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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1269-1283页

作者： Liao, Xiao-Cheng Hu, Xiao-Min Chen, Xiang-Ling Mei, Yi Jia, Ya-Hui Chen, Wei-Neng Victoria University of Wellington Centre for Data Science and Artificial Intelligence School of Engineering and Computer Science Wellington6140 New Zealand Guangdong University of Technology School of Computer Science and Technology Guangzhou510006 China Hanyang University Department of Electrical and Electronic Engineering Ansan15588 Korea Republic of South China University of Technology School of Future Technology Guangzhou510006 China Pazhou Lab Guangzhou510005 China South China University of Technology School of Computer Science and Engineering State Key Laboratory of Subtropical Building and Urban Science Guangzhou510006 China

Genetic programming hyperheuristic (GPHH) has recently become a promising methodology for large-scale dynamic path planning (LDPP) since it can produce reusable heuristics rather than disposable solutions. However, in this methodology, the extracted local and decentralized heuristic for agents that lack a global systemic view sometimes may be problematic. Therefore, a new challenge is to strike a balance between conciseness to improve generalization ability and incorporation of more global information to obtain better performance. In this work, we target the LDPP problem and propose a communication learning mechanism (ComLGP) for GPHH to address the above difficulties. In ComLGP, a communication function is introduced to serve as a communication protocol and exist in the form of an extra terminal in GPHH. Compared to the classic terminals which are fixed in genetic programing, this communication function undergoes optimization along with the evolutionary process of GPHH. In this way, the communication function can be learned which enables agents to communicate without a predefined communication protocol. Then, a caching and lazy updating mechanism for ComLGP is presented to accelerate the calculation of communication content. Last, we verified our method on 22 scenarios including two real world road networks. The experimental results demonstrate that the proposed ComLGP can successfully learn to communicate. Although in the absence of any manually designed communication features, ComLGP is capable of achieving performance competitive to the state-of-the-art method that employs a predefined communication protocol and outperforms the remaining compared methods in most scenarios. © 2020 IEEE.

关键词： Genetic programming

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Data-Driven Digital Twins for Power Estimations of a Solar Photovoltaic Plant

Data-Driven Digital Twins for Power Estimations of a Solar P...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Walters, Michael Yonce, John Venayagamoorthy, Ganesh K. Clemson University Realtime Power and Intelligent Systems Laboratory Holcombe Department of Electrical and Computer Engineering Clemson United States

ISBN: (纸本)9781665430654

Renewable energy generation sources (RESs) are gaining increased popularity due to global efforts to reduce carbon emissions and mitigate effects of climate change. Planning and managing increasing levels of RESs, specifically solar photovoltaic (PV) generation sources is becoming increasingly challenging. Estimations of solar PV power generations provide situational awareness in distribution system operations. A digital twin (DT) can replicate PV plant behaviors and characteristics in a virtual platform, providing realistic solar PV estimations. Furthermore, neural networks, a popular paradigm of artificial intelligence may be used to adequately learn and replicate the relationship between input and output variables for data-driven DTs (DD-DTs). In this paper, DD-DTs are developed for Clemson University's 1 MW solar PV plant located in South Carolina, USA to perform realistic solar PV power estimations. The DD-DTs are implemented utilizing multilayer perceptron (MLP) and Elman neural networks. Typical practical results for two DD-DT architectures are presented and validated. © 2023 IEEE.

关键词： Digital twin neural network power estimation solar photovoltaic

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Neuro-symbolic artificial intelligence: a survey

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Neural Computing and Applications 2024年第21期36卷 12809-12844页

作者： Bhuyan, Bikram Pratim Ramdane-Cherif, Amar Tomar, Ravi Singh, T.P. LISV Laboratory University of Paris Saclay 10-12 Avenue of Europe Velizy78140 France School of Computer Science University of Petroleum and Energy Studies Uttarakhand Bidholi Dehradun248006 India Persistent Systems Pune Mumbai411016 India School of Computer Science Engineering and Technology Bennett University Greater Noida201306 India

The goal of the growing discipline of neuro-symbolic artificial intelligence (AI) is to develop AI systems with more human-like reasoning capabilities by combining symbolic reasoning with connectionist learning. We survey the literature on neuro-symbolic AI during the last two decades, including books, monographs, review papers, contribution pieces, opinion articles, foundational workshops/talks, and related PhD theses. Four main features of neuro-symbolic AI are discussed, including representation, learning, reasoning, and decision-making. Finally, we discuss the many applications of neuro-symbolic AI, including question answering, robotics, computer vision, healthcare, and more. Scalability, explainability, and ethical considerations are also covered, as well as other difficulties and limits of neuro-symbolic AI. This study summarizes the current state of the art in neuro-symbolic artificial intelligence. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Machine learning

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Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3235-3248页

作者： Liang, Weisheng Amer, Abdelhakim Mehndiratta, Mohit Chen, Zheng Yao, Bin Kayacan, Erdal Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China Aarhus University Artificial Intelligence in Robotics Laboratory Department of Electrical and Computer Engineering Aarhus8000 Denmark GIM Robotics Espoo02650 Finland Zhejiang University Ocean College Ocean Research Center of Zhoushan Zhoushan316021 China Purdue University School of Mechanical Engineering West Lafayette47907 United States Department of Electrical Engineering and Information Technology Paderborn33098 Germany

With increasingly challenging applications for quadrotors, higher requirements are emerging for tracking accuracy and safety. While high accuracy is a prerequisite for complex tasks, safety is ensured through tolerance to actuator faults and resistance to external disturbances. In this article, adaptive robust control (ARC) integrated with Gaussian processes (GPs), i.e., ARC-GP, is proposed to achieve enhanced accuracy, fault tolerance, and anti-disturbance. These three requirements are interrelated and affected by uncertainties. The primary idea of this article is to categorize uncertainties into parametric and nonparametric types, which are then addressed through parameter adaptation and GP, respectively. First, a detailed dynamic model is established, including actuator models that reflect different types of faults corresponding to changes in different physical parameters. Then, parameter adaptation is designed, with direct and indirect methods adopted for different parameters. In particular, the actuator parameters are effectively estimated to achieve targeted fault compensation. Regarding GP for nonparametric uncertainties, its model parameters are also updated via parameter adaptation. The GP thereby also learns parameter estimation errors along with external disturbances. Accordingly, ARC controllers are designed, for which robust feedback terms are constructed to further mitigate uncertainties on the basis of the covariances predicted by GP. The experiments demonstrate that the proposed ARC-GP can actively tolerate various types of actuator faults and better resist wind disturbances. © 2013 IEEE.

关键词： Robust control

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Asymptotic Stability Preservation of Input Delayed Nonlinear systems under Sampled-Data Feedback 63

Asymptotic Stability Preservation of Input Delayed Nonlinear...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Yu, Xin Lin, Wei Jiangsu Normal University School of Electrical Engineering and Automation Xuzhou221116 China Case Western Reserve University Dept. of Electrical Systems and Computer Engineering ClevelandOH United States

ISBN: (纸本)9798350316339

We study the problem of global asymptotic stability preservation (GASP) for C0 non-smoothly stabilizable systems with input delay under sampled-data feedback. With the aid of Halanay inequality and the notion of homogeneity, the following sampled-data control results are established under a fast sampling: 1) GAS is preservable if the nonlinear system is homogeneous of degree zero and globally asymptotically stabilizable by homogeneous feedback;2) As a consequence, GAS via sampled-data feedback is achieved for a class of non-smoothly stabilizable systems with input delay in a lower-triangular or upper-triangular form. © 2024 IEEE.

关键词： Delay control systems

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A Comparative Study of a Reflectarray Antenna Based on Optical Transparent Materials 12

A Comparative Study of a Reflectarray Antenna Based on Optic...

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12th International Conference on Modern Circuits and systems Technologies, MOCAST 2023

作者： Vassos, Evangelos Theoharis, Panagiotis Ioannis Chalkidis, Savvas Tubbal, Faisel Raad, Raad Feresidis, Alexandros University of Birmingham Electronic Electrical and Systems Engineering Birmingham United Kingdom University of Wollongong School of Electrical Computer and Telecomunication Engineering WollongongNSW Australia

ISBN: (纸本)9798350321074

Reflectarray antennas and Intelligent Reflection Surfaces (IRSs) are key elements in 5G and beyond cellular networks. Optical transparency of the aforementioned structures can increase their potential applications. The transparency of the surface can be achieved by using materials such as indium tin oxide (ITO) and quartz. However, the use of very thin layers of low-conductivity materials can significantly increase the complexity of the electromagnetic simulations. A comparative study that includes simulations of a reflectarray antenna using CST microwave studio and QUPES has been conducted. Simulations suggest a reflectarray with directivity of 26.2 dBi at 60 GHz which is suitable for 5G and Beyond Wireless Networks or emerging Satellite Networks. © 2023 IEEE.

关键词： Electromagnetic simulation

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Berry Curvature engineering in Optical Resonator Networks using Long-Range Hopping

Berry Curvature Engineering in Optical Resonator Networks us...

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2023 Novel Optical Materials and Applications, NOMA 2023

作者： Kim, Gyunghun Suh, Joseph Lee, Ikbeom Yu, Sunkyu Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

We propose the engineering of the Berry curvature in optical resonator networks by exploiting long-range hopping. By generalizing the Hofstadter model, we examine the effect of hopping orders for the design of topolog... 详细信息

关键词： Optical resonators

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Fractal Dimension Analysis Demonstrates Overestimation and Underestimation of Time in EEG Signal 1

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13th National Technical Symposium on Unmanned System Technology, NUSYS 2023

作者： Azari, Maryam Mollazadeh Sarbaz, Yashar Koohestani, Behrooz Farzamnia, Ali Modeling Biological System’s Laboratory Department of Biomedical Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Computer Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Faculty of Engineering Universiti Malaysia Sabah Sabah Kota Kinabalu Malaysia School of Computing and Engineering University of Huddersfield Huddersfield United Kingdom

ISBN: (数字)9789819720279

ISBN: (纸本)9789819720262

Keeping track of time is regarded as an essential human behavior. The question of how the brain deals with temporal information remains a subject of scholarly debate. The current investigation aims to explore the mechanism underlying time perception by extracting fractal dimension from an electroencephalogram (EEG) signal and its frequency bands. To accomplish this, Higuchi’s fractal dimension was calculated for 42 healthy subjects’ electroencephalogram (EEG) signal and its sub-bands during the time perception task. The EEG signal was recorded from 19 channels. Subsequently, a statistical analysis was conducted to compare participants who underestimated versus those who overestimated the elapsed time and significantly different channels were presented. The findings suggest an elevated level of fractal dimensionality in persons who displayed a tendency to overestimate time. The EEG signal and Gamma rhythm emerged as the most distinguishing signals between the two cohorts. The contrast in fractal dimension between the two groups was predominantly apparent in the parietal and central channels. To summarize, an increased level of complexity is discernible in the EEG signal and high-frequency rhythms when there is an overestimation of temporal duration. It can be asserted that the employment of FD yields presents an exceptional approach to comprehending cerebral functionalities, notably temporal perception. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electroencephalography

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CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

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Recent Advances in Parity-Time Symmetry-Enabled Electromagnetic Sensors

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Progress In Electromagnetics Research B 2024年 105卷 107-121页

作者： Yang, Minye Ye, Zhilu Chen, Pai-Yen Erricolo, Danilo Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL60607 United States State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education School of Electronic Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China State Key Laboratory for Manufacturing Systems Engineering The Key Laboratory of Biomedical Information Engineering of Ministry of Education Center for Mitochondrial Biology and Medicine School of Life Science and Technology International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi’an Key Laboratory for Biomedical Testing and High-end Equipment Xi’an Jiaotong University Shaanxi Xi’an710049 China

Parity-time (PT) reversal symmetry, as a representative example in the field of non-Hermitian physics, has attracted widespread research interest in the past few years due to its extraordinary wave dynamics. PT symmetry enables unique spectral singularities including the exceptional point (EP) degeneracy where two or more eigenvalues and eigenvectors coalesce, as well as the coherent perfect absorber-laser (CPAL) point where laser and its time-reversal counterpart (i.e., coherent perfect absorber) can coexist at the same frequency. These singular points not only give rise to new physical phenomena but also provide new plausibility for building the next-generation sensors and detectors with unprecedented sensitivity. To date, investigations into EPs and CPAL points have unveiled their great potential in various sensing scenarios across a broad spectral range, spanning optics, photonics, electronics, and acoustics. In this review article, we will discuss ongoing developments of EP- and CPAL-based sensors composed of PT-synthetic structures and offer a glimpse into the future research directions in this emerging field. © (2024), (Electromagnetics Academy). All rights reserved.

关键词： Eigenvalues and eigenfunctions

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