Data Fusion Classification Method Based on Multi Agents System

被引：0
作者：
Ben Boussada, Elhoucine [1 ]
Ben Ayed, Mounir [1 ,2 ]
Alimi, Adel M. [1 ]
机构：
[1] Natl Engn Sch Sfax, Comp Engn & Appl Math Dept, Sfax, Tunisia
[2] Fac Sci Sfax, Comp Sci & Commun Dept, Sfax, Tunisia
来源：
INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA 2016) | 2017年 / 557卷
关键词：
Data fusion; ECG classification; Artificial intelligence; Multi-agent system; Neural network; MIT-BIH;
D O I：
10.1007/978-3-319-53480-0_85
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Computer analysis of electrocardiogram (ECG) data has proven to be an important method to detect cardiac arrhythmias, so that can be of great assistance to the experts in detecting cardiac abnormalities. In this study, we propose to develop a system to aid in the diagnosis of anomalies cardiac signals. This system is based on data fusion and architected by using the multi-agents system. Therefore, the proposed system helps doctors to quickly and precisely diagnose a heart disease by examining only the class of the ECG beats. In order to achieve the goal of real-time classification, the data used are divided into two datasets: the training set for the unsupervised learning of the classifier and the testing set for the real-time classification. This system is tested on a MIT-BIH arrhythmia database.
引用
收藏
页码：863 / 870
页数：8
相关论文
共 50 条
  • [31] Object-oriented classification based on multi-scale segmentation and data fusion technique
    Liu, F. J.
    Wu, X. C.
    Mei, L. L.
    Guo, Y.
    Hu, Y. S.
    2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 4, 2008, : 1058 - 1062
  • [32] Targets Classification Based on Multi-sensor Data Fusion and Supervised Learning for Surveillance Application
    Mohamed Hechmi Jeridi
    Hacen Khlaifi
    Amine Bouatay
    Tahar Ezzedine
    Wireless Personal Communications, 2019, 105 : 313 - 333
  • [33] A novel data-driven integrated detection method for network intrusion classification based on multi-feature imbalanced data
    Wang, Chia-Hung
    Ye, Qing
    Cai, Jiongbiao
    Suo, Yifan
    Lin, Shengming
    Yuan, Jinchen
    Wu, Xiaojing
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (03) : 5893 - 5910
  • [34] Targets Classification Based on Multi-sensor Data Fusion and Supervised Learning for Surveillance Application
    Jeridi, Mohamed Hechmi
    Khalaifi, Hacen
    Bouatay, Amine
    Ezzedine, Tahar
    WIRELESS PERSONAL COMMUNICATIONS, 2019, 105 (01) : 313 - 333
  • [35] An Image-Based Classification Module for Data Fusion Anti-drone System
    Jajaga, Edmond
    Rushiti, Veton
    Ramadani, Blerant
    Pavleski, Daniel
    Cantelli-Forti, Alessandro
    Stojkovska, Biljana
    Petrovska, Olivera
    IMAGE ANALYSIS AND PROCESSING, ICIAP 2022 WORKSHOPS, PT II, 2022, 13374 : 422 - 433
  • [36] Method of fusion for multi-sensors data in statistic
    Wan Shuping
    Proceedings of the First International Symposium on Test Automation & Instrumentation, Vols 1 - 3, 2006, : 430 - 432
  • [37] Study of Fault Diagnosis Method Based on Data Fusion Technology
    Du, Hailian
    Lv, Feng
    Li, Shue
    Xin, Tao
    2012 INTERNATIONAL WORKSHOP ON INFORMATION AND ELECTRONICS ENGINEERING, 2012, 29 : 2590 - 2594
  • [38] Pedestrian Detection Method Based on Neural Network and Data Fusion
    Zhu B.
    Huang M.
    Tan D.
    Hu X.
    Gu J.
    Tan, Dongkui (tandongkui@126.com), 1600, SAE-China (42): : 1482 - 1489
  • [39] A Q-learning-based multi-agent system for data classification
    Pourpanah, Farhad
    Tan, Choo Jun
    Lim, Chee Peng
    Mohamad-Saleh, Junita
    APPLIED SOFT COMPUTING, 2017, 52 : 519 - 531
  • [40] A Data Fusion Method in LPG Monitoring System
    Yang Jiandong
    Si Nong
    Liu Hongfei
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 6416 - 6421
12345