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  • Search: subject:"GA (genetic algorithm)"
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GA (genetic algorithm) 4 Artificial neural network 1 Demand 1 Diesel engine 1 EPD (economic power dispatch) 1 FFA (firefly algorithm) 1 Group-hole injector 1 Hybrid method 1 Hybrid optimization algorithms 1 Nanofluid 1 Oil 1 PSO (particle swarm optimization) 1 Parabolic trough collector 1 Projection 1 SQP (sequential quadratic programming 1 Spray 1 Wind power 1
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Akbarzadeh, A. 1 Assareh, E. 1 Assari, M.R. 1 Behrang, M.A. 1 Ghanbarzadeh, A. 1 Jafarmadar, Samad 1 Kasaeian, A.B. 1 Khalilarya, Shahram 1 Kherfane, Riad Lakhdar 1 Khodja, Fouad 1 Kowsary, F. 1 Mohammad Zadeh, P. 1 Sokhansefat, T. 1 Taghavifar, Hadi 1 Younes, Mimoun 1
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Energy 4
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Showing 1 - 4 of 4
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Hybrid optimization algorithm for thermal analysis in a solar parabolic trough collector based on nanofluid
Mohammad Zadeh, P.; Sokhansefat, T.; Kasaeian, A.B.; … - In: Energy 82 (2015) C, pp. 857-864
(genetic algorithm) and SQP (sequential quadratic programming) is introduced in the optimization process. The optimization …-linear and computationally intensive process. In order to overcome these difficulties, a hybrid optimization method involving GA …
Persistent link: https://www.econbiz.de/10011209542
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Diesel engine spray characteristics prediction with hybridized artificial neural network optimized by genetic algorithm
Taghavifar, Hadi; Khalilarya, Shahram; Jafarmadar, Samad - In: Energy 71 (2014) C, pp. 656-664
ANN (artificial neural network) modeling is adopted along GA (genetic algorithm) optimization method in order to …
Persistent link: https://www.econbiz.de/10010807603
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Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration
Younes, Mimoun; Khodja, Fouad; Kherfane, Riad Lakhdar - In: Energy 67 (2014) C, pp. 595-606
This paper presents a new and efficient method for solving EPD (economic power dispatch) problem. To solve this problem we have combined two meta-heuristic methods, the FFA and the mGA. The acceleration of the convergence speed, the improved solution quality and the balance between exploration...
Persistent link: https://www.econbiz.de/10010809494
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Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran
Assareh, E.; Behrang, M.A.; Assari, M.R.; Ghanbarzadeh, A. - In: Energy 35 (2010) 12, pp. 5223-5229
This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate …
Persistent link: https://www.econbiz.de/10010809434
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