Matches in SemOpenAlex for { <https://semopenalex.org/work/W2089424411> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W2089424411 endingPage "387" @default.
- W2089424411 startingPage "371" @default.
- W2089424411 abstract "Abstract Methane emissions from a longwall ventilation system are an important indicator of how much methane a particular mine is producing and how much air should be provided to keep the methane levels under statutory limits. Knowing the amount of ventilation methane emission is also important for environmental considerations and for identifying opportunities to capture and utilize the methane for energy production. Prediction of methane emissions before mining is difficult since it depends on a number of geological, geographical, and operational factors. This study proposes a principle component analysis (PCA) and artificial neural network (ANN)-based approach to predict the ventilation methane emission rates of U.S. longwall mines. Ventilation emission data obtained from 63 longwall mines in 10 states for the years between 1985 and 2005 were combined with corresponding coalbed properties, geographical information, and longwall operation parameters. The compiled database resulted in 17 parameters that potentially impacted emissions. PCA was used to determine those variables that most influenced ventilation emissions and were considered for further predictive modeling using ANN. Different combinations of variables in the data set and network structures were used for network training and testing to achieve minimum mean square errors and high correlations between measurements and predictions. The resultant ANN model using nine main input variables was superior to multilinear and second-order non-linear models for predicting the new data. The ANN model predicted methane emissions with high accuracy. It is concluded that the model can be used as a predictive tool since it includes those factors that influence longwall ventilation emission rates." @default.
- W2089424411 created "2016-06-24" @default.
- W2089424411 creator A5086772514 @default.
- W2089424411 date "2008-02-01" @default.
- W2089424411 modified "2023-10-13" @default.
- W2089424411 title "Modeling and prediction of ventilation methane emissions of U.S. longwall mines using supervised artificial neural networks" @default.
- W2089424411 cites W1541662325 @default.
- W2089424411 cites W1985416021 @default.
- W2089424411 cites W1987667670 @default.
- W2089424411 cites W1991041654 @default.
- W2089424411 cites W1998442441 @default.
- W2089424411 cites W2008071947 @default.
- W2089424411 cites W2012508940 @default.
- W2089424411 cites W2039786974 @default.
- W2089424411 cites W2043151388 @default.
- W2089424411 cites W2056411474 @default.
- W2089424411 cites W2058044542 @default.
- W2089424411 cites W2064053953 @default.
- W2089424411 cites W2064695941 @default.
- W2089424411 cites W2064820716 @default.
- W2089424411 cites W2084965880 @default.
- W2089424411 cites W2137983211 @default.
- W2089424411 cites W2166186246 @default.
- W2089424411 doi "https://doi.org/10.1016/j.coal.2007.09.003" @default.
- W2089424411 hasPublicationYear "2008" @default.
- W2089424411 type Work @default.
- W2089424411 sameAs 2089424411 @default.
- W2089424411 citedByCount "104" @default.
- W2089424411 countsByYear W20894244112012 @default.
- W2089424411 countsByYear W20894244112013 @default.
- W2089424411 countsByYear W20894244112014 @default.
- W2089424411 countsByYear W20894244112015 @default.
- W2089424411 countsByYear W20894244112016 @default.
- W2089424411 countsByYear W20894244112017 @default.
- W2089424411 countsByYear W20894244112018 @default.
- W2089424411 countsByYear W20894244112019 @default.
- W2089424411 countsByYear W20894244112020 @default.
- W2089424411 countsByYear W20894244112021 @default.
- W2089424411 countsByYear W20894244112022 @default.
- W2089424411 countsByYear W20894244112023 @default.
- W2089424411 crossrefType "journal-article" @default.
- W2089424411 hasAuthorship W2089424411A5086772514 @default.
- W2089424411 hasConcept C127313418 @default.
- W2089424411 hasConcept C127413603 @default.
- W2089424411 hasConcept C154945302 @default.
- W2089424411 hasConcept C16674752 @default.
- W2089424411 hasConcept C18903297 @default.
- W2089424411 hasConcept C200457457 @default.
- W2089424411 hasConcept C39432304 @default.
- W2089424411 hasConcept C41008148 @default.
- W2089424411 hasConcept C50644808 @default.
- W2089424411 hasConcept C516920438 @default.
- W2089424411 hasConcept C548081761 @default.
- W2089424411 hasConcept C78519656 @default.
- W2089424411 hasConcept C78762247 @default.
- W2089424411 hasConcept C86803240 @default.
- W2089424411 hasConceptScore W2089424411C127313418 @default.
- W2089424411 hasConceptScore W2089424411C127413603 @default.
- W2089424411 hasConceptScore W2089424411C154945302 @default.
- W2089424411 hasConceptScore W2089424411C16674752 @default.
- W2089424411 hasConceptScore W2089424411C18903297 @default.
- W2089424411 hasConceptScore W2089424411C200457457 @default.
- W2089424411 hasConceptScore W2089424411C39432304 @default.
- W2089424411 hasConceptScore W2089424411C41008148 @default.
- W2089424411 hasConceptScore W2089424411C50644808 @default.
- W2089424411 hasConceptScore W2089424411C516920438 @default.
- W2089424411 hasConceptScore W2089424411C548081761 @default.
- W2089424411 hasConceptScore W2089424411C78519656 @default.
- W2089424411 hasConceptScore W2089424411C78762247 @default.
- W2089424411 hasConceptScore W2089424411C86803240 @default.
- W2089424411 hasIssue "3-4" @default.
- W2089424411 hasLocation W20894244111 @default.
- W2089424411 hasOpenAccess W2089424411 @default.
- W2089424411 hasPrimaryLocation W20894244111 @default.
- W2089424411 hasRelatedWork W1985401686 @default.
- W2089424411 hasRelatedWork W2035444882 @default.
- W2089424411 hasRelatedWork W2048213226 @default.
- W2089424411 hasRelatedWork W2383255080 @default.
- W2089424411 hasRelatedWork W2529448872 @default.
- W2089424411 hasRelatedWork W2906446976 @default.
- W2089424411 hasRelatedWork W2912796002 @default.
- W2089424411 hasRelatedWork W3166433123 @default.
- W2089424411 hasRelatedWork W325618420 @default.
- W2089424411 hasRelatedWork W4283067741 @default.
- W2089424411 hasVolume "73" @default.
- W2089424411 isParatext "false" @default.
- W2089424411 isRetracted "false" @default.
- W2089424411 magId "2089424411" @default.
- W2089424411 workType "article" @default.