[HTML][HTML] Imputation of missing daily rainfall data; A comparison between artificial intelligence and statistical techniques
Handling missing values is a critical component of the data processing in hydrological
modeling. The key objective of this research is to assess statistical techniques (STs) and …
modeling. The key objective of this research is to assess statistical techniques (STs) and …
Utilization of Machine Learning Approaches for Rainfall Data Imputation: A Systematic Literature Review
W Abdillah, S Fauziati… - … Conference on Computer …, 2023 - ieeexplore.ieee.org
Incomplete data is a frequent issue in rainfall observation data records which can affect the
results of analysis or modeling using rainfall data. Incompleteness of rainfall data can occur …
results of analysis or modeling using rainfall data. Incompleteness of rainfall data can occur …
Missing rainfall data estimation using artificial neural network and nearest neighbor imputation
Handling the missing values play important step in the preprocessing phase of hydrological
modeling analysis. One of the challenges in preprocessing phase is to deal with the …
modeling analysis. One of the challenges in preprocessing phase is to deal with the …
Estimating missing daily rainfall data via artificial neural network over peninsular Malaysia
WS Loh - 2021 - eprints.utar.edu.my
The presence of missing rainfall data has always known to be an obstacle for rain gauge
stations to preserve a serially complete real time rainfall database. Various techniques were …
stations to preserve a serially complete real time rainfall database. Various techniques were …