In recent decades, there has been an increasing interest in the prognosis of maximum surface ozone concentrations due to the adverse effects on human health, animal population, agricultural productivity and forestry. The present study deals with the development and application of Artificial Neural...

In the present study, batch adsorption studies were performed for the removal of malachite green and acid blue 161 dyes from aqueous solutions by varying parameters such as contact time, waste marble dust amount, initial dye concentration and temperature. The equilibrium adsorption data were...

This paper presents the sensitivity analysis results of feed forward multilayer perceptron based Artificial Neural Network model for water level prediction in a data constraint transnational Surma River of Bangladesh. Catchment characteristics, hydro-geomorphological, meteorological and headwater...

Since a spectrum of hydrological and geomorphological conditions produce flood pulse environment in a riverine or a deltaic system, it is essential to have the knowledge on spatial and temporal distributions of river flow and dependent processes for environmental flow requirements, ecosystem...

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...

This study focuses on the estimation of thermal comfort conditions in a high alt. site (1455 m) in Apodotia (MA), Greece, by using the MLP neural network model. This estimation is based on the air temperature (t) and relative humidity (f) data of the middle (1078-1163 m) and of the low altitude...

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...

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...

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...

Artificial neural networks are one of the advanced technologies employed in hydrology modelling. This paper investigates the potential of two algorithm networks, the feed forward backpropagation (BP) and generalized regression neural network (GRNN) in comparison with the classical regression for...

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...

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...

Human thermal comfort conditions were determined in two mountainous regions of Greece, Gerania mountains (MG) in east continental Greece, and mountainous Nafpaktia (MN) in west continental Greece. Both regions are unexploited with considerable tourist potential. Four sites in each study region were...

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...

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...