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Optimization of classification model for electric vehicle charging station placement using dynamic graylag goose algorithm

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Frontiers in Energy Research 2024年 12卷

作者： Alhussan, Amel Ali Khafaga, Doaa Sami El-kenawy, El-Sayed M. Eid, Marwa M. Ibrahim, Abdelhameed Department of Computer Sciences College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia MEU Research Unit Middle East University Amman Jordan Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt Faculty of Artificial Intelligence Delta University for Science and Technology Mansoura Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

The study of electric vehicles (EVs) aims to address the critical challenges of promoting widespread adoption. These challenges include EVs’ high upfront costs compared to conventional vehicles, the need for more sufficient charging stations, limitations in battery technology and charging speeds, and concerns about the distance EVs can travel on a single charge. This paper is dedicated to designing an innovative strategy to handle EV charging station arrangement issues in different cities. Our research will support the development of sustainable transportation by intelligently replying to the challenges related to short ranges and long recharging times through the distribution of fast and ultra-fast charge terminals by allocating demand to charging stations while considering the cost variable of traffic congestion. A hybrid combination of Dynamic Greylag Goose Optimization (DGGO) algorithm, as well as a Long Short-Term Memory (LSTM) model, is employed in this approach to determine, in a cost-sensitive way, the location of the parking lots, factoring in the congestion for traffic as a variable. This study examines in detail the experiments on the DGGO + LSTM model performance for the purpose of finding an efficient charging station place. The results show that the DGGO + LSTM model has achieved a stunning accuracy of 0.988,836, more than the other models. This approach shapes our finding’s primary purpose of proposing solutions in terms of EV charging infrastructure optimization that is fully justified to the EV’s wide diffusion and mitigating of the environmental consequences. Copyright © 2024 Alhussan, Khafaga, El-kenawy, Eid and Ibrahim.

关键词： Charging stations

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Modelling, Analysis and control of OmniMorph: an Omnidirectional Morphing Multi-rotor UAV

arXiv

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arXiv 2023年

作者： Aboudorra, Youssef Gabellieri, Chiara Brantjes, Ralph Sablé, Quentin Franchi, Antonio Robotics and Mechatronics group Faculty of Electrical Engineering Mathematics & Computer Science University of Twente Enschede Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy

This paper introduces for the first time the design, modelling, and control of a novel morphing multirotor Unmanned Aerial Vehicle (UAV) that we call the OmniMorph. The morphing ability allows the selection of the configuration that optimizes energy consumption while ensuring the needed maneuverability for the required task. The most energy-efficient uni-directional thrust (UDT) configuration can be used, e.g., during standard point-to-point displacements. Fully-actuated (FA) and omnidirectional (OD) configurations can be instead used for full pose tracking, such as, e.g., constant attitude horizontal motions and full rotations on the spot, and for full wrench 6D interaction control and 6D disturbance rejection. Morphing is obtained using a single servomotor, allowing possible minimization of weight, costs, and maintenance complexity. The actuation properties are studied, and an optimal controller that compromises between performance and control effort is proposed and validated in realistic simulations. Preliminary tests on the prototype are presented to assess the propellers' mutual aerodynamic interference. © 2023, CC BY.

关键词： Maneuverability

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Decentralised Iterative Learning control for High Performance Collaborative Tracking Problem with Output Constraints

Decentralised Iterative Learning Control for High Performanc...

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UKACC International Conference on control (control)

作者： Bin Chen Bing Chu Department of Automatic Control and Systems Engineering University of Sheffield Sheffield U.K. School of Electronics and Computer Science University of Southampton Southampton U.K.

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

High performance collaborative tracking problem, requiring a group of independent subsystems to generate a global output that can precisely track the desired reference in a repetitive manner, has found lots of applications in practice. However, for such an important control task, existing iterative learning control (ILC) methods have not considered the constraint on each subsystem's output, which leads to potential risk within the control process. This paper proposes a novel optimisation based ILC method to address the high performance collaborative tracking problem with output constraints. The proposed ILC framework can guarantee not only each subsystem's output constraint is always satisfied during the control process, but also the monotonic convergence of a well-defined performance index to a possibly minimum value. To avoid huge computational complexity for large scale systems, we further apply the idea of the alternative direction method of multipliers (ADMM) to implement the proposed ILC frame-work in a decentralised manner, which allows the resulting decentralised methods to be applied to large scale and changing systems. Moreover, the decentralised ILC method proposed in this paper is suitable for non-minimum phase, heterogeneous and/or homogeneous systems, which is appealing in practice. Convergence properties of the proposed ILC algorithms are analysed rigorously, and numerical examples are given to demonstrate the algorithms' effectiveness.

关键词： Collaboration Process control Performance analysis Large-scale systems Task analysis Computational complexity Optimization

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MEST: Multi-plane Embedding and Spatial-temporal Transformer for Parkinson's disease diagnosis

MEST: Multi-plane Embedding and Spatial-temporal Transformer...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Liu, Jin Du, Hao Bi, Qian Liao, Haiyan Pan, Yi Central South University School of Computer Science and Engineering Changsha China Hunan Frist Normal University School of Mathematics and Statistics Changsha China Central South University Department of Radiology The Second Xiangya Hospital Changsha China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Faculty of Computer Science and Control Engineering Shenzhen China

ISBN: (纸本)9781665468190

Parkinson's disease (PD) is a common neurodegenerative disorder that impairs the patient's quality of life. Medical imaging technology has provided a variety of neuroimages for PD diagnosis studies. However, how to effectively integrate the rich representations from multi-modality data is still a challenging task. To address this challenging task, we propose a multiplane embedding and spatial-temporal Transformer (MEST) framework for PD diagnosis. Firstly, we project structural magnetic resonance imaging (sMRI) into 2D images from coronal, sagittal and axial directions, respectively. Then, the multi-plane dynamic images are learned by pre-trained VGG11 and attention mechanism for representation learning. Afterwards, time series information of functional magnetic resonance imaging (fMRI) is used to construct dynamic functional connection images. To capture information changes in brain, spatial-temporal connectivity Transformer (SCTransformer) is utilized to address spatial-temporal redundancy and dependencies. To integrate multimodality data, ensemble learning is designed based on majority voting strategy to perform PD diagnosis. We evaluate the proposed method on 279 subjects from an in-house and Parkinsons Progression Markers Initiative (PPMI) dataset. Experimental results show that the MEST achieves promising performance with accuracies of 0.856 and 0.885, and outperforms some state-of-the-art methods. © 2022 IEEE.

关键词： Embeddings

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Adversarial attacks and defenses in physiological computing:a systematic review

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National science Open 2023年第1期2卷 62-90页

作者： Dongrui Wu Jiaxin Xu Weili Fang Yi Zhang Liuqing Yang Xiaodong Xu Hanbin Luo Xiang Yu Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China College of Public Administration Huazhong University of Science and TechnologyWuhan 430074China Electrical Engineering and Computer Science Department University of MichiganAnn Arbor MI 48109USA School of Management and Sino-European Institute for Intellectual Property Huazhong University of Science and TechnologyWuhan 430074China

Physiological computing uses human physiological data as system inputs in real *** includes,or significantly overlaps with,brain-computer interfaces,affective computing,adaptive automation,health informatics,and physiological signal based *** computing increases the communication bandwidth from the user to the computer,but is also subject to various types of adversarial attacks,in which the attacker deliberately manipulates the training and/or test examples to hijack the machine learning algorithm output,leading to possible user confusion,frustration,injury,or even ***,the vulnerability of physiological computing systems has not been paid enough attention to,and there does not exist a comprehensive review on adversarial attacks to *** study fills this gap,by providing a systematic review on the main research areas of physiological computing,different types of adversarial attacks and their applications to physiological computing,and the corresponding defense *** hope this review will attract more research interests on the vulnerability of physiological computing systems,and more importantly,defense strategies to make them more secure.

关键词： physiological computing brain-computer interfaces health informatics biometrics machine learning adversarial attack

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Application of Image Processing and Machine Learning Technologies for Home Care Bed

Application of Image Processing and Machine Learning Technol...

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2022 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Suponenkovs, Artjoms Lacis, Matiss Markovics, Zigurds Kovalovs, Mihails Platkajis, Ardis Kalnins, Andrejs Process Engineering and Equipment Manufacturing Company PERUZA Riga Latvia Riga Technical University Department of Computer Control and Computer Networks Riga Latvia Riga Technical University Faculty of Computed Science and Information Technology Riga Latvia Riga Stradins University Department of Radiology Riga Latvia

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

The problem of analysing a bed bound patient (that is, a patient who is confined to their bed) is a relevant factor in whether or not they will receive timely medical care. This paper aims to investigate the challenges and possible solutions to such problems. It describes an approach and methods for such analysis, as well as for home care bed control. This paper also addresses the challenges of Image Processing and Machine Learning. The experimental part describes important aspects regarding analysing brain activity, facial expression, blood flow, and human body pose. These experimental results and the proposed approach based upon them can be helpful for ensuring timely medical care. In addition, the results of this work can be useful for home care bed development. © 2022 IEEE.

关键词： Machine learning

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement

arXiv

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arXiv 2024年

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia1678 Cyprus Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node’s local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3-bits). Our proposed algorithm respects the network’s bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm’s operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm’s unique characteristics. © 2024, CC BY.

关键词： Optimization algorithms

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Rethinking development and major research plans of Industrial Internet in China

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Fundamental Research 2024年第1期4卷 3-7页

作者： Chunxiao Jiang Yang Cong Jiming Chen Chenghong Wang Guozheng Wu Ruizhen Zhao Zhiheng Wang Bin Xiao Ting Chen Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Tsinghua Space Center Tsinghua UniversityBeijing 100084China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China Division III Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Division II Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Chongqing Key Laboratory of Image Cognition School of Computer Science and TechnologyChongqing University of Posts and TelecommunicationsChongqing 400065China University of Electronic Science and Technology of China Chengdu 611731China

This paper gives a definition of the Industrial Internet and expounds on the academic connotation of the future Industrial *** this foundation,we outline the development and current status of the Industrial Internet in China and ***,we detail the avant-garde paradigms encompassed within the National Natural science Foundation of China(NSFC)’s“Future Industrial Internet Fundamental Theory and Key Technologies”research plan and its corresponding management *** research initiative endeavors to enhance interdisciplinary collaborations,aiming for a synergistic alignment of industry,academia,research,and practical *** primary focus of the research plan is on the pivotal scientific challenges inherent to the future industrial *** is poised to traverse the“first mile”,encompassing foundational research and pioneering innovations specific to the industrial internet,and seamlessly bridges to the“last mile”,ensuring the effective commercialization of scientific and technological breakthroughs into tangible industrial market *** anticipated contributions from this initiative are projected to solidify both the theoretical and practical scaffolding essential for the cultivation of a globally competitive industrial internet infrastructure in China.

关键词： Industrial Internet Academic connotation Major research plan Scientific problem Policy advice

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Hybrid SIC Aided Hybrid NOMA: A New Approach For Improving Energy Efficiency

arXiv

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arXiv 2024年

作者： Sun, Yanshi Cao, Wei Wang, Ning Zhou, Momiao Ding, Zhiguo School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Department of Computer and Information Engineering Khalifa University Abu Dhabi United Arab Emirates

Hybrid non-orthogonal multiple access (NOMA), which organically combines pure NOMA and conventional OMA, has recently received significant attention to be a promising multiple access framework for future wireless communication networks. However, most of the literatures on hybrid NOMA only consider fixed order of successive interference cancellation (SIC), namely FSIC, for the NOMA transmission phase of hybrid NOMA, resulting in limited performance. Differently, this paper aims to reveal the potential of applying hybrid SIC (HSIC) to improve the energy efficiency of hybrid NOMA. Specifically, a HSIC aided hybrid NOMA scheme is proposed, which can be treated as a simple add-on to the legacy orthogonal multiple access (OMA) based network. The proposed scheme offers some users (termed "opportunistic users") to have more chances to transmit by transparently sharing legacy users’ time slots. For a fair comparison, a power reducing coefficient β is introduced to ensure that the energy consumption of the proposed scheme is less than conventional OMA. Given β, the probability for the event that the achievable rate of the proposed HSIC aided hybrid NOMA scheme cannot outperform its OMA counterpart is obtained in closed-form, by considering impact of user pairing. Furthermore, asymptotic analysis shows that the aforementioned probability can approach zero in the high SNR regime under some given conditions, which are compositely determined by the users’ transmit powers, primary user’s target data rate and β, indicating that the energy efficiency of the proposed scheme is almost surely higher than that of OMA for these given conditions. Numerical results are presented to verify the analysis and also demonstrate the benefit of applying HSIC compared to FSIC. Copyright © 2024, The Authors. All rights reserved.

关键词： Hybrid power

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Beyond the network-based multi-omics data integration in COPD: a pathway-centric analysis

Beyond the network-based multi-omics data integration in COP...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Pasquale Sibilio Federica Conte Paola Paci Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Institute for Systems Analysis and Computer Science “Antonio Ruberti” National Research Council Rome Italy Karolinska Institutet Stockholm Sweden

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Chronic obstructive pulmonary disease (COPD) is a lung disease causing hundred thousand of death each year worldwide and defined as a respiratory and airflow impairment majorly due to large and small airways dysfunctions. COPD could be considered as a syndrome that includes disease axes of variable pathological and clinical conditions. Despite recent advances, the comprehension of the molecular mechanisms responsible for COPD disease spectrum is far to be reached. Moreover, we should also consider continuous smoking exposure, which could lead to variability in the disease mechanisms and progression. Network-based multi-omics data integration can help to study the association between molecular determinants on diverse biomolecular layers in a disease context. In a previous study, we leveraged lung RNA-seq and DNA-methylation data of a COPD-control cohort to build a correlation-based integrated network (called coupled network), that helped to unveil genes involved in immune and inflammatory modulation of COPD. Therefore, in our previous study we highlighted the most important genes of the coupled network and inspected their single contribution to disease-related pathways. In this study we aim to overcome this limitation by performing a pathway activity analysis by considering the expression and DNA methylation profiles of coupled network genes. Moreover, we exploit this analysis to study the possible contribution of coupled network genes to the differential disease progression between current and former smokers patients.

关键词： Pathology Lungs Data integration Modulation DNA Chronic obstructive pulmonary disease Biology Bioinformatics Immune system

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