Selection of Measurements in Topology Estimation with Mutual Information

被引：0
|
作者：
Krstulovic, Jakov [1 ]
Miranda, Vladimiro [1 ]
机构：
[1] INESC TEC Porto, Oporto, Portugal
来源：
2014 IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON 2014) | 2014年
关键词：
Mutual information; autoencoders; feature selection; power system topology estimation; STATE ESTIMATION; IDENTIFICATION; ERRORS;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
This paper discusses mechanisms for establishing an efficient decentralized methodology for the reconstruction of topology in power systems. The maximum mutual information criterion is proposed as a selection criterion for the inputs of a distributed topology estimator, based on mosaic of local auto-associative neural networks. The proposed concepts offer some strong theoretical support for an information theoretic perspective on power system state estimation. The results are confirmed by extensive tests conducted on the IEEE RTS 24-bus system.
引用
收藏
页码：589 / 596
页数：8
相关论文
共 50 条
  • [21] A Powerful Feature Selection approach based on Mutual Information
    El Akadi, Ali
    El Ouardighi, Abdeljalil
    Aboutajdine, Driss
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2008, 8 (04): : 116 - 121
  • [22] Fast binary feature selection with conditional mutual information
    Fleuret, F
    JOURNAL OF MACHINE LEARNING RESEARCH, 2004, 5 : 1531 - 1555
  • [23] Feature selection based on mutual information with correlation coefficient
    Hongfang Zhou
    Xiqian Wang
    Rourou Zhu
    Applied Intelligence, 2022, 52 : 5457 - 5474
  • [24] Mutual information-based feature selection for radiomics
    Oubel, Estanislao
    Beaumont, Hubert
    Iannessi, Antoine
    MEDICAL IMAGING 2016: PACS AND IMAGING INFORMATICS: NEXT GENERATION AND INNOVATIONS, 2016, 9789
  • [25] Using Mutual Information for Feature Selection in Programmatic Advertising
    Ciesielczyk, Michal
    2017 IEEE INTERNATIONAL CONFERENCE ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA), 2017, : 290 - 295
  • [26] A review of feature selection methods based on mutual information
    Vergara, Jorge R.
    Estevez, Pablo A.
    NEURAL COMPUTING & APPLICATIONS, 2014, 24 (01) : 175 - 186
  • [27] Feature selection using Joint Mutual Information Maximisation
    Bennasar, Mohamed
    Hicks, Yulia
    Setchi, Rossitza
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (22) : 8520 - 8532
  • [28] Simultaneous feature selection and discretization based on mutual information
    Sharmin, Sadia
    Shoyaib, Mohammad
    Ali, Amin Ahsan
    Khan, Muhammad Asif Hossain
    Chae, Oksam
    PATTERN RECOGNITION, 2019, 91 : 162 - 174
  • [29] Feature selection using Decomposed Mutual Information Maximization
    Macedo, Francisco
    Valadas, Rui
    Carrasquinha, Eunice
    Oliveira, M. Rosario
    Pacheco, Antonio
    NEUROCOMPUTING, 2022, 513 : 215 - 232
  • [30] Feature selection based on mutual information with correlation coefficient
    Zhou, Hongfang
    Wang, Xiqian
    Zhu, Rourou
    APPLIED INTELLIGENCE, 2022, 52 (05) : 5457 - 5474
12345