Artificial neural networks (ANNs) are being used increasingly to predict water variables. This study offers an alternative approach to quantify the relationship between time of chlorination in potable water (due to convectional treatment procedure) and chlorination by-products concentration...

The scientific community has recognized the necessity for more efficiently selected inputs in artificial neural network models (ANNs) in river flows and has worked on this despite some shortcomings. Moreover, there is none or limited inclusion of ANN inputs coupled with atmospheric circulation under...

This work illustrates the use and some related results of Artificial Neural Networks (ANNs) for data quality control of environmental time series and for reconstruction of missing data. ANNs are applied to the following problems: i) short and medium-term predicting of air pollutant concentrations in...

When flushing carry out as pressure condition, a scour cone is performed around the outlet. As the flow around the outlet in the pressure flushing is three dimensional, therefore that it is difficult to establish a general empirical model to provide accurate estimation for scour cone volume and...

In hydrology, as in a number of diverse fields, there has been an increasing use of Artificial Neural Networks (ANN) as black-box simplified models. This is mainly justified by their ability to model complex non-linear patterns; in addition they can self-adjust and produce a consistent response when...

Two different methodologies for hydraulic head simulation were compared in this study. The first methodology is a classic numerical groundwater flow simulation model, Princeton Transport Code (PTC), while the second one is a black-box approach that uses Artificial Neural Networks (ANNs). Both...

Urban air quality nowadays is one of the major environmental issues, due to its impact to various health problems, caused by the daily exposure of the population in dangerous air pollutants. The highest levels of air pollutants are usually observed in street canyons, emitted by urban traffic. To...

The influence of microscale and mesoscale meteorology on the local scale variation of air temperature cannot be correctly simulated by the coarse resolution Global Climate Models. The scope of this work is to develop a hybrid dynamic-statistical downscaling procedure and quantify its predictive...

An artificial neural network (ANN) model-based approach was developed and applied to estimate values of air temperature and relative humidity in remote mountainous areas. The application site was the mountainous area of the Samaria National Forest canyon (Greece). Seven meteorological stations were...

Detailed meteorological data required for the equation of FAO-56 Penman-Monteith (P-M) method that was adopted by Food and Agriculture Organization (FAO) as a standard method in estimating reference evapotranspiration (ETo) are not often available, especially in developing countries. The Hargreaves...