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Lax pair and vector semi-rational nonautonomous rogue waves for a coupled time-dependent coefficient fourth-order nonlinear Schrodinger system in an inhomogeneous optical fiber
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作者 Zhong Du Bo Tian +1 位作者 Qi-Xing Qu Xue-Hui Zhao 《Chinese Physics B》 SCIE EI CAS CSCD 2020年第3期55-61,共7页
Optical fibers are seen in the optical sensing and optical fiber communication. Simultaneous propagation of optical pulses in an inhomogeneous optical fiber is described by a coupled time-dependent coefficient fourth-... Optical fibers are seen in the optical sensing and optical fiber communication. Simultaneous propagation of optical pulses in an inhomogeneous optical fiber is described by a coupled time-dependent coefficient fourth-order nonlinear Schr?dinger system, which is discussed in this paper. For such a system, we work out the Lax pair, Darboux transformation, and corresponding vector semi-rational nonautonomous rogue wave solutions. When the group velocity dispersion(GVD) and fourth-order dispersion(FOD) coefficients are the constants, we exhibit the first-and second-order vector semirational rogue waves which are composed of the four-petalled rogue waves and eye-shaped breathers. Both the width of the rogue wave along the time axis and temporal separation between the adjacent peaks of the breather decrease with the GVD coefficient or FOD coefficient. With the GVD and FOD coefficients as the linear, cosine, and exponential functions, we respectively present the first-and second-order periodic vector semi-rational rogue waves, first-and second-order asymmetry vector semi-rational rogue waves, and interactions between the eye-shaped breathers and the composite rogue waves. 展开更多
关键词 inhomogeneous optical fiber Lax pair coupled time-dependent coefficient fourth-order nonlinear Schrodinger system vector semi-rational nonautonomous rogue waves breathers
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Subband adaptive filter with variable reusing order of coefficient vectors
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作者 倪锦根 《Journal of Beijing Institute of Technology》 EI CAS 2015年第3期375-380,共6页
To increase the convergence rate of the improved normalized subband adaptive filter,a simple but effective method is presented to change the reusing order of coefficient vectors of the adaptive filter. At the beginnin... To increase the convergence rate of the improved normalized subband adaptive filter,a simple but effective method is presented to change the reusing order of coefficient vectors of the adaptive filter. At the beginning of adaptation the algorithmjust uses its current coefficient vector to update the adaptive filter to maintain fast convergence rate,while in steady state it employs several most recent coefficient vectors to update the adaptive filter to reduce misalignment. Simulation results showthat the proposed algorithmcan obtain both fast convergence rate and small steady-state misalignment. 展开更多
关键词 adaptive filtering subband adaptive filter reusing coefficient vector misalignment
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QSPR of n-Octanol/water Partition Coefficient (lgK_(ow)) for Alkyl(1-phenylsulfonyl) Cycloalkane-carboxylates 被引量:4
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作者 翟志才 柳红霞 +1 位作者 王遵尧 赵林飞 《Chinese Journal of Structural Chemistry》 SCIE CAS CSCD 2009年第2期143-150,共8页
Quantum chemistry parameters of 28 alkyl(1-phenylsulfonyl) cycloalkane-carboxy-lates were computed at the 6-31G* level in fully optimal manner using B3LYP method of density functional theory (DFT). With GQSARF2.0... Quantum chemistry parameters of 28 alkyl(1-phenylsulfonyl) cycloalkane-carboxy-lates were computed at the 6-31G* level in fully optimal manner using B3LYP method of density functional theory (DFT). With GQSARF2.0 program, the correlation equations that can predict n-octanol/water partition coefficient (lgKow) were developed using the structural and thermodynamic parameters of 28 alkyl(1-phenylsulfonyl) cycloalkane-carboxylates with experimental data of lgKow as theoretical descriptors; the correlation coefficient (R^2) was 0.9452 and the cross-validation squared correlation coefficient (Rcv^2) 0.9312. Furthermore, a four-variable model from MEDV was obtained, of which R2 = 0.9497 and Rov^2 =0.9388. The models were validated by variance inflation factor (VIF) and t-test. Cross-validation indicates that the correlation and predicting ability of the model based on both DFT method and MEDV are more advantageous than those obtained from semi-empirical AM1 method. 展开更多
关键词 quantitative structure-property relationship (QSPR) alkyl(1-phenylsulfonyl) cycloalkane-carboxylate density functional theory (DFT) n-octanol/water partition coefficient (lgKow) molecular electronegativity distance vector (MEDV)
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Forced Axial and Torsional Vibrations of a Shaft Line Using the Transfer Matrix Method Related to Solution Coefficients 被引量:2
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作者 Kandouci Chahr-Eddine Adjal Yassine 《Journal of Marine Science and Application》 2014年第2期200-205,共6页
This present paper deals with a mathematical description of linear axial and torsional vibrations. The normal and tangential stress tensor components produced by axial-torsional deformations and vibrations in the prop... This present paper deals with a mathematical description of linear axial and torsional vibrations. The normal and tangential stress tensor components produced by axial-torsional deformations and vibrations in the propeller and intermediate shafts, under the influence of propeller-induced static and variable hydrodynamic excitations are also studied. The transfer matrix method related to the constant coefficients of differential equation solutions is used. The advantage of the latter as compared with a well-known method of transfer matrix associated with state vector is the possibility of reducing the number of multiplied matrices when adjacent shaft segments have the same material properties and diameters. The results show that there is no risk of buckling and confirm that the strength of the shaft line depends on the value of the static tangential stresses which is the most important component of the stress tensor. 展开更多
关键词 shaft line stress tensor vibration axial vibration torsional vibration transfer matrix constant coefficient vector
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A hybrid original approach for prediction of the aerodynamic coefficients of an ATR-42 scaled wing model 被引量:1
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作者 Abdallah Ben Mosbah Ruxandra Mihaela Botez Thien My Dao 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2016年第1期41-52,共12页
A new approach for the prediction of lift,drag,and moment coefficients is presented.This approach is based on the support vector machines(SVMs)methodology and an optimization meta-heuristic algorithm called extended g... A new approach for the prediction of lift,drag,and moment coefficients is presented.This approach is based on the support vector machines(SVMs)methodology and an optimization meta-heuristic algorithm called extended great deluge(EGD).The novelty of this approach is the hybridization between the SVM and the EGD algorithm.The EGD is used to optimize the SVM parameters.The training and validation of this new identification approach is realized using the aerodynamic coefficients of an ATR-42 wing model.The aerodynamic coefficients data are obtained with the XFoil software and experimental tests using the Price-Paidoussis wind tunnel.The predicted results with our approach are compared with those from the XFoil software and experimental results for different flight cases of angles of attack and Mach numbers.The main pur-pose of this methodology is to rapidly Predict aircraft aerodynamic coefficients. 展开更多
关键词 Aerodynamic coefficients Estimation Extended great deluge METAHEURISTIC Model identification Optimization Support vector machines Wind tunnel tests
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Water inrush evaluation of coal seam floor by integrating the water inrush coefficient and the information of water abundance 被引量:3
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作者 Shi Longqing Qiu Mei +2 位作者 Wei Wenxue Xu Dongjing Han Jin 《International Journal of Mining Science and Technology》 SCIE EI 2014年第5期677-681,共5页
The method of singular coefficient of water inrush to achieve safety mining has limitation and one sidedness. Aiming at the problem above, large amounts of data about water inrush were collected. Then the data, includ... The method of singular coefficient of water inrush to achieve safety mining has limitation and one sidedness. Aiming at the problem above, large amounts of data about water inrush were collected. Then the data, including the maximum water inrush, water inrush coefficient and water abundance in aquifers of working face, were processed by the statistical analysis. The analysis results indicate that both water inrush coefficient and water abundance in aquifers should be taken into consideration when evaluating the danger of water inrush from coal seam floor. The prediction model of safe-mining evaluation grade was built by using the support vector machine, and the result shows that this model has high classification accuracy. A feasible classification system of water-inrush safety evaluation can be got by using the data visualization method which makes the implicit support vector machine models explicit. 展开更多
关键词 Floor water inrush Water inrush coefficient Water abundance Units-inflow Support vector machine
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The Calculation of the Effective Tensor Coefficient of the Medium for the Objects with Microinclusions
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作者 Ella P. Shurina Mikhail I. Epov +1 位作者 Nadejda V. Shtabel Ekaterina I. Mikhaylova 《Engineering(科研)》 2014年第3期101-112,共12页
In this paper, several approaches for calculation of the effective tensor coefficient for domains with inclusions have been proposed. The limits of the approaches using are found. The series of numerical experiments a... In this paper, several approaches for calculation of the effective tensor coefficient for domains with inclusions have been proposed. The limits of the approaches using are found. The series of numerical experiments are made on the different frequencies, for different inclusions location and boundary conditions for the contrast properties of the matrix and inclusion materials. 展开更多
关键词 Composite Materials EFFECTIVE TENSOR coefficient vector FINITE Element Method
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Derivation of Reliability Index Vector Formula for Series System and Its Application
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作者 康海贵 张晶 +1 位作者 孙英伟 郭伟 《China Ocean Engineering》 SCIE EI CSCD 2013年第2期159-168,共10页
In this study, a reliability index vector formula is proposed for series system with two failure modes in term of the concept of reliability index vector and equivalent failure modes. Firstly, the reliability index ve... In this study, a reliability index vector formula is proposed for series system with two failure modes in term of the concept of reliability index vector and equivalent failure modes. Firstly, the reliability index vector is introduced to determine the correlation coefficient between two failure modes, and then, the reliability index vector of a series system can be obtained. Several numerical cases and an analysis on offshore platform are performed, and the results show that this scheme provided here has better computational accuracy, and its calculation process is simpler for the series systems reliability calculations compared with the other methods. Also this scheme is more convenient for the engineering applications. 展开更多
关键词 reliability index vector series system equivalent failure mode correlation coefficient
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On the Massless Vector Fields in a Rindler Space
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作者 Roberto Soldati Caterina Specchia 《Journal of Modern Physics》 2015年第12期1743-1755,共13页
We study the quantum theory of the mass-less vector fields on the Rindler space. We evaluate the Bogoliubov coefficients by means of a new technique based upon the use of light-front coordinates and Mellin transform. ... We study the quantum theory of the mass-less vector fields on the Rindler space. We evaluate the Bogoliubov coefficients by means of a new technique based upon the use of light-front coordinates and Mellin transform. We briefly comment about the ensuing Unruh effect and its consequences. 展开更多
关键词 Rindler SPACE Unruh Effect vector FIELDS BOGOLIUBOV coefficientS
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Study on Flow Characteristics and Performance of Baffled Shock Two-Dimensional Vector Nozzle
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作者 Masum Hossain Yasir Kamal +1 位作者 Sourav Mallick Md Rifat Jahan Angkon 《Advances in Aerospace Science and Technology》 2024年第4期148-166,共19页
This research paper presents a numerical study on the flow characteristics and performance of a baffled shock two-dimensional vector nozzle. The baffled shock vector nozzle is a type of fluid thrust vectoring nozzle t... This research paper presents a numerical study on the flow characteristics and performance of a baffled shock two-dimensional vector nozzle. The baffled shock vector nozzle is a type of fluid thrust vectoring nozzle that uses a secondary injection to deflect the primary flow and generate a vector angle. The fluid thrust vectoring technology is regarded as a key technology for the development of very low detectable vehicles because of its advantages, such as fast response, lightweight, and good stealth performance. The main objectives of this study are to investigate the effects of various parameters such as slot interval distance, slot width, injection angle, nozzle pressure ratio, secondary flow pressure ratio, and outflow Mach number on the deflection angle, thrust coefficient, thrust efficiency, and secondary flow ratio of the nozzle. The numerical simulations are carried out using the k-epsilon turbulence model, which is validated by comparing it with experimental data. The results indicate that optimizing the slot interval distance and width, increasing the injection angle, adjusting the nozzle pressure ratio and secondary flow pressure ratio, and controlling the outflow Mach number can enhance the nozzle performance. The results also reveal the complex flow phenomena inside the nozzle, such as shock wave interactions, flow separation and reattachment, and boundary layer effects. The study provides a comprehensive understanding of the flow characteristics and performance of a baffled shock two-dimensional vector nozzle and offers some guidance for its design and optimization. 展开更多
关键词 Thrust vector Control Baffle Displacement The Opening of Discharge Gap The Thrust vector Angle Thrust coefficient
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基于机器学习的油藏动态分析研究
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作者 王小燕 谢文昊 +1 位作者 李娟妮 王亦鑫 《现代电子技术》 北大核心 2025年第14期117-122,共6页
针对油藏开发过程中,传统储量预测方法精度低、复杂度高,以及人工分析信息滞后导致不能及时发现潜力井等问题,提出一种智能化油藏动态分析方法,实现油藏开发问题的实时精确处理。在油田生产过程采集的20个参数中,利用皮尔逊相关系数最... 针对油藏开发过程中,传统储量预测方法精度低、复杂度高,以及人工分析信息滞后导致不能及时发现潜力井等问题,提出一种智能化油藏动态分析方法,实现油藏开发问题的实时精确处理。在油田生产过程采集的20个参数中,利用皮尔逊相关系数最终选用当前年产油量、含水、体积液量、累产油量、排量、冲次和泵效共7个参数表征油田生产能力。然后基于回归的支持向量机模型,利用不同核函数下的SVR模型对油田月产油量进行预测,最终选定超参数d=2、C=54的二阶多项式核函数下的SVR模型作为最优的油田月产量预测模型,该模型预测结果的平均绝对误差为-0.0061,均方误差为-0.1028。实验结果表明,智能化油藏动态分析方法在勘探数据分析的基础上,能够准确地动态预测油藏,优化勘探规划结构并提高油藏发现效率。 展开更多
关键词 智能油田 油藏动态分析 油田产量预测 支持向量机模型 核函数 皮尔逊相关系数
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基于语音信号时频特征融合的帕金森病检测方法 被引量:2
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作者 王晨哲 季薇 +1 位作者 郑慧芬 李云 《郑州大学学报(理学版)》 CAS 北大核心 2025年第1期53-60,共8页
发音障碍是帕金森病的早期症状之一。近年来,基于语音信号的帕金森病检测的研究大多采用梅尔刻度下的相关语音特征与深度神经网络模型相结合的方法。然而,现有的模型无法充分关注语音信号的全局时序信息,且梅尔刻度特征在准确表征帕金... 发音障碍是帕金森病的早期症状之一。近年来,基于语音信号的帕金森病检测的研究大多采用梅尔刻度下的相关语音特征与深度神经网络模型相结合的方法。然而,现有的模型无法充分关注语音信号的全局时序信息,且梅尔刻度特征在准确表征帕金森病的病理信息方面效果有限。为此,提出了一种基于语音时频特征融合的帕金森病检测方法。首先,提取语音的梅尔频率倒谱系数,并将其作为模型的输入。接着,在已有的S-vectors模型中引入Conformer编码器模块,以提取语音的时域全局特征。最后,将与帕金森病语音检测相关的频域全局特征嵌入时域特征中进行时频信息融合,以实现帕金森病语音检测。在公开帕金森病语音数据集和自采语音数据集上验证了方法的有效性。 展开更多
关键词 帕金森病 梅尔频率倒谱系数 S-vectors CONFORMER 时频特征融合
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基于MFCC和PSO-SVM的雨量识别方法 被引量:1
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作者 曾豫宁 行鸿彦 +2 位作者 侯天浩 王心怡 郑锦程 《电子测量与仪器学报》 北大核心 2025年第2期83-91,共9页
针对现有基于雨声信号及机器学习方法的雨量识别准确率较低等问题,通过分析雨声信号的频率特性,研究雨声信号的梅尔倒谱系数静态与动态特征,提出了一种梅尔倒谱系数(MFCC)与粒子群算法优化支持向量机(PSO-SVM)相结合的雨量识别方法。通... 针对现有基于雨声信号及机器学习方法的雨量识别准确率较低等问题,通过分析雨声信号的频率特性,研究雨声信号的梅尔倒谱系数静态与动态特征,提出了一种梅尔倒谱系数(MFCC)与粒子群算法优化支持向量机(PSO-SVM)相结合的雨量识别方法。通过提取雨声信号的MFCC静态与动态特征,利用随机森林算法内置的重要性评估机制进行特征选择,引入PSO算法对SVM的惩罚参数c以及核函数参数g进行微调,寻找最优参数组合,实现精准的雨量识别。实验结果表明,MFCC特征与其他特征相比能更有效的表征雨滴声纹信号特征,经过随机森林特征选择后的总体雨量识别准确率提高了5%,结合优化后的PSO-SVM进行雨量识别,其总体雨量识别准确率达到了91.1%,其中大雨、小雨的降雨识别准确率也均超过了90%,中雨的降雨识别准确率稍低,但也达到了86.5%。 展开更多
关键词 梅尔倒谱系数 粒子群优化算法 支持向量机 雨量识别
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半参数与支持向量机组合模型的BDS-3钟差预报 被引量:1
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作者 潘雄 黄伟凯 +2 位作者 王聪 赵万卓 金丽宏 《武汉大学学报(信息科学版)》 北大核心 2025年第4期617-627,共11页
针对卫星钟差序列中非线性特性较为复杂的问题,为了有效地分离周期项改正误差和顾及不能函数化的因素,提高钟差预报的精度,将钟差周期项模型扩充到半参数模型。利用核估计方法将窗宽参数与模型参数解算综合考虑,建立了半参数变系数模型... 针对卫星钟差序列中非线性特性较为复杂的问题,为了有效地分离周期项改正误差和顾及不能函数化的因素,提高钟差预报的精度,将钟差周期项模型扩充到半参数模型。利用核估计方法将窗宽参数与模型参数解算综合考虑,建立了半参数变系数模型,综合支持向量机进行卫星钟差数据的参数解算、周期项改正分离、异常值识别和残差拟合。首先,利用泰勒展开式对非参数分量进行修正,引入核估计方法,建立了半参数变系数模型;然后,构造分值检验统计量进行异常值识别,提出了一种综合分值检验统计量的钟差异常值识别方法;最后,为了避免对观测值过拟合或拟合不足,对经过预处理的残差利用支持向量机进行拟合,提高模型的预报精度。采用北斗三号全球卫星导航系统(BeiDou-3 global navigation satellite system,BDS-3)的钟差数据与常用方法进行了对比实验,验证了新模型的可靠性。实验结果表明,建立的模型能够精确高效地对BDS-3钟差异常值进行定位,识别并分离周期项改正,有效地提高BDS-3钟差数据预处理的质量和效率。建立的组合模型预报精度优于传统的二次多项式模型、周期项模型和半参数模型,对于1 h、6 h和12 h预报,新模型的钟差数据的预报平均精度优于0.164 ns。 展开更多
关键词 BDS钟差 异常值 半参数变系数模型 支持向量机 组合预报
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基于灰狼算法优化DBN-SVM的入侵检测方法 被引量:2
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作者 彭庆媛 王晓峰 +3 位作者 唐傲 王军霞 华盈盈 何飞 《南京大学学报(自然科学版)》 北大核心 2025年第2期270-282,共13页
入侵检测技术作为一种可靠的网络安全防御手段,在保障网络安全方面具有重要意义.深度信念网络(Deep Belief Network,DBN)结合支持向量机(Support Vector Machine,SVM)是一种具有良好泛化能力和分类性能的机器学习方法,在入侵检测领域有... 入侵检测技术作为一种可靠的网络安全防御手段,在保障网络安全方面具有重要意义.深度信念网络(Deep Belief Network,DBN)结合支持向量机(Support Vector Machine,SVM)是一种具有良好泛化能力和分类性能的机器学习方法,在入侵检测领域有着广泛的应用.然而,该方法在处理高维数据时容易出现“维数灾难”问题,并且参数选择对分类性能有很大影响,针对以上不足,提出了一种基于灰狼算法(Grey Wolf Optimization,GWO)优化DBN-SVM的入侵检测方法.在GWO算法中,通过引入自适应狩猎权重系数和改进头狼位置更新公式来加快收敛速度和扩展狼群搜索范围,通过加入最优灰狼个体自适应扰动策略来避免陷入局部最优.进一步利用改进后的GWO算法优化DBN-SVM,并应用于入侵检测.实验结果表明,提出的方法在NSL-KDD和UNSW-NB15数据集上的准确率比未改进的DBN-SVM分别提高6.5%和5.7%,满足入侵检测的应用需求. 展开更多
关键词 深度信念网络 支持向量机 灰狼优化算法 自适应狩猎权重系数 t分布扰动 入侵检测
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基于改进MFCC-OCSVM和贝叶斯优化BiGRU的GIS异常工况声纹识别算法 被引量:5
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作者 庄小亮 李乾坤 +3 位作者 刘紫罡 张禄亮 季天瑶 张长虹 《南方电网技术》 北大核心 2025年第1期30-40,共11页
为了准确识别气体绝缘开关柜(gas insulated switchgear,GIS)设备的异常工况,提出了一种基于加权梅尔频率谱系数单类支持向量机(Mel frequency cestrum coefficient-one class support vector machine,MFCC-OCSVM)和贝叶斯优化的门控循... 为了准确识别气体绝缘开关柜(gas insulated switchgear,GIS)设备的异常工况,提出了一种基于加权梅尔频率谱系数单类支持向量机(Mel frequency cestrum coefficient-one class support vector machine,MFCC-OCSVM)和贝叶斯优化的门控循环单元(bidirectional gate recurrent unit,BiGRU)声纹识别算法。首先,利用基于F统计量的MFCC对声纹数据进行加权特征提取,突出重要特征并减弱噪声的影响,然后利用OCSVM对加权后的特征进行异常检测并去除异常值,提高数据质量。为解决样本不平衡问题,采用合成少数类过采样技术(synthetic minority over-sampling technique,SMOTE)进行声纹样本的均衡。最后,应用基于贝叶斯优化的BiGRU模型进行声纹识别。以某气体绝缘全封闭组合电器(gas insulated switchgear,GIS)为例,采集了20类不同工况下操纵机构的声音样本,与多种经典分类模型进行对比。结果显示,所提算法取得的最高平均识别准确率达到了92.8%,相比于自适应增强、朴素贝叶斯和线性判别分析算法分别提升了30.1%、14.7%和11.5%。通过消融实验进一步评估和验证了所提算法各个流程对声纹识别的实际效果和性能影响,研究成果可为GIS设备异常工况的声纹识别提供高效技术路线。 展开更多
关键词 GIS设备 梅尔频谱倒谱系数 单类支持向量机 双向门控循环单元 声纹识别 贝叶斯优化
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基于可解释优化SVR算法AZ31镁合金轧板的力学性能预测
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作者 刘筱 林煜昕 +4 位作者 朱必武 刘文辉 郭鹏程 徐从昌 李落星 《中国有色金属学报》 北大核心 2025年第9期2925-2937,共13页
本文将鲸鱼优化算法引入SVR算法中,建立镁合金轧制温度、下压量、轧制线速度、轧后厚度和轧辊半径与抗拉强度和伸长率的联系。采用Person图分析了AZ31镁合金轧板轧制工艺参数与力学性能的相关性;采用SHAP解释模型结合轧制机理分析,确定... 本文将鲸鱼优化算法引入SVR算法中,建立镁合金轧制温度、下压量、轧制线速度、轧后厚度和轧辊半径与抗拉强度和伸长率的联系。采用Person图分析了AZ31镁合金轧板轧制工艺参数与力学性能的相关性;采用SHAP解释模型结合轧制机理分析,确定了影响力学性能的主要轧制工艺参数。结果表明:轧制线速度、轧辊半径和轧后厚度相较于平均应变速率与镁合金抗拉强度和伸长率线性相关性更强;优化后的SVR模型预测抗拉强度的相关系数从0.7提升到0.86,平均绝对误差从7.4降低到5.2,平均相对误差从0.16%降低为0.11%,均方误差从8.9降低到6.2;伸长率的相关系数从0.59提升到0.85,平均绝对误差从2.3降低到1.4,平均相对误差从0.56%降低为0.39%,均方误差从3降低到1.8。由SHAP解释模型结果分析可知,抗拉强度主要受到下压量的影响,其次是轧后厚度和轧辊半径;伸长率主要受到轧制线速度的影响,其次是温度和轧辊半径。 展开更多
关键词 鲸鱼优化算法 支持向量回归 AZ31镁合金 轧制工艺 Pearson相关系数
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煤矿地表移动下沉系数预测方法研究 被引量:1
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作者 侯晓松 王凡华 +4 位作者 尚亚博 马敬龙 刘荣彬 栾亨宣 栾元重 《煤炭技术》 2025年第7期1-5,共5页
为了实现地表变形的精确预测,以山东省某矿区为研究区域,根据地表移动监测数据,使用BP神经网络模型、支持向量机回归模型和熵值法3种模型研究了下沉系数优化方法。通过选取25个实际工作面地质采矿信息及下沉系数训练样本,构建了下沉系... 为了实现地表变形的精确预测,以山东省某矿区为研究区域,根据地表移动监测数据,使用BP神经网络模型、支持向量机回归模型和熵值法3种模型研究了下沉系数优化方法。通过选取25个实际工作面地质采矿信息及下沉系数训练样本,构建了下沉系数优化模型,分别对5个测试样本进行计算,分析发现使用熵值权系数组合模型优化下沉系数的精度最高。优化后的采深分别为-550、-750、-950 m的3个工作面煤层开采地表下沉系数,其地表移动与变形概率积分法预测值与实测值相对误差均小于8%。研究成果为地表变形的准确预测提供了新的技术方法。 展开更多
关键词 地表移动与变形 下沉系数 概率积分法预测 BP神经网络模型 支持向量机回归模型 熵值法
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基于特征融合与贝叶斯算法优化SVM的墙面空鼓检测
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作者 周尹辉 丁勇 +2 位作者 吴玉龙 李登华 葛大龙 《中国安全科学学报》 北大核心 2025年第11期131-138,共8页
为高精度识别墙面空鼓声信号,提高多类别墙体空鼓检测准确率,提出一种基于贝叶斯算法优化-支持向量机(BO-SVM)的多特征融合空鼓检测方法。首先,对采集的不同墙体敲击声音信号进行预加重、分帧、加窗等预处理,并分别提取梅尔倒谱系数特征... 为高精度识别墙面空鼓声信号,提高多类别墙体空鼓检测准确率,提出一种基于贝叶斯算法优化-支持向量机(BO-SVM)的多特征融合空鼓检测方法。首先,对采集的不同墙体敲击声音信号进行预加重、分帧、加窗等预处理,并分别提取梅尔倒谱系数特征(MFCC)和梅尔频谱系数特征(MSC);其次,将2种声学特征进行帧级串联融合,并归一化处理融合特征,形成融合特征数据集;然后,构建BO-SVM分类模型,并利用五折交叉验证方法优化核函数惩罚系数和参数,建立MFCC+MSC-BO-SVM模型;最后,以水泥墙、涂料墙、大理石墙和瓷砖墙等多类墙体的空鼓和非空鼓样本为对象开展分类试验。结果表明:融合特征在分类准确率、召回率和F_(1)值等指标上均优于单一特征;MFCC+MSC-BO-SVM模型整体识别准确率为96.36%,相较于标准SVM、随机森林、K近邻算法、网格搜索优化SVM模型和混沌粒子群优化SVM模型,准确率分别提高6.61%、9.58%、15.27%、13.90%和5.02%;BO法能够在较少迭代次数内获得最优参数组合,并表现出较好的模型收敛性与分类稳定性。 展开更多
关键词 特征融合 贝叶斯优化(BO) 支持向量机(SVM) 墙面空鼓检测 梅尔倒谱系数特征(MFCC) 梅尔频谱系数特征(MSC)
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基于MWPE和DBO-SVM的齿轮故障诊断
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作者 飞能 钱晶 +4 位作者 李佳 张淦源 杨卫斌 曾云 李想 《振动.测试与诊断》 北大核心 2025年第6期1090-1097,1270,共9页
针对齿轮故障领域识别率低和识别时间长的问题,基于多尺度加权排列熵(multiscale weighted permutation entropy,简称MWPE)、蜣螂算法(dung beetle optimizer,简称DBO)与支持向量机(support vector machine,简称SVM)的原理,提出基于MWPE... 针对齿轮故障领域识别率低和识别时间长的问题,基于多尺度加权排列熵(multiscale weighted permutation entropy,简称MWPE)、蜣螂算法(dung beetle optimizer,简称DBO)与支持向量机(support vector machine,简称SVM)的原理,提出基于MWPE和DBO结合SVM的故障识别方法。首先,由于MWPE的嵌入维数难以确定且对结果影响较大,通过MWPE熵值分析引入变异系数(coefficient of variation,简称CV)来确定嵌入维数;其次,构建故障特征集;最后,利用DBO与SVM结合的分类器DBO-SVM进行故障识别。结果表明:MWPE与多尺度排列熵(multiscale permutation entropy,简称MPE)、多尺度熵(multiscale entropy,简称MSE)、多尺度模糊熵(multiscale fuzzy entropy,简称MFE)等算法相比,对齿轮故障信息的提取效果较好;DBO-SVM分类器在识别准确率和效率上均优于常规优化分类器,所提方法在齿轮特征测试集上达到99.13%的识别准确率,在噪声状态下达到94.10%的识别准确率,证明MWPE的噪声鲁棒性较好。 展开更多
关键词 齿轮故障诊断 多尺度加权排列熵 蜣螂算法 支持向量机 变异系数 噪声鲁棒性
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