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Speed Regulation Method Using Genetic Algorithm for Dual Three-phase Permanent Magnet Synchronous Motors 认领 引用 被引量：6
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作者 Xiuhong Jiang Yuying Wang Jiarui Dong 《CES Transactions on Electrical Machines and Systems》 CSCD 2023年第2期171-178,共8页
Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the... Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the requirements of fast response,high accuracy and good robustness.In order to improve the performance of DTP-PMSM speed regulation system,a control strategy of PI controller based on genetic algorithm is proposed.Firstly,the basic mathematical model of DTP-PMSM is established,and the PI parameters of DTP-PMSM speed regulation system are optimized by genetic algorithm,and the modeling and simulation experiments of DTP-PMSM control system are carried out by MATLAB/SIMULINK.The simulation results show that,compared with the traditional PI control,the proposed algorithm significantly improves the performance of the control system,and the speed output overshoot of the GA-PI speed control system is smaller.The anti-interference ability is stronger,and the torque and double three-phase current output fluctuations are smaller. 展开更多
关键词 Dual three-phase permanent magnet synchronous motor Genetic algorithm PI control Speed regulation
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Research of Genetic Training Algorithm for Identifying Mechanical Failure Modes within the Framework of Case-Based Reasoning 认领 引用 被引量：1
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作者 徐元铭 张洋 陈丽娜 《Chinese Journal of Aeronautics》 EI CAS 2005年第2期122-129,共8页
The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such... The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such as matching attributes selection, similarity measure calculation, weights learning and training evaluation policies are carefully studied. The testing applications illustrate that an accuracy of 74.67 % can be achieved with 75 balanced-distributed failure cases covering 3 failure modes, and that the resulting learning weight vector can be well applied to the other 2 failure modes, achieving 73.3 % of recognition accuracy. It is also proved that its popularizing capability is good to the recognition of even more mixed failure modes. 展开更多
关键词 failure mode identification case-based reasoning genetic algorithm learning train
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A Simulated Annealing Algorithm for Training Empirical Potential Functions of Protein Folding 认领 引用 被引量：1
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作者 WANGYu-hong LIWei 《Chemical Research in Chinese Universities》 SCIE EI CAS 2005年第1期73-77,共5页
In this paper are reported the local minimum problem by means of current greedy algorithm for training the empirical potential function of protein folding on 8623 non-native structures of 31 globular proteins and a so... In this paper are reported the local minimum problem by means of current greedy algorithm for training the empirical potential function of protein folding on 8623 non-native structures of 31 globular proteins and a solution of the problem based upon the simulated annealing algorithm. This simulated annealing algorithm is indispensable for developing and testing highly refined empirical potential functions. 展开更多
关键词 Empirical potential function of protein folding Training Simulated annealing Greedy algorithm
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Impacts of random negative training datasets on machine learning-based geologic hazard susceptibility assessment 认领 引用 被引量：2
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作者 Hao Cheng Wei Hong +3 位作者 Zhen-kai Zhang Zeng-lin Hong Zi-yao Wang Yu-xuan Dong 《China Geology》 CAS CSCD 2025年第4期676-690,共15页
This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,... This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,China.Based on randomly generated 40 NTDs,the study developed models for the geologic hazard susceptibility assessment using the random forest algorithm and evaluated their performances using the area under the receiver operating characteristic curve(AUC).Specifically,the means and standard deviations of the AUC values from all models were then utilized to assess the overall spatial correlation between the conditioning factors and the susceptibility assessment,as well as the uncertainty introduced by the NTDs.A risk and return methodology was thus employed to quantify and mitigate the uncertainty,with log odds ratios used to characterize the susceptibility assessment levels.The risk and return values were calculated based on the standard deviations and means of the log odds ratios of various locations.After the mean log odds ratios were converted into probability values,the final susceptibility map was plotted,which accounts for the uncertainty induced by random NTDs.The results indicate that the AUC values of the models ranged from 0.810 to 0.963,with an average of 0.852 and a standard deviation of 0.035,indicating encouraging prediction effects and certain uncertainty.The risk and return analysis reveals that low-risk and high-return areas suggest lower standard deviations and higher means across multiple model-derived assessments.Overall,this study introduces a new framework for quantifying the uncertainty of multiple training and evaluation models,aimed at improving their robustness and reliability.Additionally,by identifying low-risk and high-return areas,resource allocation for geologic hazard prevention and control can be optimized,thus ensuring that limited resources are directed toward the most effective prevention and control measures. 展开更多
关键词 Landslides Debris flows Collapses Ground fissures Geologic hazard prevention and control engineering Geologic hazard susceptibility assessment Negative training dataset Average spatial correlation Random forest algorithm Risk and return analysis Geological survey engineering Loess Plateau area
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5G network planning in connecting urban areas for trains service using a genetic algorithm 认领 引用
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作者 Evangelos D.Spyrou Vassilios Kappatos 《High-Speed Railway》 CSCD 2025年第2期155-162,共8页
The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensur... The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensure passengers have a satisfactory experience throughout their journey.Installing base stations along urban environments can improve coverage but can dramatically reduce the experience of users due to interference.In particular,when a user with a mobile phone is a passenger in a high speed train traversing between urban centres,the coverage and the 5G resources in general need to be adequate not to diminish her experience of the service.The utilization of macro,pico,and femto cells may optimize the utilization of 5G resources.In this paper,a Genetic Algorithm(GA)-based approach to address the challenges of 5G network planning for 5G-R services is presented.The network is divided into three cell types,macro,pico,and femto cells—and the optimization process is designed to achieve a balance between key objectives:providing comprehensive coverage,minimizing interference,and maximizing energy efficiency.The study focuses on environments with high user density,such as high-speed trains,where reliable and high-quality connectivity is critical.Through simulations,the effectiveness of the GA-driven framework in optimizing coverage and performance in such scenarios is demonstrated.The algorithm is compared with the Particle Swarm Optimisation(PSO)and the Simulated Annealing(SA)methods and interesting insights emerged.The GA offers a strong balance between coverage and efficiency,achieving significantly higher coverage than PSO while maintaining competitive energy efficiency and interference levels.Its steady fitness improvement and adaptability make it well-suited for scenarios where wide coverage is a priority alongside acceptable performance trade-offs. 展开更多
关键词 High speed train 5G Network planning Genetic algorithm
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Driving manipulation analysis and control reconfiguration of heavy-haul trains 认领 引用
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作者 LI Zi-yi ZHOU Yan-li +2 位作者 YANG Hui YU Yong-sheng LI Guang-wei 《Journal of Central South University》 SCIE EI CAS CSCD 2026年第1期506-522,共17页
The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the ... The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains. 展开更多
关键词 heavy-haul trains driving manipulation K-means clustering algorithm hidden Markov model control reconfiguration
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Predictive direct power control of three-phase PWM rectifier based on TOGI grid voltage sensor free algorithm 认领 引用
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作者 ZHAO Feng LI Shute +4 位作者 CHEN Xiaoqiang WANG Ying GAN Yanqi NIU Xinqiang ZHANG Fan 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2022年第4期451-459,共9页
In predictive direct power control(PDPC)system of three-phase pulse width modulation(PWM)rectifier,grid voltage sensor makes the whole system more complex and costly.Therefore,third-order generalized integrator(TOGI)i... In predictive direct power control(PDPC)system of three-phase pulse width modulation(PWM)rectifier,grid voltage sensor makes the whole system more complex and costly.Therefore,third-order generalized integrator(TOGI)is used to generate orthogonal signals with the same frequency to estimate the grid voltage.In addition,in view of the deviation between actual and reference power in the three-phase PWM rectifier traditional PDPC strategy,a power correction link is designed to correct the power reference value.The grid voltage sensor free algorithm based on TOGI and the corrected PDPC strategy are applied to three-phase PWM rectifier and simulated on the simulation platform.Simulation results show that the proposed method can effectively eliminate the power tracking deviation and the grid voltage.The effectiveness of the proposed method is verified by comparing the simulation results. 展开更多
关键词 three-phase PWM rectifier predictive direct power control grid voltage sensor free algorithm third-order generalized integrator power correction
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A Second Order Training Algorithm for Multilayer Feedforward Neural Networks 认领 引用
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作者 谭营 何振亚 邓超 《Journal of Southeast University(English Edition)》 CAS 1997年第1期32-36,共5页
ASecondOrderTrainingAlgorithmforMultilayerFeedforwardNeuralNetworksTanYing（谭营）HeZhenya（何振亚）（DepartmentofRadioEngineering，Sou...
关键词 multilayer feedforward neural networks second order training algorithm BP algorithm learning factors XOR problem
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A multi-criteria fusion feature selection algorithm for fault diagnosis of helicopter planetary gear train 认领 引用 被引量：9
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作者 Canfei SUN Youren WANG Guodong SUN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2020年第5期1549-1561,共13页
Planetary gear train is a prominent component of helicopter transmission system and its health is of great significance for the flight safety of the helicopter.During health condition monitoring,the selection of a fau... Planetary gear train is a prominent component of helicopter transmission system and its health is of great significance for the flight safety of the helicopter.During health condition monitoring,the selection of a fault sensitive feature subset is meaningful for fault diagnosis of helicopter planetary gear train.According to actual situation,this paper proposed a multi-criteria fusion feature selection algorithm (MCFFSA) to identify an optimal feature subset from the highdimensional original feature space.In MCFFSA,a fault feature set of multiple domains,including time domain,frequency domain and wavelet domain,is first extracted from the raw vibration dataset.Four targeted criteria are then fused by multi-objective evolutionary algorithm based on decomposition (MOEA/D) to find Proto-efficient subsets,wherein two criteria for measuring diagnostic performance are assessed by sparse Bayesian extreme learning machine (SBELM).Further,Fmeasure is adopted to identify the optimal feature subset,which was employed for subsequent fault diagnosis.The effectiveness of MCFFSA is validated through six fault recognition datasets from a real helicopter transmission platform.The experimental results illustrate the superiority of combination of MOEA/D and SBELM in MCFFSA,and comparative analysis demonstrates that the optimal feature subset provided by MCFFSA can achieve a better diagnosis performance than other algorithms. 展开更多
关键词 Fault detection Feature selection F-measure Helicopter planetary gear train Multi-objective evolutionary algorithm
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Sound quality evaluation of high-speed train interior noise by adaptive Moore loudness algorithm 认领 引用 被引量：5
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作者 Le LUO Xu ZHENG +2 位作者 Zhi-yong HAO Wen-qiang DAI Wen-ying YANG 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2017年第9期690-703,共14页
An online experiment to acquire the interior noise of a China Railways High-speed(CRH)train showed that it wasmainly composed of middle-low frequency components and could not be described properly by linear or A-weigh... An online experiment to acquire the interior noise of a China Railways High-speed(CRH)train showed that it wasmainly composed of middle-low frequency components and could not be described properly by linear or A-weighted soundpressure level(SPL).Thus,the appropriate way to evaluate the high-speed train interior noise is to use sound quality parameters,and the most important is loudness.To overcome the disadvantages of the existing loudness algorithms,a novel signal-adaptiveMoore loudness algorithm(AMLA)based on the equivalent rectangular bandwidth(ERB)spectrum was introduced.The valida-tion reveals that AMLA can obtain higher accuracy and efficiency,and the simulated dark red noise conforms best to thehigh-speed train interior noise by loudness and auditory assessment.The main loudness component of the interior noise is below27.6 ERB rate(erbr),and the sound quality of the interior noise is relatively stable between 300-350 km/h.The specific loudnesscomponents among 12-15 erbr stay invariable throughout the acceleration or deceleration process while components among20-27 erbr are evidently speed related.The unusual random noise is effectively identified,which indicates that AMLA is anappropriate method for sound quality assessment of the high-speed train under both steady and transient conditions. 展开更多
关键词 High-speed train Sound quality evaluation Equivalent rectangular bandwidth(ERB)spectrum Adaptive Moore loudness algorithm(AMLA) Unusual random noise
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基于交叉熵的安全Tri-training算法 认领 引用 被引量：9
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作者 张永 陈蓉蓉 张晶 《计算机研究与发展》 EI CSCD 北大核心 2021年第1期60-69,共10页
半监督学习方法通过少量标记数据和大量未标记数据来提升学习性能.Tri-training是一种经典的基于分歧的半监督学习方法,但在学习过程中可能产生标记噪声问题.为了减少Tri-training中的标记噪声对未标记数据的预测偏差,学习到更好的半监... 半监督学习方法通过少量标记数据和大量未标记数据来提升学习性能.Tri-training是一种经典的基于分歧的半监督学习方法,但在学习过程中可能产生标记噪声问题.为了减少Tri-training中的标记噪声对未标记数据的预测偏差,学习到更好的半监督分类模型,用交叉熵代替错误率以更好地反映模型预估结果和真实分布之间的差距,并结合凸优化方法来达到降低标记噪声的目的,保证模型效果.在此基础上,分别提出了一种基于交叉熵的Tri-training算法、一个安全的Tri-training算法,以及一种基于交叉熵的安全Tri-training算法.在UCI(University of California Irvine)机器学习库等基准数据集上验证了所提方法的有效性,并利用显著性检验从统计学的角度进一步验证了方法的性能.实验结果表明,提出的半监督学习方法在分类性能方面优于传统的Tri-training算法,其中基于交叉熵的安全Tri-training算法拥有更高的分类性能和泛化能力. 展开更多
关键词 半监督学习 Tri-training算法 交叉熵 凸优化 样本标记
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基于Tri-Training半监督分类算法的研究 认领 引用 被引量：9
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作者 张雁 吕丹桔 吴保国 《计算机技术与发展》 2013年第7期77-79,83,共3页
在实际应用中,容易获取大量的未标记样本数据,而样本数据是有限的,因此,半监督分类算法成为研究者关注的热点。文中在协同训练Tri-Training算法的基础上,提出了采用两个不同的训练分类器的Simple-Tri-Training方法和对标记数据进行编辑... 在实际应用中,容易获取大量的未标记样本数据,而样本数据是有限的,因此,半监督分类算法成为研究者关注的热点。文中在协同训练Tri-Training算法的基础上,提出了采用两个不同的训练分类器的Simple-Tri-Training方法和对标记数据进行编辑的Edit-Tri-Training方法,给出了这三种分类方法与监督分类SVM的分类实验结果的比较和分析。实验表明,无标记数据的引入,在一定程度上提高了分类的性能;初始训练集和分类器的选取以及标记过程中数据编辑技术,都是影响半监督分类稳定性和性能的关键点。 展开更多
关键词 半监督分类 Tri—Training算法 数据编辑
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基于Tri-training的主动学习算法 认领 引用 被引量：3
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作者 张雁 吴保国 +1 位作者 吕丹桔 林英 《计算机工程》 CAS CSCD 2014年第6期215-218,229,共4页
半监督学习和主动学习都是利用未标记数据,在少量标记数据代价下同时提高监督学习识别性能的有效方法。为此,结合主动学习方法与半监督学习的Tri-training算法,提出一种新的分类算法,通过熵优先采样算法选择主动学习的样本。针对UCI数... 半监督学习和主动学习都是利用未标记数据,在少量标记数据代价下同时提高监督学习识别性能的有效方法。为此,结合主动学习方法与半监督学习的Tri-training算法,提出一种新的分类算法,通过熵优先采样算法选择主动学习的样本。针对UCI数据集和遥感数据,在不同标记训练样本比例下进行实验,结果表明,该算法在标记样本数较少的情况下能取得较好的效果。将主动学习与Tri-training算法相结合,是提高分类性能和泛化性的有效途径。 展开更多
关键词 半监督学习 主动学习 Tri—training算法 熵优先采样 Tri-EPS算法
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基于Tri-training-SSAE半监督学习算法的电力系统暂态稳定评估 认领 引用 被引量：10
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作者 卫志农 李超凡 +4 位作者 丁爱飞 孙国强 黄蔓云 臧海祥 方熙程 《电力自动化设备》 EI CSCD 北大核心 2023年第7期110-116,共7页
基于机器学习的暂态稳定评估方法主要采用监督学习方法,为了解决监督学习方法所需的有标签样本难以获取的问题,提出基于三体训练-稀疏堆叠自动编码器(Tri-training-SSAE)半监督学习算法的电力系统暂态稳定评估方法。构建基于堆叠稀疏自... 基于机器学习的暂态稳定评估方法主要采用监督学习方法,为了解决监督学习方法所需的有标签样本难以获取的问题,提出基于三体训练-稀疏堆叠自动编码器(Tri-training-SSAE)半监督学习算法的电力系统暂态稳定评估方法。构建基于堆叠稀疏自动编码器的暂态稳定评估模型;在传统的三体训练过程中加入伪标签样本置信度判断,以减小噪声数据对模型训练的影响;以堆叠稀疏自动编码器为基分类器构建三体训练-稀疏堆叠自动编码器模型,利用大量的无标签样本提高模型的泛化能力。通过IEEE 39节点系统与华东某省级电网进行分析验证,结果表明,所提方法在有标签样本数较少时具有更高的评估准确度。 展开更多
关键词 暂态稳定评估 机器学习 半监督学习 三体训练算法 堆叠稀疏自动编码器
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融合光谱度量标记迁移和Tri-training的高光谱遥感图像半监督分类算法 认领 引用 被引量：3
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作者 曹峰 李文涛 +4 位作者 骆剑承 李德玉 钱宇华 白鹤翔 张超 《大数据》 2023年第6期72-89,共18页
针对海量的高光谱遥感图像光谱和丰富的空间信息中可用于分类的有标记样本远少于无标记样本的数据特性,提出了一种融合光谱度量标记迁移和Tri-training的高光谱遥感图像半监督光谱-空间分类算法。该算法提出了一种基于光谱度量的标记迁... 针对海量的高光谱遥感图像光谱和丰富的空间信息中可用于分类的有标记样本远少于无标记样本的数据特性,提出了一种融合光谱度量标记迁移和Tri-training的高光谱遥感图像半监督光谱-空间分类算法。该算法提出了一种基于光谱度量的标记迁移方法,通过结合迁移标记和Tri-training预测标记进行扩充样本标记预测,提高了扩充样本标记的准确性。同时,该算法基于空间相关性选择扩充样本,综合运用光谱和空间特征提升图像分类的精度。在两个公开的高光谱遥感图像数据集上进行了实验,结果表明该算法优于基于Tri-training算法的高光谱遥感图像的分类性能。 展开更多
关键词 高光谱图像分类 半监督分类 纹理特征 光谱度量 Tri-training算法
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基于Tri-training算法的构造性学习方法 认领 引用 被引量：3
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作者 吴涛 李萍 王允强 《计算机工程》 CAS CSCD 2012年第6期13-15,共3页
构造性机器学习(CML)算法在训练分类器时需要大量有标记样本,而获取这些有标记样本十分困难。为此,提出一种基于Tri-training算法的构造性学习方法。根据已标记的样本,采用不同策略构造3个差异较大的初始覆盖分类网络,用于对未标记数据... 构造性机器学习(CML)算法在训练分类器时需要大量有标记样本,而获取这些有标记样本十分困难。为此,提出一种基于Tri-training算法的构造性学习方法。根据已标记的样本,采用不同策略构造3个差异较大的初始覆盖分类网络,用于对未标记数据进行标记,再将已标记数据加入到训练样本中,调整各分类网络参数,反复进行上述过程,直至获得稳定的分类器。实验结果证明,与CML算法和基于NB分类器的半监督学习算法相比,该方法的分类准确率更高。 展开更多
关键词 半监督学习 构造性机器学习 Tri-training算法 覆盖 分类网络
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一种自适应的Tri-Training半监督算法 认领 引用 被引量：1
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作者 彭雅琴 宫宁生 《计算机系统应用》 2016年第8期130-134,共5页
Tri-Training算法是半监督算法的一种,在学习过程中容易错误标注无标记样本,从而降低分类性能,为此提出一种ADP-Tri-Training(Adaptive Tri-Training)算法,改进协同工作方式,根据几何中心设置分类器组成,然后应用模糊数学理论将多个独... Tri-Training算法是半监督算法的一种,在学习过程中容易错误标注无标记样本,从而降低分类性能,为此提出一种ADP-Tri-Training(Adaptive Tri-Training)算法,改进协同工作方式,根据几何中心设置分类器组成,然后应用模糊数学理论将多个独立的分类器组合,使得算法可以在多因素下综合评价样本,并在此基础上引入遗传算法动态设置组合权重以适应于具体的样本集,从而尽可能降低样本标注的错误率,多个实验结果表明ADP-Tri-Training算法具有更好的分类性能. 展开更多
关键词 Tri-Training算法 自适应 遗传算法 差异性度量 半监督
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改进M-training算法的高光谱图像分类 认领 引用 被引量：2
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作者 崔颖 王雪婷 +1 位作者 陆忠军 王立国 《哈尔滨工程大学学报》 EI CAS CSCD 北大核心 2018年第10期1688-1694,共7页
为了解决高光谱数据有标签样本数量有限的分类问题,提出将M-training算法应用于高光谱图像分类。采用两个SVM、一个K近邻(KNN)以及一个随机森林(RF)进行分类器组合,对传统M-training算法进行改进,增强分类器的多样性和差异性。为了充分... 为了解决高光谱数据有标签样本数量有限的分类问题,提出将M-training算法应用于高光谱图像分类。采用两个SVM、一个K近邻(KNN)以及一个随机森林(RF)进行分类器组合,对传统M-training算法进行改进,增强分类器的多样性和差异性。为了充分考虑大量无标签样本的影响,采用有标签样本与无标签样本错误率加权作为有标签样本集更新的限制条件,从而有效地扩大了有标签样本集。实验结果表明:改进算法和传统的M-training算法相比较,在总体分类精度与Kappa系数上分别提高1. 85%～12. 10%与0. 021 5～0. 141 3,从而验证了该算法的有效性。 展开更多
关键词 高光谱图像 半监督分类 M-training算法 错误率加权 图像处理 SVM分类器 RF分类器 KNN分类器
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Optimization and Algorithm for Through Train Connections at District Stations 认领 引用
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作者 郭倩倩 陈宜军 毛介英 《Journal of Southwest Jiaotong University(English Edition)》 2010年第3期220-224,共5页
In the optimization of train diagrams, selecting the arrival and departure paths of the through gains has a great impact on the dwell time at district stations. In this paper, on the basis of train paths and the throu... In the optimization of train diagrams, selecting the arrival and departure paths of the through gains has a great impact on the dwell time at district stations. In this paper, on the basis of train paths and the through train connection time standard at district stations, we built a mathematical model aiming at minimizing dwell time of through trains at two adjacent district stations, and then converted this into a network flow model to which is added a source and a sink node. Then, we propose a new algorithm for solving the network flow model based on the minimum-cost flow algorithm. A case study for through trains from the Guiyang South Railway Station to the Chongqing West Railway Station shows that the algorithm is reliable and efficient for solving the problem of through train connections, and there is a reduction in the total dwell time that the through trains spend at two adjacent district stations. 展开更多
关键词 Train diagrams Through train connections Minimum-cost flow algorithm District stations
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Enhancing Urban Rail Transit Train Routes Planning Using Surrogate-Assisted Fish Migration Optimization 认领 引用
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作者 Zhigang Du Jengshyang Pan +2 位作者 Xiaoyang Wang Shuchuan Chu Shaoquan Ni 《Journal of Bionic Engineering》 SCIE EI CSCD 2025年第4期1702-1716,共15页
Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which c... Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which can be both costly and time-consuming.This is especially true for large-scale transportation networks,where the size of the problem and the high computational cost can hinder the algorithm’s performance.To address these challenges,recent research has focused on using surrogate-assisted models.These models aim to reduce the number of expensive evaluations and improve the efficiency of solving time-consuming optimization problems.This paper presents a new two-layer Surrogate-Assisted Fish Migration Optimization(SA-FMO)algorithm designed to tackle high-dimensional and computationally heavy problems.The global surrogate model offers a good approximation of the entire problem space,while the local surrogate model focuses on refining the solution near the current best option,improving local optimization.To test the effectiveness of the SA-FMO algorithm,we first conduct experiments using six benchmark functions in a 50-dimensional space.We then apply the algorithm to optimize urban rail transit routes,focusing on the Train Routing Optimization problem.This aims to improve operational efficiency and vehicle turnover in situations with uneven passenger flow during transit disruptions.The results show that SA-FMO can effectively improve optimization outcomes in complex transportation scenarios. 展开更多
关键词 Train routing optimization Surrogate-assisted Fish migration optimization Meta-heuristic evolutionary algorithm
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