In recent years, Earth system sciences are urgently calling for innovation on improving
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …

Research activity in the field of air pollution forecasting using artificial neural networks
(ANNs) has increased dramatically in recent years. However, the development of ANN …

Efforts to understand the influence of historical climate change, at global and regional levels,
have been increasing over the past decade. In particular, the estimates of air temperatures …

Time series prediction techniques have been used in many real-world applications such as
financial market prediction, electric utility load forecasting, weather and environmental state …

The influence of machine learning technologies is rapidly increasing and penetrating almost
in every field, and air pollution prediction is not being excluded from those fields. This paper …

In this work, we conducted a visualized bibliometric analysis to map the research trends of
machine learning in engineering (MLE) based on articles indexed in the Web of Science …

Accurate tourist demand forecasting systems are essential in tourism planning, particularly
in tourism-based countries. Artificial neural networks are attracting attention to forecast …

Accurate forecasting of inter-urban traffic flow has been one of the most important issues
globally in the research on road traffic congestion. However, the information of inter-urban …

Accurate forecasting of rainfall has been one of the most important issues in hydrological
research. Due to rainfall forecasting involves a rather complex nonlinear data pattern; there …

For time-series forecasting problems, there have been several prediction models to data, but
the development of a more accurate model is very difficult because of high non-linear and …