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自适应Transformer-LSTM的滚动轴承故障预测方法研究
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作者 董辛旻 职帅轩 崔富源 《重庆理工大学学报(自然科学)》 北大核心 2026年第2期96-104,共9页
针对滚动轴承故障预测中,模型预测精度低、参数难以确定等问题,提出一种自适应Transformer编码器与长短期记忆神经网络(long short-term memory, LSTM)的滚动轴承故障预测方法。提取轴承全周期振动信号24维时频特征,并基于信息熵、鲁棒... 针对滚动轴承故障预测中,模型预测精度低、参数难以确定等问题,提出一种自适应Transformer编码器与长短期记忆神经网络(long short-term memory, LSTM)的滚动轴承故障预测方法。提取轴承全周期振动信号24维时频特征,并基于信息熵、鲁棒性和相关性构建综合指标对特征进行筛选。采用核主元分析将优选特征进行融合,构建能够反应轴承退化状态的退化指标。综合时间序列全局特性与长短期特性,构建Transformer编码器与LSTM结合的故障预测模型,并引入极光优化算法(polar lights optimization, PLO)进行参数自适应寻优,应用XJTU-SY与IMS滚动轴承数据集进行方法分析验证。结果表明:所提模型在轴承故障预测中表现出良好效果,相较于经典的时域卷积网络(temporal convolutional network, TCN)、双向门控循环神经网络(gate recurrent unit, GRU)等,预测精度有较大提升。 展开更多
关键词 滚动轴承 故障预测 数据驱动 transformER 优化算法
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A Full-Newton Step Feasible Interior-Point Algorithm for the Special Weighted Linear Complementarity Problems Based on Algebraic Equivalent Transformation
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作者 Jing GE Mingwang ZHANG Panjie TIAN 《Journal of Mathematical Research with Applications》 2025年第4期555-568,共14页
In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transform... In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transformation to derive the search direction.It is shown that the proximity measure reduces quadratically at each iteration.Moreover,the iteration bound of the algorithm is as good as the best-known polynomial complexity for these types of problems.Furthermore,numerical results are presented to show the efficiency of the proposed algorithm. 展开更多
关键词 interior-point algorithm weighted linear complementarity problem algebraic equivalent transformation search direction iteration complexity
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基于HBA-Transformer-BiLSTM模型的短时交通流预测
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作者 代谨樯 余海兵 +3 位作者 程欣 杨鹏 刘文荐 程刚 《物流科技》 2026年第4期5-9,共5页
随着城市化进程的加速推进,交通系统的复杂性和动态性也日渐增强,短时交通流预测成为智能交通系统中的关键环节。传统方法在应对大规模、高频率交通数据时,难以兼顾预测精度与模型稳定性。由此,文章提出一种融合蜜獾优化算法(HBA)、Tran... 随着城市化进程的加速推进,交通系统的复杂性和动态性也日渐增强,短时交通流预测成为智能交通系统中的关键环节。传统方法在应对大规模、高频率交通数据时,难以兼顾预测精度与模型稳定性。由此,文章提出一种融合蜜獾优化算法(HBA)、Transformer与双向长短期记忆网络(BiLSTM)的混合模型。该模型利用Transformer的全局依赖建模能力、BiLSTM的双向时序特征提取能力以及HBA的超参数自适应优化优势,实现了对交通流时空特征的高效建模。基于PeMSD4数据集的实验结果显示,该模型在平均相对误差(MAPE)、平均绝对误差(MAE)和决定系数(R^(2))等指标上均优于CNN、GRU、XGBoost、TCN等主流模型。 展开更多
关键词 交通流预测 transformer BiLSTM 蜜獾优化算法
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基于ALA优化VMD和Transformer-BiGRU的锂离子电池RUL预测
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作者 闫来清 梁朝洋 +4 位作者 韩磊 李沁春 蔡钰濠 魏嘉轩 许志超 《电源技术》 北大核心 2026年第2期277-289,共13页
准确预测电池剩余使用寿命(RUL)对保障电池管理系统的安全运行至关重要。然而,电池容量再生效应和测量误差会影响RUL预测精度,传统经验模态分解(EMD)虽能分解信号,却存在模态混叠问题;此外,现有方法中变分模态分解、预测模型核心参数大... 准确预测电池剩余使用寿命(RUL)对保障电池管理系统的安全运行至关重要。然而,电池容量再生效应和测量误差会影响RUL预测精度,传统经验模态分解(EMD)虽能分解信号,却存在模态混叠问题;此外,现有方法中变分模态分解、预测模型核心参数大多依赖手动设置,不仅耗时费力且预测效果受主观因素影响较大。针对上述难题,提出了一种基于ALA优化VMD和Transformer-BiGRU的预测方法。利用人工旅鼠算法(ALA)对变分模态分解(VMD)的模态分解层数与惩罚因子进行优化,通过VMD将电池容量数据分解为不同频率的模态分量,减小容量再生效应和测量误差的影响。构建了结合注意力机制(Transformer)和双向门控循环单元(BiGRU)的预测模型,并通过海星优化算法(SFOA)优化模型结构和关键参数,将各分量的预测结果加和得到最终预测值。基于MATLAB平台在两组公开数据集上验证了所提模型的有效性,并与其他预测方法进行对比。结果表明,所提方法的均方根误差(RMSE)均低于0.5%,预测精度较高。 展开更多
关键词 锂离子电池 人工旅鼠算法 海星优化算法 变分模态分解 双向门控循环单元 transformer模型
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Improved Cuckoo Search Algorithm for Engineering Optimization Problems
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作者 Shao-Qiang Ye Azlan Mohd Zain Yusliza Yusoff 《Computers, Materials & Continua》 2026年第4期1607-1631,共25页
Engineering optimization problems are often characterized by high dimensionality,constraints,and complex,multimodal landscapes.Traditional deterministic methods frequently struggle under such conditions,prompting incr... Engineering optimization problems are often characterized by high dimensionality,constraints,and complex,multimodal landscapes.Traditional deterministic methods frequently struggle under such conditions,prompting increased interest in swarm intelligence algorithms.Among these,the Cuckoo Search(CS)algorithm stands out for its promising global search capabilities.However,it often suffers from premature convergence when tackling complex problems.To address this limitation,this paper proposes a Grouped Dynamic Adaptive CS(GDACS)algorithm.Theenhancements incorporated intoGDACS can be summarized into two key aspects.Firstly,a chaotic map is employed to generate initial solutions,leveraging the inherent randomness of chaotic sequences to ensure a more uniform distribution across the search space and enhance population diversity from the outset.Secondly,Cauchy and Levy strategies replace the standard CS population update.This strategy involves evaluating the fitness of candidate solutions to dynamically group the population based on performance.Different step-size adaptation strategies are then applied to distinct groups,enabling an adaptive search mechanism that balances exploration and exploitation.Experiments were conducted on six benchmark functions and four constrained engineering design problems,and the results indicate that the proposed GDACS achieves good search efficiency and produces more accurate optimization results compared with other state-of-the-art algorithms. 展开更多
关键词 Cuckoo search algorithm chaotic transformation population division adaptive update strategy Cauchy distribution
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基于BSLO优化分解与Transformer模型的滑坡位移多级置信预测方法
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作者 郑子凌 李勇 +3 位作者 王家秀 卢书强 陆昊 陈陆军 《中国地质灾害与防治学报》 2026年第1期75-87,共13页
针对阶跃型滑坡位移预测中变分模态分解(variational mode decomposition,VMD)参数选择依赖经验、传统模型长序列处理能力不足及缺乏不确定性量化等问题,文章提出基于吸水蛭算法(blood-sucking leech optimizer,BSLO)分解与Transformer... 针对阶跃型滑坡位移预测中变分模态分解(variational mode decomposition,VMD)参数选择依赖经验、传统模型长序列处理能力不足及缺乏不确定性量化等问题,文章提出基于吸水蛭算法(blood-sucking leech optimizer,BSLO)分解与Transformer模型的滑坡位移多级置信预测方法。该方法采用BSLO算法构建VMD参数自适应优化框架,基于信息熵最小化准则实现信号分解;设计Transformer模型用于时序预测,移除不适用组件并增加特征增强层;构建多级置信区间预测框架,实现多时间尺度不确定性量化。以三峡库区谭家河滑坡4个监测点为例进行验证,结果显示该方法在未来1,3,7,15 d预测中表现稳定,各时间尺度R2值均超0.95,均方根误差控制在5 mm以内,95%、90%、80%置信水平下压间覆盖率分别达到0.811~0.986、0.739~0.975、0.617~0.960,覆盖率接近理论期望。相比VMD-SSA-LSTM和CNN-BiLSTM-Attention模型,本文方法在各预测时间尺度下均表现出较好的稳定性和预测精度,为库区滑坡监测预警提供了一种技术方法。 展开更多
关键词 滑坡 位移预测 BSLO优化算法 变分模态分解 transformER 置信区间预测 K折交叉验证
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基于麻雀搜索算法优化Transformer的短文本情感分析方法
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作者 胡翔 《微处理机》 2026年第1期53-58,共6页
短文本情感分析面临诸多挑战,如语义稀疏、表达简洁、缺乏上下文信息等,导致情感特征提取不完整,进而影响分类精度。为解决这些问题,提出基于麻雀搜索算法(SSA)优化Transformer的短文本情感分析方法。该方法通过构建词向量矩阵,转变短... 短文本情感分析面临诸多挑战,如语义稀疏、表达简洁、缺乏上下文信息等,导致情感特征提取不完整,进而影响分类精度。为解决这些问题,提出基于麻雀搜索算法(SSA)优化Transformer的短文本情感分析方法。该方法通过构建词向量矩阵,转变短文本的表现形式;利用Transformer模型提取情感特征,并引入SSA优化模型超参数;将所提取情感特征输入全连接层+Softmax分类器中,采用交叉熵损失的梯度下降算法衡量文本预测情感与真实情感之间的差异,完成短文本情感分析。SSA具有全局搜索能力强、收敛速度快等优点,能有效优化Transformer模型的超参数,提升模型性能。试验结果表明,所提出方法的迭代损失值较低,分类精度较高,能够较好地捕捉情感特征且对各类情感区分能力强。 展开更多
关键词 麻雀搜索算法 transformer模型 短文本情感分析 情感特征
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基于鲸鱼优化算法-Transformer结构预测模型的医疗设备运行质量智能管理研究
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作者 周吉祥 麻耕嘉 +2 位作者 吴苏阳 林琛 陈伟杰 《中国医学装备》 2026年第2期109-114,共6页
目的:基于鲸鱼优化算法(WOA)-Transformer结构构建医疗设备运行质量预测模型,探究其在医疗设备运行质量智能管理中的应用价值。方法:采集龙泉市人民医院影像科医疗设备的运行状态、故障记录和性能参数数据,经过噪声过滤与标准化预处理,... 目的:基于鲸鱼优化算法(WOA)-Transformer结构构建医疗设备运行质量预测模型,探究其在医疗设备运行质量智能管理中的应用价值。方法:采集龙泉市人民医院影像科医疗设备的运行状态、故障记录和性能参数数据,经过噪声过滤与标准化预处理,构建基于WOA-Transformer结构的医疗设备运行质量预测模型,以预测设备运行风险,并对设备进行智能管理。选取2023年1月至2024年12月影像科在用的36台影像设备,2023年的设备运行期间采用常规管理方法进行管理,2024年的设备运行期间采用基于WOA-Transformer结构的医疗设备运行质量预测模型(模型管理方法)实施干预管理,比较两种管理方法的设备运行效果和管理质量。采用自制满意度问卷调查设备使用管理人员对设备维护管理的满意度评分。结果:采用模型管理方法的平均设备开机率和维护及时率分别为(96.69±3.58)%和(95.26±2.58)%,均高于常规管理方法,其差异有统计学意义(t=3.952、5.324,P<0.05),而平均故障率和平均管理费用增幅分别为(1.04±0.31)%和(1.76±0.43)%,均低于常规管理方法,差异均有统计学意义(t=11.952、13.138,P<0.05);设备平均使用规范度、维护有效率、维修及时性和质量检测合格率平均值均高于常规管理方法,差异有统计学意义(t=10.779、17.148、7.251、9.125,P<0.05)。设备使用管理人员对采用模型管理方法的设备可靠性、维护响应及时性和沟通协调性的满意度评分,均高于常规管理方法,差异均有统计学意义(t=3.608、4.316、3.854,P<0.05)。结论:基于WOA-Transformer结构构建的医疗设备运行质量预测模型应用于设备运行质量智能管理,能够显著提升设备运行效果和管理质量,提高设备使用管理人员对设备维护管理的满意度。 展开更多
关键词 鲸鱼优化算法(WOA) transformer模型 预测模型 医疗设备 智能管理
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基于动态滑动时间窗口与Transformer的电动汽车充电负荷预测
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作者 郝爽 祖国强 +2 位作者 贾明辉 张志杰 李少雄 《河北工业大学学报》 2026年第1期44-52,68,共10页
因电动汽车充电行为具有非线性、时变性,传统预测方法难以捕捉其负荷复杂特征,因此本文提出基于动态窗口与Transformer的电动汽车充电负荷预测方法。首先,引入结合萤火虫算法(firefly algorithm,FA)的变分模态分解(variational mode dec... 因电动汽车充电行为具有非线性、时变性,传统预测方法难以捕捉其负荷复杂特征,因此本文提出基于动态窗口与Transformer的电动汽车充电负荷预测方法。首先,引入结合萤火虫算法(firefly algorithm,FA)的变分模态分解(variational mode decomposition,VMD),利用FA算法优化VMD的超参数,提取不同频率模态分量,降低数据噪声与复杂度。其次,按各模态波动与变化率,用动态滑动时间窗口技术确定动态滑动时间大小。然后,根据动态滑动时间窗口调整长短期记忆网络(long short-term memory network,LSTM)-Transformer模型参数,将各模态分量与动态滑动时间窗口输入LSTM-Transformer模型,由LSTM负责捕捉短期动态,Transformer用于把握全局依赖,以此提升预测精度。最终,累加各分量预测值得出结果。经Palo Alto电动汽车负荷数据集验证,与固定时间窗口的VMD-LSTM-Transformer模型相比,所提方法的平均绝对百分比误差降低9.23%。 展开更多
关键词 电动汽车负荷预测 变分模态分解 萤火虫算法 动态滑动时间窗口 transformER
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融合蚁群算法和差分Transformer的农业机器人路径规划研究 被引量:2
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作者 李娟 张振荣 《中国农机化学报》 北大核心 2025年第7期164-172,共9页
针对农业机器人在复杂田间环境中路径规划精度不足、避障能力有限的问题,提出一种融合蚁群算法和差分Transformer的新型路径规划方法。采用蚁群算法进行初始全局路径搜索,利用其分布式并行搜索能力生成初始可行路径。针对传统蚁群算法... 针对农业机器人在复杂田间环境中路径规划精度不足、避障能力有限的问题,提出一种融合蚁群算法和差分Transformer的新型路径规划方法。采用蚁群算法进行初始全局路径搜索,利用其分布式并行搜索能力生成初始可行路径。针对传统蚁群算法中信息素更新方式容易陷入局部最优、对环境动态变化适应性差的缺陷,设计差分Transformer模型替代原有的信息素更新方法。差分Transformer通过自注意力机制,捕捉路径节点之间的长距离依赖关系和非线性特征,对信息素进行更精准地更新和分配,增强算法对复杂环境的适应能力。实验结果表明,所提出的方法在路径长度、规划时间和避障成功率等指标上均优于传统算法。具体而言,与蚁群算法相比,区域规模为50时,路径长度平均减少16.8%,从平均150 m降至125 m;规划时间缩短23.5%,从平均2.13 s降至1.63 s;避障成功率提高11.2%,达到96.5%。该研究为农业机器人自主导航提供有效的解决方案,具有重要的理论意义和应用价值。 展开更多
关键词 农业机器人 路径规划 蚁群算法 差分transformer 智慧农业
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Segmentation algorithm of complex ore images based on templates transformation and reconstruction 被引量:6
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作者 Guo-ying Zhang Guan-zhou Liu Hong Zhu 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2011年第4期385-389,共5页
Lots of noises and heterogeneous objects with various sizes coexist in a complex image,such as an ore image;the classical image thresholding method cannot effectively distinguish between ores.To segment ore objects wi... Lots of noises and heterogeneous objects with various sizes coexist in a complex image,such as an ore image;the classical image thresholding method cannot effectively distinguish between ores.To segment ore objects with various sizes simultaneously,two adaptive windows in the image were chosen for each pixel;the gray value of windows was calculated by Otsu's threshold method.To extract the object skeleton,the definition principle of distance transformation templates was proposed.The ores linked together in a binary image were separated by distance transformation and gray reconstruction.The seed region of each object was picked up from the local maximum gray region of the reconstruction image.Starting from these seed regions,the watershed method was used to segment ore object effectively.The proposed algorithm marks and segments most objects from complex images precisely. 展开更多
关键词 ORES image analysis image segmentation morphological transformation algorithms
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Anti-aliasing nonstationary signals detecion algorithm based on interpolation in the frequency domain using the short time Fourier transform 被引量:7
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作者 Bian Hailong Chen Guangju 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2008年第3期419-426,共8页
To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform (STFT) is brought forward. ... To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform (STFT) is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering. 展开更多
关键词 nonstationary signal INTERPOLATION ANTI-ALIASING short time Fourier transform (STFT) iterative algorithm.
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Spectral matching algorithm based on nonsubsampled contourlet transform and scale-invariant feature transform 被引量:4
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作者 Dong Liang Pu Yan +2 位作者 Ming Zhu Yizheng Fan Kui Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第3期453-459,共7页
A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low freq... A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix (or matching result) reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy. 展开更多
关键词 point pattern matching nonsubsampled contourlet transform scale-invariant feature transform spectral algorithm.
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Lane Recognition Algorithm Using the Hough Transform Based on Complicated Conditions 被引量:8
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作者 Zhicheng Zhang Xin Ma 《Journal of Computer and Communications》 2019年第11期65-75,共11页
At present, most lane line detection methods are aimed at simple road surface. There is still no good solution for the situation that the lane line contains arrow, text and other signs. The edge left by markers such a... At present, most lane line detection methods are aimed at simple road surface. There is still no good solution for the situation that the lane line contains arrow, text and other signs. The edge left by markers such as arrow and text will interfere with the detection of lane lines. In view of the situation of arrow mark and text mark interference between lane lines, the paper proposes a new processing algorithm. The algorithm consists of four parts, Gaussian blur, image graying processing, DLD-threshold (Dark-Light-Dark-threshold) algorithm, correlation filter edge extraction and Hough transform. Among them, the DLD-threshold algorithm and related filters are mainly used to remove the identification interference between lane lines. The test results on the Caltech Lanes dataset are given at the end of the article. The result of verification of this algorithm showed a max recognition rate of 97.2%. 展开更多
关键词 LANE Detection DLD-Threshold algorithm Correlation Filter Edge Extraction HOUGH transform
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RESEARCH OF PROBLEMS ON REALIZING DIRECT ALGORITHM OF WAVELET TRANSFORM 被引量:2
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作者 Tang BaopingZhong YoumingQin ShurenDepartment of Mechanical Engineering,Chongqing University,Chongqing 400044, China 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2003年第2期136-140,共5页
Direct algorithm of wavelet transform (WT) is the numerical algorithmobtained from the integral formula of WT by directly digitization. Some problems on realizing thealgorithm are studied. Some conclusions on the dire... Direct algorithm of wavelet transform (WT) is the numerical algorithmobtained from the integral formula of WT by directly digitization. Some problems on realizing thealgorithm are studied. Some conclusions on the direct algorithm of discrete wavelet transform (DWT),such as discrete convolution operation formula of wavelet coefficients and wavelet components,sampling principle and technology to wavelets, deciding method for scale range of wavelets, measuresto solve edge effect problem, etc, are obtained. The realization of direct algorithm of continuouswavelet transform (CWT) is also studied. The computing cost of direct algorithm and Mallat algorithmof DWT are still studied, and the computing formulae are obtained. These works are beneficial todeeply understand WT and Mallat algorithm. Examples in the end show that direct algorithm can alsobe applied widely. 展开更多
关键词 wavelet transform direct algorithm mallat algorithm
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基于Transformer的隧道变形预测模型及二衬支护时机
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作者 索晓庆 李世春 +3 位作者 周子寒 邓勇 周元辅 蒙伟 《公路交通科技》 北大核心 2025年第10期301-312,321,共13页
【目标】二衬支护时机的合理性直接关系到隧道结构的长期稳定与施工安全,为提升隧道变形预测的精度与计算效率,确定二次衬砌支护的最佳时机,研究并构建高效、稳定且具有较强适应性的隧道变形预测模型,为隧道施工安全提供技术支撑。【方... 【目标】二衬支护时机的合理性直接关系到隧道结构的长期稳定与施工安全,为提升隧道变形预测的精度与计算效率,确定二次衬砌支护的最佳时机,研究并构建高效、稳定且具有较强适应性的隧道变形预测模型,为隧道施工安全提供技术支撑。【方法】以Transformer算法为核心框架,在前馈神经网络结构中引入Adaptive Dropout层,根据神经元的重要性动态调整网络结构,有效抑制过拟合并提升模型的泛化能力,选取影响隧道变形的9个关键参数作为输入特征,包括强度应力比、埋深、隧道等效直径等,以保证预测过程对多维信息的综合利用,构建基于Transformer的隧道变形预测模型。根据极限位移准则,以围岩变形达到极限位移的90%所对应的时间作为二次衬砌的合理支护时机,实现对隧道二次衬砌支护时机的智能预测。【结果】基于某隧道工程案例的验证结果表明,Transformer预测模型结果的平均绝对误差较传统BP神经网络降低了6.5%,迭代次数减少了59.6%,模型拟合优度R2由0.72提升至0.99,准确地预测了隧道的二衬支护时机。【结论】该隧道变形预测模型在预测精度、计算效率及稳定性方面均优于传统方法。其快速收敛的特性与较强的适应性,使其能够有效应对不同地质条件与施工环境下的预测任务,从而为二次衬砌支护时机的科学决策提供可靠的数据支撑,在保障隧道施工安全和优化支护设计方案中具有应用价值。 展开更多
关键词 隧道工程 围岩变形预测 transformer算法 二衬支护时机 极限位移准则
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An Algorithm for Ship Wake Detection from the SAR Images Using the Radon Transform and Morphological Image Processing 被引量:2
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作者 金亚秋 王世庆 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2001年第4期7-12,共6页
Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gra... Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linear texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size. 展开更多
关键词 algorithmS Image processing Mathematical transformations Radar clutter Radar target recognition Spurious signal noise Synthetic aperture radar
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一种基于LWT-DCT-SVD抗压缩的图像水印方案
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作者 杨志疆 《肇庆学院学报》 2025年第2期69-74,共6页
针对图像水印的透明性和鲁棒性的矛盾问题,以及图像水印在图像压缩攻击中鲁棒性较差的问题,提出基于LWT-DCT-SVD混合域的抗压缩鲁棒性图像水印方案.该方案应用混沌序列和置乱变换加密水印,提高水印的安全性,并选取LWT-DCT变换的低频系... 针对图像水印的透明性和鲁棒性的矛盾问题,以及图像水印在图像压缩攻击中鲁棒性较差的问题,提出基于LWT-DCT-SVD混合域的抗压缩鲁棒性图像水印方案.该方案应用混沌序列和置乱变换加密水印,提高水印的安全性,并选取LWT-DCT变换的低频系数进行SVD变换,并在奇异值中采用自适应量化嵌入水印,实现盲检测.仿真实验结果表明,水印保持较好的透明性,同时在噪声污染、低通滤波、图像缩放、恶意剪切等常见图像处理具有较强的鲁棒性,尤其对于图像压缩攻击,本水印方案显示出较强的抗压缩特征. 展开更多
关键词 提升小波变换 离散余弦变换 奇异值分解 抗压缩 鲁棒性
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Power Quality Disturbance Classification Method Based on Wavelet Transform and SVM Multi-class Algorithms 被引量:1
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作者 Xiao Fei 《Energy and Power Engineering》 2013年第4期561-565,共5页
The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wav... The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wavelet transform coefficients and wavelet transform energy distribution constitute feature vectors. These vectors are then trained and tested using SVM multi-class algorithms. Experimental results demonstrate that the SVM multi-class algorithms, which use the Gaussian radial basis function, exponential radial basis function, and hyperbolic tangent function as basis functions, are suitable methods for power quality disturbance classification. 展开更多
关键词 Power Quality DISTURBANCE Classification WAVELET transform SVM MULTI-CLASS algorithmS
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Embedding and Extracting Digital Watermark Based on DCT Algorithm 被引量:1
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作者 Haiming Li Xiaoyun Guo 《Journal of Computer and Communications》 2018年第11期287-298,共12页
The principle of digital watermark is the method of adding digital watermark in the frequency domain. The digital watermark hides the watermark in digital media, such as image, voice, video, etc., so as to realize the... The principle of digital watermark is the method of adding digital watermark in the frequency domain. The digital watermark hides the watermark in digital media, such as image, voice, video, etc., so as to realize the functions of copyright protection, and identity recognition. DCT for Discrete Cosine Transform is used to transform the image pixel value and the frequency domain coefficient matrix to realize the embedding and extracting of the blind watermark in the paper. After success, the image is attacked by white noise and Gaussian low-pass filtering. The result shows that the watermark signal embedded based on the DCT algorithm is relatively robust, and can effectively resist some attack methods that use signal distortion to destroy the watermark, and has good robustness and imperceptibility. 展开更多
关键词 Digital WATERMARK dct algorithm White Noise GAUSSIAN LOW-PASS Filtering Robustness IMPERCEPTIBILITY
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