Solid waste generation and its impact on human health and the environment have long
been a matter of concern for governments across the world. In recent years, there has been …

The waste management processes typically involve numerous technical, climatic,
environmental, demographic, socio-economic, and legislative parameters. Such complex …

The use of machine learning techniques in waste management studies is increasingly
popular. Recent literature suggests k-fold cross validation may reduce input dataset partition …

Artificial neural networks (ANNs) have recently attracted significant attention in
environmental areas because of their great self-learning capability and good accuracy in …

This review presents the developments in artificial intelligence technologies for
environmental pollution controls. A number of AI approaches, which start with the reliable …

Municipal solid waste (MSW) management is a major concern to local governments to
protect human health, the environment and to preserve natural resources. The design and …

Rivers, as one of the freshwater resources, are generally put in the state of jeopardy in terms
of quantity and quality due to the development in industry, agriculture, and urbanization …

Accurate simulation of wastewater effluent parameters is a vital concern to reduce the
operational costs of a wastewater treatment plant. In this way, a reliable predictive model is a …

Credit risk imposes itself as a significant barrier of agriculture 4.0 investments in the supply
chain finance (SCF) especially for Small and Medium-sized Enterprises. Therefore, it is …

In the research, the role of three input selection techniques is evaluated on support vector
machine (SVM) performance for prediction of monthly stream flow. First, a SVM model is …