The present study aims to elucidate the main variables that increase level of stress at beginning military conscription service using an artificial neural network (ANN)-based prediction model. Random sample data were obtained from one battalion Lithuanian Armed Forces, and a survey was conducted generate for training testing ANN models. Using nonlinearity in research, numerous structures constr...

Applications of artificial intelligence (AI) models have been massively explored for various engineering and sciences domains over the past two decades. Their capacity in modeling complex problems confirmed motivated researchers to explore their merit different disciplines. The use AI-models (probabilistic neural network multilayer perceptron network) estimation water quality indicators (namely...

This research develops an allometric model for estimation of biomass based on the height and DBH of trees in the Hyrcanian forests of Iran. An accurate allometric model reduces the uncertainty of allometric equation in biomass estimation using radar images. In this study, 317 trees were selected randomly from the 4 different dominant tree species for the development of an allometric model cover...

Water temperature (WT) is a critical control for various physical and biochemical processes in riverine systems. Although the prediction of river water has been subject extensive research, very few studies have examined relative importance elements affecting WT how to accurately estimate under effects cascaded dams. In this study, series potential influencing variables, such as air temperature,...

The settlement growth is potentially increased by the rural-to-urban perspective change due to new era of aerotropolis in Kulon Progo. Land-use planning evaluation required, especially settlement, which has a significant impact on environment. However, land-use studies are currently focused conforming analysis official (OLUP) toward existing or predicted land use partially combination with perf...

This research work investigates the use of Artificial Neural Network (ANN) based on models for solving first and second order linear constant coefficient ordinary differential equations with initial conditions. In particular, we employ a feed-forward Multilayer Perceptron (MLPNN), but bypass standard back-propagation algorithm updating intrinsic weights. A trial solution equation is written as ...

Hydrogen is believed as a promising energy carrier that contributes to deep decarbonization, especially for the sectors hard be directly electrified. A grid-connected wind/hydrogen system typical configuration hydrogen production. For such system, critical barrier lies in poor cost-competitiveness of produced hydrogen. Researchers have found flexible operation possible thanks excellent dynamic ...

Artificial neural networks (ANNs) can understand the behavior of a given system from historical measurements its associated variables. Adjusting weight and bias ANN model using an optimization algorithm is known as training process. The reliability directly related to success Therefore, this study investigates effect algorithms on prediction accuracy multilayer perceptron (MLPNNs). complex gas ...