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A MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria

A multi-criteria decision-making approach was used for the selection of GCMs for Nigeria based on their ability to replicate historical rainfall estimated using three entropy-based feature selection methods namely, Entropy Gain (EG), Gain Ratio (GR), and Symmetrical Uncertainty (SU). Performances of four bias correction methods were compared to identify the most suitable method for downscaling and projection of rainfall using the selected GCMs. Random forest (RF) regression was used for the generation of the multi-model ensemble (MME) average of projected rainfall. The ensemble projections for…

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Source	Internet Archive
Collection	International records
Kind	Document
Publisher	Mohammed Sanusi Shiru; Shamsuddin Shahid; Eun Sung Chung; Noraliani Alias; Laura Scherer
Date	2019-01-01
Type	texts
Details	ia title
Found at	https://archive.org/details/mccl_10.1016_j.atmosres.2019.03.033
Archived copy	Look it up in the Wayback Machine
Record ID	`internet-archive:mccl_10.1016_j.atmosres.2019.03.033`

Cite this record

A MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria. Internet Archive, 2019. Vero Archive, record internet-archive:mccl_10.1016_j.atmosres.2019.03.033.