Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients,
heavy metals and persistent organic pollutants. For the modeling and optimization of …

The generation of food production that meets the rising demand for food and ecosystem
security is a big challenge. With the development of Artificial Intelligence (AI) models, there …

This study proposes a comprehensive methodology to the application of an Artificial Neural
Network Ensemble (ANNE) for the mapping of landslide susceptibility. The identification of …

This study investigates the performance of support vector machine (SVM), multivariate
adaptive regression spline (MARS), and random forest (RF) models for predicting the lead …

Artificial intelligence is an emerging technology which harbors a suite of mechanisms that
have the potential to be leveraged for reaping value across multiple domains. Lately, there is …

The arrival of the era of big data has brought new ideas to solve problems for all walks of life.
Medical clinical data is collected and stored in the medical field by utilizing the medical big …

Forest growth models can provide valuable support tools for forest recovery assessment and
forestry management, whether in the form of diagnostic or prognostic. Furthremore, they can …

Planting seedlings remains the most popular method of forest restoration, but passive
restoration may become a new promise to reduce costs, despite concerns about its efficacy …

Riparian buffer zones (RBZs) provide multiple benefits to watershed ecosystems. We aimed
to conduct an extensive sensitivity analysis of the RBZ designs to climate change nutrient …

abstract Water environment has been deteriorating in the recent decades due to the rapid
industrialization, population expansion and urbanization. Large volumes of wastewater …