Search Results - subject:"Particle Swarm Optimization"

Intelligent Business Process Optimization for the Service Industry

Kress, Markus - 2010

processes by applying sophisticated machine learning techniques such as Relational Reinforcement Learning and Particle Swarm … Optimization. …

Persistent link: https://www.econbiz.de/10009434602

A practical algorithm for optimal operation management of distribution network including fuel cell power plants

Niknam, Taher; Meymand, Hamed Zeinoddini; Nayeripour, Majid - In: Renewable Energy 35 (2010) 8, pp. 1696-1714

new evolutionary algorithm based on Fuzzy Adaptive Particle Swarm Optimization (FAPSO) to solve the optimal operation … problem and compare this method with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE …

Persistent link: https://www.econbiz.de/10010805110

A particle swarm optimization for wind energy control problem

Kongnam, C.; Nuchprayoon, S. - In: Renewable Energy 35 (2010) 11, pp. 2431-2438

proposed to apply particle swarm optimization to solve for optimum rotor speed under fixed-speed operation and optimum tip …

Persistent link: https://www.econbiz.de/10010807099

Contribution for optimal sizing of grid-connected PV-systems using PSO

Kornelakis, Aris; Marinakis, Yannis - In: Renewable Energy 35 (2010) 6, pp. 1333-1341

Particle Swarm Optimization (PSO) is an optimization algorithm considered to be highly efficient for the solution of …

Persistent link: https://www.econbiz.de/10010807154

Intelligent approach to maximum power point tracking control strategy for variable-speed wind turbine generation system

Lin, Whei-Min; Hong, Chih-Ming - In: Energy 35 (2010) 6, pp. 2440-2447

swarm optimization (MPSO) regulating controller is designed for a PMSG. The MPSO is adopted in this study to adapt to the …-speed wind turbine. A high-performance online training WRBFN using a back-propagation learning algorithm with modified particle …

Persistent link: https://www.econbiz.de/10010808077

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

Combined modeling for electric load forecasting with adaptive particle swarm optimization

Wang, Jianzhou; Zhu, Suling; Zhang, Wenyu; Lu, Haiyan - In: Energy 35 (2010) 4, pp. 1671-1678

nonlinearity shown in the electric load data and give more accurate forecasting results. The adaptive particle swarm optimization …

Persistent link: https://www.econbiz.de/10010810033

A new fuzzy adaptive particle swarm optimization for non-smooth economic dispatch

Niknam, Taher; Mojarrad, Hassan Doagou; Nayeripour, Majid - In: Energy 35 (2010) 4, pp. 1764-1778

Modified Particle Swarm Optimization (FAMPSO). Practical ED problems have non-smooth cost functions with equality and …

Persistent link: https://www.econbiz.de/10010810379

Multi-objective optimization of batteries and hydrogen storage technologies for remote photovoltaic systems

Avril, S.; Arnaud, G.; Florentin, A.; Vinard, M. - In: Energy 35 (2010) 12, pp. 5300-5308

Stand-alone photovoltaic (PV) systems comprise one of the promising electrification solutions to cover the demand of remote consumers, especially when it is coupled with a storage solution that would both increase the productivity of power plants and reduce the areas dedicated to energy production.

Persistent link: https://www.econbiz.de/10010810406

Reheat optimization of the variable-air-volume box

Kusiak, Andrew; Li, Mingyang - In: Energy 35 (2010) 5, pp. 1997-2005

modified particle swarm optimization algorithm. To increase computational efficiency, two levels of non-dominated solutions are …

Persistent link: https://www.econbiz.de/10010811062