Forecasting energy price and consumption is essential in making effective managerial decisions and plans. While there are many sophisticated mathematical methods developed so far to forecast, some nature-based intelligent algorithms with desired characteristics have been developed recently. The main objective of this research is short term forecasting of energy price and consumption in Iranian ...

Transformer incipient fault diagnostic method based on dissolved gas analysis (DGA) using Artificial Neural Networks (ANN) and Neural-Imperialistic Competitive Algorithm (Nero-ICA) hybrid approach is simulated in this paper and the results has been compared with IEC standard. Firstly, dissolved gas analysis method and IEC DGA standard has been presented. In the second step, application of ANN a...

abstract evapotranspiration as one of the important elements in agriculture has a considerable role in water resource management. therefore, using a more exact estimation method is an essential step of agricultural development, especially in arid semi-arid area. in this research, in order to exact estimate of garlic evapotranspiration using lysimeteric data, an artificial neural network (ann) m...

evaporation is one of the most important components of hydrologic cycle.accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. in order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. using direct methods require installing meteorological stations andinstruments ...

This paper presents an analytical work for better design system that contributes to the reduction of fuel consumption and emission for vehicle performance. The main technological issue on engines today is to comply with emission standards with cost-effective measures in order to keep the engine price still attractive to customer. The experimental research of engine performance are time consumin...

Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...

In the present study, Computational Fluid Dynamics (CFD) techniques and Artificial Neural Networks (ANN) are used to predict the pressure drop value (Δp ) of Al2O3-water nanofluid in flat tubes. Δp  is predicted taking into account five input variables: tube flattening (H), inlet volumetric flow rate (Qi  ), wall heat flux (qnw  ), nanoparticle volume fraction (Φ) and nanoparticle diameter (dp ...

Depending upon the nonlinear feature between neural units in artificial neural networks (ANN), artificial neural network was used to develop a model for greenhouse inside air temperature management. Data was collected and processed for training and simulation of temperature model. The design of the network structure and transfer function was also discussed. Because heuristic logic of greenhouse...

background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...

abstract cation exchange capacity (cec) is an important characteristic of soil in terms of nutrient and water holding capacities and contamination management. measurement of cec is laborious and time-consuming. therefore, cec estimation through other easily - measured properties is desirable. in this study, ptfs for estimation of cation exchange capacity from basic soil properties such as parti...