Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313515431> ?p ?o ?g. }
- W4313515431 endingPage "509" @default.
- W4313515431 startingPage "509" @default.
- W4313515431 abstract "Interest in biomass has increased due to current environmental issues, and biomass analysis is usually performed using element and proximate analyses to ascertain its fuel characteristics. Mainly, element component prediction models have been developed based on proximate analysis, yet few studies have predicted proximate components based on element analysis. Hence, this study developed a proximate component prediction model following the calorific value calculation. Analysis of Pearson’s correlation coefficient showed that volatile matter (VM) and fixed carbon (FC) were positively correlated with hydrogen and oxygen, and with carbon, respectively. Thus, the model correlation was developed using a combination of the “stepwise” and “enter” methods along with linear or nonlinear regressions. The optimal models were developed for VM and ash content (Ash). The VM optimal model values were: R2 = 0.9402, root-mean-square error (RMSE) = 7.0063, average absolute error (AAE) = 14.8170%, and average bias error (ABE) = −11.7862%. For Ash, the values were: R2 = 0.9249, RMSE = 2.9614, AAE = 168.9028%, and ABE = 167.2849%, and for FC, the values were: R2 = 9505, RMSE = 6.3214, AAE = 18.3199%, and ABE = 15.0094%. This study provides a model to predict the proximate component by element analysis. Contrary to existing method, proximate analysis can be predicted based on elemental analysis, and shows that consume samples can be performed at once." @default.
- W4313515431 created "2023-01-06" @default.
- W4313515431 creator A5035023285 @default.
- W4313515431 creator A5037482593 @default.
- W4313515431 creator A5060055185 @default.
- W4313515431 creator A5063483243 @default.
- W4313515431 creator A5086816455 @default.
- W4313515431 date "2023-01-02" @default.
- W4313515431 modified "2023-10-15" @default.
- W4313515431 title "Developing a Proximate Component Prediction Model of Biomass Based on Element Analysis" @default.
- W4313515431 cites W1839451719 @default.
- W4313515431 cites W1975057776 @default.
- W4313515431 cites W1984325256 @default.
- W4313515431 cites W1990719311 @default.
- W4313515431 cites W1993510483 @default.
- W4313515431 cites W2012694910 @default.
- W4313515431 cites W2016062622 @default.
- W4313515431 cites W2038218867 @default.
- W4313515431 cites W2044969119 @default.
- W4313515431 cites W2047007942 @default.
- W4313515431 cites W2053727082 @default.
- W4313515431 cites W2065888511 @default.
- W4313515431 cites W2068286237 @default.
- W4313515431 cites W2068733733 @default.
- W4313515431 cites W2087616324 @default.
- W4313515431 cites W2090758660 @default.
- W4313515431 cites W2099428723 @default.
- W4313515431 cites W2103805660 @default.
- W4313515431 cites W2139474336 @default.
- W4313515431 cites W2160715470 @default.
- W4313515431 cites W2257531027 @default.
- W4313515431 cites W2322101761 @default.
- W4313515431 cites W2466095297 @default.
- W4313515431 cites W2563176325 @default.
- W4313515431 cites W2563353077 @default.
- W4313515431 cites W2596798111 @default.
- W4313515431 cites W2597097757 @default.
- W4313515431 cites W2605363270 @default.
- W4313515431 cites W2742964162 @default.
- W4313515431 cites W2752380498 @default.
- W4313515431 cites W2782207599 @default.
- W4313515431 cites W2799454763 @default.
- W4313515431 cites W2800938341 @default.
- W4313515431 cites W2889105136 @default.
- W4313515431 cites W2891005877 @default.
- W4313515431 cites W2912074501 @default.
- W4313515431 cites W2914573379 @default.
- W4313515431 cites W2955068814 @default.
- W4313515431 cites W2969343624 @default.
- W4313515431 cites W2973201497 @default.
- W4313515431 cites W2981684961 @default.
- W4313515431 cites W2997394973 @default.
- W4313515431 cites W2999931441 @default.
- W4313515431 cites W3011476212 @default.
- W4313515431 cites W3041313760 @default.
- W4313515431 cites W3042633634 @default.
- W4313515431 cites W3092027487 @default.
- W4313515431 cites W3124031981 @default.
- W4313515431 cites W3126231553 @default.
- W4313515431 cites W3134370653 @default.
- W4313515431 cites W3134539865 @default.
- W4313515431 cites W3138468083 @default.
- W4313515431 cites W3202609398 @default.
- W4313515431 cites W3204253514 @default.
- W4313515431 cites W3210245544 @default.
- W4313515431 cites W793913982 @default.
- W4313515431 doi "https://doi.org/10.3390/en16010509" @default.
- W4313515431 hasPublicationYear "2023" @default.
- W4313515431 type Work @default.
- W4313515431 citedByCount "3" @default.
- W4313515431 countsByYear W43135154312023 @default.
- W4313515431 crossrefType "journal-article" @default.
- W4313515431 hasAuthorship W4313515431A5035023285 @default.
- W4313515431 hasAuthorship W4313515431A5037482593 @default.
- W4313515431 hasAuthorship W4313515431A5060055185 @default.
- W4313515431 hasAuthorship W4313515431A5063483243 @default.
- W4313515431 hasAuthorship W4313515431A5086816455 @default.
- W4313515431 hasBestOaLocation W43135154311 @default.
- W4313515431 hasConcept C104779481 @default.
- W4313515431 hasConcept C105795698 @default.
- W4313515431 hasConcept C105923489 @default.
- W4313515431 hasConcept C11413529 @default.
- W4313515431 hasConcept C115540264 @default.
- W4313515431 hasConcept C139945424 @default.
- W4313515431 hasConcept C140205800 @default.
- W4313515431 hasConcept C156383657 @default.
- W4313515431 hasConcept C178790620 @default.
- W4313515431 hasConcept C185592680 @default.
- W4313515431 hasConcept C18903297 @default.
- W4313515431 hasConcept C22354355 @default.
- W4313515431 hasConcept C2780092901 @default.
- W4313515431 hasConcept C2780539549 @default.
- W4313515431 hasConcept C31903555 @default.
- W4313515431 hasConcept C33923547 @default.
- W4313515431 hasConcept C39432304 @default.
- W4313515431 hasConcept C48921125 @default.
- W4313515431 hasConcept C64885871 @default.
- W4313515431 hasConcept C86803240 @default.