FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3149698533> ?p ?o ?g. }

• W3149698533 abstract "In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Networks and a simple Group Contribution Method (ANN–GCM). For model comprehensiveness, materials were chosen from various families. Most of materials are from 12 families. Vapor pressure data of 100 compounds is used to train, validate and test the ANN-GCM model. Vapor pressure data were taken from literature for wide ranges of temperature (68.55-559.15 K). Based on results, the best structure for feed-forward back propagation neural network is Levenberg-Marquardt back propagation training algorithm, logsig transfer function for hidden layer and linear transfer function for output layer. The multiplayer network model consists of temperature, acentric factor, critical temperature, critical pressure and the structure of molecules as inputs, 10 neurons in the hidden layer and one neuron in the output layer corresponding to vapor pressure. The weights are optimized to minimize error between experimental and calculated data. Results show that optimum neural network architecture is able to predict vapor pressure data with an acceptable level. The trained network predicts the vapor pressure data with average relative deviation percent of 1.18%." @default.
• W3149698533 created "2021-04-13" @default.
• W3149698533 creator A5006248907 @default.
• W3149698533 creator A5012106666 @default.
• W3149698533 date "2015-01-01" @default.
• W3149698533 modified "2023-09-24" @default.
• W3149698533 title "Prediction of the Liquid Vapor Pressure Using the Artificial Neural Network-Group Contribution Method" @default.
• W3149698533 cites W167932096 @default.
• W3149698533 cites W1969191121 @default.
• W3149698533 cites W1969580317 @default.
• W3149698533 cites W1974041460 @default.
• W3149698533 cites W1974293275 @default.
• W3149698533 cites W1978657141 @default.
• W3149698533 cites W1991691351 @default.
• W3149698533 cites W1992691508 @default.
• W3149698533 cites W1996498195 @default.
• W3149698533 cites W2006159911 @default.
• W3149698533 cites W2008442493 @default.
• W3149698533 cites W2009116977 @default.
• W3149698533 cites W2009393178 @default.
• W3149698533 cites W2014793734 @default.
• W3149698533 cites W2014913895 @default.
• W3149698533 cites W2016173878 @default.
• W3149698533 cites W2019665278 @default.
• W3149698533 cites W2021136490 @default.
• W3149698533 cites W2024036762 @default.
• W3149698533 cites W2025237310 @default.
• W3149698533 cites W2028015892 @default.
• W3149698533 cites W2029472915 @default.
• W3149698533 cites W2031179965 @default.
• W3149698533 cites W2031952333 @default.
• W3149698533 cites W2032500947 @default.
• W3149698533 cites W2033462180 @default.
• W3149698533 cites W2040563899 @default.
• W3149698533 cites W2040813822 @default.
• W3149698533 cites W2042654012 @default.
• W3149698533 cites W2047351099 @default.
• W3149698533 cites W2056022500 @default.
• W3149698533 cites W2059098418 @default.
• W3149698533 cites W2067342842 @default.
• W3149698533 cites W2069717437 @default.
• W3149698533 cites W2072395974 @default.
• W3149698533 cites W2079159371 @default.
• W3149698533 cites W2079604771 @default.
• W3149698533 cites W2080735343 @default.
• W3149698533 cites W2088941859 @default.
• W3149698533 cites W2089353382 @default.
• W3149698533 cites W2090667566 @default.
• W3149698533 cites W2093905546 @default.
• W3149698533 cites W2097801537 @default.
• W3149698533 cites W2110139942 @default.
• W3149698533 cites W2237519698 @default.
• W3149698533 cites W2312908317 @default.
• W3149698533 cites W2319793333 @default.
• W3149698533 cites W2324156692 @default.
• W3149698533 cites W2327000361 @default.
• W3149698533 cites W2327878591 @default.
• W3149698533 cites W2333527301 @default.
• W3149698533 cites W2579757603 @default.
• W3149698533 hasPublicationYear "2015" @default.
• W3149698533 type Work @default.
• W3149698533 sameAs 3149698533 @default.
• W3149698533 citedByCount "0" @default.
• W3149698533 crossrefType "journal-article" @default.
• W3149698533 hasAuthorship W3149698533A5006248907 @default.
• W3149698533 hasAuthorship W3149698533A5012106666 @default.
• W3149698533 hasConcept C11413529 @default.
• W3149698533 hasConcept C119599485 @default.
• W3149698533 hasConcept C121332964 @default.
• W3149698533 hasConcept C127413603 @default.
• W3149698533 hasConcept C154945302 @default.
• W3149698533 hasConcept C155032097 @default.
• W3149698533 hasConcept C163115403 @default.
• W3149698533 hasConcept C19184958 @default.
• W3149698533 hasConcept C41008148 @default.
• W3149698533 hasConcept C50644808 @default.
• W3149698533 hasConcept C81299745 @default.
• W3149698533 hasConcept C97355855 @default.
• W3149698533 hasConceptScore W3149698533C11413529 @default.
• W3149698533 hasConceptScore W3149698533C119599485 @default.
• W3149698533 hasConceptScore W3149698533C121332964 @default.
• W3149698533 hasConceptScore W3149698533C127413603 @default.
• W3149698533 hasConceptScore W3149698533C154945302 @default.
• W3149698533 hasConceptScore W3149698533C155032097 @default.
• W3149698533 hasConceptScore W3149698533C163115403 @default.
• W3149698533 hasConceptScore W3149698533C19184958 @default.
• W3149698533 hasConceptScore W3149698533C41008148 @default.
• W3149698533 hasConceptScore W3149698533C50644808 @default.
• W3149698533 hasConceptScore W3149698533C81299745 @default.
• W3149698533 hasConceptScore W3149698533C97355855 @default.
• W3149698533 hasLocation W31496985331 @default.
• W3149698533 hasOpenAccess W3149698533 @default.
• W3149698533 hasPrimaryLocation W31496985331 @default.
• W3149698533 hasRelatedWork W1551733436 @default.
• W3149698533 hasRelatedWork W1968528659 @default.
• W3149698533 hasRelatedWork W1974048947 @default.
• W3149698533 hasRelatedWork W2014211982 @default.
• W3149698533 hasRelatedWork W2026509834 @default.
• W3149698533 hasRelatedWork W2052596099 @default.
• W3149698533 hasRelatedWork W2067716082 @default.

• next