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 …

With the development of industry, air pollution has become a serious problem. It is very
important to create an air quality prediction model with high accuracy and good …

The current calculations of water quality index (WQI) were sometimes can be very complex
and time-consuming which involves sub-index calculation like BOD and COD, however with …

The existing methods of calculating air pollution index are complex and time consuming.
Therefore new accurate and efficient modeling techniques need to be proposed. Thus, a …

This study investigates the applicability of multilayer perceptron (MLP), radial basis function
(RBF) and support vector machine (SVM) models for prediction of river flow time series …

Air pollution has become a serious issue in many developing countries, especially in China,
and could generate adverse effects on human beings. Air quality early-warning systems play …

The trade-off between computation time and predictive accuracy is important in the design
and implementation of clinical decision support systems. Machine learning techniques with …

Many real water issues involve rivers' sediment load or the load that rivers can bring without
degrading the fluvial ecosystem. Therefore, the assessment of sediments carried by a river is …

Air-quality forecasting in urban areas is difficult because of the uncertainties in describing
both the emission and meteorological fields. The use of incomplete information in the …

Rice is a major dietary source of the toxic metal cadmium (Cd). Concentration of Cd in rice
grain varies widely at the regional scale, and it is challenging to predict grain Cd …