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| Taki, Morteza; Ajabshirchi, Yahya; Ranjbar, Seyed Faramarz; Matloobi, Mansour. |
| Artificial Neural Networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. After a comprehensive literature survey on the application of ANNs in greenhouses, this work describes the results of using ANNs to predict the roof temperature, inside air humidity, soil temperature and inside soil humidity (Tri, RHia, Tis, RHis), in a semi-solar greenhouse according to use some inside and outside parameters in the institute of renewable energy in East Azerbaijan province, Iran. For this purpose, a semi-solar greenhouse was designed and constructed for the first time in Iran. The model database selected beside on the main and important factors influence the four above variables inside... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Artificial Neural Networks; Semi-solar greenhouse; Multiple linear regression model; Iran. |
| Ano: 2016 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3672 |
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| Rahnama, Majid; Kazemi, Navab; Godarzi, Behroz; Taki, Morteza. |
| Geothermal source is a perspective technology able to use the ground as a thermal sink or heat source. It is one of the energy resources in Iran that can be used with long-term investment. This study provided a new idea to use of this energy for heating and cooling of buildings. Two wells were used for heating and cooling due to the constant temperature of the water in depth of 12 m underground (approximately is equal to the annual temperature environment during the year). Water flowed in six speeds: 10, 11.5, 13, 16, 29 and 34 lit/min using a hydraulic pump (12 meters hydraulic height and 2 inch diameter) from first well, and after passing through radiator, discharge to other well. The outdoor temperature was 9oC, 40 °C and 15.5-16 °C for heating,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Air speed; Geothermal source; Net energy ratio; Water flow rate. |
| Ano: 2019 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/4664 |
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| Ghasemi Mobtaker, Hassan; Taki, Morteza; Salehi, Marzie; Zarei Shahamat, Ebrahim. |
| The nonparametric method of data envelopment analysis (DEA) was used to investigate the energy efficiency and CO2 emission of barley farm in Hamedan province of Iran. The method was used based on eight energy inputs including human labor, machinery, diesel fuel, fertilizers, farmyard manure, biocide, electricity and seed energy and single output of barley yield and technical, pure technical, scale and cross efficiencies were calculated using CCR and BCC models. The results showed that the average values of technical, pure technical and scale efficiency scores of farmers were 0.788, 0.941 and 0.833, respectively. Also, energy saving target ratio for barley production was calculated as 11.45%, indicating that by following the recommendations of this... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data envelopment analysis; Energy saving; Barley; Chemical fertilizers. |
| Ano: 2013 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2618 |
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