Matches in SemOpenAlex for { <https://semopenalex.org/work/W2349523910> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W2349523910 abstract "To improve short-term load forecasting accuracy,a modified particle swarm optimizer(MPSO) and fuzzy neural network(FNN) hybrid optimization algorithm is proposed.In which the FNN is trained by MPSO to implement the optimization of FNN parameters.The short-term load-forecasting model is established based on the modified particle swarm optimizer and fuzzy neural network hybrid optimization algorithm.In load forecasting such factors impacting loads as meteorology,weather and date types are comprehensively considered.Using the method and history load data of Guizhou power system,the shortterm load forecasting was carried out.The result shows the convergence of method is faster and forecast accuracy is more accurate than that of the traditional fuzzy neural network,BP neural network,the particle swarm optimizer(PSO) and BP neural networks,PSO and fuzzy neural networks.The hybrid algorithm improves the fuzzy neural network generalization capacity,and overcomes the traditional PSO algorithm and fuzzy neural network that exist in some of the shortcomings.The short-term load-forecasting accuracy is improved in Guizhou power system,which average percentage error is not more than 1.2%.The hybrid algorithm can be used efficaciously in short time load forecasting of the power system." @default.
- W2349523910 created "2016-06-24" @default.
- W2349523910 creator A5035574012 @default.
- W2349523910 date "2010-01-01" @default.
- W2349523910 modified "2023-09-23" @default.
- W2349523910 title "Short-term load forecasting based on modified particle swarm optimizer and fuzzy neural network model" @default.
- W2349523910 hasPublicationYear "2010" @default.
- W2349523910 type Work @default.
- W2349523910 sameAs 2349523910 @default.
- W2349523910 citedByCount "3" @default.
- W2349523910 crossrefType "journal-article" @default.
- W2349523910 hasAuthorship W2349523910A5035574012 @default.
- W2349523910 hasConcept C11413529 @default.
- W2349523910 hasConcept C121332964 @default.
- W2349523910 hasConcept C126255220 @default.
- W2349523910 hasConcept C154945302 @default.
- W2349523910 hasConcept C162324750 @default.
- W2349523910 hasConcept C163258240 @default.
- W2349523910 hasConcept C2777303404 @default.
- W2349523910 hasConcept C33923547 @default.
- W2349523910 hasConcept C41008148 @default.
- W2349523910 hasConcept C50522688 @default.
- W2349523910 hasConcept C50644808 @default.
- W2349523910 hasConcept C58166 @default.
- W2349523910 hasConcept C61797465 @default.
- W2349523910 hasConcept C62520636 @default.
- W2349523910 hasConcept C85617194 @default.
- W2349523910 hasConcept C89227174 @default.
- W2349523910 hasConceptScore W2349523910C11413529 @default.
- W2349523910 hasConceptScore W2349523910C121332964 @default.
- W2349523910 hasConceptScore W2349523910C126255220 @default.
- W2349523910 hasConceptScore W2349523910C154945302 @default.
- W2349523910 hasConceptScore W2349523910C162324750 @default.
- W2349523910 hasConceptScore W2349523910C163258240 @default.
- W2349523910 hasConceptScore W2349523910C2777303404 @default.
- W2349523910 hasConceptScore W2349523910C33923547 @default.
- W2349523910 hasConceptScore W2349523910C41008148 @default.
- W2349523910 hasConceptScore W2349523910C50522688 @default.
- W2349523910 hasConceptScore W2349523910C50644808 @default.
- W2349523910 hasConceptScore W2349523910C58166 @default.
- W2349523910 hasConceptScore W2349523910C61797465 @default.
- W2349523910 hasConceptScore W2349523910C62520636 @default.
- W2349523910 hasConceptScore W2349523910C85617194 @default.
- W2349523910 hasConceptScore W2349523910C89227174 @default.
- W2349523910 hasOpenAccess W2349523910 @default.
- W2349523910 hasRelatedWork W1986992195 @default.
- W2349523910 hasRelatedWork W1994437173 @default.
- W2349523910 hasRelatedWork W2009847409 @default.
- W2349523910 hasRelatedWork W2022166137 @default.
- W2349523910 hasRelatedWork W2042328617 @default.
- W2349523910 hasRelatedWork W2063426666 @default.
- W2349523910 hasRelatedWork W2085176070 @default.
- W2349523910 hasRelatedWork W2093774277 @default.
- W2349523910 hasRelatedWork W2099167440 @default.
- W2349523910 hasRelatedWork W2126275275 @default.
- W2349523910 hasRelatedWork W2355865853 @default.
- W2349523910 hasRelatedWork W2369591185 @default.
- W2349523910 hasRelatedWork W2374444706 @default.
- W2349523910 hasRelatedWork W2387307238 @default.
- W2349523910 hasRelatedWork W2387858752 @default.
- W2349523910 hasRelatedWork W2580721657 @default.
- W2349523910 hasRelatedWork W2906108515 @default.
- W2349523910 hasRelatedWork W2978799650 @default.
- W2349523910 hasRelatedWork W3155617174 @default.
- W2349523910 hasRelatedWork W2123682392 @default.
- W2349523910 isParatext "false" @default.
- W2349523910 isRetracted "false" @default.
- W2349523910 magId "2349523910" @default.
- W2349523910 workType "article" @default.