Matches in SemOpenAlex for { <https://semopenalex.org/work/W2513216991> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W2513216991 abstract "The study aimed to realize the automatic production scheduling of waste paper in paper mills. Based on the quantities of the field data (mixing ratios of waste paper and pulp properties) stored in a paper mill, the methods of back propagation neural networks (BP-NN) and support vector machine (SVM), the all data set and the average data set, were firstly applied to develop the prediction models of the pulp properties; and then the genetic algorithm was used to search for the suitable scheduling solutions. The simulation results revealed that: demonstrating its acceptable prediction accuracy and fast training time, the prediction model with SVM method and the average data set was good enough to be used in the genetic algorithm to search for the optimal scheduling ratios of waste paper, the obtained optimal scheduling solution not only had the lowest purchase cost of waste paper, but also met the requirements of the mill: specified types of waste paper, specified ratio of some kind of waste paper and the required pulp brightness." @default.
- W2513216991 created "2016-09-16" @default.
- W2513216991 creator A5017822292 @default.
- W2513216991 creator A5020769177 @default.
- W2513216991 date "2016-05-01" @default.
- W2513216991 modified "2023-09-23" @default.
- W2513216991 title "Data-driven approach of scheduling the ratio of waste paper and pulp properties prediction" @default.
- W2513216991 cites W1976275608 @default.
- W2513216991 cites W1978837761 @default.
- W2513216991 cites W1986852908 @default.
- W2513216991 cites W2023787363 @default.
- W2513216991 cites W2038520650 @default.
- W2513216991 cites W2040859370 @default.
- W2513216991 cites W2044723795 @default.
- W2513216991 cites W2057802213 @default.
- W2513216991 cites W2074324725 @default.
- W2513216991 cites W2144277759 @default.
- W2513216991 cites W2172073485 @default.
- W2513216991 cites W2493126027 @default.
- W2513216991 doi "https://doi.org/10.1109/ccdc.2016.7531872" @default.
- W2513216991 hasPublicationYear "2016" @default.
- W2513216991 type Work @default.
- W2513216991 sameAs 2513216991 @default.
- W2513216991 citedByCount "1" @default.
- W2513216991 countsByYear W25132169912017 @default.
- W2513216991 crossrefType "proceedings-article" @default.
- W2513216991 hasAuthorship W2513216991A5017822292 @default.
- W2513216991 hasAuthorship W2513216991A5020769177 @default.
- W2513216991 hasConcept C111919701 @default.
- W2513216991 hasConcept C119857082 @default.
- W2513216991 hasConcept C12267149 @default.
- W2513216991 hasConcept C126255220 @default.
- W2513216991 hasConcept C127413603 @default.
- W2513216991 hasConcept C142724271 @default.
- W2513216991 hasConcept C147455438 @default.
- W2513216991 hasConcept C16057445 @default.
- W2513216991 hasConcept C188442228 @default.
- W2513216991 hasConcept C206729178 @default.
- W2513216991 hasConcept C2776106130 @default.
- W2513216991 hasConcept C33923547 @default.
- W2513216991 hasConcept C41008148 @default.
- W2513216991 hasConcept C50644808 @default.
- W2513216991 hasConcept C548081761 @default.
- W2513216991 hasConcept C55416958 @default.
- W2513216991 hasConcept C68387754 @default.
- W2513216991 hasConcept C71924100 @default.
- W2513216991 hasConcept C78519656 @default.
- W2513216991 hasConcept C8880873 @default.
- W2513216991 hasConceptScore W2513216991C111919701 @default.
- W2513216991 hasConceptScore W2513216991C119857082 @default.
- W2513216991 hasConceptScore W2513216991C12267149 @default.
- W2513216991 hasConceptScore W2513216991C126255220 @default.
- W2513216991 hasConceptScore W2513216991C127413603 @default.
- W2513216991 hasConceptScore W2513216991C142724271 @default.
- W2513216991 hasConceptScore W2513216991C147455438 @default.
- W2513216991 hasConceptScore W2513216991C16057445 @default.
- W2513216991 hasConceptScore W2513216991C188442228 @default.
- W2513216991 hasConceptScore W2513216991C206729178 @default.
- W2513216991 hasConceptScore W2513216991C2776106130 @default.
- W2513216991 hasConceptScore W2513216991C33923547 @default.
- W2513216991 hasConceptScore W2513216991C41008148 @default.
- W2513216991 hasConceptScore W2513216991C50644808 @default.
- W2513216991 hasConceptScore W2513216991C548081761 @default.
- W2513216991 hasConceptScore W2513216991C55416958 @default.
- W2513216991 hasConceptScore W2513216991C68387754 @default.
- W2513216991 hasConceptScore W2513216991C71924100 @default.
- W2513216991 hasConceptScore W2513216991C78519656 @default.
- W2513216991 hasConceptScore W2513216991C8880873 @default.
- W2513216991 hasLocation W25132169911 @default.
- W2513216991 hasOpenAccess W2513216991 @default.
- W2513216991 hasPrimaryLocation W25132169911 @default.
- W2513216991 hasRelatedWork W1480821801 @default.
- W2513216991 hasRelatedWork W1679090545 @default.
- W2513216991 hasRelatedWork W1964179186 @default.
- W2513216991 hasRelatedWork W2072857362 @default.
- W2513216991 hasRelatedWork W2098480637 @default.
- W2513216991 hasRelatedWork W2107873021 @default.
- W2513216991 hasRelatedWork W2150160775 @default.
- W2513216991 hasRelatedWork W2157184049 @default.
- W2513216991 hasRelatedWork W2168624428 @default.
- W2513216991 hasRelatedWork W2187555662 @default.
- W2513216991 hasRelatedWork W2289505187 @default.
- W2513216991 hasRelatedWork W2367107142 @default.
- W2513216991 hasRelatedWork W2383944601 @default.
- W2513216991 hasRelatedWork W2384335367 @default.
- W2513216991 hasRelatedWork W2391235926 @default.
- W2513216991 hasRelatedWork W2392148872 @default.
- W2513216991 hasRelatedWork W2518536237 @default.
- W2513216991 hasRelatedWork W2580428024 @default.
- W2513216991 hasRelatedWork W2775190808 @default.
- W2513216991 hasRelatedWork W3071641682 @default.
- W2513216991 isParatext "false" @default.
- W2513216991 isRetracted "false" @default.
- W2513216991 magId "2513216991" @default.
- W2513216991 workType "article" @default.