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Mathematical Problems in Engineering
Volume 2013, Article ID 197690, 9 pages
http://dx.doi.org/10.1155/2013/197690
Research Article

Neural Model with Particle Swarm Optimization Kalman Learning for Forecasting in Smart Grids

1CUCEI, Universidad de Guadalajara, Apartado Postal 51-71, Colonia Las Aguilas, 45080 Zapopan, JAL, Mexico
2UADY, Faculty of Engineering, Avenida Industrias no Contaminantes por Periferico Norte, Apartado Postal 115 Cordemex, Merida, Yuc, Mexico
3DISI, Università degli Studi di Genova, Via Dodecaneso 35, 16146 Genova, Italy

Received 29 March 2013; Accepted 27 May 2013

Academic Editor: Yudong Zhang

Copyright © 2013 Alma Y. Alanis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [10 citations]

The following is the list of published articles that have cited the current article.

  • M. J. Mahmoodabadi, M. Taherkhorsandi, and A. Bagheri, “Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB’s Toolbox,” The Scientific World Journal, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
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  • Alma Y. Alanis, Nancy Arana-Daniel, and Carlos López-Franco, “Particle Swarm Optimization to Improve Neural Identifiers for Discrete-time Unknown Nonlinear Systems,” Bio-inspired Algorithms for Engineering, pp. 71–105, 2018. View at Publisher · View at Google Scholar
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  • Akhendra Kumar Padavala, and Bheema Rao Nistala, “Design of an on-chip Hilbert fractal inductor using an improved feed forward neural network for Si RFICs,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 26, no. 5, pp. 2437–2447, 2018. View at Publisher · View at Google Scholar