• 3
  • 3
  • 82
  • 82
IPM
30
YEARS OLD

“School of Cognitive Sciences”

Paper   IPM / Cognitive Sciences / 7420
   School of Cognitive Sciences
  Title: Short term load forecasting using fuzzy neural network modified by the similarity and subsethood measures
  Author(s):
1 . M.R. Ganjavi
2 . C. Lucas
3 . M.H. Javadi
  Status: Published
  Journal: J. of Intelligent and Fuzzy Systems
  Vol.: 7
  Year: 1999
  Pages: 347-357
  Supported by: IPM
  Abstract:
In this paper the linguistic approximate reasoning method is used for short term load forecasting. A neural structure for inference processing units is put forward. Two different Analogical and deductive  approaches to the inference method have been distinguished. Correspondingly, two different architectures  Analogical and Deductive fuzzy neural networks  are introduced in this paper. The accuracy of the load forecasting, as well as the size of the required rule base have been compared for Analogical, Deductive, and conventional fuzzy neural networks. It is shown that analogical and Deductive approaches have superior performance in this application.


Download TeX format
back to top
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
scroll left or right