Cargando…

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 artificial intelligence-based techniques (AITs) for imputing missing daily rainfall values and recommend a methodology app...

Descripción completa

Detalles Bibliográficos
Autores principales:	Wangwongchai, Angkool, Waqas, Muhammad, Dechpichai, Porntip, Hlaing, Phyo Thandar, Ahmad, Shakeel, Humphries, Usa Wannasingha
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2023
Materias:	Engineering
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10654590/ https://www.ncbi.nlm.nih.gov/pubmed/38023312 http://dx.doi.org/10.1016/j.mex.2023.102459

Ejemplares similares

A Well-Posed Fractional Order Cholera Model with Saturated Incidence Rate
por: Baba, Isa Abdullahi, et al.
Publicado: (2023)

Role of Vaccines in Controlling the Spread of COVID-19: A Fractional-Order Model
por: Baba, Isa Abdullahi, et al.
Publicado: (2023)

Statistical analysis of annual maximum daily rainfall for Nelspruit and its environs
por: Masereka, Eric M., et al.
Publicado: (2018)

Imputation of missing genotypes: an empirical evaluation of IMPUTE
por: Zhao, Zhenming, et al.
Publicado: (2008)

Stochastic COVID-19 SEIQ epidemic model with time-delay
por: Khan, Amir, et al.
Publicado: (2021)

Accounting for missing data in statistical analyses: multiple imputation is not always the answer
por: Hughes, Rachael A, et al.
Publicado: (2019)

A Fractional Order Model Studying the Role of Negative and Positive Attitudes towards Vaccination
por: Baba, Isa Abdullahi, et al.
Publicado: (2022)

Fractional optimal control of COVID-19 pandemic model with generalized Mittag-Leffler function
por: Khan, Amir, et al.
Publicado: (2021)

Flexible imputation of missing data
por: van Buuren, Stef
Publicado: (2018)

Missing Data and Imputation Methods
por: Schober, Patrick, et al.
Publicado: (2020)

Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
por: Seaman, Shaun R, et al.
Publicado: (2012)

Imputation of Missing Values for Multi-Biospecimen Metabolomics Studies: Bias and Effects on Statistical Validity
por: Wilson, Machelle D., et al.
Publicado: (2022)

KOMPUTE: imputing summary statistics of missing phenotypes in high-throughput model organism data
por: Warkentin, Coby, et al.
Publicado: (2023)

Missing value imputation in high-dimensional phenomic data: imputable or not, and how?
por: Liao, Serena G, et al.
Publicado: (2014)

Determination of the impact of rainfall on road accidents in Thailand
por: Sangkharat, Kamolrat, et al.
Publicado: (2021)

Translation and psychometric testing of the Thai version of cancer survivors’ unmet needs measure among cancer survivors
por: Lekdamrongkul, Pichitra, et al.
Publicado: (2022)

A new approach for processing climate missing databases applied to daily rainfall data in Soummam watershed, Algeria
por: Aieb, Amir, et al.
Publicado: (2019)

Missing value imputation for epistatic MAPs
por: Ryan, Colm, et al.
Publicado: (2010)

Imputing missing distances in molecular phylogenetics
por: Xia, Xuhua
Publicado: (2018)

The Frailty Index, Missing Data, and Imputation
por: Pridham, Glen, et al.
Publicado: (2020)

Exploring the nanomechanical concepts of development through recent updates in magnetically guided system
por: Khan, Noor Saeed, et al.
Publicado: (2021)

Modeling the dynamics of COVID-19 with real data from Thailand
por: Ibrahim, Alhassan, et al.
Publicado: (2023)

Imputing missing genotypes: effects of methods and patterns of missing data
por: Ogut, Funda, et al.
Publicado: (2011)

Rainfall statistics, stationarity, and climate change
por: Sun, Fubao, et al.
Publicado: (2018)

COVID-19 Model with High- and Low-Risk Susceptible Population Incorporating the Effect of Vaccines
por: Ibrahim, Alhassan, et al.
Publicado: (2022)

Estimation of missing data of monthly rainfall in southwestern Colombia using artificial neural networks
por: Canchala-Nastar, Teresita, et al.
Publicado: (2019)

Multiple imputation of missing data using SAS
por: Berglund, Patricia A, et al.
Publicado: (2014)

Imputation methods for missing data for polygenic models
por: Fridley, Brooke, et al.
Publicado: (2003)

Imputing missing covariate values for the Cox model
por: White, Ian R, et al.
Publicado: (2009)

SICE: an improved missing data imputation technique
por: Khan, Shahidul Islam, et al.
Publicado: (2020)

Imputation of missing information in worldwide patent data
por: de Rassenfosse, Gaétan, et al.
Publicado: (2020)

Impute the missing data using retrieved dropouts
por: Wang, Shuai, et al.
Publicado: (2022)

Imputing Missing Data in Hourly Traffic Counts
por: Shafique, Muhammad Awais
Publicado: (2022)

The importance of batch sensitization in missing value imputation
por: Hui, Harvard Wai Hann, et al.
Publicado: (2023)

A simulation study on missing data imputation for dichotomous variables using statistical and machine learning methods
por: Ge, Yingfeng, et al.
Publicado: (2023)

A new analytical framework for missing data imputation and classification with uncertainty: Missing data imputation and heart failure readmission prediction
por: Hu, Zhiyong, et al.
Publicado: (2020)

Multiple imputation of missing data under missing at random: including a collider as an auxiliary variable in the imputation model can induce bias
por: Curnow, Elinor, et al.
Publicado: (2023)

Comparing Methods to Impute Missing Daily Ground-Level PM(10) Concentrations between 2010–2017 in South Africa
por: Arowosegbe, Oluwaseyi Olalekan, et al.
Publicado: (2021)

Robust imputation method for missing values in microarray data
por: Yoon, Dankyu, et al.
Publicado: (2007)

Comparison of imputation methods for missing laboratory data in medicine
por: Waljee, Akbar K, et al.
Publicado: (2013)

Cannot write session to /tmp/vufind_sessions/sess_vh628d26u96fsn42v4vu49a3ht