Search Results - subject:"Particle Swarm Optimization"

Multi-objective efficiency enhancement using workload spreading in an operational data center

Habibi Khalaj, Ali; Scherer, Thomas; Siriwardana, Jayantha - In: Applied Energy 138 (2015) C, pp. 432-444

. The efficient load spreading method is achieved by applying a multi-objective particle swarm optimization (MOPSO …

Persistent link: https://www.econbiz.de/10011116169

Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network

Kayal, Partha; Chanda, C.K. - In: Renewable Energy 75 (2015) C, pp. 173-186

particle swarm optimization technique is employed to optimize the objective functions considering bus voltage limit, line …

Persistent link: https://www.econbiz.de/10011116507

Short-term wind power forecasting using adaptive neuro-fuzzy inference system combined with evolutionary particle swarm optimization, wavelet transform and mutual information

Osório, G.J.; Matias, J.C.O.; Catalão, J.P.S. - In: Renewable Energy 75 (2015) C, pp. 301-307

-term, successfully combining mutual information, wavelet transform, evolutionary particle swarm optimization, and the adaptive neuro …

Persistent link: https://www.econbiz.de/10011116512

A multiple objective decision making model for energy generation portfolio under fuzzy uncertainty: Case study of large scale investor-owned utilities in Florida

Zeng, Ziqiang; Nasri, Ehsan; Chini, Abdol; Ries, Robert; … - In: Renewable Energy 75 (2015) C, pp. 224-242

then solved by employing a multiple objective particle swarm optimization algorithm. The analysis for four large scale …

Persistent link: https://www.econbiz.de/10011116567

Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions

Sundareswaran, K.; Vignesh kumar, V.; Palani, S. - In: Renewable Energy 75 (2015) C, pp. 308-317

under partial shading conditions (PSC). The new algorithm combines the use of particle swarm optimization (PSO) for MPPT …

Persistent link: https://www.econbiz.de/10011116581

Optimal management of hybrid PV/fuel cell/battery power system: A comparison of optimal hybrid approaches

Bigdeli, Nooshin - In: Renewable and Sustainable Energy Reviews 42 (2015) C, pp. 377-393

Optimization (PSO), Quantum behaved Particle Swarm Optimization (QPSO), Ant Colony Optimization (ACO), and Cuckoo Optimization …-known optimization approaches for load sharing among the available resources. Imperialist Competitive Algorithm (ICA), Particle Swarm …

Persistent link: https://www.econbiz.de/10011117016

A review on hybrid wavelet regrouping particle swarm optimization neural networks for characterization of partial discharge acoustic signals

Al-geelani, Nasir A.; Piah, M.; Afendi, M.; Bashir, … - In: Renewable and Sustainable Energy Reviews 45 (2015) C, pp. 20-35

a hybrid algorithm combining particle swarm optimization (PSO) with a neural network, referred to as PSO-NN. …

Persistent link: https://www.econbiz.de/10011209066

Multi-objective portfolio optimization considering the dependence structure of asset returns

Babaei, Sadra; Sepehri, Mohammad Mehdi; Babaei, Edris - In: European Journal of Operational Research 244 (2015) 2, pp. 525-539

resulted in a non-continuous feasible region. Hence, we propose two variants of multi-objective particle swarm optimization …

Persistent link: https://www.econbiz.de/10011209331

A novel hybrid approach based on self-organizing maps, support vector regression and particle swarm optimization to forecast solar irradiance

Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M. - In: Energy 82 (2015) C, pp. 570-577

(support vector regression) and PSO (particle swarm optimization). In order to solve the noise and stationarity problems in the …

Persistent link: https://www.econbiz.de/10011209523

A data-driven feed-forward decision framework for building clusters operation under uncertainty

Hu, Mengqi - In: Applied Energy 141 (2015) C, pp. 229-237

stage that employs an augmented multi-objective particle swarm optimization based decision framework to obtain operation …

Persistent link: https://www.econbiz.de/10011189424