Context and background Corona virus (COVID) has rapidly gained a foothold and caused a
global pandemic. Particularists try their best to tackle this global crisis. New challenges …

Highly imbalanced class distribution has been well-recognized as a major cause of
performance degradation for most supervised learning algorithms. Unfortunately, such …

High-durability concrete is required in extremely cold or ocean environments, making the
design of concrete mixes highly important and complicated. In this study, a hybrid intelligent …

Autism spectrum disorders (ASD) are a diverse group of conditions characterized by
difficulty with social interaction and communication. ASD is expected to be a high‐risk …

The development of image classification is one of the most important research topics in
remote sensing. The prediction accuracy depends not only on the appropriate choice of the …

Children with autism spectrum disorders (ASDs) tremendously impact people's lives, and the
incidence and prevalence of ASDs are increasing globally. Global health organisations and …

Hyperspectral image (HSI) classification often faces the problem of multiclass imbalance,
which is considered to be one of the major challenges in the field of remote sensing. In …

The fusion of multi-spectral and synthetic aperture radar (SAR) images could retain the
advantages of each data, hence benefiting accurate land cover classification. However …

In this paper, an adaptive semi-supervised rotation forest (SSRoF) algorithm is proposed for
the classification of hyperspectral images with limited training data. Our proposition is based …

North China is one of the country's most important socio-economic centers, but its severe air
pollution is a huge concern. In this region, precisely forecasting the daily photovoltaic power …