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...

Water famine is very cruel. The desalination plant was brought in to alleviate the water shortage. A desalination plant has been set up in many places around the world. In the view of expanding worldwide need of fresh water, the usage of desalination plant becomes more common. There are more than...

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...

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...

Water balance studies in the Okavango Delta indicate that more than 90% of inflow into the Delta is lost through evaporation. This coupled with high climatic variability threatens the ecohydrology of the Delta. Trends indicate decreasing rainfall amounts and increasing temperature at the area of the...

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...

Wind Energy is one of the important sources of renewable energy. There is a need to prepare the availability of wind energy in the area where there is no measured wind speed data. For this type of situation, it seems to be necessary to predict the wind energy potential using such as wind speed using...

This paper deals with prediction of the response of karstic springs by means of artificial neural networks (ANNs). A feed-forward back propagation ANN with three layers has been developed, to predict flow rates of two karstic springs, located at Rouvas area, Crete, Greece, using rainfall data as...

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...

An economic system focused on low energy usage, low pollution, and low emission is known as a "low-carbon economy". The concept of environmentally friendly and low-carbon food packaging architecture directs practice growth and reform in accordance with the customer's green psychology. As the primary...

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...

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...

Air pollution monitoring is becoming increasingly important, with an emphasis on the effects on human health. Because nitrogen dioxide (NO2) and sulphur dioxide (SO2) are the principal pollutants, many models for forecasting their potential harm have been created. Nonetheless, making precise...

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...

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...

Toxicity poses a significant threat to the environment and human health. Heavy metals, such as cadmium, lead, copper, and zinc, have been shown to harm both agricultural ecosystems and human health. This paper aims to examine the effects of these heavy metals on the environment and human health, as...

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...

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...

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...