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An evolutionary multiobjective method based on dominance and decomposition for feature selection in classification

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Science China(information Sciences) 2024年第2期67卷 5-19页

作者： Jing LIANG Yuyang ZHANG Ke CHEN Boyang QU Kunjie YU Caitong YUE Ponnuthurai Nagaratnam SUGANTHAN School of Electrical and information {1. Zhengzhou University State Key Laboratory of Intelligent Agricultural Power Equipment School of Electrical engineering and Automation Henan Institute of Technology School of Electronics and information Zhongyuan University of Technology KINDI Center for Computing Research College of EngineeringQatar University

Feature selection in classification can be considered a multiobjective problem with the objectives of increasing classification accuracy and decreasing the size of the selected feature subset. Dominance-based and decomposition-based multiobjective evolutionary algorithms(MOEAs) have been extensively used to address the feature selection problem due to their strong global search capability. However, most of them face the problem of not effectively balancing convergence and diversity during the evolutionary process. In addressing the aforementioned issue, this study proposes a unified evolutionary framework that combines two search forms of dominance and decomposition. The advantages of the two search methods assist one another in escaping the local optimum and inclining toward a balance of convergence and diversity. Specifically, an improved environmental selection strategy based on the distributions of individuals in the objective space is presented to avoid duplicate feature subsets. Furthermore, a novel knowledge transfer mechanism that considers evolutionary characteristics is developed, allowing for the effective implementation of positive knowledge transfer between dominance-based and decomposition-based feature selection methods. The experimental results demonstrate that the proposed algorithm can evolve feature subsets with good convergence and diversity in a shorter time compared with 9 state-of-the-art feature selection methods on 20 classification problems.

关键词： evolutionary algorithms feature selection multiobjective optimization knowledge transfer classification

UNIFORM SUPERCONVERGENCE ANALYSIS OF A TWO-GRID MIXED FINITE ELEMENT METHOD FOR THE TIME-DEPENDENT BI-WAVE PROBLEM MODELING D-WAVE SUPERCONDUCTORS

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Journal of Computational Mathematics 2024年第2期42卷 415-431页

作者： Yanmi Wu Dongyang Shi PLA information {1. University Zhengzhou 450001China School of Mathematics and information Sciences Yantai UniversityYantai 264005China

In this paper,a two-grid mixed finite element method(MFEM)of implicit Backward Euler(BE)formula is presented for the fourth order time-dependent singularly perturbed Bi-wave problem for d-wave superconductors by the nonconforming EQ_(1.^(rot) *** this approach,the original nonlinear system is solved on the coarse mesh through the Newton iteration method,and then the linear system is computed on the fine mesh with Taylor’s *** on the high accuracy results of the chosen element,the uniform superclose and superconvergent estimates in the broken H^(1.-norm are derived,which are independent of the negative powers of the perturbation parameter appeared in the considered *** results illustrate that the computing cost of the proposed two-grid method is much less than that of the conventional Galerkin MFEM without loss of accuracy.

关键词： Time-dependent Bi-wave problem Two-grid mixed finite element method Uniform superclose and superconvergent estimates

Track correlation algorithm based on CNN-LSTM for swarm targets

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Journal of Systems engineering and Electronics 2024年第2期35卷 417-429页

作者： CHEN Jinyang WANG Xuhua CHEN Xian Research institute for National Defense {1. Academy of Military SciencesLuoyang 471023China information {1. University Zhengzhou 450001China School of Computer Science and Technology Xidian UniversityXi’an 710071China

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for *** this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm ***, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

关键词： track correlation correlation accuracy rate swarm target convolutional neural network(CNN) long short-term memory(LSTM)neural network

Nacre-inspired MXene-based film for highly sensitive piezoresistive sensing over a broad sensing range

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Bio-Design and Manufacturing 2024年第4期7卷 463-475页

作者： Gaofeng Wang Lingxian Meng Xinyi Ji Xuying Liu Jiajie Liang Shuiren Liu School of Materials Science and engineering Zhengzhou UniversityZhengzhou 450001China School of Materials Science and engineering National Institute for Advanced MaterialsNankai UniversityTianjin 300350China

As the main component of wearable electronic equipment,flexible pressure sensors have attracted wide attention due to their excellent sensitivity and their promise with respect to applications in health monitoring,electronic skin,and human-computer ***,it remains a significant challenge to achieve epidermal sensing over a wide sensing range,with short response/recovery time and featuring seamless conformability to the skin *** is critical since the capture of minute electrophysiological signals is important for health care *** this paper,we report the preparation of a nacre-like MXene/sodium carboxymethyl cellulose(CMC)nanocomposite film with a“brick-and-mortar”interior structure using a vacuum-induced self-assembly *** synergistic behavior of the MXene“brick”and flexible CMC“mortar”contributes to attenuating interlamellar self-stacking and creates numerous variable conductive pathways on the sensing *** resulted in a high sensitivity over a broad pressure range(i.e.,0.03-22.37 kPa:1.2.1. kPa^(-1.;22.37-1.5.71.kPa:1.7.88 kPa^(-1.;1.5.71.286.49 kPa:1.0.58 kPa^(-1.).This sensor also has a low detection limit(0.85 Pa),short response/recovery time(8.58 ms/34.34 ms),and good stability(2000 cycles).Furthermore,we deployed pressure sensors to distinguish among tiny particles,various physiological signals of the human body,space arrays,robot motion monitoring,and other related applications to demonstrate their feasibility for a variety of health and motion monitoring use cases.

关键词： Flexible pressure sensor MXene Bioinspired Physiological signals Interlayer spacing

Improved Weighted Local Contrast Method for Infrared Small Target Detection

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Journal of Beijing institute of Technology 2024年第1期33卷 19-27页

作者： Pengge Ma Jiangnan Wang Dongdong Pang Tao Shan Junling Sun Qiuchun Jin School of Intelligent engineering Zhengzhou University of AeronauticsZhengzhou 450000China Beijing Key Laboratory of Fractional Signals and Systems School of Information and ElectronicsBeijing Institute of TechnologyBeijing 100081China

In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this ***,the ratio information between the target and local background is utilized as an enhancement *** local contrast is calculated by incorporating the heterogeneity between the target and local ***,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing ***,the location of target is obtained by adaptive threshold *** experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV).

关键词： infrared small target unmanned aerial vehicles(UAV) local contrast target detection

Supramolecular Macrocycle Regulated Single-Atom MoS2@Co Catalysts for Enhanced Oxygen Evolution Reaction

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Energy & Environmental Materials 2024年第5期7卷 287-295页

作者： Shuai Cao Wenzhuo Wu Chaozhong Liu Leqian Song Qun Xu Huacheng Zhang Yanli Zhao School of Chemical engineering and Technology Xi’an Jiaotong University Henan institute of Advanced Technology Zhengzhou University Department of Materials Science and engineering Zhengzhou University School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University

The development of active water oxidation catalysts for water splitting has stimulated considerable interest. Herein, the design and building of single atom Co sites using a supramolecular tailoring strategy are reported, that is,the introduction of pillar[4]arene[1.quinone （P4A1.） permits mononuclear Co species stereoelectronically assembled on MoS2matrix to construct an atomically dispersed MoS2@Co catalyst with modulated local electronic structure, definite chemical environment and enhanced oxygen evolution reaction performance. Theoretical calculations indicate that immsobilized single-Co sites exhibit an optimized adsorption capability of oxygencontaining intermediates, endowing the catalyst an excellent electrocatalytic oxygen evolution reaction activity, with a low overpotential of 370 mV at1. mA cm-2and a small Tafel slope of 90 mV dec-1. The extendable potential of this strategy to other electrocatalysts such as MoS2@Ni and MoS2@Zn, and other applications such as the hydrogen evolution reaction was also demonstrated. This study affords new insights into the rational design of single metal atom systems with enhanced electrocatalytic performance.

关键词： electrocatalysis oxygen evolution reaction pillararenequinone single atoms transition-metal dichalcogenides

Porous silica nano-flowers stabilized Pt-Pd bimetallic nanoparticles as heterogeneous catalyst for efficiently synthesizing guaiacol from 2-methoxycyclohexanol

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Chinese Journal of Chemical engineering 2024年第6期70卷 222-233页

作者： Junbo Feng Junyan Wu Dongdong Yan Yadong Zhang School of Chemical engineering Zhengzhou UniversityZhengzhou 450001China State Key Laboratory of Coking Coal Exploitation and Comprehensive Utilization Pingdingshan 467000China Jiyuan Research institute Zhengzhou UniversityJiyuan 459000China School of Materials and Chemical engineering Zhongyuan University of TechnologyZhengzhou 450007China

Porous silica nano-flowers(KCC-1.immobilized Pt-Pd alloy NPs(Pt-Pd/KCC-1.with different mass ratios of Pd and Pt were successfully prepared by a facile in situ one-step reduction,using hydrazinium hydroxide as a reducing *** as-synthesized silica nanospheres possess radial fibers with a distance of 1. nm,exhibiting a high specific surface area(443.56 m^(2)·g^(-1.).Meanwhile,the obtained Pt-Pd alloy NPs are uniformly dispersed on the silica surface with a metallic particle size of 4-6 nm,which exist as metallic Pd and Pt on the surface of monodisperse KCC-1.showing the transfer of electrons from Pd to *** as-synthesized 2.5%Pt-2.5%Pd/KCC-1.exhibited excellent catalytic activity and stability for the continuous dehydrogenation of 2-methoxycyclohexanol to prepare *** with Pt or Pd single metal supported catalysts,the obtained 2.5%Pt-2.5%Pd/KCC-1.shows 97.2%conversion rate of 2-methoxycyclohexanol and 76.8%selectivity for guaiacol,which attributed to the significant synergistic effect of bimetallic Pt-Pd alloy ***,turn over frequency value of the obtained 2.5%Pt-2.5%Pd/KCC-1.NPs achieved 4.36 s^(-1.,showing higher catalytic efficiency than other two monometallic *** pathways of dehydro-aromatization of 2-methoxycyclohexanol over the obtained catalyst are ***,the obtained 2.5%Pt-2.5%Pd/KCC-1.NPs prove their potential in the dehydrogenation of 2-methoxycyclohexanol,while the kinetics and mechanistic study of the dehydrogenation reaction over the catalyst in a continuous fixed-bed reactor may provide valuable information for the development of green,outstanding and powerful synthetic pathway of guaiacol.

关键词： Supported catalyst Nanoparticles Dehydrogenation 2-Methoxycyclohexanol Guaiacol

A Hybrid Feature Fusion Traffic Sign Detection Algorithm Based on YOLOv7

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Computers, Materials & Continua 2024年第7期80卷 1425-1440页

作者： Bingyi Ren Juwei Zhang Tong Wang School of Mechanical engineering Henan University of Science and TechnologyLuoyang471000China School of information {1. Henan University of Science and TechnologyLuoyang471000China School of Electronic information Zhengzhou Institute of Aeronautical Industry ManagementZhengzhou450046China Henan Province New Energy Vehicle Power Electronics and Power Transmission engineering Research Center Luoyang471000China

Autonomous driving technology has entered a period of rapid development,and traffic sign detection is one of the important *** target detection networks are difficult to adapt to scenarios where target sizes are seriously imbalanced,and traffic sign targets are small and have unclear features,which makes detection more ***,we propose aHybrid Feature Fusion Traffic Sign detection algorithmbased onYOLOv7(HFFTYOLO).First,a self-attention mechanism is incorporated at the end of the backbone network to calculate feature interactions within scales;Secondly,the cross-scale fusion part of the neck introduces a bottom-up multi-path fusion *** reuse paths at the end of the neck,paying particular attention to cross-scale fusion of highlevel *** addition,we found the appropriate channel width through a lot of experiments and reduced the superfluous *** terms of training,a newregression lossCMPDIoUis proposed,which not only considers the problem of loss degradation when the aspect ratio is the same but the width and height are different,but also enables the penalty term to dynamically change at different ***,our proposed improved method shows excellent results on the TT1.0K *** with the baseline model,without increasing the number of parameters and computational complexity,AP0.5 and AP increased by 2.2%and 2.7%,respectively,reaching 92.9%and 58.1..

关键词： Small target detection YOLOv7 traffic sign detection regression loss

A novel non-intrusive load monitoring technique using semi-supervised deep learning framework for smart grid

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Building Simulation 2024年第3期17卷 441-457页

作者： Mohammad Kaosain Akbar Manar Amayri Nizar Bouguila Concordia institute for {1. Systems engineering Concordia UniversityMontrealCanada

Non-intrusive load monitoring(NILM)is a technique which extracts individual appliance consumption and operation state change information from the aggregate power consumption made by a single residential or commercial *** plays a pivotal role in modernizing building energy management by disaggregating total energy consumption into individual appliance-level *** enables informed decision-making,energy optimization,and cost ***,NILM encounters substantial challenges like signal noise,data availability,and data privacy concerns,necessitating advanced algorithms and robust methodologies to ensure accurate and secure energy disaggregation in real-world *** learning techniques have recently shown some promising results in NILM research,but training these neural networks requires significant labeled *** initial sets of labeled data for the research by installing smart meters at the end of consumers’appliances is laborious and expensive and exposes users to severe privacy *** is also important to mention that most NILM research uses empirical observations instead of proper mathematical approaches to obtain the threshold value for determining appliance operation states(On/Off)from their respective energy consumption *** paper proposes a novel semi-supervised multilabel deep learning technique based on temporal convolutional network(TCN)and long short-term memory(LSTM)for classifying appliance operation states from labeled and unlabeled *** two thresholding techniques,namely Middle-Point Thresholding and Variance-Sensitive Thresholding,which are needed to derive the threshold values for determining appliance operation states,are also compared *** superiority of the proposed model,along with finding the appliance states through the Middle-Point Thresholding method,is demonstrated through 1.%improved overall improved F1.icro score and almost 26%improved Hamming loss,F1.and Specificity score for the p

关键词： semi-supervised learning non-intrusive load monitoring middle-point thresholding deep learning TCN LSTM