FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1996750440> ?p ?o ?g. }

• W1996750440 endingPage "117" @default.
• W1996750440 startingPage "108" @default.
• W1996750440 abstract "Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987–1991) of measurements of independent variables of rainfall and runoff values. The models used in the study were Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) which are Artificial Intelligence (AI) approaches. The applied models were trained and tested using various combinations of the independent variables. The goodness of fit for the model was evaluated in terms of the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and scatter index (SI). A comparison was also made between these models and traditional Multi Linear Regression (MLR) model. The study provides evidence that GEP (with RMSE=17.82 l/s, MAE=6.61 l/s, CE=0.72 and R2=0.978) is capable of modeling rainfall-runoff process and is a viable alternative to other applied artificial intelligence and MLR time-series methods." @default.
• W1996750440 created "2016-06-24" @default.
• W1996750440 creator A5044658695 @default.
• W1996750440 creator A5075190563 @default.
• W1996750440 creator A5081589463 @default.
• W1996750440 date "2013-02-01" @default.
• W1996750440 modified "2023-10-16" @default.
• W1996750440 title "Modeling rainfall-runoff process using soft computing techniques" @default.
• W1996750440 cites W110181068 @default.
• W1996750440 cites W1509600564 @default.
• W1996750440 cites W1971486607 @default.
• W1996750440 cites W1971498752 @default.
• W1996750440 cites W1971801516 @default.
• W1996750440 cites W1973739515 @default.
• W1996750440 cites W1975201621 @default.
• W1996750440 cites W1981751431 @default.
• W1996750440 cites W1988523040 @default.
• W1996750440 cites W1992176519 @default.
• W1996750440 cites W1997052296 @default.
• W1996750440 cites W1998300065 @default.
• W1996750440 cites W1998863178 @default.
• W1996750440 cites W2008429402 @default.
• W1996750440 cites W2009218392 @default.
• W1996750440 cites W2011412119 @default.
• W1996750440 cites W2017703815 @default.
• W1996750440 cites W2019207321 @default.
• W1996750440 cites W2025590911 @default.
• W1996750440 cites W2031292142 @default.
• W1996750440 cites W2032223839 @default.
• W1996750440 cites W2037460094 @default.
• W1996750440 cites W2041925826 @default.
• W1996750440 cites W2055107850 @default.
• W1996750440 cites W2059666149 @default.
• W1996750440 cites W2063756720 @default.
• W1996750440 cites W2072697915 @default.
• W1996750440 cites W2074770406 @default.
• W1996750440 cites W2077967845 @default.
• W1996750440 cites W2079325629 @default.
• W1996750440 cites W2084526672 @default.
• W1996750440 cites W2089686343 @default.
• W1996750440 cites W2090598548 @default.
• W1996750440 cites W2092966701 @default.
• W1996750440 cites W2116671676 @default.
• W1996750440 cites W2122522444 @default.
• W1996750440 cites W2163718649 @default.
• W1996750440 cites W2169690625 @default.
• W1996750440 cites W2170262218 @default.
• W1996750440 cites W2171675708 @default.
• W1996750440 cites W2172147742 @default.
• W1996750440 cites W2323316069 @default.
• W1996750440 cites W2093857752 @default.
• W1996750440 doi "https://doi.org/10.1016/j.cageo.2012.07.001" @default.
• W1996750440 hasPublicationYear "2013" @default.
• W1996750440 type Work @default.
• W1996750440 sameAs 1996750440 @default.
• W1996750440 citedByCount "175" @default.
• W1996750440 countsByYear W19967504402012 @default.
• W1996750440 countsByYear W19967504402013 @default.
• W1996750440 countsByYear W19967504402014 @default.
• W1996750440 countsByYear W19967504402015 @default.
• W1996750440 countsByYear W19967504402016 @default.
• W1996750440 countsByYear W19967504402017 @default.
• W1996750440 countsByYear W19967504402018 @default.
• W1996750440 countsByYear W19967504402019 @default.
• W1996750440 countsByYear W19967504402020 @default.
• W1996750440 countsByYear W19967504402021 @default.
• W1996750440 countsByYear W19967504402022 @default.
• W1996750440 countsByYear W19967504402023 @default.
• W1996750440 crossrefType "journal-article" @default.
• W1996750440 hasAuthorship W1996750440A5044658695 @default.
• W1996750440 hasAuthorship W1996750440A5075190563 @default.
• W1996750440 hasAuthorship W1996750440A5081589463 @default.
• W1996750440 hasConcept C105795698 @default.
• W1996750440 hasConcept C119857082 @default.
• W1996750440 hasConcept C124101348 @default.
• W1996750440 hasConcept C128990827 @default.
• W1996750440 hasConcept C139945424 @default.
• W1996750440 hasConcept C140073362 @default.
• W1996750440 hasConcept C150217764 @default.
• W1996750440 hasConcept C154945302 @default.
• W1996750440 hasConcept C186108316 @default.
• W1996750440 hasConcept C18903297 @default.
• W1996750440 hasConcept C195975749 @default.
• W1996750440 hasConcept C2780092901 @default.
• W1996750440 hasConcept C33923547 @default.
• W1996750440 hasConcept C41008148 @default.
• W1996750440 hasConcept C48921125 @default.
• W1996750440 hasConcept C50477045 @default.
• W1996750440 hasConcept C50644808 @default.
• W1996750440 hasConcept C58166 @default.
• W1996750440 hasConcept C6980683 @default.
• W1996750440 hasConcept C86803240 @default.
• W1996750440 hasConceptScore W1996750440C105795698 @default.
• W1996750440 hasConceptScore W1996750440C119857082 @default.
• W1996750440 hasConceptScore W1996750440C124101348 @default.
• W1996750440 hasConceptScore W1996750440C128990827 @default.
• W1996750440 hasConceptScore W1996750440C139945424 @default.
• W1996750440 hasConceptScore W1996750440C140073362 @default.

• next