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5th International Conference on Power and Energy Technology, ICPET 2023

作者： Chen, Kaiwen Wang, Qingyi Kang, Kai Wang, Hao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China PowerChina Hubei Electric Engineering Co. Ltd Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

ISBN: (纸本)9798350339673

Based on the background of photovoltaic development in the whole county and the demand for energy storage on the user-side, this paper establishes an economic evaluation model of user-side photovoltaic energy storage system considering shared energy storage. Firstly, three schemes of no energy storage, independent energy storage and shared energy storage are proposed, and the influence of photovoltaic energy storage system loss on annual power generation is considered. Secondly, based on the whole life cycle theory, the cost and benefit model of the user-side photovoltaic energy storage system is established, and the unit electricity cost of the user is used as the evaluation index. Finally, the relevant data of user in hubei area are analyzed as an example to verify the effectiveness of the model and provide reference for the investment of related projects. © 2023 IEEE.

关键词： photovoltaic energy storage system shared energy storage the unit electricity cost of the user user-side

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Optimal Portfolio of Wind-solar-hydro Hybrid Renewable Generation based on Variable Speed Pumped Storage 6

Optimal Portfolio of Wind-solar-hydro Hybrid Renewable Gener...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Xiang, Shizhe Xu, Da Gao, Menglu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Dc Company of State Grid Hubei Electric Power Co. Ltd. Yichang443000 China

ISBN: (纸本)9798350346671

Compared with separate solar or wind generation, the hybrid wind-solar-hydro renewable portfolio can achieve better generation characteristics due to their temporal-spatial complementarities. This paper proposes optimal portfolio of wind-solar-hydro hybrid renewable generation based on variable speed pumped storage (VSPS). In this portfolio, the complementarities of hydro-solar-wind hybrid renewable energy sources (RESs) are fully exploited via various conversion and storage devices for zero carbon 100% renewable supplies. Compared to traditional fixed speed pumped storage (FSPS), the VSPS has obvious advantages in power regulation and renewable accommodation, which is comprehensively modeled to capture its dynamic operational dispatchability and flexibility. The portfolio production, conversion, storage, and consumption are formulated via a two-stage framework, which takes the minimum system investment cost as the objective function. Case studies on southwest China are performed to show the effectiveness and superiority of the proposed methodology on cost-effective accommodation. © 2023 IEEE.

关键词： Cost effectiveness

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Drug-target interaction prediction using high order nonlinear features via neural factorization machines 4

Drug-target interaction prediction using high order nonlinea...

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2022 4th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2022

作者： Qian, Quan Zhu, Yuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Medication design and repositioning are sped up by the prediction of drug-target interactions (DTIs). Two main kinds of prediction methods are commonly used, which are based on chemical structure feature extraction and deep learning methods. However, on the one hand, the DTI prediction approaches based on chemical structural feature extraction may not wholly explore the possible network characteristics in the data. On the other hand, many deep learning methods call for numerous layers of neural networks to be layered to learn higher-order feature interaction information. To sum up, the existing computation methods often have the limitations of gradient disappearance and overfitting. This study presents a novel method (JRD-NFM) by calculating Jaccard similarities, getting an eigenvector through Restarted random walk (RWR), and generating low-dimensional feature vectors by Disposition Component Analysis (DCA). Besides decoding the topological features and similarity information of target and drug node, it can also get the context information of a single network. Considering the advantages of Neural Factorization Machines (NFM) in extracting high-order nonlinear features and processing sparse data, this study use NFM to classifier the collection data to integrate drug and target biochemical structure information. The experimental results demonstrate that JRD-NFM can outperform widely used deep learning methods and conventional chemical structure approaches. It could provide fresh ideas for combining molecular structure and heterogeneous network data to predict DTIs. © Published under licence by IOP Publishing Ltd.

关键词： Feature extraction

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Correction of Images Projected on Non-White Surfaces Based on Deep Neural Network 14

Correction of Images Projected on Non-White Surfaces Based o...

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14th International Conference on Digital Image Processing, ICDIP 2022

作者： Wang, Zewei Zhang, Jingjing Du, Xingzhuo Cao, Sihua Wei, Wenxuan School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9781510657564

When projecting onto a non-white surface, the projected image is distorted or color mixing by complex luminance and chrominance information, which makes the projection result different from the visual perception of the human eye. The purpose of projection image correction is to remove these effects, and traditional solutions usually estimate parameters from the collected projection samples, compute an inverse model of the projection imaging process, and try to fit a correction function. In this paper, a deep neural network-based projection image correction network (PICN) is designed to implicitly learn complex correction functions. PICN consists of a U-shaped backbone network, a convolutional neural network that extracts projected surface features, and a perceptual loss network that optimizes the correction results. Such a structure can not only extract the deep features and surface interference features of the projected image, but also make the corrected projected image more in line with human visual perception. In addition, we built a projector-camera system under the condition of a fixed global illumination environment for verification experiment, and proved the effectiveness of the proposed method by calculating the evaluation metrics of projected images before and after correction. © 2022 SPIE.

关键词： Deep neural networks

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CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

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Optimal Carbon Capture, Utilization and Storage Planning for Multi-Energy System 42

Optimal Carbon Capture, Utilization and Storage Planning for...

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42nd Chinese control Conference, CCC 2023

作者： Hu, Aoyu Xu, Da Gao, Menglu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Dc Company of State Grid Hubei Electric Power Co. Ltd. Yichang443000 China

ISBN: (纸本)9789887581543

In response to the national dual carbon policy, carbon capture, utilization and storage (CCUS) are currently attracting much attention. This paper proposes optimal CCUS planning for multi-energy system. In this multi-energy system, transmission network and natural gas network are coupled via conversion and storage devices in the energy hubs. The CCUS planning is formulated based on a source-sink matching method to analyze the CO2 capture points, CO2 storage points and CO2 transportation routes. Furthermore, the original CCUS planning problem is reformulated as a mixed integer second order cone programming (MISOCP) and subsequently solved to guarantee a satisfactory convergence performance. Numerical studies on an urban multi-energy system are implemented to verify the effectiveness and superiority of the proposed methodology over conventional scheme. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Carbon capture

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Full Attention Tracker: A Good Combination of Pixel-Level and Region-Level Cross-Correlation 42

Full Attention Tracker: A Good Combination of Pixel-Level an...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yuxuan Yan, Liping Feng, Zihang Xia, Yuanqing Xiao, Bo School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100081 China

ISBN: (纸本)9789887581543

The tracker based on Siamese neural network is currently a technical method with high accuracy in the tracking field. With the introduction of transformer in the visual tracking field, the attention mechanism has gradually emerged in tracking tasks. However, due to the characteristics of attention operation, Transformer usually has slow convergence speed, and its pixel-level correlation discrimination in tracking is more likely to lead to overfitting, which is not conducive to long-term tracking. A brand new framework FAT was designed, which is the improvement of MixFormer. The operation for simultaneous feature extraction and target information integration in MixFormer is retained, and the Mixing block is introduced to suppress the background as much as possible before the information interaction. In addition, a new operation is designed: the result of region-level cross-correlation is used as a guidance to help the learning of pixel-level cross-correlation in attention, thereby accelerating the model convergence speed and enhancing the model generalization. Finally, a joint loss function is designed to further improve the accuracy of the model. Experiments show that the presented tracker achieves excellent performance on five benchmark datasets. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Pixels

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Frequency Domain-Based Low-Rank Approximation for Magnetic Anomaly Detection

Frequency Domain-Based Low-Rank Approximation for Magnetic A...

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Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Yumeng Lv Congyu Liao Huan Liu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Wuhan China Department of Radiology Stanford University CA USA

ISBN: (数字)9798331529192

ISBN: (纸本)9798331529208

Current magnetic anomaly detection (MAD) methods prioritize signal-to-noise ratio (SNR) over signal features and edge information, leading to signal distortion. To address this issue, a new MAD approach utilizes structured lowrank approximation and block singular value decomposition based on the spatial frequency domain, dubbed FL-BSVD is proposed. First, the low-rankness structure of the magnetic anomaly signal is obtained through 2D Discrete Fourier Transform (2D-DFT) and structured Hankel transformation. Then, block singular value decomposition is applied to the Hankel matrix to reduce noise while preserving more signal edge features and enhancing detection accuracy. Finally, a field experiment comparing FL-BSVD with four commonly used methods is conducted. The experiment confirms that FL-BSVD can effectively recover magnetic anomaly signal features and edge information in a strong noisy environment.

关键词： Image edge detection Frequency-domain analysis Noise reduction Magnetic domains Feature extraction Noise measurement Magnetic anomaly detection Signal to noise ratio Singular value decomposition Periodic structures

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Multi-UAV Coverage Path Planning Method Based on Improved Particle Swarm Optimization

Multi-UAV Coverage Path Planning Method Based on Improved Pa...

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Chinese automation Congress (CAC)

作者： Yan Zhou Yonghua Xiong Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The widespread application of unmanned aerial vehicle (UAV) has made the coverage path planning problem for multiple UAV systems a research hotspot. In this paper, we propose a multi-UAV solution to achieve complete coverage of multi-region. Based on this solution, we present an improved particle swarm optimization (PSO) algorithm that combines PSO algorithm, greedy strategy, and back-and-forth (BAF) algorithm. Its purpose is to plan the optimal paths for multi-UAV while achieving the shortest total distance and the highest UAV cooperation efficiency with the minimum number of UAVs, thereby enhancing the multi-UAV coverage cooperation and path optimization capabilities. Simulation results demonstrate the feasibility and superiority of this algorithm.

关键词： automation Simulation Autonomous aerial vehicles Path planning Particle swarm optimization Collision avoidance Optimization

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Simulation and optimization of inchworm-like pneumatic crawling actuator based on ABAQUS software

Simulation and optimization of inchworm-like pneumatic crawl...

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Robotics, control and automation Engineering (RCAE), International Conference on

作者： Junqi Mu Xiaofeng Zong Yiyang Wei Xuping Hou School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

The actuator, serving as the fundamental power source of a soft robot, functions as its central component. The field of soft robotics has garnered increasing research attention since its inception. Pneumatic crawling robots, being an essential branch within the realm of soft robotics, possess notable characteristics such as rapid response time, cost-effectiveness, and human-computer interaction safety. Consequently, they hold significant research value. Among various types of crawling robots that have garnered considerable interest from researchers is the inchworm crawling robot. This paper aims to address the design and development aspects pertaining to inchworm actuators. By utilizing ABAQUS simulation software and taking displacement as the reference parameter, an analysis was conducted to investigate the impact of various geometric parameters on actuator displacement. Additionally, optimization of these geometric parameters was performed. The values of aspect ratio, length-to-width ratio, vertex angle and gap depth suitable for inchworm-like actuator are obtained. These findings are presented for the first time in the field of crawling soft robots and provide a theoretical basis for the development of pneumatic inchworm-like actuators.

关键词： Pneumatic actuators Transportation Pneumatic systems Soft robotics Bending Solids Software Safety Time factors Optimization

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