Prediction of power in solar stirling heat engine by using neural network based on hybrid genetic algorithm and particle swarm optimization
In this paper, the model based on a feed-forward artificial neural network optimized by particle swarm optimization (HGAPSO) to estimate the power of the solar stirling heat engine is proposed. Particle swarm optimization is used to decide the initial weights of the neural network. The HGAPSO-ANN mo...
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| Published in | Neural computing & applications Vol. 22; no. 6; pp. 1141 - 1150 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Springer-Verlag
01.05.2013
Springer |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0941-0643 1433-3058 |
| DOI | 10.1007/s00521-012-0880-y |
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| Abstract | In this paper, the model based on a feed-forward artificial neural network optimized by particle swarm optimization (HGAPSO) to estimate the power of the solar stirling heat engine is proposed. Particle swarm optimization is used to decide the initial weights of the neural network. The HGAPSO-ANN model is applied to predict the power of the solar stirling heat engine which data set reported in literature of china. The performance of the HGAPSO-ANN model is compared with experimental output data. The results demonstrate the effectiveness of the HGAPSO-ANN model. |
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| AbstractList | In this paper, the model based on a feed-forward artificial neural network optimized by particle swarm optimization (HGAPSO) to estimate the power of the solar stirling heat engine is proposed. Particle swarm optimization is used to decide the initial weights of the neural network. The HGAPSO-ANN model is applied to predict the power of the solar stirling heat engine which data set reported in literature of china. The performance of the HGAPSO-ANN model is compared with experimental output data. The results demonstrate the effectiveness of the HGAPSO-ANN model. |
| Author | Ahmadi, Mohammad Hossien Sorouri Ghare Aghaj, Saman Nazeri, Alireza |
| Author_xml | – sequence: 1 givenname: Mohammad Hossien surname: Ahmadi fullname: Ahmadi, Mohammad Hossien email: mohammadhosein.ahmadi@gmail.com organization: Faculty of Mechanical Engineering, K.N. Toosi University – sequence: 2 givenname: Saman surname: Sorouri Ghare Aghaj fullname: Sorouri Ghare Aghaj, Saman organization: Department of Industrial Engineering, Science and Research Branch, Islamic Azad University – sequence: 3 givenname: Alireza surname: Nazeri fullname: Nazeri, Alireza organization: Department of Industrial Engineering, Science and Research Branch, Islamic Azad University |
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| Cites_doi | 10.1016/S0098-1354(02)00148-5 10.1016/0893-6080(90)90005-6 10.1016/j.rser.2006.07.001 10.1109/TNN.2003.810618 10.1115/1.1562634 10.1109/TSMCB.2003.818557 10.1016/S0360-5442(00)00023-2 10.1016/S0196-8904(00)00063-7 10.1016/j.pecs.2003.10.003 10.1016/j.renene.2010.06.037 10.1016/S0196-8904(99)00065-5 10.1109/MHS.1995.494215 10.2514/6.2005-1897 |
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| Keywords | Solar dish Hybrid Stirling heat engine Artificial neural network Genetic algorithm Particle swarm optimization Neural computation Experimental data Optimization method Prediction Neural network Optimization |
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| Title | Prediction of power in solar stirling heat engine by using neural network based on hybrid genetic algorithm and particle swarm optimization |
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