Ensemble learning combines several individual models to obtain better generalization
performance. Currently, deep learning architectures are showing better performance …

Solar irradiation data are imperatively required for any solar energy-based project. The non-
accessibility and uncertainty of these data can greatly affect the implementation …

Researchers have made great progress in developing cutting-edge solar energy forecasting
methods. However, these methods are far from optimal in terms of their accuracy …

In many parts of semiarid and arid regions, qanats are the leading supplier of water demand
for agricultural and drinking usage. Qanat is an ancient collecting water system, and qanat …

A reliable air quality prediction model is required for pollution control, human health
monitoring, and sustainability. The existing air quality prediction models lack efficiency due …

Being able to predict the power to be generated by solar power plants in a smart grid,
microgrid or nanogrid with high accuracy and speed brings a lot of advantages in the …

Accurate and dependable air quality forecasting is critical to environmental and human
health. However, most methods usually aim to improve overall prediction accuracy but …

In remote sensing images, change detection (CD) is required in many applications, such as:
resource management, urban expansion research, land management, and disaster …

The increasing integration of solar sources into the energy mix presents significant
challenges, particularly in short-term energy management. Accurate solar irradiance …

Recently, smart cities have emerged as an effective approach to deliver high-quality
services to the people through adaptive optimization of the available resources. Despite the …