A New Multiple Imputation Approach Using Machine Learning to Enhance Climate Databases in Senegal Article Swipe
Mory Touré
,
Nana Ama Browne Klutse
,
Mamadou Adama Sarr
,
Annine Duclaire Kenne
,
Md Abul Ehsan Bhuiyanr
,
Ousmane Ndiaye
,
Daouda Badiane
,
Wassila M. Thiaw
,
Ibrahima Sy
,
Cheikh Mbow
,
Saïdou Moustapha Sall
,
Amadou Gaye
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-3287168/v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-3287168/v1
This study aims at enhancing climate data in Senegal using information from the Global Surface Summary of the Day (GSOD). It uses data from 1991 to 2022 from major secondary synoptic stations in Senegal. These data are subject to missing values (data gaps). To address these gaps, multiple imputation was used based on three machine learning models: PMM (Predictive Mean Matching), RF (Random Forest), and NORM (Bayesian Linear Regression). The PMM model relies on averages of similar data, the RF model handles complex relationships between variables, even on an intra-seasonal scale, while the NORM model captures seasonal variations and extreme values. The results highlight the higher performance of the RF model in terms of accuracy and variance explanation compared to the others. The findings of this study open new avenues for informed decision-making in sectors such as agriculture and urban planning, where accurate climate data play a crucial role. However, while this study lays the groundwork for better utilization of climate data in Senegal, challenges persist, including the ongoing need to collect high-quality data and adapt models to data intricacies.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-3287168/v1
- https://www.researchsquare.com/article/rs-3287168/latest.pdf
- OA Status
- green
- References
- 64
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386253445
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4386253445Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-3287168/v1Digital Object Identifier
- Title
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A New Multiple Imputation Approach Using Machine Learning to Enhance Climate Databases in SenegalWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-08-29Full publication date if available
- Authors
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Mory Touré, Nana Ama Browne Klutse, Mamadou Adama Sarr, Annine Duclaire Kenne, Md Abul Ehsan Bhuiyanr, Ousmane Ndiaye, Daouda Badiane, Wassila M. Thiaw, Ibrahima Sy, Cheikh Mbow, Saïdou Moustapha Sall, Amadou GayeList of authors in order
- Landing page
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https://doi.org/10.21203/rs.3.rs-3287168/v1Publisher landing page
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https://www.researchsquare.com/article/rs-3287168/latest.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-3287168/latest.pdfDirect OA link when available
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Imputation (statistics), Random forest, Missing data, Computer science, Data quality, Bayesian probability, Variance (accounting), Machine learning, Artificial intelligence, Engineering, Metric (unit), Operations management, Accounting, BusinessTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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64Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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