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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Liu, Xiaodong Wang, Siqi Liu, Huanyu Li, Junbao Department of Automatic Test and Control School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China School of Computer Science and Technology Information Countermeasure Technique Institute Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9789819700677

In recent years, the hyperspectral image (HSI) classification has attracted great attention in the field of earth observation. With the expansion of application scenarios and the continuous improvement of application requirements, new classes of HSI continue to emerge. In the face of open and dynamic application scenarios, the model is required to be able to continuously learn new categories based on maintaining existing category knowledge. Class incremental learning algorithms have received extensive attention as key solutions to the problem above. In this paper, we use a regularization-based incremental learning algorithm, elastic weight consolidation (EWC) for class incremental learning for HSI classification. After data preprocessing to reduce data dimensions, we select new classes for research on class incremental learning. We combine 3D-2D convolutional structures and residual blocks as the classification network and use real data playback mechanism to improve class recognition accuracy and realize class incremental recognition of HSI data. We demonstrate the feasibility of the algorithm with extensive experiments based on three widely used hyperspectral datasets. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Learning algorithms

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African Bison Optimization Algorithm:A New Bio-Inspired Optimizer with engineering Applications

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Computers, Materials & Continua 2024年第10期81卷 603-623页

作者： Jian Zhao Kang Wang Jiacun Wang Xiwang Guo Liang Qi School of Science University of Science and Technology LiaoningAnshan114051China Team of Artificial Intelligence Theory and Application University of Science and Technology LiaoningAnshan114051China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Information and Control Engineering College Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China

This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foraging behavior prompts the bison to seek a richer food source for *** bison find a food source,they stick around for a while by bathing *** jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating *** eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent *** above behaviors are translated into ABO by mathematical *** assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with *** findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.

关键词： Optimization metaheuristics African bison optimization engineering problems

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Aerial refueling scheduling of multi-receiver and multi-tanker under spatial-temporal constraints for forest firefighting

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Chinese Journal of Aeronautics 2024年第5期37卷 71-91,I0001页

作者： Jing HUANG Jiaqi XING Jinrui REN Quan QUAN Youmin ZHANG Department of Information and Control Engineering Xi’an University of TechnologyXi’an 710048China Jiujiang Measuring Test Technology Research Institute Jiujiang 332000China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Automation Xi’an University of Posts&TelecommunicationsShaanxiXi’an 710121China Department of Mechanical Industrial and Aerospace EngineeringConcordia UniversityMontreal H3G 1M8Canada

Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest *** the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and *** order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver ***,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for *** methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling *** optimization problem is established as nonlinear optimization models along with *** integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified *** has a complete solution space and excels in optimizing total fuel *** decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational ***,this comes at the cost of sacrificing optimality by excluding specific feasible ***,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed *** simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world *** comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.

关键词： Aerial refueling Scheduling Planning Spatial-temporal constraint Firefighting

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Pango FPGA Implementation of a Real-Time Display System for Multi-Channel Video Processing

Pango FPGA Implementation of a Real-Time Display System for ...

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2024 IEEE International Conference on Sensing, Diagnostics, Prognostics, and control, SDPC 2024

作者： Huang, Cao Du, Lifu Peng, Yu Xiang, Gang Yu, Yang Chen, Jingyi School of Electronics Information Engineering Habin Institute of Technology Harbin China Beijing Aerospace Automatic Control Institute Beijing China Beijing Aerospace Automatic Control Institute Department of System Engineering Beijing China

ISBN: (纸本)9798350388855

A Pango FPGA-based solution for merging and processing multiple independent video streams and reconstructing a real-time display system is presented. The system handles each video stream individually, then produces a combined video output in HDMI format. To ensure high efficiency and low latency, a parallel processing scheme and a hardware-oriented architecture are employed. The Pango PG50K FPGA board acts as the central hardware for managing inputs, reconstructing video, and producing outputs. Rapid-access DDR3-SDRAM ensures efficient data caching and signal integrity. This system is ideal for applications requiring rapid response, such as traffic monitoring and industrial automation, and supports quick algorithm iteration and optimization, enhancing performance and adaptability. © 2024 IEEE.

关键词： Video streaming

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Urban Electric Vehicle Charging Station Placement Optimization with Graylag Goose Optimization Voting Classifier

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Computers, Materials & Continua 2024年第7期80卷 1163-1177页

作者： Amel Ali Alhussan Doaa Sami Khafaga El-Sayed M.El-kenawy Marwa M.Eid Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute for Engineering and TechnologyMansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

To reduce the negative effects that conventional modes of transportation have on the environment,researchers are working to increase the use of electric *** demand for environmentally friendly transportation may be hampered by obstacles such as a restricted range and extended rates of *** establishment of urban charging infrastructure that includes both fast and ultra-fast terminals is essential to address this ***,the powering of these terminals presents challenges because of the high energy requirements,whichmay influence the quality of *** the maximum hourly capacity of each station based on its geographic location is necessary to arrive at an accurate estimation of the resources required for charging *** is vital to do an analysis of specific regional traffic patterns,such as road networks,route details,junction density,and economic zones,rather than making arbitrary conclusions about traffic *** vehicle traffic is simulated using this data and other variables,it is possible to detect limits in the design of the current traffic engineering ***,the binary graylag goose optimization(bGGO)algorithm is utilized for the purpose of feature ***,the graylag goose optimization(GGO)algorithm is utilized as a voting classifier as a decision algorithm to allocate demand to charging stations while taking into consideration the cost variable of traffic *** on the results of the analysis of variance(ANOVA),a comprehensive summary of the components that contribute to the observed variability in the dataset is *** results of the Wilcoxon Signed Rank Test compare the actual median accuracy values of several different algorithms,such as the voting GGO algorithm,the voting grey wolf optimization algorithm(GWO),the voting whale optimization algorithm(WOA),the voting particle swarm optimization(PSO),the voting firefly algorithm(FA),and the voting genetic algori

关键词： Electric vehicle graylag goose optimization metaheuristics optimization machine learning

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Tackling Real-world Complexity: Hierarchical Modeling and Dynamic Prompting for Multimodal Long Document Classification

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IEEE Transactions on Circuits and Systems for Video technology 2025年第6期35卷 5776-5790页

作者： Liu, Tengfei Hu, Yongli Li, Mingjie Yi, Junfei Chang, Xiaojun Gao, Junbin Yin, Baocai Beijing University of Technology Beijing Key Laboratory of Multimedia and Intelligent Software Technology Beijing Institute of Artificial Intelligence School of Information Science and Technology Beijing100124 China Stanford University Department of Radiation Oncology StanfordCA94305 United States Hunan University National Engineering Laboratory of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha410082 China University of Technology Sydney ReLER Laboratory Australian Artificial Intelligence Institute Faculty of Engineering and Information Technology UltimoNSW2007 Australia The University of Sydney Business School The University of Sydney Discipline of Business Analytics CamperdownNSW2006 Australia

With the rapid growth of internet content, multimodal long document data has become increasingly prominent, drawing significant attention from researchers. However, most existing methods primarily focus on scenarios where all modalities are present, often overlooking more challenging and realistic cases involving missing image modality. To address this limitation, we propose a robust multimodal long document classification (MLDC) framework that integrates hierarchical modeling and dynamic prompting to handle complex multimodal long document data. Our approach begins by leveraging hierarchical modeling combined with an Adaptive Correlation Multimodal Transformer (ACMT) to effectively capture relationships between text and images at both section and sentence levels. We also introduce a Dynamic Prompt Generation (DPG) module at both levels to enhance the model's robustness in handling missing image data. By evaluating sample uncertainty, the DPG module dynamically adjusts both the number of prompts and the prompts themselves, allowing the model to better adapt to the varying needs of different samples. Finally, a Hierarchical Heterogeneous Graph (HHG) is introduced to enhance feature interactions across levels, further improving the coherence and accuracy of the model. Extensive experiments on four multi-modal long document datasets demonstrate that our model shows superior performance compared to existing state-of-the-art MLDC classification methods in various conditions. © 1991-2012 IEEE.

关键词： Adaptation models Transformers Data models Correlation Circuits and systems Electronic mail Robustness Uncertainty Training Complexity theory

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Generic model of IoT Edge device for object monitoring via LoRaWAN

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IFAC-PapersOnLine 2024年第9期58卷 160-165页

作者： Peter Peniak Emília Bubeníková Peter Holečko Department of Control and Information Systems Faculty of Electrical Engineering and Information Technology University of Žilina Slovakia

This article deals with the generic model for object monitoring and tracking in an industrial environment and manufacturing. We focus on the design of generic IoT Edge device model that enables the integration of various LoRa sensors independently on vendor solutions for common use cases. Our model is based on the MQTT protocol, which is proven for sensor applications and gives needed independency on proprietary protocols. The model was implemented in Node-RED software and subsequently validated with sensors of different vendors to confirm the generic approach and base for independent object tracking solutions. The proposed Edge device model supports independent object tracking, such as object status monitoring, localization and triggered events, giving independent approach for tailored solutions and wide application portfolio based on combined different sensors and devices.

关键词： LoRaWAN GPS sensors monitoring tracking generic model MQTT NodeRED

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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EOG acquisition system based on ATmega AVR microcontroller

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16589-16605页

作者： Abdel-Samei, Abdel-Gawad A. Shaaban, Abdel-Salam Brisha, Ayman M. El-Samie, Fathi E. Abd Ali, Ahmed S. Department of Electronics Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Department of Process of Control Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Department of Mechanical Engineering Mechatronics Division Faculty of Engineering Assiut University Assiut Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

This paper presents a hardware and software of an electrooculogram (EOG) acquisition system based on ATmega AVR microcontroller for the acquisition of vertical and horizontal eye movements. The presented system is used to acquire a dataset of eye movements for volunteers. This system gives two channels representing vertical and horizontal EOG signals. The frequency range of the EOG signal is known to be 0.1 to 10 Hz, and hence this frequency range is isolated with a High-Pass Filter (HPF) with a cutoff frequency of 0.1 Hz followed by a Low-Pass Filter (LPF) with a cutoff frequency of 10 Hz. The EOG acquisition system is interfaced with an ATmega AVR microcontroller to acquire a dataset that can be used for controlling hardware such as Light Emitting Diodes (LEDs), wheelchair, and robot arm. The presented system is composed of EOG signal acquisition, Ag/AgCl electrodes, analog-to-digital converter through Arduino Mega 2560 board microcontroller unit, trainer board, laptop, keypad, and Liquid Crystal Display (LCD). The eye movement is detected by measuring the potential difference between cornea and retina using five Ag–Agcl disposable electrodes. Different volunteers of different ages at different times have been treated with the presented system to obtain data. Classified vertical and horizontal EOG signals and the basic eye movements e.g., open eye, left, right, up, and down can be used to control robots and wheelchairs for rehabilitation purposes. © 2023, The Author(s).

关键词： Electrodes

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Fuzzy control design for time-delay systems under adaptive event-triggered mechanism

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Neural Computing and Applications 2024年第9期36卷 4727-4739页

作者： Du, Zhenbin Qu, Zifang Kao, Yonggui Wu, Zhaojing School of Computer and Control Engineering Yantai University Shandong Yantai264005 China School of Mathematics and Information Science Shandong Technology and Business University Shandong Yantai264005 China Department of Mathematics Harbin Institute of Technology Weihai264209 China School of Mathematics and Information Sciences Yantai University Shandong Yantai264005 China

This manuscript studies the fuzzy H∞ control design problem for nonlinear time-varying delay systems in fuzzy form via adaptive event-triggered mechanism. The fuzzy model and an adaptive event-triggered controller are connected in closed-loop form. A looped-functional is established to conduct stability analysis, and the main feature of this functional can fully reflect the sampling feature of control systems. Thus, the achieved results are less conservative. The Wringter inequality is also used to further relax stability analysis. Finally, sufficient conditions are achieved for the existence of event-triggered fuzzy controller, and the resulting closed-loop system reaches an H∞ control performance. Two examples verify the efficiency of the presented control strategy. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023.

关键词： Time delay

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