FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3150752008> ?p ?o ?g. }

• W3150752008 endingPage "626" @default.
• W3150752008 startingPage "605" @default.
• W3150752008 abstract "Abstract Machine learning (ML) has been increasingly adopted due to its ability to model complex and non-linearities between river water temperature (RWT) and its predictors (e.g., Air Temperature, AT). Most of these ML approaches have been applied using average AT without any detailed sensitivity analysis of other forms of AT (e.g., maximum and minimum). The present study demonstrates how new ML approaches, such as ridge regression (RR), K-nearest neighbors (KNN) regressor, random forest (RF) regressor, and support vector regression (SVR), can be coupled with Sobol’ global sensitivity analysis (GSA) to predict accurate RWT estimates with the most appropriate form of AT. Furthermore, the proposed ML approaches have been combined with the Ensemble Kalman Filter (EnKF), a data assimilation (DA) technique to improve the predicted values based on the measured data. The proposed modelling framework's effectiveness is demonstrated with a tropical river system of India, Tunga-Bhadra River, as a case study. The SVR has been noted as the most robust ML model to predict RWT at a monthly time scale compared with daily and seasonal. The study demonstrates how ML methods can be coupled with a global sensitivity algorithm and DA techniques to generate accurate RWT predictions in river water quality modelling." @default.
• W3150752008 created "2021-04-13" @default.
• W3150752008 creator A5038516849 @default.
• W3150752008 creator A5072761437 @default.
• W3150752008 date "2021-04-07" @default.
• W3150752008 modified "2023-10-10" @default.
• W3150752008 title "Prediction of river water temperature using machine learning algorithms: a tropical river system of India" @default.
• W3150752008 cites W1749851208 @default.
• W3150752008 cites W1964450499 @default.
• W3150752008 cites W1968317731 @default.
• W3150752008 cites W1972609382 @default.
• W3150752008 cites W1974614011 @default.
• W3150752008 cites W1974756800 @default.
• W3150752008 cites W1976676731 @default.
• W3150752008 cites W1989910206 @default.
• W3150752008 cites W1997823550 @default.
• W3150752008 cites W1998027527 @default.
• W3150752008 cites W2004655349 @default.
• W3150752008 cites W2009056490 @default.
• W3150752008 cites W2009463445 @default.
• W3150752008 cites W2021638339 @default.
• W3150752008 cites W2022783833 @default.
• W3150752008 cites W2025867198 @default.
• W3150752008 cites W2026645785 @default.
• W3150752008 cites W2030043236 @default.
• W3150752008 cites W2033904036 @default.
• W3150752008 cites W2035174903 @default.
• W3150752008 cites W2035682098 @default.
• W3150752008 cites W2038098184 @default.
• W3150752008 cites W2041202986 @default.
• W3150752008 cites W2042262906 @default.
• W3150752008 cites W2050022705 @default.
• W3150752008 cites W2057705926 @default.
• W3150752008 cites W2064424033 @default.
• W3150752008 cites W2073453836 @default.
• W3150752008 cites W2078621841 @default.
• W3150752008 cites W2084172666 @default.
• W3150752008 cites W2088765131 @default.
• W3150752008 cites W2088876159 @default.
• W3150752008 cites W2097196347 @default.
• W3150752008 cites W2101589741 @default.
• W3150752008 cites W2122111042 @default.
• W3150752008 cites W2125931262 @default.
• W3150752008 cites W2126890351 @default.
• W3150752008 cites W2127403333 @default.
• W3150752008 cites W2135134353 @default.
• W3150752008 cites W2141007997 @default.
• W3150752008 cites W2145781284 @default.
• W3150752008 cites W2147984563 @default.
• W3150752008 cites W2157098139 @default.
• W3150752008 cites W2158159695 @default.
• W3150752008 cites W2167126571 @default.
• W3150752008 cites W2168313526 @default.
• W3150752008 cites W2168458287 @default.
• W3150752008 cites W2170273899 @default.
• W3150752008 cites W2190225614 @default.
• W3150752008 cites W2190286232 @default.
• W3150752008 cites W2286333062 @default.
• W3150752008 cites W2290873233 @default.
• W3150752008 cites W2292167608 @default.
• W3150752008 cites W2347057720 @default.
• W3150752008 cites W2428180765 @default.
• W3150752008 cites W2467099544 @default.
• W3150752008 cites W2468477327 @default.
• W3150752008 cites W2474376079 @default.
• W3150752008 cites W2569457803 @default.
• W3150752008 cites W2587306689 @default.
• W3150752008 cites W2599704556 @default.
• W3150752008 cites W2605732569 @default.
• W3150752008 cites W2735434310 @default.
• W3150752008 cites W2753937361 @default.
• W3150752008 cites W2756376687 @default.
• W3150752008 cites W2785712409 @default.
• W3150752008 cites W2786467596 @default.
• W3150752008 cites W2788939438 @default.
• W3150752008 cites W2792277382 @default.
• W3150752008 cites W2801177356 @default.
• W3150752008 cites W2801896044 @default.
• W3150752008 cites W2807044567 @default.
• W3150752008 cites W2895395273 @default.
• W3150752008 cites W2900276876 @default.
• W3150752008 cites W2911964244 @default.
• W3150752008 cites W2921836670 @default.
• W3150752008 cites W2923781542 @default.
• W3150752008 cites W2948035356 @default.
• W3150752008 cites W2955085624 @default.
• W3150752008 cites W2972302268 @default.
• W3150752008 cites W3006101764 @default.
• W3150752008 cites W3036893550 @default.
• W3150752008 cites W4234698323 @default.
• W3150752008 doi "https://doi.org/10.2166/hydro.2021.121" @default.
• W3150752008 hasPublicationYear "2021" @default.
• W3150752008 type Work @default.
• W3150752008 sameAs 3150752008 @default.
• W3150752008 citedByCount "10" @default.
• W3150752008 countsByYear W31507520082022 @default.
• W3150752008 countsByYear W31507520082023 @default.
• W3150752008 crossrefType "journal-article" @default.

• next