Search Results - subject:"Particle Swarm Optimization"

Scheduling electric power production at a wind farm

Zhang, Zijun; Kusiak, Andrew; Song, Zhe - In: European Journal of Operational Research 224 (2013) 1, pp. 227-238

We present a model for scheduling power generation at a wind farm, and introduce a particle swarm optimization …

Persistent link: https://www.econbiz.de/10010580827

Groundwater Model Calibration by Meta-Heuristic Algorithms

Haddad, O.; Tabari, M.; Fallah-Mehdipour, E.; Mariño, M. - In: Water Resources Management 27 (2013) 7, pp. 2515-2529

-heuristic algorithms: (1) particle swarm optimization (PSO) and (2) pattern search (PS) are applied and compared in the Ghaen aquifer, by …

Persistent link: https://www.econbiz.de/10010997894

Particle swarm optimization with cocktail decoding method for hybrid flow shop scheduling problems with multiprocessor tasks

Chou, Fuh-Der - In: International Journal of Production Economics 141 (2013) 1, pp. 137-145

particle swarm optimization (PSO) algorithm that can be combined with the cocktail decoding method. In the PSO, a variety of …

Persistent link: https://www.econbiz.de/10010594401

Studying the effect of using low-discrepancy sequences to initialize population-based optimization algorithms

Omran, Mahamed; al-Sharhan, Salah; Salman, Ayed; Clerc, … - In: Computational Optimization and Applications 56 (2013) 2, pp. 457-480

In this paper, we investigate the use of low-discrepancy sequences to generate an initial population for population-based optimization algorithms. Previous studies have found that low-discrepancy sequences generally improve the performance of a population-based optimization algorithm. However,...

Persistent link: https://www.econbiz.de/10010698279

A comparative study of optimal hybrid methods for wind power prediction in wind farm of Alberta, Canada

Bigdeli, Nooshin; Afshar, Karim; Gazafroudi, Amin Shokri; … - In: Renewable and Sustainable Energy Reviews 27 (2013) C, pp. 20-29

), and particle swarm optimization approach. The simulation results are representative of the out-performance of ICA in …

Persistent link: https://www.econbiz.de/10010703025

Forecasting iron ore import and consumption of China using grey model optimized by particle swarm optimization algorithm

Ma, Weimin; Zhu, Xiaoxi; Wang, Miaomiao - In: Resources Policy 38 (2013) 4, pp. 613-620

develops a high-precision hybrid model based on grey prediction and rolling mechanism optimized by particle swarm optimization …

Persistent link: https://www.econbiz.de/10010719904

Swarm intelligence and gravitational search algorithm for multi-objective optimization of synthesis gas production

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku; Zilati, Ku; … - In: Applied Energy 103 (2013) C, pp. 368-374

(Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO)) were then applied in conjunction with the NBI method …

Persistent link: https://www.econbiz.de/10010602998

The emergence of scaling laws search dynamics in a particle swarm optimization

Qi, Jie; Rong, Zhihai - In: Physica A: Statistical Mechanics and its Applications 392 (2013) 6, pp. 1522-1531

This paper investigates the search dynamics of a fundamental particle swarm optimization (PSO) algorithm via gathering …

Persistent link: https://www.econbiz.de/10010608609

Nonlinear forecasting of the Gold Miner Spread : an application of correlations filters

Dunis, Christian; Laws, Jason; Middleton, Peter W.; … - In: Intelligent systems in accounting finance and … 20 (2013) 4, pp. 207-231

Persistent link: https://www.econbiz.de/10010233196

A loan default discrimination model using cost-sensitive support vector machine improved by PSO

Cao, Jie; Lu, Hongke; Wang, Weiwei; Wang, Jian - In: Information technology and management 14 (2013) 3, pp. 193-204

Persistent link: https://www.econbiz.de/10010196427