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Complexity
Volume 2019, Article ID 2782715, 14 pages
https://doi.org/10.1155/2019/2782715
Research Article

Development of Multidecomposition Hybrid Model for Hydrological Time Series Analysis

1Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
2Faculty of Health Studies, University of Bradford, Bradford BD7 1DP, UK
3Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
4Arriyadh Community College, King Saud University, Riyadh, Saudi Arabia
5KSA Workers University, El-Mansoura, Egypt
6College of Business Administration, King Saud University, Al-Muzahimiyah, Saudi Arabia
7Department of Mathematics, College of Science, King Khalid University, Abha 61413, Saudi Arabia
8Department of Mathematics and Statistics, Faculty of Basic and Applied Sciences, International Islamic University, 44000 Islamabad, Pakistan

Correspondence should be addressed to Ijaz Hussain; kp.ude.uaq@zaji

Received 1 October 2018; Accepted 13 December 2018; Published 2 January 2019

Guest Editor: Pedro Palos

Copyright © 2019 Hafiza Mamona Nazir 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 [1 citation]

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

  • Hafiza Mamona Nazir, Ijaz Hussain, Ishfaq Ahmad, Muhammad Faisal, and Ibrahim M. Almanjahie, “An improved framework to predict river flow time series data,” PeerJ, vol. 7, pp. e7183, 2019. View at Publisher · View at Google Scholar