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Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer
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作者 Hongliang Zhang Yi Chen +1 位作者 Yuteng Zhang Gongjie Xu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第8期1459-1483,共25页
The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worke... The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality. 展开更多
关键词 Distributed flexible job shop scheduling problem dual resource constraints energy-saving scheduling multi-objective grey wolf optimizer Q-LEARNING
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Energy-Saving Construction Technologies for Buildings
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作者 Jingjing Sun 《Journal of World Architecture》 2024年第3期43-48,共6页
The development of the construction industry is shifting towards low-carbon construction,so it is necessary to improve and optimize related construction concepts,methods,and processes.By improving resource and energy ... The development of the construction industry is shifting towards low-carbon construction,so it is necessary to improve and optimize related construction concepts,methods,and processes.By improving resource and energy control efficiency in building projects,minimizing construction waste,and reducing environmental impact,a foundation for the sustainable development of the industry can be established.This paper mainly analyzes the significance of low-carbon energy-saving construction technology and the control factors of construction,summarizes the status quo of the development of building energy-saving construction,and puts forward strategies for applying building energy-saving construction technology.These strategies serve to achieve low-carbon and energy-saving goals to promote the healthy development of energy-saving construction. 展开更多
关键词 Low-carbon energy-saving concept CONSTRUCTION energy-saving construction Thermal insulation technology Intelligent technology
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Application of Energy-Saving Materials in Architectural Design
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作者 Yajuan Liu 《Journal of World Architecture》 2024年第3期72-77,共6页
The conventional process of building construction is associated with issues such as the waste of construction materials and environmental pollution.Sustainable development highlights the importance of energy conservat... The conventional process of building construction is associated with issues such as the waste of construction materials and environmental pollution.Sustainable development highlights the importance of energy conservation and eco-friendly practices.It is essential to use energy-efficient and green materials in building designs to ensure the healthy growth of construction companies.This article discusses the advantages and principles of incorporating energy-saving materials in architectural design.It examines the strategies and critical control points for using energy-saving materials in architectural design,offering guidance for the sustainable development of the construction industry. 展开更多
关键词 energy-saving materials Architectural design Advantages Control strategy
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Exploration of Energy-Saving Technologies in Building Electrical System Design
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作者 Yong Zhang 《Journal of Electronic Research and Application》 2024年第4期28-33,共6页
Green energy conservation is the mainstream trend in the current development of the construction industry.The application of energy-saving technology in building electrical system design can effectively reduce energy ... Green energy conservation is the mainstream trend in the current development of the construction industry.The application of energy-saving technology in building electrical system design can effectively reduce energy consumption,avoid unnecessary energy consumption,and truly achieve energy conservation and environmental protection.Based on this,the article elaborates on the principles of energy-saving design in building electrical systems,and actively explores the application of energy-saving technologies from different perspectives such as optimizing power supply and distribution system design,adopting high-efficiency energy-saving lighting equipment,applying renewable energy,promoting smart home technology,and improving the efficiency of building electrical equipment. 展开更多
关键词 Building electrical system design energy-saving technology
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Green,Sustainable Architectural Bamboo with High Light Transmission and Excellent Electromagnetic Shielding as a Candidate for Energy-Saving Buildings 被引量:6
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作者 Jing Wang Xinyu Wu +5 位作者 Yajing Wang Weiying Zhao Yue Zhao Ming Zhou Yan Wu Guangbin Ji 《Nano-Micro Letters》 SCIE EI CAS CSCD 2023年第1期209-224,共16页
Currently,light-transmitting,energy-saving,and electromagnetic shielding materials are essential for reducing indoor energy consumption and improving the electromagnetic environment.Here,we developed a cellulose compo... Currently,light-transmitting,energy-saving,and electromagnetic shielding materials are essential for reducing indoor energy consumption and improving the electromagnetic environment.Here,we developed a cellulose composite with excellent optical transmittance that retained the natural shape and fiber structure of bamboo.The modified whole bamboo possessed an impressive optical transmittance of approximately 60%at 6.23 mm,illuminance of 1000 luminance(lux),water absorption stability(mass change rate less than 4%),longitudinal tensile strength(46.40 MPa),and surface properties(80.2 HD).These were attributed to not only the retention of the natural circular hollow structure of the bamboo rod on the macro,but also the complete bamboo fiber skeleton template impregnated with UV resin on the micro.Moreover,a multilayered device consisting of translucent whole bamboo,transparent bamboo sheets,and electromagnetic shielding film exhibited remarkable heat insulation and heat preservation performance as well as an electromagnetic shielding performance of 46.3 dB.The impressive optical transmittance,mechanical properties,thermal performance,and electromagnetic shielding abilities combined with the renewable and sustainable nature,as well as the fast and efficient manufacturing process,make this bamboo composite material suitable for effective application in transparent,energy-saving,and electromagnetic shielding buildings. 展开更多
关键词 Electromagnetic interference shielding Biomass material TRANSMITTANCE energy-saving BAMBOO
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Low-content Pt-triggered the optimized d-band center of Rh metallene for energy-saving hydrogen production coupled with hydrazine degradation 被引量:1
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作者 Qiqi Mao Wenxin Wang +6 位作者 Kai Deng Hongjie Yu Ziqiang Wang You Xu Xiaonian Li Liang Wang Hongjing Wang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2023年第10期58-66,I0004,共10页
Utilizing the hydrazine-assisted water electrolysis for energy-efficient hydrogen production shows a promising application, which relies on the development and design of efficient bifunctional electrocatalysts. Herein... Utilizing the hydrazine-assisted water electrolysis for energy-efficient hydrogen production shows a promising application, which relies on the development and design of efficient bifunctional electrocatalysts. Herein, we reported a low-content Pt-doped Rh metallene(Pt-Rhene) for hydrazine-assisted water electrolysis towards energy-saving hydrogen(H_(2)) production, where the ultrathin metallene is constructed to provide enough favorable active sites for catalysis and improve atom utilization.Additionally, the synergistic effect between Rh and Pt can optimize the electronic structure of Rh for improving the intrinsic activity. Therefore, the required overpotential of Pt-Rhene is only 37 mV to reach a current density of-10 mA cm^(-2) in the hydrogen evolution reaction(HER), and the Pt-Rhene exhibits a required overpotential of only 11 mV to reach a current density of 10 mA cm^(-2) in the hydrazine oxidation reaction(HzOR). With the constructed HER-HzOR two-electrode system, the Pt-Rhene electrodes exhibit an extremely low voltage(0.06/0.19/0.28 V) to achieve current densities of 10/50/100 mA cm^(-2) for energy-saving H_(2) production, which greatly reduces the electrolysis energy consumption. Moreover,DFT calculations further demonstrate that the introduction of Pt modulates the electronic structure of Rh and optimizes the d-band center, thus enhancing the adsorption and desorption of reactant/intermediates in the electrocatalytic reaction. 展开更多
关键词 Pt-Rhene Synergistic effect Hydrogen evolution reaction Hydrazine oxidation reaction energy-saving H_(2)production
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基于Blending-Clustering集成学习的大坝变形预测模型
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作者 冯子强 李登华 丁勇 《水利水电技术(中英文)》 北大核心 2024年第4期59-70,共12页
【目的】变形是反映大坝结构性态最直观的效应量,构建科学合理的变形预测模型是保障大坝安全健康运行的重要手段。针对传统大坝变形预测模型预测精度低、误报率高等问题导致的错误报警现象,【方法】选取不同预测模型和聚类算法集成,构... 【目的】变形是反映大坝结构性态最直观的效应量,构建科学合理的变形预测模型是保障大坝安全健康运行的重要手段。针对传统大坝变形预测模型预测精度低、误报率高等问题导致的错误报警现象,【方法】选取不同预测模型和聚类算法集成,构建了一种Blending-Clustering集成学习的大坝变形预测模型,该模型以Blending对单一预测模型集成提升预测精度为核心,并通过Clustering聚类优选预测值改善模型稳定性。以新疆某面板堆石坝变形监测数据为实例分析,通过多模型预测性能比较,对所提出模型的预测精度和稳定性进行全面评估。【结果】结果显示:Blending-Clustering模型将预测模型和聚类算法集成,均方根误差(RMSE)和归一化平均百分比误差(nMAPE)明显降低,模型的预测精度得到显著提高;回归相关系数(R~2)得到提升,模型具备更强的拟合能力;在面板堆石坝上22个测点变形数据集上的预测评价指标波动范围更小,模型的泛化性和稳定性得到有效增强。【结论】结果表明:Blending-Clustering集成预测模型对于预测精度、泛化性和稳定性均有明显提升,在实际工程具有一定的应用价值。 展开更多
关键词 大坝 变形 预测模型 Blending集成 clustering集成 模型融合
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Clustered张拉整体结构的动力学建模
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作者 张子宇 王彤 周斌 《振动与冲击》 EI CSCD 北大核心 2024年第16期287-294,共8页
针对clustered张拉整体结构,提出了一种基于任意拉格朗日-欧拉(arbitrary Lagrangian-Eulerian, ALE)法的多体动力学模型。相较于传统的拉格朗日法模型,该研究中的模型具有更为简单的运动学约束。首先,引入了一种ALE时变长度索单元,其... 针对clustered张拉整体结构,提出了一种基于任意拉格朗日-欧拉(arbitrary Lagrangian-Eulerian, ALE)法的多体动力学模型。相较于传统的拉格朗日法模型,该研究中的模型具有更为简单的运动学约束。首先,引入了一种ALE时变长度索单元,其网格节点与物质点可以独立运动,提供了一种自然的方式描述结构中运动的滑轮和滑动绳索;其次,利用达朗贝尔原理,推导了该单元的广义力向量并计算了相应的雅可比矩阵;然后,建立了张拉整体系统的动力学方程,并利用广义α算法对其进行求解,选取节点的全局位置坐标和物质坐标作为广义坐标,其中全局位置坐标可以被不同物体共享,以减少动力学方程的自由度数和消除物体间的约束;最后,展示了一个数值算例,10层可折叠张拉整体塔架,对其折叠过程进行了准静态和动力学仿真,验证了模型的有效性。所提出的模型和算法可为clustered张拉整体结构的设计提供理论指导,具有工程意义。 展开更多
关键词 多体动力学模型 clustered张拉整体 任意拉格朗日-欧拉(ALE) 可展开空间结构
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Design of Diversified Intelligent Control System for Energy-saving Optimization of Solar Greenhouse in North China
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作者 Yanmeng HE Baohui MA 《Asian Agricultural Research》 2023年第7期45-50,53,共7页
Intelligent greenhouse can promote the development of modern agriculture, realize the high quality and high yield of crops, and also bring greater economic benefits. In accordance with the climate conditions in northw... Intelligent greenhouse can promote the development of modern agriculture, realize the high quality and high yield of crops, and also bring greater economic benefits. In accordance with the climate conditions in northwest China, a set of intelligent control system for diversified environment of solar greenhouse was designed. The system divides the annual greenhouse control into six stages according to the optimal energy saving. It uses modern detection technology to collect the greenhouse environmental temperature, environmental humidity, soil humidity, CO_(2) concentration and illumination parameters under different working modes. It uses programmable logic control technology to realize the data processing of various parameters and the action control of rolling film, wet curtain fan and other actuators. It uses KingView monitoring software to realize the monitoring and manual control of greenhouse environment parameters. The operation results indicate that the control system runs stably and basically meets the control requirements. 展开更多
关键词 Solar greenhouse energy-saving optimization Diversified Control Intelligent control
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Behavior characteristics and market operation problems of existing building energy-saving renovation market
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作者 GUO Han-ding WANG Ming-yu +1 位作者 MA Xing-neng ZHANG Yin-xian 《Ecological Economy》 2023年第3期271-283,共13页
The long-term and effective implementation of the existing building energy efficiency renovation depends on the development of the existing building energy efficiency renovation market.The key to the development of th... The long-term and effective implementation of the existing building energy efficiency renovation depends on the development of the existing building energy efficiency renovation market.The key to the development of the existing building energy efficiency renovation market is the joint role of the market players.Starting with the analysis of the externalities and information asymmetry of the existing building energy efficiency renovation market,this paper analyzes the behavioral characteristics and influencing factors of the existing building energy efficiency renovation market entities(central government,local government,owners,energy conservation service enterprises,third-party evaluation institutions,and other market entities),and reveals the problems of the existing building energy efficiency renovation market,such as the absence of government,the lack of main power,and the lack of financing channels,Thus,it lays a platform foundation for the research on the behavior strategy and security system of the existing building energy-s aving renovation market. 展开更多
关键词 the existing buildings energy-saving transformation subjective behavior EXTERNALITY information asymmetry
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Multi-subject and multi-objective integrated optimization system and implementation strategy for energy-saving renovation of the existing residential buildings
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作者 GUO Han-ding JIN Zhen-xing +1 位作者 QIAO Wan-zhen ZHANG Yin-xian 《Ecological Economy》 2023年第2期149-162,共14页
The core of the healthy and orderly operation of the existing residential building energy-saving renovation market lies in the exploration of the implementation mechanism of multi-subject and multi-objective integrate... The core of the healthy and orderly operation of the existing residential building energy-saving renovation market lies in the exploration of the implementation mechanism of multi-subject and multi-objective integrated optimization.The multi-agent and multi-objective integrated optimization system framework is a powerful tool to guide the scientific decision-making of the market core structural entities in the future market practice. This paper analyzes the practical dilemma of energy-saving renovation of theexisting residential buildings in China, summarizes the practical experience of multi-subject and multi-objective integrated optimization of energy-saving renovation of the existing residential buildings in foreign countries, and puts forward beneficial practical enlightenment on the basis of comparison at home and abroad;The design principles of the target integrated optimization system have established a multi-subject and multi-objective integrated optimization system framework for the energy-saving renovation of the existing residential buildings, from six aspects: government guidance, trust consensus, value co-creation, risk sharing, revenue sharing, and social responsibility sharing. This paper proposes a multi-subject and multi-objective integrated practice strategy, in order to promote the efficient and orderly development of China's existing residential building energy-saving renovation market. 展开更多
关键词 the existing residential buildings energy-saving renovation win-win cooperation multi-objective integration hierarchical optimization
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Effects of interstitial cluster mobility on dislocation loops evolution under irradiation of austenitic steel
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作者 Xin‑Hua Yan Lu Sun +5 位作者 Du Zhou Teng Xie Chang Peng Ye‑Xin Yang Li Chen Zhen‑Feng Tong 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2024年第8期69-78,共10页
The evolution of dislocation loops in austenitic steels irradiated with Fe^(+)is investigated using cluster dynamics(CD)simulations by developing a CD model.The CD predictions are compared with experimental results in... The evolution of dislocation loops in austenitic steels irradiated with Fe^(+)is investigated using cluster dynamics(CD)simulations by developing a CD model.The CD predictions are compared with experimental results in the literature.The number density and average diameter of the dislocation loops obtained from the CD simulations are in good agreement with the experimental data obtained from transmission electron microscopy(TEM)observations of Fe~+-irradiated Solution Annealed 304,Cold Worked 316,and HR3 austenitic steels in the literature.The CD simulation results demonstrate that the diffusion of in-cascade interstitial clusters plays a major role in the dislocation loop density and dislocation loop growth;in particular,for the HR3 austenitic steel,the CD model has verified the effect of temperature on the density and size of the dislocation loops. 展开更多
关键词 cluster dynamics Dislocation loops In-cascade interstitial clusters Austenitic steels
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Weak Merging Scenario of CLASH Cluster A209
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作者 Wen-Cheng Feng Heng Yu +7 位作者 Hai-Hui Zhao Xiao-Lan Hou Shu-Mei Jia Cheng-Kui Li Yu-Lin Cheng Paolo Tozzi Ming Sun Yong Chen 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2024年第4期174-182,共9页
We study the structural and dynamical properties of A209 based on Chandra and XMM-Newton observations.We obtain detailed temperature,pressure,and entropy maps with the contour binning method,and find a hot region in t... We study the structural and dynamical properties of A209 based on Chandra and XMM-Newton observations.We obtain detailed temperature,pressure,and entropy maps with the contour binning method,and find a hot region in the NW direction.The X-ray brightness residual map and corresponding temperature profiles reveal a possible shock front in the NW direction and a cold front feature in the SE direction.Combined with the galaxy luminosity density map we propose a weak merger scenario.A young sub-cluster passing from the SE to NW direction could explain the optical subpeak,the intracluster medium temperature map,the X-ray surface brightness excess,and the X-ray peak offset together. 展开更多
关键词 X rays:galaxies:clusters galaxies:clusters:intracluster medium galaxies:clusters:Abell 209
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A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters
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作者 Zhongshang Chen Ji Feng +1 位作者 Fapeng Cai Degang Yang 《Computers, Materials & Continua》 SCIE EI 2024年第8期2031-2048,共18页
In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared... In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple structures.In life,people’s first instinct for complex things is to divide them into multiple parts to complete.Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures.Taking inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold clusters.Tested on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes. 展开更多
关键词 cluster analysis shared natural neighbor hierarchical clustering
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Multiscale and Auto-Tuned Semi-Supervised Deep Subspace Clustering and Its Application in Brain Tumor Clustering
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作者 Zhenyu Qian Yizhang Jiang +4 位作者 Zhou Hong Lijun Huang Fengda Li Khin Wee Lai Kaijian Xia 《Computers, Materials & Continua》 SCIE EI 2024年第6期4741-4762,共22页
In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world da... In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data,particularly in the field of medical imaging.Traditional deep subspace clustering algorithms,which are mostly unsupervised,are limited in their ability to effectively utilize the inherent prior knowledge in medical images.Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process,thereby enhancing the discriminative power of the feature representations.Additionally,the multi-scale feature extraction mechanism is designed to adapt to the complexity of medical imaging data,resulting in more accurate clustering performance.To address the difficulty of hyperparameter selection in deep subspace clustering,this paper employs a Bayesian optimization algorithm for adaptive tuning of hyperparameters related to subspace clustering,prior knowledge constraints,and model loss weights.Extensive experiments on standard clustering datasets,including ORL,Coil20,and Coil100,validate the effectiveness of the MAS-DSC algorithm.The results show that with its multi-scale network structure and Bayesian hyperparameter optimization,MAS-DSC achieves excellent clustering results on these datasets.Furthermore,tests on a brain tumor dataset demonstrate the robustness of the algorithm and its ability to leverage prior knowledge for efficient feature extraction and enhanced clustering performance within a semi-supervised learning framework. 展开更多
关键词 Deep subspace clustering multiscale network structure automatic hyperparameter tuning SEMI-SUPERVISED medical image clustering
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Application Strategy of PLC Technology in Energy-Saving Control of Tunnel Lighting
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作者 Yuling Zhang 《Journal of Electronic Research and Application》 2023年第3期7-12,共6页
In this study,we investigated on the application of planar lightwave circuit(PLC)technology in energy-saving control of tunnel lighting.The application status of PLC in the field of energy saving followed by the neces... In this study,we investigated on the application of planar lightwave circuit(PLC)technology in energy-saving control of tunnel lighting.The application status of PLC in the field of energy saving followed by the necessity of energy saving in tunnel lighting was analyzed.Finally,the application of PLC in tunnel lighting energy-saving control around the three dimensions of system overall architecture design,control scheme,and program control process was investigated.The results showed that the system meets the requirements of control effect,robustness,and visual effect after trial operation,and is suitable for practical applications. 展开更多
关键词 energy-saving tunnel lighting PLC technology Control scheme Program control
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Knowledge-Driven Possibilistic Clustering with Automatic Cluster Elimination
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作者 Xianghui Hu Yiming Tang +2 位作者 Witold Pedrycz Jiuchuan Jiang Yichuan Jiang 《Computers, Materials & Continua》 SCIE EI 2024年第9期4917-4945,共29页
Traditional Fuzzy C-Means(FCM)and Possibilistic C-Means(PCM)clustering algorithms are data-driven,and their objective function minimization process is based on the available numeric data.Recently,knowledge hints have ... Traditional Fuzzy C-Means(FCM)and Possibilistic C-Means(PCM)clustering algorithms are data-driven,and their objective function minimization process is based on the available numeric data.Recently,knowledge hints have been introduced to formknowledge-driven clustering algorithms,which reveal a data structure that considers not only the relationships between data but also the compatibility with knowledge hints.However,these algorithms cannot produce the optimal number of clusters by the clustering algorithm itself;they require the assistance of evaluation indices.Moreover,knowledge hints are usually used as part of the data structure(directly replacing some clustering centers),which severely limits the flexibility of the algorithm and can lead to knowledgemisguidance.To solve this problem,this study designs a newknowledge-driven clustering algorithmcalled the PCM clusteringwith High-density Points(HP-PCM),in which domain knowledge is represented in the form of so-called high-density points.First,a newdatadensitycalculation function is proposed.The Density Knowledge Points Extraction(DKPE)method is established to filter out high-density points from the dataset to form knowledge hints.Then,these hints are incorporated into the PCM objective function so that the clustering algorithm is guided by high-density points to discover the natural data structure.Finally,the initial number of clusters is set to be greater than the true one based on the number of knowledge hints.Then,the HP-PCM algorithm automatically determines the final number of clusters during the clustering process by considering the cluster elimination mechanism.Through experimental studies,including some comparative analyses,the results highlight the effectiveness of the proposed algorithm,such as the increased success rate in clustering,the ability to determine the optimal cluster number,and the faster convergence speed. 展开更多
关键词 Fuzzy C-Means(FCM) possibilistic clustering optimal number of clusters knowledge-driven machine learning fuzzy logic
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Fixed-Time Cluster Optimization for Multi-Agent Systems Based on Piecewise Power-Law Design
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作者 Suna Duan Xinchun Jia Xiaobo Chi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第5期1301-1303,共3页
Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective fun... Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective functions of all clusters.A novel piecewise power-law control protocol with cooperative-competition relations is proposed.Furthermore,a sufficient condition is obtained to ensure that the FOMASs achieve the cluster consensus within an FXT. 展开更多
关键词 AGENT cluster OPTIMIZATION
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Path-Based Clustering Algorithm with High Scalability Using the Combined Behavior of Evolutionary Algorithms
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作者 Leila Safari-Monjeghtapeh Mansour Esmaeilpour 《Computer Systems Science & Engineering》 2024年第3期705-721,共17页
Path-based clustering algorithms typically generate clusters by optimizing a benchmark function.Most optimiza-tion methods in clustering algorithms often offer solutions close to the general optimal value.This study a... Path-based clustering algorithms typically generate clusters by optimizing a benchmark function.Most optimiza-tion methods in clustering algorithms often offer solutions close to the general optimal value.This study achieves the global optimum value for the criterion function in a shorter time using the minimax distance,Maximum Spanning Tree“MST”,and meta-heuristic algorithms,including Genetic Algorithm“GA”and Particle Swarm Optimization“PSO”.The Fast Path-based Clustering“FPC”algorithm proposed in this paper can find cluster centers correctly in most datasets and quickly perform clustering operations.The FPC does this operation using MST,the minimax distance,and a new hybrid meta-heuristic algorithm in a few rounds of algorithm iterations.This algorithm can achieve the global optimal value,and the main clustering process of the algorithm has a computational complexity of O�k2×n�.However,due to the complexity of the minimum distance algorithm,the total computational complexity is O�n2�.Experimental results of FPC on synthetic datasets with arbitrary shapes demonstrate that the algorithm is resistant to noise and outliers and can correctly identify clusters of varying sizes and numbers.In addition,the FPC requires the number of clusters as the only parameter to perform the clustering process.A comparative analysis of FPC and other clustering algorithms in this domain indicates that FPC exhibits superior speed,stability,and performance. 展开更多
关键词 clusterING global optimization the minimax matrix MST path-based clustering FPC
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Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network
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作者 Ruchun Jia Jianwei Zhang +2 位作者 Yi Lin Yunxiang Han Feike Yang 《Computers, Materials & Continua》 SCIE EI 2024年第5期2523-2546,共24页
In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set f... In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network. 展开更多
关键词 Air traffic control network security attack behavior cluster detection behavioral characteristics information gain cluster threshold automatic encoder
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