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Many studies are performed by researchers about shell and tube heat exchanger (STHE) but the multi-objective particle swarm optimization (PSO) technique has never been used in such studies. This paper presents application of thermal-economic multi-objective optimization of STHE using PSO. For optimal design of a STHE, it was first thermally modeled using e-number of transfer units method while Bell–Delaware...
Growing energy demand of the world, made the major oil and gas exporting countries to have critical role in the energy supply. The geostrategic situation of Iran and its access to the huge hydrocarbon resources placed the country among important areas and resulted in the investment development of oil and gas industry.In this study, a novel approach for oil consumption modeling is presented. Three...
PSO (particle swarm optimization) technique is applied to estimate monthly average daily GSR (global solar radiation) on horizontal surface for different regions of Iran. To achieve this, five new models were developed as well as six models were chosen from the literature. First, for each city, the empirical coefficients for all models were separately determined using PSO technique. The results indicate...
This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO–DEM and GA–DEM (PSO and GA demand estimation models) are developed to estimate the future oil demand values based...
The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32°16′N, 48°25′E), are used in this study. In order...
The main objective is to predict daily global solar radiation (GSR) in future time domain based on measured air temperature, relative humidity and sunshine hours values between 2002 and 2006 for Dezful city in Iran using artificial neural network method. The estimations of GSR were made using three combinations of data sets: (I) length of day, daily mean air temperature and relative humidity as inputs...
Present study develops two scenarios to analyse gasoline consumption and makes future projections based on the particle swarm optimisation (PSO) and genetic algorithm (GA). The gasoline consumption is estimated based on the basic indicators of the population, gross domestic product (GDP), import, export, gasoline production and number of cars figures. Two different exponential and linear estimation...
Air temperature, relative humidity and vapor pressure data during 1993-2004 for city of Manjil in Iran were used for the estimation of wind speed in future time domain using artificial neural network method. The estimations of wind speed were made using three combinations of data sets namely: (i) month of the year, monthly mean daily air temperature and relative humidity as inputs and wind speed as...
The main objective of this research is to investigate Iran's coal demand, projection and supplies by using the structure of the Iranian socio-economic conditions. This study develops a scenario to analyse coal consumption and make future projections based on particle swarm optimisation (PSO) and genetic algorithm (GA) methods. The models developed in two forms (exponential and linear) and applied...
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