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- W2001734217 endingPage "5746" @default.
- W2001734217 startingPage "5733" @default.
- W2001734217 abstract "In this work, a database (containing 4360 experimental data points) on water gas shift reaction (WGS) over Pt and Au based catalysts was constructed using the data obtained from the published papers between the years 2002 and 2012. Then, the database was analyzed using three data mining tools to extract knowledge in three areas: Decision trees to determine the empirical rules and conditions that lead to high catalytic performance (high CO conversion); artificial neural networks (ANNs) to determine the relative importance of various catalyst preparation and operational variables and their effects on CO conversion; support vector machines (SVMs) to predict the outcome of unstudied experimental conditions. It was concluded that, all three models were quite successful and they complement each other to extract knowledge from the past published works and to deduce useful trends, rules and correlations, which are not easily comprehensible by the naked eyes." @default.
- W2001734217 created "2016-06-24" @default.
- W2001734217 creator A5057251374 @default.
- W2001734217 creator A5077169073 @default.
- W2001734217 creator A5083517243 @default.
- W2001734217 date "2014-04-01" @default.
- W2001734217 modified "2023-09-30" @default.
- W2001734217 title "Knowledge extraction for water gas shift reaction over noble metal catalysts from publications in the literature between 2002 and 2012" @default.
- W2001734217 cites W101862313 @default.
- W2001734217 cites W1967884154 @default.
- W2001734217 cites W1968551433 @default.
- W2001734217 cites W1968806874 @default.
- W2001734217 cites W1971014296 @default.
- W2001734217 cites W1973045231 @default.
- W2001734217 cites W1974020598 @default.
- W2001734217 cites W1974218023 @default.
- W2001734217 cites W1974380584 @default.
- W2001734217 cites W1974485531 @default.
- W2001734217 cites W1977086660 @default.
- W2001734217 cites W1977603877 @default.
- W2001734217 cites W1981749487 @default.
- W2001734217 cites W1982668744 @default.
- W2001734217 cites W1990019557 @default.
- W2001734217 cites W1994259651 @default.
- W2001734217 cites W1994837831 @default.
- W2001734217 cites W1995906655 @default.
- W2001734217 cites W2008799217 @default.
- W2001734217 cites W2009314188 @default.
- W2001734217 cites W2009570116 @default.
- W2001734217 cites W2009575286 @default.
- W2001734217 cites W2009724999 @default.
- W2001734217 cites W2010457675 @default.
- W2001734217 cites W2013687516 @default.
- W2001734217 cites W2015912400 @default.
- W2001734217 cites W2016317615 @default.
- W2001734217 cites W2016458956 @default.
- W2001734217 cites W2020559106 @default.
- W2001734217 cites W2020766620 @default.
- W2001734217 cites W2022190308 @default.
- W2001734217 cites W2023938284 @default.
- W2001734217 cites W2024176887 @default.
- W2001734217 cites W2027858784 @default.
- W2001734217 cites W2031959569 @default.
- W2001734217 cites W2033955352 @default.
- W2001734217 cites W2037415288 @default.
- W2001734217 cites W2043020900 @default.
- W2001734217 cites W2044381379 @default.
- W2001734217 cites W2048389041 @default.
- W2001734217 cites W2051005593 @default.
- W2001734217 cites W2052529734 @default.
- W2001734217 cites W2054335083 @default.
- W2001734217 cites W2054844841 @default.
- W2001734217 cites W2056330545 @default.
- W2001734217 cites W2056889689 @default.
- W2001734217 cites W2058804659 @default.
- W2001734217 cites W2061649139 @default.
- W2001734217 cites W2062541345 @default.
- W2001734217 cites W2066539876 @default.
- W2001734217 cites W2067011550 @default.
- W2001734217 cites W2069576432 @default.
- W2001734217 cites W2070128489 @default.
- W2001734217 cites W2070482188 @default.
- W2001734217 cites W2071878759 @default.
- W2001734217 cites W2074158698 @default.
- W2001734217 cites W2077303396 @default.
- W2001734217 cites W2077667363 @default.
- W2001734217 cites W2083383840 @default.
- W2001734217 cites W2083970451 @default.
- W2001734217 cites W2084077217 @default.
- W2001734217 cites W2085832182 @default.
- W2001734217 cites W2086774514 @default.
- W2001734217 cites W2087822421 @default.
- W2001734217 cites W2089828291 @default.
- W2001734217 cites W2091881056 @default.
- W2001734217 cites W2092379976 @default.
- W2001734217 cites W2092626962 @default.
- W2001734217 cites W2095369191 @default.
- W2001734217 cites W2095446125 @default.
- W2001734217 cites W2100357645 @default.
- W2001734217 cites W2104179786 @default.
- W2001734217 cites W2115220647 @default.
- W2001734217 cites W2129665392 @default.
- W2001734217 cites W2129978092 @default.
- W2001734217 cites W2132613504 @default.
- W2001734217 cites W2133960502 @default.
- W2001734217 cites W2133990480 @default.
- W2001734217 cites W2141644301 @default.
- W2001734217 cites W2153569781 @default.
- W2001734217 cites W2159211917 @default.
- W2001734217 cites W2323062365 @default.
- W2001734217 cites W2324248953 @default.
- W2001734217 cites W2324632367 @default.
- W2001734217 cites W2412720018 @default.
- W2001734217 cites W2480828247 @default.
- W2001734217 cites W2582071875 @default.
- W2001734217 cites W260476061 @default.
- W2001734217 cites W4376634008 @default.
- W2001734217 doi "https://doi.org/10.1016/j.ijhydene.2014.01.160" @default.