• DocumentCode
    2624433
  • Title

    Neural data mining and modelling for electric load prediction

  • Author

    Brierley, Philip ; Batty, Bill

  • Author_Institution
    Appl. Energy & Opt. Diagnostics Group, Cranfield Univ., Bedford, UK
  • fYear
    1998
  • fDate
    35923
  • Firstpage
    42522
  • Abstract
    The authors examine the total daily load data for a large region of the UK over an eight year period. The objective is to examine the data and determine what factors influence the load level. The approach is to assume little knowledge of the system, starting with a minimal number of inputs and a network with few hidden neurons. This way the network will formulate a relationship between the given inputs and the load. By examining the peculiarities of those days which do not fit into the model it is possible to discover why they do not and to create extra inputs that convey the information required
  • Keywords
    load forecasting; UK; electric load prediction; hidden neurons; minimal inputs; modelling; neural data mining; total daily load data;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Knowledge Discovery and Data Mining (1998/434), IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19980646
  • Filename
    710061