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Multi-strategy improved red-billed blue magpie optimizer for Kapur multi-threshold image segmentation 认领 引用
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作者 WU Jin XIONG Hao +1 位作者 LUO Wenxuan GUO Linlin 《High Technology Letters》 EI CAS 2025年第4期365-372,共8页
Multi-threshold image segmentation techniques based on intelligent optimization algorithms show great potential in low-cost,real-time applications.These methods are efficient even with limited computational resources.... Multi-threshold image segmentation techniques based on intelligent optimization algorithms show great potential in low-cost,real-time applications.These methods are efficient even with limited computational resources.This paper proposes a multi-strategy improved red-billed blue magpie optimizer(MIRBMO)for Kapur multi-threshold image segmentation,aiming to enhance segmentation quality.First,Sobol sequences with elite reverse learning are used to optimize the distribution of the initial population,accelerating the optimization process.Second,lens imaging reverse learning is introduced to help the algorithm escape local optima.Finally,the golden sine strategy is adopted to increase the search space diversity and explore potential optimal solutions.The algorithm’s performance is evaluated using the 8 classic benchmark test functions,and results show that MIRBMO outperforms red-billed blue magpie optimizer(RBMO)in optimization capability and demonstrates clear advantages over other intelligent optimization algorithms.When applied to Kapur multi-threshold segmentation,MIRBMO yields a threshold combination with higher entropy values and produces segmented images with superior peak signal-to-noise ratio(PSNR),structural similarity index measure(SSIM),and feature similarity index measure(FSIM)values,indicating its strong application potential. 展开更多
关键词 red-billed blue magpie optimizer image segmentation multi-threshold Kapur maximum entropy
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Multi-dimensional and Multi-threshold Airframe Damage Region Division Method Based on Correlation Optimization 认领 引用
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作者 CAI Shuyu SHI Tao SHI Lizhong 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第5期788-799,共12页
In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlatio... In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed.On the basis of airframe damage feature analysis,the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image,and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division.Through the correlation parameter optimization algorithm,the problem of low efficiency of multi-dimensional multi-threshold division method is solved.Finally,the proposed method is compared and verified by instances of airframe damage image.The results show that compared with the traditional threshold division method,the damage region divided by the proposed method is complete and accurate,and the boundary is clear and coherent,which can effectively reduce the interference of many factors such as uneven luminance,chromaticity deviation,dirt attachment,image compression,and so on.The correlation optimization algorithm has high efficiency and stable convergence,and can meet the requirements of aircraft intelligent maintenance. 展开更多
关键词 airframe damage region division multi-dimensional feature entropy multi-threshold correlation optimization aircraft intelligent maintenance
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Pattern-Moving-Based Parameter Identification of Output Error Models with Multi-Threshold Quantized Observations 认领 引用 被引量：2
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作者 Xiangquan Li Zhengguang Xu +1 位作者 Cheng Han Ning Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2022年第3期1807-1825,共19页
This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-thresho... This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm. 展开更多
关键词 Pattern moving multi-threshold quantized observations output error model auxiliary model parameter identification
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Two-dimensional cross entropy multi-threshold image segmentation based on improved BBO algorithm 认领 引用 被引量：2
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作者 LI Wei HU Xiao-hui WANG Hong-chuang 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2018年第1期42-49,共8页
In order to improve the global search ability of biogeography-based optimization(BBO)algorithm in multi-threshold image segmentation,a multi-threshold image segmentation based on improved BBO algorithm is proposed.Whe... In order to improve the global search ability of biogeography-based optimization(BBO)algorithm in multi-threshold image segmentation,a multi-threshold image segmentation based on improved BBO algorithm is proposed.When using BBO algorithm to optimize threshold,firstly,the elitist selection operator is used to retain the optimal set of solutions.Secondly,a migration strategy based on fusion of good solution and pending solution is introduced to reduce premature convergence and invalid migration of traditional migration operations.Thirdly,to reduce the blindness of traditional mutation operations,a mutation operation through binary computation is created.Then,it is applied to the multi-threshold image segmentation of two-dimensional cross entropy.Finally,this method is used to segment the typical image and compared with two-dimensional multi-threshold segmentation based on particle swarm optimization algorithm and the two-dimensional multi-threshold image segmentation based on standard BBO algorithm.The experimental results show that the method has good convergence stability,it can effectively shorten the time of iteration,and the optimization performance is better than the standard BBO algorithm. 展开更多
关键词 two-dimensional cross entropy biogeography-based optimization(BBO)algorithm multi-threshold image segmentation
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A Steganography Based on Optimal Multi-Threshold Block Labeling 认领 引用
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作者 Shuying Xu Chin-Chen Chang Ji-Hwei Horng 《Computer Systems Science & Engineering》 SCIE EI 2023年第1期721-739,共19页
Hiding secret data in digital images is one of the major researchfields in information security.Recently,reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud servi... Hiding secret data in digital images is one of the major researchfields in information security.Recently,reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services.This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique(OMTBL-RDHEI).In our scheme,the content owner encrypts the cover image with block permutation,pixel permutation,and stream cipher,which preserve the in-block correlation of pixel values.After uploading to the cloud service,the data hider applies the prediction error rearrangement(PER),the optimal threshold selection(OTS),and the multi-threshold labeling(MTL)methods to obtain a compressed version of the encrypted image and embed secret data into the vacated room.The receiver can extract the secret,restore the cover image,or do both according to his/her granted authority.The proposed MTL labels blocks of the encrypted image with a list of threshold values which is optimized with OTS based on the features of the current image.Experimental results show that labeling image blocks with the optimized threshold list can efficiently enlarge the amount of vacated room and thus improve the embedding capacity of an encrypted cover image.Security level of the proposed scheme is analyzed and the embedding capacity is compared with state-of-the-art schemes.Both are concluded with satisfactory performance. 展开更多
关键词 Reversible data hiding encryption image prediction error compression multi-threshold block labeling
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Multi-Threshold Algorithm Based on Havrda and Charvat Entropy for Edge Detection in Satellite Grayscale Images 认领 引用
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作者 Mohamed A. El-Sayed Hamida A. M. Sennari 《Journal of Software Engineering and Applications》 2014年第1期42-52,共11页
Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and... Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and scene analysis. This paper introduces an edge-detection algorithm, which generates multi-threshold values. It is based on non-Shannon measures such as Havrda & Charvat’s entropy, which is commonly used in gray level image analysis in many types of images such as satellite grayscale images. The proposed edge detection performance is compared to the previous classic methods, such as Roberts, Prewitt, and Sobel methods. Numerical results underline the robustness of the presented approach and different applications are shown. 展开更多
关键词 Multi-Threshold Edge Detection Measure Entropy Havrda Charvat’s Entropy
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Research on Otsu multi-threshold image segmentation based on improved transient search algorithm 认领 引用 被引量：1
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作者 Wu Jin Feng Haoran +1 位作者 Xiong Hao Chen Wenfeng 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2025年第5期34-52,95,共19页
Multi-threshold image segmentation divides an image into regions with distinct features. However,as the number of thresholds increases,its computational complexity grows exponentially. To address this issue,an improve... Multi-threshold image segmentation divides an image into regions with distinct features. However,as the number of thresholds increases,its computational complexity grows exponentially. To address this issue,an improved transient search optimization(ITSO) algorithm is proposed to overcome the limitations of the original transient search optimization(TSO) algorithm,such as susceptibility to local optima and low convergence accuracy. ITSO enhances the diversity of initial solutions through a dynamic reflection learning strategy based on the Beta distribution,improves exploration capability using a Cauchy inverse cumulative distribution operator,and balances exploration and exploitation through a dynamic perturbation strategy. Tests on CEC2022 demonstrate that ITSO outperforms the dandelion optimizer(DO),tunicate swarm algorithm(TSA), whale optimization algorithm(WOA),golden jackal optimization(GJO),TSO,goose algorithm(GOOSE),and love evolution algorithm(LEA). When applied to image segmentation,ITSO achieves superior performance in terms of Otsu fitness,peak signal-to-noise ratio(PSNR),structural similarity(SSIM),and feature similarity(FSIM),showcasing its strong research value and application potential. 展开更多
关键词 image segmentation transient search optimization(TSO) tunicate swarm algorithm(TSA)multi-threshold Otsu algorithm
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Research on Kapur multi-threshold image segmentation based on improved sparrow search algorithm 认领 引用
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作者 Wu Jin Feng Haoran +1 位作者 Chong Gege Xiong Hao 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2025年第2期31-43,共13页
Multilevel threshold image segmentation divides an image into several regions with distinct characteristics.While effective,its computational complexity increases exponentially with the number of thresholds,highlighti... Multilevel threshold image segmentation divides an image into several regions with distinct characteristics.While effective,its computational complexity increases exponentially with the number of thresholds,highlighting the need for more efficient and stable methods.An improved sparrow search algorithm(ISSA)that combines multiple strategies to address the dependency on the initial population and solution accuracy issues in the basic sparrow search algorithm(SSA)was proposed in this paper.ISSA leverages circle chaotic mapping to enhance population diversity,a tangent flight operator to improve search diversity,and a triangular random walk to perturb the optimal solution,thereby enhancing global search capability and avoiding local optima.Performance evaluations on 16 benchmark functions demonstrate that ISSA surpasses the gray wolf optimizer(GWO),whale optimization algorithm(WOA),rat swarm optimizer(RSO),moth-flame optimization(MFO),and SSA in terms of search speed,accuracy,and robustness.When applied to multilevel threshold image segmentation,ISSA excels in Kapur's maximum entropy,peak signal-to-noise ratio(PSNR),structural similarity(SSIM),and feature similarity(FSIM),highlighting its significant research value and application potential in the field of image segmentation. 展开更多
关键词 image segmentation sparrow search algorithm(SSA) multi-threshold Kapur's maximum entropy
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Spatiotemporal Variations of Meteorological Droughts in China During 1961–2014: An Investigation Based on Multi-Threshold Identification 认领 引用 被引量：13
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作者 Jun He Xiaohua Yang +2 位作者 Zhe Li Xuejun Zhang Qiuhong Tang 《International Journal of Disaster Risk Science》 SCIE CSCD 2016年第1期63-76,共14页
As a major agricultural country, China suffers from severe meteorological drought almost every year.Previous studies have applied a single threshold to identify the onset of drought events, which may cause problems to... As a major agricultural country, China suffers from severe meteorological drought almost every year.Previous studies have applied a single threshold to identify the onset of drought events, which may cause problems to adequately characterize long-term patterns of droughts.This study analyzes meteorological droughts in China based on a set of daily gridded(0.5° 9 0.5°) precipitation data from 1961 to 2014. By using a multi-threshold run theory approach to evaluate the monthly percentage of precipitation anomalies index(Pa), a drought events sequence was identified at each grid cell. The spatiotemporal variations of drought in China were further investigated based on statistics of the frequency, duration,severity, and intensity of all drought events. Analysis of the results show that China has five distinct meteorological drought-prone regions: the Huang-Huai-Hai Plain, Northeast China, Southwest China, South China coastal region,and Northwest China. Seasonal analysis further indicates that there are evident spatial variations in the seasonal contribution to regional drought. But overall, most contribution to annual drought events in China come from the winter. Decadal variation analysis suggests that most of China's water resource regions have undergone an increase in drought frequency, especially in the Liaohe, Haihe, and Yellow River basins, although drought duration and severity clearly have decreased after the 1960 s. 展开更多
关键词 China Meteorological drought Multi-threshold run theory method Spatiotemporal variations
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考虑决策惯性的城市轨道交通多交路出行选择模型 认领 引用 被引量：1
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作者 巩亮 朱欣雨 +2 位作者 许得杰 胡晨皓 杨阳阳 《深圳大学学报（理工版）》 CAS CSCD 北大核心 2026年第1期47-56,共10页
多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用... 多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用与后悔机制的多尺度混合模型,克服了传统模型未考虑路径熟悉度导致的乘客出行行为与实际出行行为之间的决策偏差.通过整合容忍阈值与决策惯性,提出一种多交路出行选择建模方法,基于典型案例的陈述偏好(stated preference,SP)调查数据,完成模型参数估计与性能验证.研究结果表明,乘客对出行时间属性的容忍阈值为6.98 min;相较于基准模型,考虑决策惯性的模型在似然值、贝叶斯信息准则(Bayesian information criterion,BIC)及命中率指标上均表现更优,表明其具备更强的数据拟合能力;支付意愿分析进一步揭示乘客愿意为服务提升承担额外时间成本,从而验证了所提模型的有效性与实用性. 展开更多
关键词 城市轨道交通 路径选择 决策惯性 容忍阈值 多交路 混合效用-后悔模型
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短期围封对藏东高寒草地土壤质量与多功能性的影响 认领 引用
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作者 张宁 魏海娟 +4 位作者 李佳 孙建 张林 罗栋梁 王金牛 《草地学报》 CAS CSCD 北大核心 2026年第8期3049-3059,共11页
围栏封育是退化草地恢复的重要措施,但短期围封对土壤质量及多功能性的影响尚不明确。本研究以西藏三江并流区典型高寒草地为对象,比较连续两年围封与自由放牧(对照)对土壤理化性质、植物群落多样性及土壤多功能性的影响。结果表明:(1)... 围栏封育是退化草地恢复的重要措施,但短期围封对土壤质量及多功能性的影响尚不明确。本研究以西藏三江并流区典型高寒草地为对象,比较连续两年围封与自由放牧(对照)对土壤理化性质、植物群落多样性及土壤多功能性的影响。结果表明:(1)围封显著影响土壤温度、电导率和有机碳含量(F1=6.945,F2=5.216,F3=25.344,P<0.05);(2)与2022年相比,2023年围封提高了植物群落多样性指数(0.966)和禾本科重要值(19.296),自由放牧对照中植物根冠比(17.671)、杂类草(8.215)和莎草科重要值(90.628)增加;(3)Mantel检验表明,2023年植物多样性与土壤理化性质相关性增强,放牧对照下群落对土壤变化更敏感,围封则增加了土壤因子间相关性。(4)多功能性分析表明,围封处理下生态系统功能较稳定,而放牧对照中高阈值多功能性波动较大。综上,短期围封对土壤理化性质的直接影响有限,但可通过调节植物群落结构间接影响土壤多功能性。 展开更多
关键词 西藏三江并流区 围栏封育 土壤多功能性 多阈值法 生态恢复
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基于激光测距的深松作业检测技术 认领 引用
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作者 侯云涛 吴泽全 +4 位作者 蔡晓华 东忠阁 程睿 李源源 祝天宇 《农机化研究》 北大核心 2026年第4期110-117,共8页
针对激光测距技术在深松作业检测中的应用进行深入研究,提出了一种自适应多门限值误差拟合方法。算法通过自适应调整多个门限值,动态寻找激光飞行时间误差最佳拟合校正方案,能够有效克服回波信号上升沿鉴别时刻因干扰脉冲产生的误差。... 针对激光测距技术在深松作业检测中的应用进行深入研究,提出了一种自适应多门限值误差拟合方法。算法通过自适应调整多个门限值,动态寻找激光飞行时间误差最佳拟合校正方案,能够有效克服回波信号上升沿鉴别时刻因干扰脉冲产生的误差。基于此方法,研发了一款智能化深松作业检测设备,其能够自主进行耕层断面数据的采集和保存,提高数据采集和处理的效率。同时,开展了测距试验,具体方法为:将SICK DL100-22AA2101激光测距仪的测距值作为标准距离,试验距离为1~4 m,取1 m作为步长,基于所研发设备,采用本文方法与双门限值时刻鉴别方法分别对同一距离进行5次测量作为实测距离,比较实测距离的标准差,以及实测距离均值与对应标准距离的误差。采用本文研发设备和人工方式分别对土壤膨松度和扰动系数进行检测,设备检测结果为土壤蓬松度27.0%、土壤扰动系数22.3%,人工方式检测结果为土壤蓬松度27.1%、土壤扰动系数22.7%。试验证明:研发设备在显著提高测量效率的前提下,得到的测量结果与传统人工测量方式几乎没有差异,具有较高的实用性和可靠性。 展开更多
关键词 深松作业检测 激光测距 自适应多门限值误差拟合算法
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基于光纤激光扫描与红外热成像的矿山巷道变形实时监测方法 认领 引用
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作者 张红娟 郑娇娇 张卓彤 《激光杂志》 CAS 北大核心 2026年第5期252-260,共9页
矿山巷道在深部开采条件下,受围岩应力、地质构造、采动扰动等多因素影响,变形呈现非线性、局部突变的特点,仅依靠单一特征难以精准监测矿山巷道变形情况,导致矿山巷道变形监测均方误差和误报率上升。因此,提出基于光纤激光扫描与红外... 矿山巷道在深部开采条件下,受围岩应力、地质构造、采动扰动等多因素影响,变形呈现非线性、局部突变的特点,仅依靠单一特征难以精准监测矿山巷道变形情况,导致矿山巷道变形监测均方误差和误报率上升。因此,提出基于光纤激光扫描与红外热成像的矿山巷道变形实时监测方法。首先,利用光纤激光扫描技术获取矿山巷道高密度三维点云数据,通过二次曲面拟合方法估算点云曲率,通过点云曲率获取巷道变形特征;其次,借助红外热成像捕捉矿山巷道红外辐射生成热红外影像,利用多阈值Otsu法分割温度差异区域,获取巷道温度特征;最后,利用改进BP神经网络模型融合巷道变形特征与巷道温度特征,实时监测矿山巷道变形状态。经验证,所提方法可以精准监测到不同程度的变形情况,监测结果的均方误差在0.5以下,决定系数接近1,误报率在5%以下,具有较高的实际应用价值。 展开更多
关键词 光纤激光扫描 红外热成像 巷道变形 二次曲面拟合 多阈值Otsu法 改进BP神经网络
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协同自进化的粒子群优化算法及其在图像分割的应用 认领 引用
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作者 韩佳伶 陈芋渝 《控制与决策》 EI CSCD 北大核心 2026年第6期1743-1752,共10页
粒子群优化算法因其参数设置简单、收敛速度快等优点,被广泛应用于复杂优化问题的求解.然而,经典粒子群算法存在早熟收敛倾向和后期收敛速度减慢等局限性.鉴于此,提出一种协同自进化的粒子群优化算法.首先,所提出算法采用一种新的双群... 粒子群优化算法因其参数设置简单、收敛速度快等优点,被广泛应用于复杂优化问题的求解.然而,经典粒子群算法存在早熟收敛倾向和后期收敛速度减慢等局限性.鉴于此,提出一种协同自进化的粒子群优化算法.首先,所提出算法采用一种新的双群协同进化策略用于提高求解收敛速度,同时,为了平衡算法全局搜索与局部开发的寻优能力,提出一个自进化框架,通过概率性带偏向的方向学习策略结合衰减性的混动扰动策略,有效提升求解算法的整体性能;然后,对算法边界理论进行改进,提升算法在大多数优化问题上的适应性;接着,将所提出改进算法在CEC-2017测试函数集上进行测试,验证该算法在低、中、高维复杂问题上的快速收敛能力和寻优性能;最后,将所提出改进算法应用于多阈值图像分割的阈值求解问题.实验结果表明,所提出改进算法能够有效提升图像的分割精度和效率,验证了所提出算法在解决现实优化问题的有效性. 展开更多
关键词 粒子群优化算法 进化算法 算法优化 最大类间方差法 图像分割 多阈值求解
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小波域语音降噪多算法对比研究 认领 引用 被引量：1
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作者 田玉静 张民 左红伟 《青岛理工大学学报》 CAS 2026年第1期105-114,共10页
深入研究了低信噪比输入下小波包语音增强技术,提出了一种改进的小波包自适应阈值降噪算法。通过与小波软阈值降噪方法的分析与比较,仿真实验验证了该算法在语音增强领域的有效性。为了获得更好的听觉感受,进一步探讨了多小波包自适应... 深入研究了低信噪比输入下小波包语音增强技术,提出了一种改进的小波包自适应阈值降噪算法。通过与小波软阈值降噪方法的分析与比较,仿真实验验证了该算法在语音增强领域的有效性。为了获得更好的听觉感受,进一步探讨了多小波包自适应阈值算法降噪技术及多小波包分析结合维纳滤波语音降噪技术。设计了4种算法的语音降噪处理仿真实验,对比研究了4种算法的语音降噪处理效果。通过对多小波包的精细分解和维纳滤波的优化处理,多小波包维纳滤波在提高输出信号质量、去除噪声干扰方面展现出了卓越的性能。该研究不仅在理论上具有重要意义,在实际应用中也有着广泛的前景。 展开更多
关键词 语音降噪 小波包 多小波包 自适应阈值算法 维纳滤波
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特征融合与多策略聚合的自适应立体匹配算法 认领 引用
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作者 雷经发 宋泊奇 +2 位作者 赵汝海 李永玲 张淼 《测绘科学》 CSCD 北大核心 2026年第3期74-87,共14页
针对现有双目立体匹配在光照变化、噪声干扰以及边缘区域匹配精度不足的问题,提出了一种特征融合与多策略聚合的自适应立体匹配算法。在代价计算阶段,先将HSV颜色特征空间的色调分量融入AD算法,以减少光照变化对匹配精度的影响;利用局... 针对现有双目立体匹配在光照变化、噪声干扰以及边缘区域匹配精度不足的问题,提出了一种特征融合与多策略聚合的自适应立体匹配算法。在代价计算阶段,先将HSV颜色特征空间的色调分量融入AD算法,以减少光照变化对匹配精度的影响;利用局部灰度特征计算自适应噪声阈值用于优化Census代价,增强算法的抗噪性能;设计了一种边缘感知代价,以提升边缘区域的匹配精度;在代价聚合阶段,通过结合十字交叉聚合策略和基于梯度信息的自适应窗口聚合策略,构建多策略聚合方法,以优化非边缘区域与边缘区域的匹配代价;经过视差计算与优化得到最终视差图。实验结果表明,本文算法在非遮挡区域和全部区域的平均误匹配率分别为4.36%和8.20%,有效提升了抗干扰能力与边缘区域的匹配精度。 展开更多
关键词 立体匹配 双目机器视觉 特征融合 自适应阈值 多策略聚合
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基于改进灰狼优化算法的多阈值图像分割研究 认领 引用
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作者 任永强 汪超 韩冲 《合肥工业大学学报（自然科学版）》 CAS 北大核心 2026年第3期330-336,共7页
针对传统阈值分割方法在确定最优阈值时容易陷入局部最优、效率不足和对噪声的高敏感性等问题,文章提出一种结合多种策略的灰狼优化(modified strategy integrated grey wolf optimizer,MSI-GWO)算法,并将其用于基于最小对称交叉熵的阈... 针对传统阈值分割方法在确定最优阈值时容易陷入局部最优、效率不足和对噪声的高敏感性等问题,文章提出一种结合多种策略的灰狼优化(modified strategy integrated grey wolf optimizer,MSI-GWO)算法,并将其用于基于最小对称交叉熵的阈值图像分割。该算法引入改进的Tent混沌进行初始化,以增强全局搜索能力并加速优化进程;通过改进控制参数,辅助种群跳脱局部极值;同时加入随机游走策略,有效提升对最优解的搜索效率。经过6个标准测试函数的验证,MSI-GWO算法在收敛性能上相较于传统智能优化算法表现更佳。在应用于基于最小对称交叉熵的阈值图像分割时,MSI-GWO算法在特征相似性指数、结构相似性指数和峰值信噪比等性能指标上,随着阈值数的增加表现出明显的性能提升,验证了该算法在图像分割领域的应用潜力。 展开更多
关键词 灰狼优化(GWO)算法 Tent混沌初始化 随机游走策略 最小对称交叉熵 多阈值分割
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兼顾通信轮数与计算开销的门限多方隐私集合交集协议 认领 引用
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作者 张恩 黄昱晨 +1 位作者 郑东 禹勇 《软件学报》 EI CSCD 北大核心 2026年第4期1819-1837,共19页
(t,N)门限多方隐私集合交集协议(threshold multi-party private set intersection,TMP-PSI)允许当指定参与方的集合元素x在其余不少于t-1(t<N)个参与方的私有集合中出现时,数据元素x作为交集结果输出,在提案投票、金融交易威胁识别... (t,N)门限多方隐私集合交集协议(threshold multi-party private set intersection,TMP-PSI)允许当指定参与方的集合元素x在其余不少于t-1(t<N)个参与方的私有集合中出现时,数据元素x作为交集结果输出,在提案投票、金融交易威胁识别、安全评估等场景具有广泛应用.现有的门限多方隐私集合交集协议运行效率低、通信轮数多且只能由某一个指定参与方获取交集.针对这些问题,设计一种基于弹性秘密共享的参与方门限测试方法,结合不经意键值对存储(oblivious key-value store,OKVS)提出一种TMP-PSI方案,能够有效减少计算开销和通信轮数.为了满足多参与方获取私有集合中交集信息的需求,提出第2种拓展门限多方隐私集合交集(extended threshold multi-party private set intersection,ETMP-PSI)协议对份额分发方式进行改变,与第1种方案相比,秘密分发者和秘密重构方没有额外增加通信轮数和计算复杂度,实现了多参与方获取私有集合中的交集元素.所设计的协议在数据集合大小为n=216的三方场景下运行时间为6.4 s(TMP-PSI)和8.7 s(ETMP-PSI),与现有的门限多方隐私集合交集协议相比,重构方和分发方的通信复杂度由O(nNtlognλ)降为O(bNλ). 展开更多
关键词 门限多方隐私集合交集协议 通信轮数 计算开销 弹性秘密共享 不经意键值对存储
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智能采掘设备振动信号降噪方法研究 认领 引用 被引量：1
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作者 秦朝中 甘涛 +4 位作者 彭博 李勇 孙传猛 赵云飞 梁勇 《矿业安全与环保》 CAS 北大核心 2026年第1期205-214,共10页
准确采集各种信号及提取特征是实现采掘装备自动控制的关键。电动机轴承的振动信号是采掘装备自动识别煤岩的重要信号之一,其在复杂工况条件下受到环境噪声及部件摩擦的严重干扰,易导致信号特征模糊,影响采掘设备信号特征提取。提出一... 准确采集各种信号及提取特征是实现采掘装备自动控制的关键。电动机轴承的振动信号是采掘装备自动识别煤岩的重要信号之一,其在复杂工况条件下受到环境噪声及部件摩擦的严重干扰,易导致信号特征模糊,影响采掘设备信号特征提取。提出一种基于改进型自适应噪声完备集合经验模态分解(ICEEMDAN)与遗传算法优化多尺度排列熵(MPE)的联合小波降噪方法,并通过信噪比、均方误差和降噪误差比来评价其有效性。研究表明:相较于EEMD-MPE、CEEMDAN-MPE与ICEEMDAN-MPE等传统方法,联合小波降噪方法在仿真信号和机械设备轴承振动数据集中的信噪比最大、均方误差最小、降噪误差比最大,该方法不仅展现出优异的噪声抑制能力,同时有效保留了表征机械状态的特征信息。通过研究煤矿采掘设备的电动机轴承信号,可为研究整个采掘设备的信号特征提供前置研究,并为后续煤岩自动识别与工矿设备自动化、智能化奠定了一定的基础。 展开更多
关键词 采掘设备 振动信号 信号降噪 ICEEMDAN 多尺度排列熵 遗传算法 小波阈值
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基于多源监测数据和自适应故障阈值的变压器绕组绝缘故障预测方法 认领 引用
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作者 曲岳晗 何林 +3 位作者 杨冬锋 刘晓军 相禹维 刘云鹏 《仪器仪表学报》 EI CAS CSCD 北大核心 2026年第3期372-389,共18页
为解决现有变压器绕组绝缘实时故障预测方法在绝缘劣化路径差异性考量及故障阈值确定性方面的不足,针对不同实际工况和制造工艺对绕组绝缘劣化路径与故障阈值的影响,提出一种融合多源监测数据和自适应故障阈值的故障预测方法。首先,该... 为解决现有变压器绕组绝缘实时故障预测方法在绝缘劣化路径差异性考量及故障阈值确定性方面的不足,针对不同实际工况和制造工艺对绕组绝缘劣化路径与故障阈值的影响,提出一种融合多源监测数据和自适应故障阈值的故障预测方法。首先,该方法融合电、热、机械等应力造成的累积损伤机制,通过低秩张量融合对电压、电流等多源数据高效融合,生成轻量化综合劣化数据;其次,结合不同实际工况对劣化进程的影响,根据函数时间配准技术对齐不同设备的劣化时序,通过非线性时间变换将物理时间映射至反映绝缘劣化进程的劣化时间,有效消除时序漂移,并借助函数主成分分析从对齐后的时序数据中提取共性劣化趋势及个体差异特征,并据此建立数据驱动的劣化预测模型;然后,结合贝叶斯动态更新主成分得分,利用先验分布与实时监测信息持续修正后验分布,实现劣化趋势个性化实时预测,降低误差;最后,计及制造工艺的差异性导致的故障阈值不确定性,提出基于动态时间规整距离(DTW)的自适应阈值建模方法,通过曲线形态相似性构建自适应故障阈值模型并预测故障时间置信区间。结果表明,综合劣化数据与标准化糠醛指标相似度极高,该方法能准确预测绕组绝缘的故障时间,实际故障时间点均落在故障预测结果的置信区间内。 展开更多
关键词 电力变压器 绕组绝缘 故障预测 多源监测数据 自适应故障阈值
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