Neural Network Using to Analyze the Results of Environmental Monitoring of Water

被引:2
|
作者
Usachev, V. A. [1 ]
Voronova, L., I [1 ]
Voronov, V., I [1 ]
Zharov, I. A. [1 ]
Strelnikov, V. G. [1 ]
机构
[1] Moscow Tech Univ Commun & Informat, Moscow, Russia
来源
2019 SYSTEMS OF SIGNALS GENERATING AND PROCESSING IN THE FIELD OF ON BOARD COMMUNICATIONS | 2019年
关键词
big data; neural network; machine learning; water quality monitoring; sensors;
D O I
10.1109/sosg.2019.8706733
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The acuteness of the environmental tracking problem is constantly growing. Currently, environmental issues are analyzed using big data. Many open data sources (Kaggle, Open Data Portal of the Russian Federation, etc.) contain a variety of environmental information. Based on the data and using the tools for analyzing big data and machine learning, a system has been developed that simulates the state of water quality in the Moscow waters. On the basis of the indicators obtained, the neural network was trained, which classifies the state of the reservoir into good and deviant.
引用
收藏
页数:6
相关论文
共 50 条
  • [21] Risk evaluation of urban water distribution network pipes using neural network
    Yang, Yanying
    Han, Yonghua
    Zheng, Jianchun
    Wang, Jingjing
    Zhao, Ming
    Zhu, Wei
    PROCEEDINGS OF THE 4TH ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON SAFETY AND RESILIENCE (EM-GIS 2018), 2018,
  • [22] Environmental monitoring network along a mountain valley using embedded controllers
    Villagran, Victor
    Montecinos, Aldo
    Franco, Cristian
    Munoz, Ricardo C.
    MEASUREMENT, 2017, 106 : 221 - 235
  • [23] Monitoring of Bacterial Pustule on Soybean by Neural Network Using Hyperspectral Data
    Kosaka, Naoko
    Minekawa, Yohei
    Uto, Kuniaki
    Kosugi, Yukio
    Oda, Kunio
    Saito, Genya
    2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 3879 - +
  • [24] On-line monitoring of tool wear in turning using a neural network
    Choudhury, SK
    Jain, VK
    Rao, CVVR
    INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 1999, 39 (03): : 489 - 504
  • [25] ACTIVITY MONITORING SYSTEM USING NEURAL NETWORK IN PRODUCTION SHOP FLOOR
    Okubo, Hiroki
    Yanagawa, Yohinari
    Arizono, Ikuo
    ICIM2012: PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON INDUSTRIAL MANAGEMENT, 2012, : 498 - 502
  • [26] Tool Wear Monitoring during Milling Using an Autoassociative Neural Network
    Oh, Dae Jin
    Sim, Beom Sik
    Lee, Wonkyun
    TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS A, 2021, 45 (04) : 285 - 291
  • [27] PERSONALIZED TRAITS MONITORING USING A NEURAL NETWORK BASED ON OSCILLOMETRIC MEASUREMENTS
    Shin, Young-Suk
    BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2013, 25 (02):
  • [28] Tool condition monitoring using reflectance of chip surface and neural network
    S. H. Yeo
    L. P. Khoo
    S. S. Neo
    Journal of Intelligent Manufacturing, 2000, 11 : 507 - 514
  • [29] Neural Cryptography with Fog Computing Network for Health Monitoring Using IoMT
    Ravikumar, G.
    Venkatachalam, K.
    AlZain, Mohammed A.
    Masud, Mehedi
    Abouhawwash, Mohamed
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2023, 44 (01): : 945 - 959
  • [30] Tool condition monitoring using reflectance of chip surface and neural network
    Yeo, SH
    Khoo, LP
    Neo, SS
    JOURNAL OF INTELLIGENT MANUFACTURING, 2000, 11 (06) : 507 - 514