Reliable runoff forecasting plays an important role in water resource management. In this
study, we propose a homogeneous selective ensemble forecasting framework based on …

A single model usually cannot learn all the appropriate features with limited data, thus
leading to poor performance when test data are used. To improve model performance, we …

A deep learning-based quantitative structure–activity relationship analysis, namely the
molecular image-based DeepSNAP–deep learning method, can successfully and …

Fruits represent a valuable source of bioactivity, vitamins, minerals and antioxidants. They
are often used in research due to their potential to extend sustainability and edibility. In this …

With the increasing global demand for new energy sources, Photovoltaic (PV) is increasingly
emphasized as a renewable energy source globally. Consequently, the assessment of PV …

Civil infrastructure worldwide is ageing and enduring increasingly adverse weather
conditions. Traditional structural health monitoring (SHM) involves the expensive and time …

The cuffless blood pressure (BP) measurement allows for frequent measurement without
discomfort to the patient compared to the cuff inflation measurement. With the availability of a …

In the modern times of technological development, it is important to select adequate
methods to support various food and industrial problems, including innovative techniques …

Using recent machine learning results that present an information-theoretic perspective on
underfitting and overfitting, we prove that deciding whether an encodable learning algorithm …

Earthquakes pose a significant threat to urban areas, necessitating accurate forecasting
models to mitigate their impact. This study focuses on earthquake forecasting in Los …