Matches in SemOpenAlex for { <https://semopenalex.org/work/W2066269320> ?p ?o ?g. }
- W2066269320 endingPage "328" @default.
- W2066269320 startingPage "323" @default.
- W2066269320 abstract "Electricity is an important asset that influences not only the economy, but political or social security of a country. Reliable and accurate planning and prediction of electricity demand for a country are therefore vital. In this paper, electricity demand in Ontario province of Canada from the year 1976–2005 is modeled by using an (adaptive neuro fuzzy inference system) ANFIS. A neuro fuzzy structure can be defined as an ANN (artificial neural network) which is trained by experimental data to find the parameters of (fuzzy inference system) FIS. Inputs for the model include number of employment, (gross domestic product) GDP, population, dwelling count and two meteorological parameters related to annual weather temperature. The data were collected and screened using statistical methods. Then, based on the data, a neuro-fuzzy model for the electricity demand is built. It was found that electricity demand is most sensitive to employment." @default.
- W2066269320 created "2016-06-24" @default.
- W2066269320 creator A5001727956 @default.
- W2066269320 creator A5038709614 @default.
- W2066269320 creator A5053208030 @default.
- W2066269320 creator A5070558220 @default.
- W2066269320 creator A5074804653 @default.
- W2066269320 date "2013-01-01" @default.
- W2066269320 modified "2023-10-17" @default.
- W2066269320 title "Electricity demand estimation using an adaptive neuro-fuzzy network: A case study from the Ontario province – Canada" @default.
- W2066269320 cites W1968112823 @default.
- W2066269320 cites W1986983672 @default.
- W2066269320 cites W1991488986 @default.
- W2066269320 cites W1992844247 @default.
- W2066269320 cites W1993601879 @default.
- W2066269320 cites W2001631452 @default.
- W2066269320 cites W2014542721 @default.
- W2066269320 cites W2016632558 @default.
- W2066269320 cites W2019207321 @default.
- W2066269320 cites W2032168110 @default.
- W2066269320 cites W2041280856 @default.
- W2066269320 cites W2044410443 @default.
- W2066269320 cites W2046854739 @default.
- W2066269320 cites W2046933993 @default.
- W2066269320 cites W2049622828 @default.
- W2066269320 cites W2055755942 @default.
- W2066269320 cites W2058326618 @default.
- W2066269320 cites W2067742577 @default.
- W2066269320 cites W2070190840 @default.
- W2066269320 cites W2071358277 @default.
- W2066269320 cites W2073002835 @default.
- W2066269320 cites W2074437014 @default.
- W2066269320 cites W2076566755 @default.
- W2066269320 cites W2076744640 @default.
- W2066269320 cites W2085110978 @default.
- W2066269320 cites W2099635347 @default.
- W2066269320 cites W2130197137 @default.
- W2066269320 cites W2150209595 @default.
- W2066269320 cites W2164353564 @default.
- W2066269320 cites W2170917304 @default.
- W2066269320 cites W4236706032 @default.
- W2066269320 cites W4304118855 @default.
- W2066269320 doi "https://doi.org/10.1016/j.energy.2012.10.019" @default.
- W2066269320 hasPublicationYear "2013" @default.
- W2066269320 type Work @default.
- W2066269320 sameAs 2066269320 @default.
- W2066269320 citedByCount "91" @default.
- W2066269320 countsByYear W20662693202013 @default.
- W2066269320 countsByYear W20662693202014 @default.
- W2066269320 countsByYear W20662693202015 @default.
- W2066269320 countsByYear W20662693202016 @default.
- W2066269320 countsByYear W20662693202017 @default.
- W2066269320 countsByYear W20662693202018 @default.
- W2066269320 countsByYear W20662693202019 @default.
- W2066269320 countsByYear W20662693202020 @default.
- W2066269320 countsByYear W20662693202021 @default.
- W2066269320 countsByYear W20662693202022 @default.
- W2066269320 countsByYear W20662693202023 @default.
- W2066269320 crossrefType "journal-article" @default.
- W2066269320 hasAuthorship W2066269320A5001727956 @default.
- W2066269320 hasAuthorship W2066269320A5038709614 @default.
- W2066269320 hasAuthorship W2066269320A5053208030 @default.
- W2066269320 hasAuthorship W2066269320A5070558220 @default.
- W2066269320 hasAuthorship W2066269320A5074804653 @default.
- W2066269320 hasConcept C114350782 @default.
- W2066269320 hasConcept C119599485 @default.
- W2066269320 hasConcept C121332964 @default.
- W2066269320 hasConcept C127413603 @default.
- W2066269320 hasConcept C146733006 @default.
- W2066269320 hasConcept C149782125 @default.
- W2066269320 hasConcept C154945302 @default.
- W2066269320 hasConcept C162324750 @default.
- W2066269320 hasConcept C163258240 @default.
- W2066269320 hasConcept C186108316 @default.
- W2066269320 hasConcept C187736073 @default.
- W2066269320 hasConcept C188573790 @default.
- W2066269320 hasConcept C195975749 @default.
- W2066269320 hasConcept C206658404 @default.
- W2066269320 hasConcept C29470771 @default.
- W2066269320 hasConcept C2988649059 @default.
- W2066269320 hasConcept C38652104 @default.
- W2066269320 hasConcept C41008148 @default.
- W2066269320 hasConcept C423512 @default.
- W2066269320 hasConcept C50522688 @default.
- W2066269320 hasConcept C50644808 @default.
- W2066269320 hasConcept C58166 @default.
- W2066269320 hasConcept C62520636 @default.
- W2066269320 hasConcept C76178495 @default.
- W2066269320 hasConcept C96250715 @default.
- W2066269320 hasConceptScore W2066269320C114350782 @default.
- W2066269320 hasConceptScore W2066269320C119599485 @default.
- W2066269320 hasConceptScore W2066269320C121332964 @default.
- W2066269320 hasConceptScore W2066269320C127413603 @default.
- W2066269320 hasConceptScore W2066269320C146733006 @default.
- W2066269320 hasConceptScore W2066269320C149782125 @default.
- W2066269320 hasConceptScore W2066269320C154945302 @default.
- W2066269320 hasConceptScore W2066269320C162324750 @default.
- W2066269320 hasConceptScore W2066269320C163258240 @default.