Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384470941> ?p ?o ?g. }
- W4384470941 abstract "Soil temperature (TS) is a crucial parameter in many fields, especially agriculture. In developing countries like Algeria, the soil temperatures (TS) and the meteorological data are limited. This study investigates the use of Extreme Learning Machine (ELM) for the accurate prediction of daily ST at three different depths (30 cm, 60 cm, and 100 cm) using a minimal number of climatic inputs. The inputs used in this study include maximum and minimum air temperatures, relative humidity, and day of the year (DOY) as a representative of the temporal component. Five different combinations of inputs were used to develop ELM models and determine the best set of input variables. The ELM models were then compared with traditional methods such as multiple linear regression, artificial neural networks, and adaptive neuro-fuzzy inference system. Based on evaluation metrics such as R, RMSE, and MAPE, the ELM models with air temperatures and DOY as inputs (ELM-M0 and ELM-M3) demonstrated superior performance at all depths when compared to the other techniques. The most accurate predictions were found at a depth of 100 cm using the ELM-M3 model, which employed inputs of minimum and maximum air temperatures and DOY, with R value of 0.98, RMSE of 0.68 °C, and MAPE of 3.4%. The results demonstrate that the inclusion of DOY in the climatic dataset significantly enhances the performance and accuracy of machine learning models for ST prediction. The ELM was found to be a fast, simple, effective, and useful tool for TS prediction." @default.
- W4384470941 created "2023-07-17" @default.
- W4384470941 creator A5045375904 @default.
- W4384470941 creator A5082732019 @default.
- W4384470941 date "2023-07-16" @default.
- W4384470941 modified "2023-09-25" @default.
- W4384470941 title "Extreme learning machine for soil temperature prediction using only air temperature as input" @default.
- W4384470941 cites W1124861640 @default.
- W4384470941 cites W1132038451 @default.
- W4384470941 cites W1740585449 @default.
- W4384470941 cites W1870036743 @default.
- W4384470941 cites W1972641521 @default.
- W4384470941 cites W1974182808 @default.
- W4384470941 cites W1979182925 @default.
- W4384470941 cites W1983188045 @default.
- W4384470941 cites W1983945090 @default.
- W4384470941 cites W1986241067 @default.
- W4384470941 cites W1989665358 @default.
- W4384470941 cites W1993717606 @default.
- W4384470941 cites W1999112280 @default.
- W4384470941 cites W2004742220 @default.
- W4384470941 cites W2007262340 @default.
- W4384470941 cites W2019207321 @default.
- W4384470941 cites W2046936767 @default.
- W4384470941 cites W2049275357 @default.
- W4384470941 cites W2061540890 @default.
- W4384470941 cites W2080184475 @default.
- W4384470941 cites W2081036931 @default.
- W4384470941 cites W2082548142 @default.
- W4384470941 cites W2090587727 @default.
- W4384470941 cites W2090707328 @default.
- W4384470941 cites W2093202588 @default.
- W4384470941 cites W2097202102 @default.
- W4384470941 cites W2106721205 @default.
- W4384470941 cites W2108121251 @default.
- W4384470941 cites W2111072639 @default.
- W4384470941 cites W2121971770 @default.
- W4384470941 cites W2134603844 @default.
- W4384470941 cites W2138795008 @default.
- W4384470941 cites W2146165890 @default.
- W4384470941 cites W2167150744 @default.
- W4384470941 cites W2327641771 @default.
- W4384470941 cites W2339447311 @default.
- W4384470941 cites W2343616468 @default.
- W4384470941 cites W2346419773 @default.
- W4384470941 cites W2568438559 @default.
- W4384470941 cites W2586872059 @default.
- W4384470941 cites W2608837339 @default.
- W4384470941 cites W2609607268 @default.
- W4384470941 cites W2618548677 @default.
- W4384470941 cites W2751773190 @default.
- W4384470941 cites W2805995599 @default.
- W4384470941 cites W2809928955 @default.
- W4384470941 cites W2869473304 @default.
- W4384470941 cites W2902947938 @default.
- W4384470941 cites W2904794441 @default.
- W4384470941 cites W2905485021 @default.
- W4384470941 cites W2921836670 @default.
- W4384470941 cites W2941966292 @default.
- W4384470941 cites W2994602700 @default.
- W4384470941 cites W3009054973 @default.
- W4384470941 cites W3036869571 @default.
- W4384470941 cites W3045683890 @default.
- W4384470941 cites W3200442999 @default.
- W4384470941 cites W332085899 @default.
- W4384470941 cites W4256261962 @default.
- W4384470941 cites W768109304 @default.
- W4384470941 doi "https://doi.org/10.1007/s10661-023-11566-2" @default.
- W4384470941 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37454387" @default.
- W4384470941 hasPublicationYear "2023" @default.
- W4384470941 type Work @default.
- W4384470941 citedByCount "0" @default.
- W4384470941 crossrefType "journal-article" @default.
- W4384470941 hasAuthorship W4384470941A5045375904 @default.
- W4384470941 hasAuthorship W4384470941A5082732019 @default.
- W4384470941 hasBestOaLocation W43844709412 @default.
- W4384470941 hasConcept C105795698 @default.
- W4384470941 hasConcept C119857082 @default.
- W4384470941 hasConcept C139945424 @default.
- W4384470941 hasConcept C154945302 @default.
- W4384470941 hasConcept C186108316 @default.
- W4384470941 hasConcept C195975749 @default.
- W4384470941 hasConcept C2780150128 @default.
- W4384470941 hasConcept C33923547 @default.
- W4384470941 hasConcept C39432304 @default.
- W4384470941 hasConcept C41008148 @default.
- W4384470941 hasConcept C48921125 @default.
- W4384470941 hasConcept C50644808 @default.
- W4384470941 hasConcept C58166 @default.
- W4384470941 hasConceptScore W4384470941C105795698 @default.
- W4384470941 hasConceptScore W4384470941C119857082 @default.
- W4384470941 hasConceptScore W4384470941C139945424 @default.
- W4384470941 hasConceptScore W4384470941C154945302 @default.
- W4384470941 hasConceptScore W4384470941C186108316 @default.
- W4384470941 hasConceptScore W4384470941C195975749 @default.
- W4384470941 hasConceptScore W4384470941C2780150128 @default.
- W4384470941 hasConceptScore W4384470941C33923547 @default.
- W4384470941 hasConceptScore W4384470941C39432304 @default.
- W4384470941 hasConceptScore W4384470941C41008148 @default.
- W4384470941 hasConceptScore W4384470941C48921125 @default.