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Journal of Network Intelligence 2024年第3期9卷 1706-1724页

作者： Hong, Chuanbo Liang, Quan Liang, Qiaoxin Yu, Wenjie Yu, Wenze Xiong, Neng School of Mechanical and Electrical Engineering Quanzhou University of Information Engineering Quanzhou362000 China College of Computer Science and Mathematics Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China Quanzhou Management Branch Fujian Expressway Group Cp. Ltd Quanzhou362000 China

The research of swarm intelligence shows a rapid development trend. People have studied a lot of swarm intelligence algorithms inspired by biology. Sparrow search algorithm is concerned by many scholars because of its powerful search performance. However, in the case of high-dimension optimization problems, if only a single sparrow search algorithm is used to solve optimization problems, the optimal solution often cannot be found, and the phenomenon of dimension disaster will occur or it is easy to fall into the local optimal solution. In order to make sparrow search algorithm have better performance in solving high-dimensional complex problems, In this paper, we propose a new Sparrow Search Algorithm with Adaptive Collaborative Updating (SSA-ACU). The SSA-ACU algorithm initializes the population through the chaotic search strategy to make the population distribution more diverse. Then, adaptive parameters are introduced to update the position of the leader to provide a more reliable direction for particle search. Finally, in order to enhance the development ability of the population, the position of the adjoint is updated through the pseudo-affine transformation mechanism to change the mode of its position update. Then CEC2013 was used to test and compare SSA-ACU algorithm with other sparrow search algorithm variants and classical algorithms, and it was verified that SSA-ACU algorithm has good performance in convergence speed and optimization ability. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Swarm intelligence

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Bias Beware: The Impact of Cognitive Biases on LLM-Driven Product Recommendations

arXiv

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arXiv 2025年

作者： Filandrianos, Giorgos Dimitriou, Angeliki Lymperaiou, Maria Thomas, Konstantinos Stamou, Giorgos School of Electrical and Computer Engineering AILS Laboratory National Technical University of Athens Greece

The advent of Large Language Models (LLMs) has revolutionized product recommendation systems, yet their susceptibility to adversarial manipulation poses critical challenges, particularly in real-world commercial applications. Our approach is the first one to tap into human psychological principles, seamlessly modifying product descriptions, making these adversarial manipulations hard to detect. In this work, we investigate cognitive biases as black-box adversarial strategies, drawing parallels between their effects on LLMs and human purchasing behavior. Through extensive experiments on LLMs of varying scales, we reveal significant vulnerabilities in their use as recommenders, providing critical insights into safeguarding these systems. © 2025, CC BY-NC-ND.

关键词： Real time systems

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Intruder trajectory tracking in a three-dimensional vibration-driven granular system:Unveiling the mechanism of the Brazil nut effect

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Chinese Physics B 2023年第10期32卷 106-111页

作者：李拓程可彭政杨晖厚美瑛 School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Soft Matter Laboratory Institute of PhysicsChinese Academy of SciencesBeijing 100190China School of Physics Central South UniversityChangsha 410012China College of Medical Instrumentation Shanghai University of Medicine&Health SciencesShanghai 201318China

We employ a Hall-effect magnetic sensor array to accurately track the trajectory of a single magnetic sphere,referred to as the“intruder,”within a three-dimensional vibro-fluidized granular bed to unravel the underlying physical mechanism governing the motion of the *** the acceleration range of 3.5 g≥Γ≥1.5 g,we find that,regardless of the intruder's initial position,it consistently reaches the same equilibrium depth when the vibration acceleration(Γ)and frequency(ω)are ***Γ≤2.5 g,the equilibrium position lies on the surface of the granular bed,while forΓ>2.5 g,it shifts below the ***,intruders with different densities exhibit varying equilibrium depths,with higher density resulting in a deeper equilibrium *** understand the mechanism behind the intruder's upward or downward motion,we measure its rising or sinking velocities under different vibration *** findings demonstrate that the rising velocity of the intruder,under varying vibration accelerations(Γ)and frequencies(ω),can be collapsed using the ratioΓ/ω,while the sinking velocity remains unaffected by the vibration *** confirms that the upward motion of the larger sphere,associated with the Brazil nut effect,primarily arises from the void-filling mechanism of the bed ***,our experiments reveal that the presence of convection within the bed particles has minimal impact on the motion of the intruder.

关键词： granular matter segregation Brazil nut effect vibro-fluidization

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Bi-level Optimal Planning of Voltage Regulator in Distribution systems Considering Maximization of Incentive-based Photovoltaic Energy Integration

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CSEE Journal of Power and Energy systems 2023年第6期9卷 2008-2017页

作者： Xu Xu Youwei Jia Chun Sing Lai Minghao Wang Zhao Xu Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHung HomHong Kong SARChina Department of Electrical and Electronic Engineering University Key Laboratory of Advanced Wireless Communications of Guangdong ProvinceSouthern University of Science and TechnologyShenzhen 515100China Department of Electronic and Computer Engineering Brunel Institute of Power SystemsBrunel University LondonLondonUB83PH United Kingdom Department of Electrical Engineering Shenzhen Research InstituteThe Hong Kong Polytechnic UniversityHung HomHong Kong SARChina

This paper focuses on optimal voltage regulator(VR)planning to maximize the photovoltaic(PV)energy integration in distribution *** describe the amount of dynamic PV energy that can be integrated into the power system,the concept of PV accommodation capability(PVAC)is introduced and modeled with *** proposed planning model is formulated as a Benders decomposition based bi-level stochastic optimization *** the upper-level problem,VR planning decisions and PVAC are determined via mixed integer linear programming(MILP)before considering *** in the lower-level problem,the feasibility of first-level results is checked by critical network constraints(*** magnitude constraints and line capacity constraints)under uncertainties considered by time-varying loads and PV *** this paper,these uncertainties are represented in the form of operational scenarios,which are generated by the Gaussian copula theory and reduced by a well-studied backward-reduction *** modified IEEE 33-node distribution grid is utilized to verify the effectiveness of the proposed *** results demonstrate that a PV energy integration can be significantly enhanced after optimal voltage regulator planning.

关键词： Bi-level stochastic optimization problem critical network constraints photovoltaic energy integration uncertainties voltage regulator planning

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Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection 24

Dual-Modeling Decouple Distillation for Unsupervised Anomaly...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Liu, Xinyue Wang, Jianyuan Leng, Biao Zhang, Shuo School of Computer Science and Engineering Beihang University Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer & Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798400706868

Knowledge distillation based on student-teacher network is one of the mainstream solution paradigms for the challenging unsupervised Anomaly Detection task, utilizing the difference in representation capabilities of the teacher and student networks to implement anomaly localization. However, over-generalization of the student network to the teacher network may lead to negligible differences in representation capabilities of anomaly, thus affecting the detection effectiveness. Existing methods address the possible over-generalization by using differentiated students and teachers from the structural perspective or explicitly expanding distilled information from the content perspective, which inevitably results in an increased likelihood of underfitting of the student network and poor anomaly detection capabilities in anomaly center or edge. In this paper, we propose Dual-Modeling Decouple Distillation (DMDD) for the unsupervised Anomaly Detection. In DMDD, a Decouple Student-Teacher Network is proposed to decouple the initial student features into normality and abnormality features. We further introduce Dual-Modeling Distillation based on normal-anomalous image pairs, fitting normality features of anomalous image and the teacher features of the corresponding normal image, widening the distance between abnormality features and the teacher features in anomalous regions. Synthesizing these two distillation ideas, we achieve anomaly detection which focuses on both edge and center of anomaly. Finally, a Multi-perception Segmentation Network is proposed to achieve focused anomaly map fusion based on multiple attention. Experimental results on MVTec AD show that DMDD surpasses SOTA localization performance of previous knowledge distillation-based methods, reaching 98.85% on pixel-level AUC and 96.13% on PRO. © 2024 ACM.

关键词： Students

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Deployment of Three-Body Chain-Type Tethered Satellites in Low-Eccentricity Orbits Using Only Tether

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Space(Science & Technology) 2023年第1期3卷 478-486页

作者： Cheng Jia Zhongjie Meng Bingheng Wang School of Astronautics Northwestern Polytechnical UniversityXi'an 710072China National Key Laboratory of Aerospace Flight Dynamics Northwestern Polytechnical UniversityXi'an 710072China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

The tethered TSAR(tomographic synthetic aperture radar)system is a group of tethered SAR satellites that can be rapidly deployed and provide a stable baseline for 3-dimensional topographic mapping and moving target *** deployment is critical for TSAR tethered *** paper discusses the deployment strategy for a 3-body chain-type tethered satellite system in a low-eccentric elliptical *** deployment strategies are ***,the tension on the tether is used to deploy it to the desired length and suppress its sway motion,resulting in an underactuated and input-constrained *** sliding mode control(HSMC)with anti-windup technology is employed to overcome the above *** addition,the proposed approach includes the use of a disturbance observer to estimate the second derivative signal and a robust differentiator to estimate the sliding surfaces of the unacted ***,the effectiveness of the proposed deployment strategy is verified by MATLAB/Simulink.

关键词： MATLAB/Simulink system overcome

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Intelligent Control Based in Neural-Fuzzy of Adaptive Backstepping for The Double Stator IPMSM Powered by a Five-Level NPC Inverter 13

Intelligent Control Based in Neural-Fuzzy of Adaptive Backst...

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13th IEEE International Conference and Expositions on Electric and Power engineering, EPEi 2024

作者： Benaissa, Rabie Mansouri, Smail Ouledali, Omar University of Adrar Faculty of Sciences and Technology Department of Electrical Engineering Laboratory for Sustainable Development and Computer Science 01000 Algeria University of Adrar Faculty of Sciences and Technology Department of Hydrocarbons and Renewable Energies Laboratory for Energy Environment and Information Systems 01000 Algeria

ISBN: (纸本)9798350356199

This article supplies a proposed approach Neuro Fuzzy Controller (NFC)-Adaptive Backstepping Controller (ABC)-Space Vector Modulation (SVM) for a five-level NPC inverter-Double Stator Interior Permanent Magnet Synchronous Motor (DSIPMSM). This paper's primary objective is to enhance DSIPMSM's performance by the use of strong control using the proposed approach. Given its benefits - including high torque density, high efficiency, high power density, and minimal maintenance - DSIPMSM, have recently been the focus of much research. Using the input-output linearization approach and Lyapunov stability theory, asymptotically stable trajectory-following dynamics are demonstrated using nonlinear adaptive backstepping control. The use of fuzzy logic and intelligence-based controllers are increasingly being used to enhance traditional control's performance and output. In addition, the fuzzy logic controller has a lot of flaws that are presently being fixed by the extremely effective NFC tool. The proposed method's worth was demonstrated by the simulation results in terms of durability, effective tracking dynamics, precision, and good disturbance rejection with little ripple. © 2024 IEEE.

关键词： Disturbance rejection

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Using Deep Reinforcement Learning in Optimal Energy Management for Residential House Aggregators with Uncertain User Behaviors 7

Using Deep Reinforcement Learning in Optimal Energy Manageme...

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7th IEEE Student Conference on Electric Machines and systems, SCEMS 2024

作者： Lin, Yujun Yan, Linfang Hui, Hongxun Chen, Yin Chen, Xia Wen, Jinyu School of Electrical and Electronic Engineering Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology Wuhan China City & Energy Research Institute Suzhou China University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China University of Strathclyde Department of Electronic and Electrical Engineering Glasgow United Kingdom

ISBN: (纸本)9798350366945

In this study, the home energy management problem, which can be regarded as a high-dimensional optimization problem, for numerous residential houses, is addressed. The concept of the aggregator is utilized to reduce the state and action space and to handle the high dimensionality. A two-stage deep reinforcement learning (DRL)-based approach is proposed for the aggregators to track the schedule from a superior grid and guarantee the operation constraints. In the first stage, a DRL control agent is set to learn the optimal scheduling strategy interacting with the environment based on the soft-actor-critic framework and generate the aggregate control actions. In the second stage, the aggregate control actions are disaggregated to individual appliances considering the users' behaviors. The uncertainty of an electric vehicle's charging demand is quantitatively expressed based on the driver's experience. An aggregate anxiety concept is introduced to characterize the driver's anxiety on the electric vehicle's range and uncertain events. Finally, simulations are conducted to verify the effectiveness of the proposed approach under dynamic user behaviors, and comparisons show the superiority of the proposed approach over other benchmark methods. © 2024 IEEE.

关键词： Deep reinforcement learning

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Economical generation of high-quality optical vortices with gradual-width Fermat spiral slit mask

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Science China(Physics,Mechanics & Astronomy) 2023年第4期66卷 75-83页

作者： Qi Huang Xingyuan Lu Hao Zhang Zhuoyi Wang Yuanjie Yang Qiwen Zhan Yangjian Cai ChengLiang Zhao School of Physical Science and Technology Soochow UniversitySuzhou 215006China School of Physics University of Electronic Science and Technology of ChinaChengdu 610054China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shandong Provincial Engineering and Technical Center of Light Manipulations&Shandong Provincial Key Laboratory of Optics and Photonic Device School of Physics and ElectronicsShandong Normal UniversityJinan 250358China

A general model for creating an optical vortex using a variable-width Fermat spiral slit(FSS)mask was *** generated optical vortex demonstrates much better quality than those produced by slits with a uniform *** depth of focus was nearly doubled,which can be explained by discretizing the gradual-width *** demonstrate the generation robustness,the slits were printed on a transparent slide,and an output vortex beam with greater than 98%intensity purity was *** the high quality and simplicity of this vortex generation method,its analysis and generation scheme are expected to be extended to generation of plasmonic vortices and short-wavelength light sources such as X-rays and electron *** of highquality optical vortex beams at an almost negligible cost will make investigation much more accessible.

关键词： optical vortex gradual-width Fermat spiral slit high quality economical generation

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Wavelet method optimised by ant colony algorithm used for extracting stable and unstable signals in intelligent substations

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CAAI Transactions on Intelligence Technology 2022年第2期7卷 292-300页

作者： Tianyan Jiang Xiao Yang Yuan Yang Xi Chen Maoqiang Bi Jianfei Chen School of Electrical and Electronic Engineering Chongqing University of TechnologyChongqingChina DepartmentState Key Laboratory of Power Transmission Equipment&System and New Technology Chongqing UniversityChongqingChina Department of Electrical and Computer Engineering University of MarylandCollege ParkMarylandUSA

Partial discharge(PD)signals are an important index to evaluate the operation state of intelligent *** correct distinction of PD pulse and interference pulse has become a challenging *** of the noise and the low signal-to-noise ratio,the stable signals become *** selection of a wavelet basis,the selection rule of thresholdλand the design of the threshold function are the key factors affecting the final denoising ***,an enhanced ant colony optimisition wavelet(ACOW)algorithm was applied to find the global optimal threshold through the continuous derivative threshold function and the ant colony optimisation(ACO)*** the same time the efficiency of adaptive search calculation,was also significantly *** method of the ACOW algorithm was compared with the soft wavelet method,gradient-based wavelet method and the genetic optimisation wavelet(GOW)*** these four methods to denoise four typical signals,different mean square errors(MSE),magnitude errors(ME)and time costs were ***,the results show that the ACOW method can achieve the minimum MSE and has less time *** generates significantly smaller waveform distortion than the other three threshold estimation *** addition,the high efficiency and good quality of the output signals are beneficial to the diagnosis of local discharge signals in intelligent substations.

关键词： algorithm noise method

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