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Modeling of thermal pollution in coastal area and its economical and environmental assessment
, Article International Journal of Environmental Science and Technology ; Volume 2, Issue 1 , 2005 , Pages 13-26 ; 17351472 (ISSN) ; Javid, A. H ; Moghimi, P ; Kayhan, K ; Sharif University of Technology
CEERS
2005
Abstract
The Persian Gulf is one of the aquatic ecosystems which has recently faced with different pollutions. Cooling water discharges due to various industries such as power plants can cause important disorders on present ecosystem balance because of its high temperature. Obviously, due to thermal pollution, a great number of aquatic creatures face with a new situation that they can not tolerate. Thermal pollution leads to their migration, creates a potential for new coming species which in turn can thoroughly change the marine ecosystem feature. The other impacts of this phenomenon are: disorders in reproduction, nourishment and other biological habits. In this research, thermal pollution due to...
Pinch Analysis of Heat Exchanger Networks in the Crude Oil Distillation Unit of Bandar-Abbas Refinery
, M.Sc. Thesis Sharif University of Technology ; Sadrhosseini, Hanieh (Supervisor) ; Shafii, Mohammad Behshad (Supervisor)
Abstract
Since oil prices continue to increase, energy conservation remains the prime industrial concern. Existing processes in power plants and oil refineries are not energy efficient as they should be therefore new projects can be defined to increase the energy efficiency without incurring any cost. The most appropriate utility for the processes should be explored to reduce emissions, increase the plant capacities and improve product qualities and energy efficiencies by one coherent strategic plan for the overall site which can be achieved by a full understanding of pinch technology and awareness of the available tools for applying it in practical way. Since the distillation unit of crude oil...
Using self-adaptive evolutionary algorithm to improve the performance of an extreme learning machine for estimating soil temperature
, Article Computers and Electronics in Agriculture ; Volume 124 , 2016 , Pages 150-160 ; 01681699 (ISSN) ; Habibi, J ; Mohammadi, K ; Shamshirband, S ; Al Razgan, O. S ; Sharif University of Technology
Elsevier B.V
Abstract
In this study, the self-adaptive evolutionary (SaE) agent is employed to structure the contributing elements to process the management of extreme learning machine (ELM) architecture based on a logical procedure. In fact, the SaE algorithm is utilized for possibility of enhancing the performance of the ELM to estimate daily soil temperature (ST) at 6 different depths of 5, 10, 20, 30, 50 and 100 cm. In the developed SaE-ELM model, the network hidden node parameters of the ELM are optimized using SaE algorithm. The precision of the SaE-ELM is then compared with the ELM model. Daily weather data sets including minimum, maximum and average air temperatures (Tmin, Tmax and Tavg), atmospheric...