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An Asynchronous Data Fusion Algorithm for Target Detection based on Multi-Sensor Networks

Ke Zhang, Zeyang Wang, Lele Guo, Yuanyuan Peng, Zhi Zheng
2020 IEEE Access  
INDEX TERMS Asynchronous fusion, multi sensors, track fusion, track quality with multiple model.  ...  By establishing an asynchronous track fusion model with irregular time interval of observation data and combining with the Track Quality with Multiple Model (TQMM), an asynchronous track fusion algorithm  ...  When N = 0, one step prediction is made based on the state estimate value of the previous fusion time to obtain the state estimate of the current fusion time.  ... 
doi:10.1109/access.2020.2982682 fatcat:bfdmxlexrbe3bfdxqnhuypveq4

Design of Health Monitoring Program for Filling System based on Data Level Fusion

Long Cheng, Xiaochen Xing, Weiqi Xie, Rui Cheng, Lei Wang, D. Zhang, B. Zi, G. Cui, H. Ding
2016 MATEC Web of Conferences  
On this basis, Single sensor fusion monitoring based on RTS-TA algorithm and Multi-sensor fusion monitoring based on improved weighted fusion algorithm are designed.  ...  The health monitoring type is mainly divided into two parts, fusion-threshold monitoring based on single sensor data and fusion monitoring based on multi-sensor data of the same type.  ...  monitoring based on single sensor data and another one is fusion monitoring based on multi-sensor data of the same type.  ... 
doi:10.1051/matecconf/20167705001 fatcat:el3w7po56naj3bknwidh3gupdi

Power Grid Material Demand Forecasting Based on Pearson Feature Selection and Multi-Model Fusion

Zhou Dai, Gang Wang, Ruien Bian, Chaozhi Deng
2022 Frontiers in Energy Research  
To address these problems, this study proposes a power grid material demand forecasting model based on feature selection and multi-model fusion.  ...  Then, stacking fusion algorithm is used to fuse multiple basic models. At last, the proposed method mentioned in this study is tested on a real dataset.  ...  Aiming at the aforementioned problems, this study proposes a power grid material prediction model based on feature selection and multi-model fusion.  ... 
doi:10.3389/fenrg.2022.882818 fatcat:wcvex4sdm5bspfr7nyxzriw6uq

A Novel Fuzzy Fusion Algorithm of Multi-sensor Data and Its Application in Coalmine Gas Monitoring

Xiaojie Zhu, Ze Jiang, Xiaobing Zhao, Mingjie Zhang, Xiangfei Chen
2019 Instrumentation Mesure Métrologie  
The results show that the gas states at all time points were evaluated accurately, without any false or missed alarm, and the prediction based on multi-sensor data fusion was 34% more accurate than that  ...  Based on local decisions, a data fusion decision-making model for coalmine gas disaster was established to make the global decision.  ...  The prediction based on multi-sensor data fusion was 34% more accurate than that based on single-sensor data.  ... 
doi:10.18280/i2m.180609 fatcat:iafjk7qpbjci3cf77kjipwnqxi

Author Index

2021 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)  
Bi, Xinjie Visibility Graph based Feature Extraction for Fault Diagnosis of Rolling Bearings [570256] Bin, Jie Optimization Method of Virtual Sand Table Background Server Based on Unity 3D [571175] C  ...  ) Yang, Xiuzhen Functional Failure Diagnosis Method of Multi-state Manufacturing System Based on Extended Quality State Task Network [570202] Yang, Xuesong Research on a Reliability Prediction Method Based  ...  Combined With Singular [571199] Lu, Jiale State Evaluation of Long-term Storage Product Based on Cloud Model and TFN-AHP [571215] Lu, Jiantao Research on Multiple Cross Correlation Fusion Method of Fault  ... 
doi:10.1109/phm-nanjing52125.2021.9612757 fatcat:h4xp5wbdvjdpvmsri2dktwupbi

Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis

Shafiza Ariffin Kashinath, Salama A. Mostafa, Aida Mustapha, Hairulnizam Mahdin, David Lim, Moamin A. Mahmoud, Mazin Abed Mohammed, Bander Ali Saleh Al-rimy, Mohd Farhan Md Fudzee, Tan Jhon Yang
2021 IEEE Access  
[38] suggest a hybrid method based on deep feature fusion modeling to achieve speed prediction.  ...  [116] work on a study to generate short-term traffic state prediction. This model identifies the current pattern of traffic based on the historical state to make the prediction.  ... 
doi:10.1109/access.2021.3069770 fatcat:2p52c7psrzhofgy4l2jy5fxw4u

A Data Fusion Algorithm and Simulation Based on TQMM [chapter]

Ke Zhang, Zeyang Wang, Huiling Li
2019 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
Asynchronous data fusion is more practical than synchronous data fusion, the model of track-to-track fusion in this case has been established and the concept of Track Quality with Multiple Model (TQMM)  ...  was put forward, furthermore a data fusion algorithm is proposed, in which the TQMM is used to assign weights, to improve tracking precision in asynchronous multi-sensor data fusion system.  ...  NCET-11-0075), and Project of Science and Technology on Electronic Information Control Laboratory.  ... 
doi:10.1007/978-3-030-32216-8_20 fatcat:chzui26vrbgdnnr4qua6hdgf2q

Multi-Modal Vehicle Trajectory Prediction Based on Mutual Information

xuewu ji, Cong Fei, Xiangkun He
2019 IET Intelligent Transport Systems  
The data fusion encoder summarises the mutual information by multi-LSTM with shared parameters and the multi-modal decoder generates trajectories based on driving intention.  ...  The model consists of a data fusion encoder and a multi-modal decoder.  ...  National Natural Science Foundation of China automobile industry innovation and development joint fund project (U1664263), the National Natural Science Foundation of China (51875302) and the National Key Research  ... 
doi:10.1049/iet-its.2019.0299 fatcat:zmbgcoloqbb7lapftkkyfzs6ky

A New Fusion Estimation Method for Multi-rate Multi-sensor Systems with Missing Measurements

Mojtaba Kordestani, Maryam Dehghani, Behzad Moshiri, Mehrdad Saif
2020 IEEE Access  
A new fusion strategy based on a real covariance matrix is introduced for updating the weighting factors, and proof of convergence is granted.  ...  A new fusion strategy is introduced in this article to estimate state for multi-rate multisensor systems with missing measurements.  ...  A fusion technique based on a matrix-weighted fusion estimation method is introduced in [47] for multi-sensor systems with missing measurements and unknown model parameters.  ... 
doi:10.1109/access.2020.2979222 fatcat:l5gfymalwjek3mc7ot3j6lpviu

Asynchronous Sensor Fusion using Multi-rate Kalman Filter
다중주기 칼만 필터를 이용한 비동기 센서 융합

Young Seop Son, Wonhee Kim, Seung-Hi Lee, Chung Choo Chung
2014 The Transactions of The Korean Institute of Electrical Engineers  
A model based prediction of object vehicles is performed with a decentralized multi-rate Kalman filter for each sensor (vision and radar sensors.)  ...  We propose a multi-rate sensor fusion of vision and radar using Kalman filter to solve problems of asynchronized and multi-rate sampling periods in object vehicle tracking.  ...  error is computed based on the predicted states at     .  ... 
doi:10.5370/kiee.2014.63.11.1551 fatcat:qbpwj7gl6ja5nijlbw7afeb7ze

Remaining Useful Life Prediction with Similarity Fusion of Multi-Parameter and Multi-Sample Based on the Vibration Signals of Diesel Generator Gearbox

Shenghan Zhou, Xingxing Xu, Yiyong Xiao, Wenbing Chang, Silin Qian, Xing Pan
2019 Entropy  
This paper proposes an RUL prediction model with similarity fusion of multi-parameter and multi-sample.  ...  Thirdly, based on DTWD, similarity fusion of multi-parameter and multi-sample methods is proposed here to achieve RUL prediction.  ...  At last, the RUL prediction model based on the similarity fusion of multi-parameter and multi-sample methods will be established.  ... 
doi:10.3390/e21090861 fatcat:c6fi6m7pffejrbpc6k5o7o2evq

Multi-modal Dimensional Emotion Recognition using Recurrent Neural Networks

Shizhe Chen, Qin Jin
2015 Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge - AVEC '15  
Term Memory (LSTM), multi-task learning, different structures for early feature fusion and late fusion.  ...  Our system applies the Recurrent Neural Networks (RNN) to model temporal information.  ...  For valence prediction, multi-task learning improves the performance based on video_geo feature but decreases the performance based on long-time audio features.  ... 
doi:10.1145/2808196.2811638 dblp:conf/mm/ChenJ15 fatcat:rxqecowahfalln6bcmo77x6ryq

Multi-layer Stacking-based Emotion Recognition using Data Fusion Strategy

Saba Tahseen, Ajit Danti
2022 International Journal of Advanced Computer Science and Applications  
This paper is based on the feature selection strategy by using the data fusion technique from the same source of EEG Brainwave Dataset for Classification.  ...  Features are selected based on a Linear Regression based correlation coefficient (LR-CC) score with a different range like n 1 , n 2 ,n 3 ,n 4 a, for d 1 used n 1 and n 2 dataset ,for d 2 dataset, combined  ...  As a result of the increased focus on boosting prediction performance, multi-layer stacking ensembles model depicted to improved predictive performance in this investigation.  ... 
doi:10.14569/ijacsa.2022.0130654 fatcat:t4amt3sgpfcpxmo2n5w3cntpsy

Review of Machining Equipment Reliability Analysis Methods based on Condition Monitoring Technology

Wei Dai, Jiahuan Sun, Yongjiao Chi, Zhiyuan Lu, Dong Xu, Nan Jiang
2019 Applied Sciences  
And an up-to-date comprehensive survey of multi-source information during the cutting process, failure physical analysis for signal selection and reliability assessment based on condition information will  ...  In this paper, the reliability analysis method of machining equipment based on condition monitoring technology is taken as the main line.  ...  [118] have focused on the construction of the mission reliability model based on process information fusion.  ... 
doi:10.3390/app9142786 fatcat:y6sanirmsnabnatg6avlqe22x4

A Multi-Classification Method of Improved SVM-based Information Fusion for Traffic Parameters Forecasting

Hongzhuan Zhao, Dihua Sun, Min Zhao, Senlin Cheng
2016 Promet (Zagreb)  
of the original Support Vector Machine (SVM) classification in information fusion, a multi-classification method using improved SVM in information fusion for traffic parameters forecasting is proposed  ...  Existing research results show that the multisourced traffic information through accurate classification in the process of information fusion can achieve better parameters forecasting performance.  ...  ACKNOWLEDGEMENT The authors would like to acknowledge the multi-classification method of improved SVM-based information fusion for traffic parameters forecasting is collectively supported by the national  ... 
doi:10.7307/ptt.v28i2.1643 fatcat:ccvhwqu4x5h7vc5qhdmpiv3wey
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