Matches in SemOpenAlex for { <https://semopenalex.org/work/W100792009> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W100792009 endingPage "307" @default.
- W100792009 startingPage "287" @default.
- W100792009 abstract "An important and challenging data mining application in marketing is to learn models for predicting potential customers who contribute large profits to a company under resource constraints. In this chapter, we first formulate this learning problem as a constrained optimization problem and then convert it to an unconstrained multi-objective optimization problem (MOP), which can be handled by some multi-objective evolutionary algorithms (MOEAs). However, MOEAs may execute for a long time for the MOP, because several evaluations must be performed. A promising approach to overcome this limitation is to parallelize these algorithms. Thus we propose a parallel MOEA on consumer-level graphics processing units (GPU) to tackle the MOP. We perform experiments on a real-life direct marketing problem to compare the proposed method with the parallel hybrid genetic algorithm, the DMAX approach, and a sequential MOEA. It is observed that the proposed method is much more effective and efficient than the other approaches." @default.
- W100792009 created "2016-06-24" @default.
- W100792009 creator A5006043053 @default.
- W100792009 creator A5011994181 @default.
- W100792009 date "2013-01-01" @default.
- W100792009 modified "2023-10-03" @default.
- W100792009 title "Data Mining Using Parallel Multi-objective Evolutionary Algorithms on Graphics Processing Units" @default.
- W100792009 cites W1552232626 @default.
- W100792009 cites W1749721385 @default.
- W100792009 cites W1982115278 @default.
- W100792009 cites W2011281319 @default.
- W100792009 cites W2042771001 @default.
- W100792009 cites W2049615251 @default.
- W100792009 cites W2053900989 @default.
- W100792009 cites W2063375245 @default.
- W100792009 cites W2078244692 @default.
- W100792009 cites W2103055617 @default.
- W100792009 cites W2106334424 @default.
- W100792009 cites W2109778277 @default.
- W100792009 cites W2120579720 @default.
- W100792009 cites W2126105956 @default.
- W100792009 cites W2156221357 @default.
- W100792009 cites W2165171393 @default.
- W100792009 cites W2165626989 @default.
- W100792009 cites W2348980703 @default.
- W100792009 cites W4245488342 @default.
- W100792009 doi "https://doi.org/10.1007/978-3-642-37959-8_14" @default.
- W100792009 hasPublicationYear "2013" @default.
- W100792009 type Work @default.
- W100792009 sameAs 100792009 @default.
- W100792009 citedByCount "15" @default.
- W100792009 countsByYear W1007920092013 @default.
- W100792009 countsByYear W1007920092016 @default.
- W100792009 countsByYear W1007920092017 @default.
- W100792009 countsByYear W1007920092018 @default.
- W100792009 countsByYear W1007920092019 @default.
- W100792009 countsByYear W1007920092020 @default.
- W100792009 countsByYear W1007920092021 @default.
- W100792009 crossrefType "book-chapter" @default.
- W100792009 hasAuthorship W100792009A5006043053 @default.
- W100792009 hasAuthorship W100792009A5011994181 @default.
- W100792009 hasConcept C11413529 @default.
- W100792009 hasConcept C121684516 @default.
- W100792009 hasConcept C124101348 @default.
- W100792009 hasConcept C173608175 @default.
- W100792009 hasConcept C21442007 @default.
- W100792009 hasConcept C41008148 @default.
- W100792009 hasConceptScore W100792009C11413529 @default.
- W100792009 hasConceptScore W100792009C121684516 @default.
- W100792009 hasConceptScore W100792009C124101348 @default.
- W100792009 hasConceptScore W100792009C173608175 @default.
- W100792009 hasConceptScore W100792009C21442007 @default.
- W100792009 hasConceptScore W100792009C41008148 @default.
- W100792009 hasLocation W1007920091 @default.
- W100792009 hasOpenAccess W100792009 @default.
- W100792009 hasPrimaryLocation W1007920091 @default.
- W100792009 hasRelatedWork W1491899005 @default.
- W100792009 hasRelatedWork W1502414128 @default.
- W100792009 hasRelatedWork W1558545464 @default.
- W100792009 hasRelatedWork W1604898313 @default.
- W100792009 hasRelatedWork W1984303163 @default.
- W100792009 hasRelatedWork W2074301136 @default.
- W100792009 hasRelatedWork W2117014006 @default.
- W100792009 hasRelatedWork W2172791042 @default.
- W100792009 hasRelatedWork W2372170743 @default.
- W100792009 hasRelatedWork W4233815414 @default.
- W100792009 isParatext "false" @default.
- W100792009 isRetracted "false" @default.
- W100792009 magId "100792009" @default.
- W100792009 workType "book-chapter" @default.