectronics University of Macau China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350331820

In this paper, a multi-quasi-proportional-resonant control (MQPRC) for a three-phase capacitive-coupling grid-connect inverter (CGCI) with accurate active power injection technique is proposed to mitigate the current harmonics and improve the active power injection accuracy. Then, a detail parameter design of the proposed MQPRC is provided. And the proposed accurate active power injection is verified by the simulation. Subsequently, to verify the effectiveness of the proposed MQPRC, the simulation results are presented in comparison to the quasi-proportional-resonant control (QPRC). © 2023 IEEE.

关键词： Power quality

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Review of Different Current Control Strategies for Thyristor-Controlled LC-Coupling Hybrid Active Power Filter 32

Review of Different Current Control Strategies for Thyristor...

引用

32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Sou, Wai-Kit Chan, Pak-Ian Gong, Cheng Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China University of Macau Institute of Microelectronics China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350399714

With the characteristics of low DC-link voltage and wide operating range, thyristor-controlled LC-coupling hybrid active power filter (TCLC-HAPF) is a promising power quality compensator in the medium-voltage-level power system. This paper reviews the design and implementation of different current control strategies for the TCLC-HAPF, which are hysteresis current control (HCC), multi-quasi-proportional-resonant control (MQPRC), H∞ optimal control (HOC), finite-set model predictive control (FS-MPC), second-order sliding mode control (SOSMC) and deadbeat current control (DBCC). Also, their pros and cons are fully discussed. In order to provide a deeper understanding about the steady-state and transient performances of these control strategies, the simulation study is presented under both inductive and capacitive loads. © 2023 IEEE.

关键词： Thyristors

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Exploring the Integration of Educational Robotics and the Internet of Things in Learning Environments

Exploring the Integration of Educational Robotics and the In...

引用

International Conference on Distributed Computing in Sensor systems (DCOSS)

作者： Elena Kakoulli Salomi Evripidou Department of Computer Science Intelligent Systems Laboratory Neapolis University Pafos Pafos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

This study explores the integration of Educational Robotics (ER) and the Internet of Things (IoT) in learning environments, highlighting their collective impact on educational practices. It assesses ER and IoT’s application, challenges, and opportunities, offering insights into their role in enhancing pedagogy and learning outcomes. Specifically, our exploration uncovers the transformative potential of ER and IoT in fostering critical thinking, problem-solving skills, and digital literacy among students and reveals the pivotal role these technologies play in preparing learners for the demands of the digital age and Industry 4.0, while also highlighting the need for strategic implementation and teacher support. Our findings elucidate the potential of ER and IoT to innovate teaching strategies and curriculum design, serving as a guide for educational stakeholders, such as curriculum developers, educators, researchers, and policymakers, in leveraging these technologies to revolutionize instructional practices.

关键词： Training Information age Fourth Industrial Revolution Internet of Things Stakeholders Problem-solving Distributed computing

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A High-Performance Three-Coil Wireless Charging System for Empowering Unmanned Surface Vehicle 49

A High-Performance Three-Coil Wireless Charging System for E...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Ieong, Chi-Fong Wong, Hou-Wa Iam, Io-Wa Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal Vlsi China Institute of Microelectronics University of Macau China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350331820

The use of unmanned surface vehicles (USVs) in oceanography research is widespread due to their ability to provide real-time data. Due to the limited battery size, recharging operations including plugging and unplugging decrease the overall utilization of the USV. To address this issue, wireless power transfer (WPT) can be implemented by installing coils at the dock and inside the USV. In this paper, a three-coil WPT system is designed for offshore USV wireless charging applications. The proposed three-coil structure is designed to ensure adequate coupling and achieve high transfer efficiency. Aiming to meet practical battery charging specifications, LCC-S-S compensation topology is analyzed with detailed parameter design to provide constant current output. Finally, simulations are conducted to verify the coupling and output characteristics of the system. © 2023 IEEE.

关键词： Energy transfer

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Optimal Linear Deception Attacks on Remote state Estimation with Constrained Alarm Rates: A Low-Dimensional Case

Optimal Linear Deception Attacks on Remote State Estimation ...

引用

IEEE Conference on Decision and Control

作者： Jun Shang Hanwen Zhang Jing Zhou Tongwen Chen Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack’s stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback–Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples.

关键词： Wireless communication Measurement Technological innovation System performance Kalman filters state estimation intelligent sensors

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Optimizing Inductive Power Transfer Circular Pad Coils for Electric Vehicles Using Multi-Objective Particle Swarm Optimization 49

Optimizing Inductive Power Transfer Circular Pad Coils for E...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wong, Hou-Wa Ieong, Chi-Fong Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal Vlsi China Institute of Microelectronics University of Macau China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350331820

The wireless power transfer (WPT) technology has gained significant attention in recent years due to its potential to provide a convenient and efficient method to charging electronic devices without the need for physical connections. In wireless charging, the inductive coils are significantly important as they are the component that power transfer takes place. In this context, Multi-Objective Particle Swarm Optimization (MOPSO) has emerged as a promising technique for designing WPT coils with improved performance. Aiming to verify the performance of the designed coil, LCC-S compensation topology was utilized as it can provide practical battery charging specifications. © 2023 IEEE.

关键词： Inductive power transmission

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Harmonic Transfer Function Modeling of LCC-S Inductive Power Transfer System

Harmonic Transfer Function Modeling of LCC-S Inductive Power...

引用

2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Gong, Cheng Ding, Zhaoyi Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal Vlsi China University of Macau Institute of Microelectronics China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350316445

Mathematical model of the inductive power transfer (IPT) systems is essential for stability analysis and control design. Conventional modeling approaches for IPT systems result in high-order models, as each resonant voltage or current is represented by two slowly changing real-valued variables. Alternative modeling methods may decrease the model order, but they are often plagued by drawbacks such as the absence of analytical expressions, reduced generality, and incomplete modeling. Moreover, the harmonic AC components of the IPT system are not well modeled in the existing methods, which affects the analysis accuracy and control optimality. In this paper, a harmonic transfer function (HTF) modeling of the IPT system is proposed, which has good mathematical properties and improved accuracy. First, the circuit configuration and the linear time-varying (LTV) large-signal model are proposed. Then, the derivation of the proposed HTF is comprehensively discussed. Finally, the accuracy of the proposed HTF is verified by simulation and experimental results in comparison with other representative modeling methods, which shows an improved accuracy. © 2023 IEEE.

关键词： harmonics transfer function inductive power transfer system modeling

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Dimension Dropout for Evolutionary High-Dimensional Expensive Multiobjective Optimization 11th

Dimension Dropout for Evolutionary High-Dimensional Expensiv...

引用

11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021

作者： Lin, Jianqing He, Cheng Cheng, Ran Shenzhen Key Laboratory of Computational Intelligence University Key Laboratory of Evolving Intelligent Systems of Guangdong Province Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9783030720612

In the past decades, a number of surrogate-assisted evolutionary algorithms (SAEAs) have been developed to solve expensive multiobjective optimization problems (EMOPs). However, most existing SAEAs focus on low-dimensional optimization problems, since a large number of training samples are required (which is unrealistic for EMOPs) to build an accurate surrogate model for high-dimensional problems. In this paper, an SAEA with Dimension Dropout is proposed to solve high-dimensional EMOPs. At each iteration of the proposed algorithm, it randomly selects a part of the decision variables by Dimension Dropout, and then optimizes the selected decision variables with the assistance of surrogate models. To balance the convergence and diversity, those candidate solutions with good diversity are modified by replacing the selected decision variables with those optimized ones (i.e., decision variables from some better-converged candidate solutions). Eventually, the new candidate solutions are evaluated using expensive functions to update the archive. Empirical studies on ten benchmark problems with up to 200 decision variables demonstrate the competitiveness of the proposed algorithm. © 2021, Springer Nature Switzerland AG.

关键词： Multiobjective optimization

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MMAL: Multi-Modal Analytic Learning for Exemplar-Free Audio-Visual Class Incremental Tasks 24

MMAL: Multi-Modal Analytic Learning for Exemplar-Free Audio-...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Yue, Xianghu Zhang, Xueyi Chen, Yiming Zhang, Chengwei Lao, Mingrui Zhuang, Huiping Qian, Xinyuan Li, Haizhou Department of Electrical and Computer and Engineering National University of Singapore Singapore Laboratory for Big Data and Decision National University of Defense Technology Hunan Changsha China School of Electronic Electrical and Communication Engineering University of the Chinese Academy of Sciences Beijing China National Key Laboratory of Information Systems Engineering National University of Defense Technology Hunan Changsha China Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangdong Guangzhou China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shenzhen China

ISBN: (纸本)9798400706868

Class-incremental learning poses a significant challenge under an exemplar-free constraint, leading to catastrophic forgetting and sub-par incremental accuracy. Previous attempts have focused primarily on single-modality tasks, such as image classification or audio event classification. However, in the context of Audio-Visual Class-Incremental Learning (AVCIL), the effective integration and utilization of heterogeneous modalities, with their complementary and enhancing characteristics, remains largely unexplored. To bridge this gap, we propose the Multi-Modal Analytic Learning (MMAL) framework, an exemplar-free solution for AVCIL that employs a closed-form, linear approach. To be specific, MMAL introduces a modality fusion module that re-formulates the AVCIL problem through a Recursive Least-Square (RLS) perspective. Complementing this, a Modality-Specific Knowledge Compensation (MSKC) module is designed to further alleviate the under-fitting limitation intrinsic to analytic learning by harnessing individual knowledge from audio and visual modality in tandem. Comprehensive experimental comparisons with existing methods show that our proposed MMAL demonstrates superior performance with the accuracy of 76.71%, 78.98%, and 76.19% on AVE, Kinetics-Sounds, and VGGSounds100 datasets, respectively, setting new state-of-the-art AVCIL performance. Notably, compared to those memory-based methods, our MMAL, being an exemplar-free approach, provides good data privacy and can better leverage multi-modal information for improved incremental accuracy. © 2024 ACM.

关键词： Contrastive Learning

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