Matches in SemOpenAlex for { <https://semopenalex.org/work/W2052158910> ?p ?o ?g. }
Showing items 1 to 58 of
58
with 100 items per page.
- W2052158910 abstract "Associative memory networks such as Radial Basis Functions, Neurofuzzy and Fuzzy Logic used for modelling nonlinear processes suffer from the curse of dimensionality (COD), in that as the input dimension increases the parameterization, computation cost, training data requirements, etc. increase exponentially. Here a new algorithm is introduced for the construction of a Delaunay input space partitioned optimal piecewise locally linear models to overcome the COD as well as generate locally linear models directly amenable to linear control and estimation algorithms. The training of the model is configured as a new mixture of experts network with a new fast decision rule derived using convex set theory. A very fast simulated reannealing (VFSR) algorithm is utilized to search a global optimal solution of the Delaunay input space partition. A benchmark non-linear time series is used to demonstrate the new approach." @default.
- W2052158910 created "2016-06-24" @default.
- W2052158910 creator A5022848316 @default.
- W2052158910 creator A5056518170 @default.
- W2052158910 creator A5067133312 @default.
- W2052158910 date "1999-03-22" @default.
- W2052158910 modified "2023-10-03" @default.
- W2052158910 title "<title>Optimal piecewise locally linear modeling</title>" @default.
- W2052158910 doi "https://doi.org/10.1117/12.342906" @default.
- W2052158910 hasPublicationYear "1999" @default.
- W2052158910 type Work @default.
- W2052158910 sameAs 2052158910 @default.
- W2052158910 citedByCount "6" @default.
- W2052158910 crossrefType "proceedings-article" @default.
- W2052158910 hasAuthorship W2052158910A5022848316 @default.
- W2052158910 hasAuthorship W2052158910A5056518170 @default.
- W2052158910 hasAuthorship W2052158910A5067133312 @default.
- W2052158910 hasConcept C111030470 @default.
- W2052158910 hasConcept C11413529 @default.
- W2052158910 hasConcept C126255220 @default.
- W2052158910 hasConcept C154945302 @default.
- W2052158910 hasConcept C17095337 @default.
- W2052158910 hasConcept C202444582 @default.
- W2052158910 hasConcept C2524010 @default.
- W2052158910 hasConcept C33676613 @default.
- W2052158910 hasConcept C33923547 @default.
- W2052158910 hasConcept C41008148 @default.
- W2052158910 hasConcept C45374587 @default.
- W2052158910 hasConcept C68010082 @default.
- W2052158910 hasConceptScore W2052158910C111030470 @default.
- W2052158910 hasConceptScore W2052158910C11413529 @default.
- W2052158910 hasConceptScore W2052158910C126255220 @default.
- W2052158910 hasConceptScore W2052158910C154945302 @default.
- W2052158910 hasConceptScore W2052158910C17095337 @default.
- W2052158910 hasConceptScore W2052158910C202444582 @default.
- W2052158910 hasConceptScore W2052158910C2524010 @default.
- W2052158910 hasConceptScore W2052158910C33676613 @default.
- W2052158910 hasConceptScore W2052158910C33923547 @default.
- W2052158910 hasConceptScore W2052158910C41008148 @default.
- W2052158910 hasConceptScore W2052158910C45374587 @default.
- W2052158910 hasConceptScore W2052158910C68010082 @default.
- W2052158910 hasLocation W20521589101 @default.
- W2052158910 hasOpenAccess W2052158910 @default.
- W2052158910 hasPrimaryLocation W20521589101 @default.
- W2052158910 hasRelatedWork W2005930910 @default.
- W2052158910 hasRelatedWork W2019710194 @default.
- W2052158910 hasRelatedWork W2052158910 @default.
- W2052158910 hasRelatedWork W2080397230 @default.
- W2052158910 hasRelatedWork W2198060433 @default.
- W2052158910 hasRelatedWork W2354062721 @default.
- W2052158910 hasRelatedWork W2394349965 @default.
- W2052158910 hasRelatedWork W2963659792 @default.
- W2052158910 hasRelatedWork W3120790515 @default.
- W2052158910 hasRelatedWork W4287394337 @default.
- W2052158910 isParatext "false" @default.
- W2052158910 isRetracted "false" @default.
- W2052158910 magId "2052158910" @default.
- W2052158910 workType "article" @default.