FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4375851173> ?p ?o ?g. }

• W4375851173 endingPage "110404" @default.
• W4375851173 startingPage "110404" @default.
• W4375851173 abstract "This study presents a comprehensive analysis of the model development (structure, parameter settings, and prediction accuracy) and generalization ability of neural networks in the classroom setting. A normalized database for model prediction and verification including indoor parameters from 27 high school classrooms over the course of four semesters was set up (a total of 14,112 sets of data for each variable). Three different models were compared: a back propagation artificial neural network (BP-ANN), a nonlinear autoregressive exogenous neural network (NARX), and a long-term and short-term memory neural network (LSTM). For the prediction of PM1 and PM2.5, which are impacted by outdoor PM concentrations, the best performance was achieved by the NARX model: the mean absolute percentage error (MAPE), root mean squared error (RMSE), and coefficient of determination (R2) were 41–55%, 0.45–1.27 μg/m3, and 0.81–0.87, respectively. The R2 of this model was 22% higher than that of the BP-ANN model and much higher than that of the LSTM model. For the prediction of indoor PM10, which are mostly emitted by indoor sources, relatively good performance was achieved by the LSTM model. The trained NARX model was used successfully to predict indoor time-series PM2.5 concentration and source strength in classrooms in five Chinese cities and five American cities. The calculated indoor source strength was 95.5–119.1 μg/h/P, within the range of the measured indoor source strength. The indoor PM2.5 concentrations calculated by a theoretical equation without the consideration of indoor source were 20.8–60.0% smaller than those calculated by the trained model." @default.
• W4375851173 created "2023-05-10" @default.
• W4375851173 creator A5028167410 @default.
• W4375851173 creator A5068415637 @default.
• W4375851173 creator A5086179365 @default.
• W4375851173 date "2023-06-01" @default.
• W4375851173 modified "2023-10-16" @default.
• W4375851173 title "Predicting indoor particle concentration in mechanically ventilated classrooms using neural networks: Model development and generalization ability analysis" @default.
• W4375851173 cites W1997692396 @default.
• W4375851173 cites W2011674622 @default.
• W4375851173 cites W2102031662 @default.
• W4375851173 cites W2165297076 @default.
• W4375851173 cites W2282992258 @default.
• W4375851173 cites W2294387094 @default.
• W4375851173 cites W2337481356 @default.
• W4375851173 cites W2739853341 @default.
• W4375851173 cites W2912731314 @default.
• W4375851173 cites W2951487696 @default.
• W4375851173 cites W2955624416 @default.
• W4375851173 cites W2960192598 @default.
• W4375851173 cites W2971118550 @default.
• W4375851173 cites W2977184265 @default.
• W4375851173 cites W3004417816 @default.
• W4375851173 cites W3006914608 @default.
• W4375851173 cites W3024905798 @default.
• W4375851173 cites W3029394071 @default.
• W4375851173 cites W3032966855 @default.
• W4375851173 cites W3040710200 @default.
• W4375851173 cites W3098296868 @default.
• W4375851173 cites W3123824159 @default.
• W4375851173 cites W3136030885 @default.
• W4375851173 cites W3151387141 @default.
• W4375851173 cites W3173302693 @default.
• W4375851173 cites W3186757313 @default.
• W4375851173 cites W3203676637 @default.
• W4375851173 cites W3209153824 @default.
• W4375851173 cites W3210680523 @default.
• W4375851173 cites W3214865316 @default.
• W4375851173 cites W3215996179 @default.
• W4375851173 cites W4206198657 @default.
• W4375851173 cites W4210481149 @default.
• W4375851173 cites W4213108403 @default.
• W4375851173 cites W4213230978 @default.
• W4375851173 cites W4214705633 @default.
• W4375851173 cites W4220664236 @default.
• W4375851173 cites W4224938447 @default.
• W4375851173 cites W4281680582 @default.
• W4375851173 cites W4281826975 @default.
• W4375851173 cites W4282569737 @default.
• W4375851173 cites W4283463435 @default.
• W4375851173 cites W4289525983 @default.
• W4375851173 cites W4306168981 @default.
• W4375851173 cites W4308744701 @default.
• W4375851173 doi "https://doi.org/10.1016/j.buildenv.2023.110404" @default.
• W4375851173 hasPublicationYear "2023" @default.
• W4375851173 type Work @default.
• W4375851173 citedByCount "0" @default.
• W4375851173 crossrefType "journal-article" @default.
• W4375851173 hasAuthorship W4375851173A5028167410 @default.
• W4375851173 hasAuthorship W4375851173A5068415637 @default.
• W4375851173 hasAuthorship W4375851173A5086179365 @default.
• W4375851173 hasConcept C105795698 @default.
• W4375851173 hasConcept C127413603 @default.
• W4375851173 hasConcept C128990827 @default.
• W4375851173 hasConcept C134306372 @default.
• W4375851173 hasConcept C139945424 @default.
• W4375851173 hasConcept C146978453 @default.
• W4375851173 hasConcept C150217764 @default.
• W4375851173 hasConcept C154945302 @default.
• W4375851173 hasConcept C159877910 @default.
• W4375851173 hasConcept C177148314 @default.
• W4375851173 hasConcept C204323151 @default.
• W4375851173 hasConcept C2780092901 @default.
• W4375851173 hasConcept C33923547 @default.
• W4375851173 hasConcept C39432304 @default.
• W4375851173 hasConcept C41008148 @default.
• W4375851173 hasConcept C42536954 @default.
• W4375851173 hasConcept C50644808 @default.
• W4375851173 hasConceptScore W4375851173C105795698 @default.
• W4375851173 hasConceptScore W4375851173C127413603 @default.
• W4375851173 hasConceptScore W4375851173C128990827 @default.
• W4375851173 hasConceptScore W4375851173C134306372 @default.
• W4375851173 hasConceptScore W4375851173C139945424 @default.
• W4375851173 hasConceptScore W4375851173C146978453 @default.
• W4375851173 hasConceptScore W4375851173C150217764 @default.
• W4375851173 hasConceptScore W4375851173C154945302 @default.
• W4375851173 hasConceptScore W4375851173C159877910 @default.
• W4375851173 hasConceptScore W4375851173C177148314 @default.
• W4375851173 hasConceptScore W4375851173C204323151 @default.
• W4375851173 hasConceptScore W4375851173C2780092901 @default.
• W4375851173 hasConceptScore W4375851173C33923547 @default.
• W4375851173 hasConceptScore W4375851173C39432304 @default.
• W4375851173 hasConceptScore W4375851173C41008148 @default.
• W4375851173 hasConceptScore W4375851173C42536954 @default.
• W4375851173 hasConceptScore W4375851173C50644808 @default.
• W4375851173 hasFunder F4320321001 @default.
• W4375851173 hasFunder F4320322163 @default.
• W4375851173 hasLocation W43758511731 @default.

• next