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The Scientific World Journal
Volume 2014, Article ID 152375, 12 pages
http://dx.doi.org/10.1155/2014/152375
Research Article

Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents

1Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, Chile
2Universidad Nacional de Chimborazo, 33730880 Riobamba, Ecuador

Received 26 April 2014; Revised 29 July 2014; Accepted 14 August 2014; Published 28 August 2014

Academic Editor: Cagdas Hakan Aladag

Copyright © 2014 Lida Barba 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 [6 citations]

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

  • Nhat-Duc Hoang, Anh-Duc Pham, and Minh-Tu Cao, “A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence,” Applied Computational Intelligence and Soft Computing, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
  • Chao Liu, Wensheng Niu, Hua Zhang, Xin Wang, Ji Wu, and Kui Zhang, “Application of singular spectrum analysis to failure time series analysis,” Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, vol. 42, no. 11, pp. 2321–2331, 2016. View at Publisher · View at Google Scholar
  • Lida Barba, and Nibaldo Rodríguez, “Hybrid Models Based on Singular Values and Autoregressive Methods for Multistep Ahead Forecasting of Traffic Accidents,” Mathematical Problems in Engineering, vol. 2016, pp. 1–14, 2016. View at Publisher · View at Google Scholar
  • Yong Liu, Cristian R. Munteanu, Carlos Fernandez-Lozano, Alejandro Pazos, Tao Ran, Zhiliang Tan, Yizun Yu, Chuanshe Zhou, Shaoxun Tang, and Humberto González-Díaz, “Experimental Study and ANN Dual-Time Scale Perturbation Model of Electrokinetic Properties of Microbiota,” Frontiers in Microbiology, vol. 8, 2017. View at Publisher · View at Google Scholar
  • Shaoxun Tang, Cristian R. Munteanu, Yong Liu, and Alejandro Pazos, “Experimental study and Random Forest prediction model of microbiome cell surface hydrophobicity,” Expert Systems with Applications, vol. 72, pp. 306–316, 2017. View at Publisher · View at Google Scholar
  • Lida Barba, and Nibaldo Rodríguez, “A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain,” Computational Intelligence and Neuroscience, vol. 2017, pp. 1–12, 2017. View at Publisher · View at Google Scholar