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Multi-sources information fusion algorithm in airborne detection systems 认领 引用 被引量：18
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作者 Yang Yan Jing Zhanrong Gao Tan Wang Huilong 《Journal of Systems Engineering and Electronics》 SCIE EI 2007年第1期171-176,共6页
To aim at the multimode character of the data from the airplane detecting system, the paper combines Dempster- Shafer evidence theory and subjective Bayesian algorithm and makes to propose a mixed structure multimode ... To aim at the multimode character of the data from the airplane detecting system, the paper combines Dempster- Shafer evidence theory and subjective Bayesian algorithm and makes to propose a mixed structure multimode data fusion algorithm. The algorithm adopts a prorated algorithm relate to the incertitude evaluation to convert the probability evaluation into the precognition probability in an identity frame, and ensures the adaptability of different data from different source to the mixed system. To guarantee real time fusion, a combination of time domain fusion and space domain fusion is established, this not only assure the fusion of data chain in different time of the same sensor, but also the data fusion from different sensors distributed in different platforms and the data fusion among different modes. The feasibility and practicability are approved through computer simulation. 展开更多
关键词 Information fusion Dempster-Shafer evidence theory Subjective Bayesian algorithm Airplane detecting system
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Enhancing train position perception through Al-driven multi-source information fusion 认领 引用 被引量：4
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作者 Haifeng Song Zheyu Sun +3 位作者 Hongwei Wang Tianwei Qu Zixuan Zhang Hairong Dong 《Control Theory and Technology》 EI CSCD 2023年第3期425-436,共12页
This paper addresses the challenge of accurately and timely determining the position of a train,with specific consideration given to the integration of the global navigation satellite system(GNSS)and inertial navigati... This paper addresses the challenge of accurately and timely determining the position of a train,with specific consideration given to the integration of the global navigation satellite system(GNSS)and inertial navigation system(INS).To overcome the increasing errors in the INS during interruptions in GNSS signals,as well as the uncertainty associated with process and measurement noise,a deep learning-based method for train positioning is proposed.This method combines convolutional neural networks(CNN),long short-term memory(LSTM),and the invariant extended Kalman filter(IEKF)to enhance the perception of train positions.It effectively handles GNSS signal interruptions and mitigates the impact of noise.Experimental evaluation and comparisons with existing approaches are provided to illustrate the effectiveness and robustness of the proposed method. 展开更多
关键词 Train positioning Deep learning Multi-source information fusion Dynamic adaptive model
Belief exponential divergence for D-S evidence theory and its application in multi-source information fusion 认领 引用 被引量：5
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作者 DUAN Xiaobo FAN Qiucen +1 位作者 BI Wenhao ZHANG An 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第6期1454-1468,共15页
Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this iss... Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences. 展开更多
关键词 Dempster-Shafer(D-S)evidence theory multi-source information fusion conflict measurement belief expo-nential divergence(BED) target recognition
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A multi-source information fusion method for tool life prediction based on CNN-SVM 认领 引用 被引量：1
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作者 Shuo WANG Zhenliang YU +1 位作者 Peng LIU Man Tong WANG 《Mechanical Engineering Science》 2022年第2期1-10,I0003,I0004,共10页
For milling tool life prediction and health management,accurate extraction and dimensionality reduction of its tool wear features are the key to reduce prediction errors.In this paper,we adopt multi-source information... For milling tool life prediction and health management,accurate extraction and dimensionality reduction of its tool wear features are the key to reduce prediction errors.In this paper,we adopt multi-source information fusion technology to extract and fuse the features of cutting vibration signal,cutting force signal and acoustic emission signal in time domain,frequency domain and time-frequency domain,and downscale the sample features by Pearson correlation coefficient to construct a sample data set;then we propose a tool life prediction model based on CNN-SVM optimized by genetic algorithm(GA),which uses CNN convolutional neural network as the feature learner and SVM support vector machine as the trainer for regression prediction.The results show that the improved model in this paper can effectively predict the tool life with better generalization ability,faster network fitting,and 99.85%prediction accuracy.And compared with the BP model,CNN model,SVM model and CNN-SVM model,the performance of the coefficient of determination R2 metric improved by 4.88%,2.96%,2.53%and 1.34%,respectively. 展开更多
关键词 CNN-SVM tool wear life prediction multi-source information fusion
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Fault location of distribution networks based on multi-source information 认领 引用 被引量：8
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作者 Wenbo Li Jianjun Su +2 位作者 Xin Wang Jiamei Li Qian Ai 《Global Energy Interconnection》 EI 2020年第1期77-85,共9页
In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for th... In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for the distribution network only considers the information reported by the Feeder Terminal Unit(FTU)and the fault tolerance rate is low when the information is omitted or misreported.Therefore,this study considers the influence of the distributed generations(DGs)for the distribution network.This takes the CEIAS as a redundant information source and solves the model by applying a binary particle swarm optimization algorithm(BPSO).The improved Dempster/S-hafer evidence theory(D-S evidence theory)is used for evidence fusion to achieve the fault section location for the distribution network.An example is provided to verify that the proposed method can achieve single or multiple fault locations with a higher fault tolerance. 展开更多
关键词 Internet of Things Multi-source information D-S evidence theory Binary particle swarm optimization algorithm Fault tolerance
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Neural Network Based Algorithm and Simulation of Information Fusion in the Coal Mine 认领 引用 被引量：4
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作者 ZHANG Xiao-qiang WANG Hui-bing YU Hong-zhen 《Journal of China University of Mining and Technology》 2007年第4期595-598,共4页
The concepts of information fusion and the basic principles of neural networks are introduced. Neural net-works were introduced as a way of building an information fusion model in a coal mine monitoring system. This a... The concepts of information fusion and the basic principles of neural networks are introduced. Neural net-works were introduced as a way of building an information fusion model in a coal mine monitoring system. This assures the accurate transmission of the multi-sensor information that comes from the coal mine monitoring systems. The in-formation fusion mode was analyzed. An algorithm was designed based on this analysis and some simulation results were given. Finally,conclusions that could provide auxiliary decision making information to the coal mine dispatching officers were presented. 展开更多
关键词 neural network information fusion algorithm and simulation sensors
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Structural damage detection method based on information fusion technique 认领 引用 被引量：2
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作者 刘涛 李爱群 +1 位作者 丁幼亮 费庆国 《Journal of Southeast University(English Edition)》 EI CAS 2008年第2期201-205,共5页
Multi-source information fusion （MSIF） is imported into structural damage diagnosis methods to improve the validity of damage detection. After the introduction of the basic theory, the function model, classification... Multi-source information fusion （MSIF） is imported into structural damage diagnosis methods to improve the validity of damage detection. After the introduction of the basic theory, the function model, classifications and mathematical methods of MSIF, a structural damage detection method based on MSIF is presented, which is to fuse two or more damage character vectors from different structural damage diagnosis methods on the character-level. In an experiment of concrete plates, modal information is measured and analyzed. The structural damage detection method based on MSIF is taken to localize cracks of concrete plates and it is proved to be effective. Results of damage detection by the method based on MSIF are compared with those from the modal strain energy method and the flexibility method. Damage, which can hardly be detected by using the single damage identification method, can be diagnosed by the damage detection method based on the character-level MSIF technique. Meanwhile multi-location damage can be identified by the method based on MSIF. This method is sensitive to structural damage and different mathematical methods for MSIF have different preconditions and applicabilities for diversified structures. How to choose mathematical methods for MSIF should be discussed in detail in health monitoring systems of actual structures. 展开更多
关键词 multi-source information fusion structural damage detection Bayes method D-S evidence theory
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Study on gas monitoring technology based on information fusion 认领 引用 被引量：4
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作者 HOU You-fu MENG Qing-rui +1 位作者 TONG Min-ming LIANG Tao 《Journal of Coal Science & Engineering(China)》 2010年第1期57-63,共7页
In view of the deficiency of current gas monitoring systems in coal mine roadwayexcavation, a two-level information fusion technology, which adopted the adaptiveweighted algorithm and the BP neural network technology,... In view of the deficiency of current gas monitoring systems in coal mine roadwayexcavation, a two-level information fusion technology, which adopted the adaptiveweighted algorithm and the BP neural network technology, was applied to gas monitoring.The results show that the adaptive weighted algorithm can realize self-regulation by decreasingthe weight value of the failed sensor automatically, so as to eliminate the effect ofthe failed sensor and ensure the effectiveness and accuracy of the gas monitoring system.The BP neural network can not only effectively predict the gas gush quantity of the excavationroadway, but also accurately calculate the gas concentration in the region whereone or more sensors have failed, so as to provide the basis for judging the safety status ofthe roadway excavation.The experiments prove the superiority and feasibility of the applicationof information fusion in gas monitoring. 展开更多
关键词 information fusion gas monitoring adaptive weighted algorithm BP neura network
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Applications of state estimation in multi-sensor information fusion for the monitoring of open pit mine slope deformation 认领 引用 被引量：1
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作者 付华 刘银平 肖健 《Journal of Coal Science & Engineering(China)》 2008年第2期317-320,共4页
The traditional open pit mine slope deformation monitoring system can not use the monitoring information coming from many monitoring points at the same time, can only using the monitoring data coming from a key monito... The traditional open pit mine slope deformation monitoring system can not use the monitoring information coming from many monitoring points at the same time, can only using the monitoring data coming from a key monitoring point,and that is to say it can only handle one-dimensional time series.Given this shortage in the monitoring, the multi-sensor information fusion in the state estimation techniques would be intro- duced to the slope deformation monitoring system,and by the dynamic characteristics of deformation slope,the open pit slope would be regarded as a dynamic goal,the condi- tion monitoring of which would be regarded as a dynamic target tracking.Distributed In- formation fusion technology with feedback was used to process the monitoring data and on this basis Klman filtering algorithms was introduced,and the simulation examples was used to prove its effectivenes. 展开更多
关键词 multi-sensor information fusion the side slope distortion the state estimation Klman filter algorithm
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基于FDBO+Informer-ECANet的齿轮箱故障诊断分析 认领 引用
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作者 李婷婷 贾东 《机械传动》 北大核心 2026年第3期161-171,共11页
【目的】基于智能优化算法与深度神经网络的齿轮箱故障诊断方法逐渐成为研究热点,但仍然存在较多问题。为了解决强噪声环境下齿轮故障特征提取难、诊断准确率低的问题,提出一种基于融合增强型蜣螂优化(Fusion-enhanced Dung Beetle Opti... 【目的】基于智能优化算法与深度神经网络的齿轮箱故障诊断方法逐渐成为研究热点,但仍然存在较多问题。为了解决强噪声环境下齿轮故障特征提取难、诊断准确率低的问题,提出一种基于融合增强型蜣螂优化(Fusion-enhanced Dung Beetle Optimization,FDBO)算法、Informer模型和通道注意力机制(Efficient Channel Attention Network,ECANet)模块的齿轮箱故障诊断方法。【方法】首先,针对现有蜣螂优化(Dung Beetle Optimization,DBO)算法全局搜索能力不足、易陷入局部最优等问题,引入融合Fuch混沌映射兼逆反向学习策略、自适应步长策略与凸透镜成像反转策略集成、随机差异变异策略,提高算法的全局搜索能力;其次,基于Informer模型出色的长时间序列处理能力,高效提取出序列数据中的全局特征与局部特征;尤其针对包含长时间依赖关系的故障信号,该模型可展现出极高的分类性能;再次,在Informer模型的编辑器中引入ECANet模块,对Informer提取的特征进行通道级的自适应校准,提高模型对重要特征的关注度,以增强特征表达能力、减少噪声干扰;最后,通过FDBO算法对Informer-ECANet模型多个超参数进行寻优,确定最优参数组合,以增强模型的诊断能力和泛化性能。【结果】试验结果表明,在无噪声条件下,所提模型准确率达100%;在加入-6 dB的高斯白噪声下准确率仍达到94.4%,验证了所提模型的优越性,为齿轮箱故障诊断提供了一种新型有效的智能方法。 展开更多
关键词 融合增强型蜣螂优化算法 Informer模型 ECANet模块 随机差异变异策略
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Information fusion diagnosis and early-warning method for monitoring the long-term service safety of high dams 认领 引用 被引量：4
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作者 Xing LIU Zhong-ru WU +2 位作者 Yang YANG Jiang HU Bo XU 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2012年第9期687-699,共13页
Analyzing the service behavior of high dams and establishing early-warning systems for them have become increasingly important in ensuring their long-term service.Current analysis methods used to obtain safety monitor... Analyzing the service behavior of high dams and establishing early-warning systems for them have become increasingly important in ensuring their long-term service.Current analysis methods used to obtain safety monitoring data are suited only to single survey point data.Unreliable or even paradoxical results are inevitably obtained when processing large amounts of monitoring data,thereby causing difficulty in acquiring precise conclusions.Therefore,we have developed a new method based on multi-source information fusion for conducting a comprehensive analysis of prototype monitoring data of high dams.In addition,we propose the use of decision information entropy analysis for building a diagnosis and early-warning system for the long-term service of high dams.Data metrics reduction is achieved using information fusion at the data level.A Bayesian information fusion is then conducted at the decision level to obtain a comprehensive diagnosis.Early-warning outcomes can be released after sorting analysis results from multi-positions in the dam according to importance.A case study indicates that the new method can effectively handle large amounts of monitoring data from numerous survey points.It can likewise obtain precise real-time results and export comprehensive early-warning outcomes from multi-positions of high dams. 展开更多
关键词 Dam monitoring Diagnosis Early-warning Multi-source information fusion Information entropy
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Detecting P2P Botnet by Analyzing Macroscopic Characteristics with Fractal and Information Fusion 认领 引用
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作者 SONG Yuanzhang 《China Communications》 SCIE CSCD 2015年第2期107-117,共11页
Towards the problems of existing detection methods,a novel real-time detection method(DMFIF) based on fractal and information fusion is proposed.It focuses on the intrinsic macroscopic characteristics of network,which... Towards the problems of existing detection methods,a novel real-time detection method(DMFIF) based on fractal and information fusion is proposed.It focuses on the intrinsic macroscopic characteristics of network,which reflect not the "unique" abnormalities of P2P botnets but the "common" abnormalities of them.It regards network traffic as the signal,and synthetically considers the macroscopic characteristics of network under different time scales with the fractal theory,including the self-similarity and the local singularity,which don't vary with the topology structures,the protocols and the attack types of P2P botnet.At first detect traffic abnormalities of the above characteristics with the nonparametric CUSUM algorithm,and achieve the final result by fusing the above detection results with the Dempster-Shafer evidence theory.Moreover,the side effect on detecting P2P botnet which web applications generated is considered.The experiments show that DMFIF can detect P2P botnet with a higher degree of precision. 展开更多
关键词 P2P botnet fractal information fusion CUSUM algorithm
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An information-volume-based distance measure for decision-making 认领 引用 被引量：2
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作者 Zhanhao ZHANG Fuyuan XIAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2023年第5期392-405,共14页
D-S evidence theory,as a general framework for reasoning with uncertainty,allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure.Ho... D-S evidence theory,as a general framework for reasoning with uncertainty,allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure.However,the mass assignments given by unknown information sources are disordered.How to measure the difference between the mass assignments has aroused people’s interest.In this paper,inspired by the information volume,a novel distance-based measure is proposed to measure the difference between mass assignments.The method can refine the uncertain information given by experts and compare the refined information to obtain the difference between mass assignments.At the same time,it is verified that the measure not only meets the properties of distance,but also proves the superiority of the proposed Information Volume Distance(IVD)through simulation experiments.Meanwhile,in the process of information fusion,the reliability of each source could be quantified through IVD.Therefore,based on IVD,a new multi-source information algorithm is proposed to solve the problem of multi-source information fusion.Moreover,algorithm is applied to decision-making problem and compare with other methods to verify the effectiveness. 展开更多
关键词 Basic belief assignments Decision-making Distance measure Evidence theory Multi-source information fusion
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Multi-scale intelligent fusion and dynamic validation for high-resolution seismic data processing in drilling 认领 引用 被引量：1
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作者 YUAN Sanyi XU Yanwu +2 位作者 XIE Renjun CHEN Shuai YUAN Junliang 《Petroleum Exploration and Development》 SCIE 2025年第3期680-691,共12页
During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resol... During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios.The high-resolution processing of seismic data is divided into three stages:pre-drilling processing,post-drilling correction,and while-drilling updating.By integrating seismic data from different stages,spatial ranges,and frequencies,together with information from drilled wells and while-drilling data,and applying artificial intelligence modeling techniques,a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed,which performs simple and efficient seismic information updates during drilling.Case studies show that,with the gradual integration of multi-source information,the resolution and accuracy of seismic data are significantly improved,and thin-bed weak reflections are more clearly imaged.The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit.Validation using logging,mud logging,and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data.This provides clearer and more accurate stratigraphic information for drilling operations,enhancing both drilling safety and efficiency. 展开更多
关键词 high-resolution seismic data processing while-drilling update while-drilling logging multi-source information fusion thin-bed weak reflection artificial intelligence modeling
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Production of High-Resolution Remote Sensing Images for Navigation Information Infrastructures 认领 引用
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作者 WANGZhijun DjemelZiou CostasArmenakis 《Geo-Spatial Information Science》 EI 2004年第2期129-134,共6页
This paper introduces the image fusion approach of multi-resolutionanalysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral imagesfrom high-resolution panchromatic image and low-resolu... This paper introduces the image fusion approach of multi-resolutionanalysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral imagesfrom high-resolution panchromatic image and low-resolution multi-spectral images for navigationinformation infrastructure. The mathematical model of image fusion is derived according to theprinciple of remote sensing image formation. It shows that the pixel values of a high-resolutionmulti-spectral images are determined by the pixel values of the approximation of a high-resolutionpanchromatic image at the resolution level of low-resolution multi-spectral images, and in the pixelvalae computation the M-band wavelet theory and the a trous algorithm are then used. In order toevaluate the MRAIM approach, an experiment has been carried out on the basis of the IKONOS 1 mpanchromatic image and 4 m multi-spectral images. The result demonstrates that MRAIM image fusionapproach gives promising fusion results and it can be used to produce the high-resolution remotesensing images required for navigation information infrastructures. 展开更多
关键词 image fusion MRAIM algorithm navigation information infrastructure
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空地网联集群协同模式识别方法 认领 引用
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作者 曲桂娴 周建山 +3 位作者 司杨 刘晓静 袁奇雨 马清琳 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2026年第1期147-156,共10页
空地网联集群在智慧城市、智慧农林、智慧交通等国民经济生产领域具有巨大的应用潜力,同时在战场态势感知、空地协同打击等军事领域展现出极大的应用价值。面向空地网联集群准确感知与识别复杂环境目标的需求,建立基于模式分类概率的全... 空地网联集群在智慧城市、智慧农林、智慧交通等国民经济生产领域具有巨大的应用潜力,同时在战场态势感知、空地协同打击等军事领域展现出极大的应用价值。面向空地网联集群准确感知与识别复杂环境目标的需求,建立基于模式分类概率的全局似然函数最小化模型,提出空地网联集群的分布式学习与自适应信息融合算法,该算法包括基于梯度下降的信息扩散和基于自适应加权的信息融合2个主要步骤,形成了空地协同的模式识别方法。此外,推导出了空地网联集群协同模式识别方法的平均误差递归方程,理论证明了所提算法的误差收敛性。通过建立空地网联集群网络信息交互拓扑模型,利用雷达实测数据集进行仿真测试。仿真结果表明:集群分布式融合算法对信息估计的平均均方偏差和系统误差可有效逼近理论最优水平。当节点数由10上升至40时,集群分布式融合算法的平均均方偏差由-48.70 dB下降至-53.96 dB,系统误差由-27.42 dB下降至-30.22 dB,接近于误差的理论值。对比实验表明:所提算法较传统方法具有良好的精度,可有力支撑空地网联集群对复杂环境目标的感知与识别。 展开更多
关键词 空地网联集群 协同模式识别 信息交互拓扑模型 分布式融合算法 雷达实测数据
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长大隧道环境下基于电子轨道地图辅助的列车组合定位方法 认领 引用
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作者 李小平 孙龙 张建斌 《铁道学报》 EI CAS CSCD 北大核心 2026年第6期80-90,共11页
针对列车在长大隧道中运行时由于卫星信号失锁导致列车定位精度急剧下降以及INS/ODO组合定位系统在垂向定位精度发散的问题,提出一种基于电子轨道地图辅助INS/ODO的列车组合定位方法。该方法运用INS、ODO测速传感器,通过积分运算精确计... 针对列车在长大隧道中运行时由于卫星信号失锁导致列车定位精度急剧下降以及INS/ODO组合定位系统在垂向定位精度发散的问题,提出一种基于电子轨道地图辅助INS/ODO的列车组合定位方法。该方法运用INS、ODO测速传感器,通过积分运算精确计算出列车的位置信息,并采用UKF算法根据当前时刻列车的状态进行估计;通过引入综合加权的地图匹配算法限制列车在行进方向上的误差累积,将电子轨道地图与INS/ODO系统估计的列车位置信息紧密结合,得到当前时刻的列车状态。实验结果表明:本文提出的定位方法在列车运行过程中的最大定位误差仅为4.03 m;加入电子轨道地图的定位系统在垂向位置误差RMSE降低了32.26%,而速度误差则降低了41.35%,该方法在定位精度及鲁棒性方面均显著优于传统的INS/ODO组合定位方法,能够实时精确校正列车位置,提升列车定位精度,确保列车定位与控制系统的可靠性。 展开更多
关键词 列车定位 电子轨道地图 信息融合 匹配算法 无迹卡尔曼滤波
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四驱车辆多信息自适应融合纵向状态估计方法 认领 引用
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作者 周道林 王翔宇 +3 位作者 屈新田 万若里 邵东 李亮 《机械工程学报》 EI CAS CSCD 北大核心 2026年第8期157-168,共12页
针对四驱车辆在复杂工况下纵向状态难以准确估计、影响牵引力控制系统(Traction control system,TCS)性能的问题,提出一种融合多传感器信息、轮胎非线性附着特性与轮速稳定性信息的自适应纵向状态估计算法(Multi-source information ada... 针对四驱车辆在复杂工况下纵向状态难以准确估计、影响牵引力控制系统(Traction control system,TCS)性能的问题,提出一种融合多传感器信息、轮胎非线性附着特性与轮速稳定性信息的自适应纵向状态估计算法(Multi-source information adaptive fusion algorithm,MIAFA)。该方法根据信号可信度,自适应融合基于动力学模型的纵向加速度与基于轮速信号的纵向速度估计结果,提高了纵向状态估计精度。在轮胎打滑工况下,考虑其非线性力学特性,基于纵向滑移率与侧偏角构建了非线性附着模型,并融合惯性测量单元与转向角等传感器数据,实现纵/侧向附着的统一建模。随后,利用卡尔曼滤波估计附着系数与轮胎力,并基于动力学模型实现车辆纵向加速度计算。为增强算法在复杂工况下的适应性,构建了基于轮胎滑移率与加速度的轮速稳定性相图,基于轮速传感器信息实现了车辆纵向速度计算。仿真与实车试验结果表明,所提方法能在低附着与复杂驱动-制动-转向联合工况下有效提升纵向状态估计精度,从而增强四驱车辆TCS的控制性能。 展开更多
关键词 四驱车辆 驱动防滑控制 纵向状态估计 轮胎力估计 多信息融合算法
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智能化保护定值校核技术设计 认领 引用
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作者 潘晓明 廖坤玉 +2 位作者 邓立晨 石旭江 任泳安 《电气自动化》 2026年第2期87-88,92,共2页
针对传统校核方法在复杂运行工况下出现的校核效率低下以及校核精度不足等问题,设计了一种基于多源信息融合技术和改进果蝇算法的保护装置定值自动校核技术。引入多源信息融合技术对不同传感器、监测设备以及历史数据等多源信息进行整合... 针对传统校核方法在复杂运行工况下出现的校核效率低下以及校核精度不足等问题,设计了一种基于多源信息融合技术和改进果蝇算法的保护装置定值自动校核技术。引入多源信息融合技术对不同传感器、监测设备以及历史数据等多源信息进行整合,并在传统果蝇算法中引入动态调整步长策略,对果蝇算法中的步长参数和收敛因子进行自适应整定,显著提升了算法的全局搜索能力和收敛精度。与其他技术进行对比试验,结果表明,所提技术的校核效率和准确率均在99%以上,大幅增强了校核技术对复杂运行环境的适应性。 展开更多
关键词 保护装置 定值校核 多源信息融合 改进果蝇算法 校核准确率
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基于辅助信息特征融合的序列推荐算法 认领 引用
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作者 赵铁柱 周志强 杨秋鸿 《计算机与数字工程》 2026年第3期623-629,639,共7页
序列推荐算法基于用户历史行为预测用户未来行为,为了提升预测物品的精准度,物品属性、用户属性等辅助信息被纳入算法建模范畴,但当前算法将过早的将序列信息和辅助信息融合,导致辅助信息自身的相互关联被忽略。针对此问题,论文提出了... 序列推荐算法基于用户历史行为预测用户未来行为,为了提升预测物品的精准度,物品属性、用户属性等辅助信息被纳入算法建模范畴,但当前算法将过早的将序列信息和辅助信息融合,导致辅助信息自身的相互关联被忽略。针对此问题,论文提出了一种辅助信息特征融合的序列推荐算法(Auxiliary Information Feature Fusion for Sequential Recommendation),使用注意力机制提取辅助信息内在的多粒度关系。融合后的辅助信息表征作为注意力权值,序列信息作为注意力的实值,将其输入注意力机制和神经网络融合序列信息做出推荐,对比实验显示AIFF算法在Beauty、Toys和Toys数据集上均获得了较好的推荐效果。通用性实验表明其中的辅助信息特征融合部分能够灵活地与其他注意力序列算法相结合。 展开更多
关键词 辅助信息融合 序列推荐算法 注意力机制
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