A comprehensive survey on recent metaheuristics for feature selection
Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …
preprocessing due to the ever-increasing sizes in actual data. There have been many …
Utilities of artificial intelligence in poverty prediction: a review
Artificial Intelligence (AI) is generating new horizons in one of the biggest challenges in the
world's society—poverty. Our goal is to investigate utilities of AI in poverty prediction via …
world's society—poverty. Our goal is to investigate utilities of AI in poverty prediction via …
A survey on hybrid feature selection methods in microarray gene expression data for cancer classification
N Almugren, H Alshamlan - IEEE access, 2019 - ieeexplore.ieee.org
The emergence of DNA Microarray technology has enabled researchers to analyze the
expression level of thousands of genes simultaneously. The Microarray data analysis is the …
expression level of thousands of genes simultaneously. The Microarray data analysis is the …
Precipitation projection using a CMIP5 GCM ensemble model: a regional investigation of Syria
The possible changes in precipitation of Syrian due to climate change are projected in this
study. The symmetrical uncertainty (SU) and multi-criteria decision-analysis (MCDA) …
study. The symmetrical uncertainty (SU) and multi-criteria decision-analysis (MCDA) …
Selection of climate models for projection of spatiotemporal changes in temperature of Iraq with uncertainties
A hybrid approach by combining the past performance and the envelope methods has been
proposed for the selection of an ensemble of general circulation models (GCMs) of Couple …
proposed for the selection of an ensemble of general circulation models (GCMs) of Couple …
Performance assessment of general circulation model in simulating daily precipitation and temperature using multiple gridded datasets
The performance of general circulation models (GCMs) in a region are generally assessed
according to their capability to simulate historical temperature and precipitation of the region …
according to their capability to simulate historical temperature and precipitation of the region …
Multi-criteria performance evaluation of gridded precipitation and temperature products in data-sparse regions
Inadequate climate data stations often make hydrological modelling a rather challenging
task in data-sparse regions. Gridded climate data can be used as an alternative; however …
task in data-sparse regions. Gridded climate data can be used as an alternative; however …
Model output statistics downscaling using support vector machine for the projection of spatial and temporal changes in rainfall of Bangladesh
A model output statistics (MOS) downscaling approach based on support vector machine
(SVM) is proposed in this study for the projection of spatial and temporal changes in rainfall …
(SVM) is proposed in this study for the projection of spatial and temporal changes in rainfall …
Fidelity assessment of general circulation model simulated precipitation and temperature over Pakistan using a feature selection method
Abstract General Circulation Models (GCMs) provide vital information on the likely future
climate, much needed for the effective planning and management of water resources. The …
climate, much needed for the effective planning and management of water resources. The …
Symmetrical uncertainty and random forest for the evaluation of gridded precipitation and temperature data
MS Nashwan, S Shahid - Atmospheric Research, 2019 - Elsevier
Selection of appropriate gridded rainfall and temperature data is a key problem for hydro-
climatic studies, particularly in regions where long-term reliable and dense observations are …
climatic studies, particularly in regions where long-term reliable and dense observations are …