Volume 3, Issue 6-1, December 2014, Page: 103-108
Modeling and Prediction of Changes in Anzali Pond Using Multiple Linear Regression and Neural Network
Farshad Parhizkar Miandehi, Department of Computer Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran
Erfan Zidehsaraei, Department of Computer Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran
Mousa Doostdar, Department of Computer Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran
Received: Nov. 3, 2014;       Accepted: Nov. 6, 2014;       Published: Nov. 11, 2014
DOI: 10.11648/j.ijiis.s.2014030601.29      View  3050      Downloads  124
Abstract
Iranian ponds and water ecosystems are valuable assets which play decisive roles in economic, social, security and political affairs. Within the past few years, many Iranian water ecosystems such asUrmia Lake, Karoun River and Anzali Pond have been under disappearance threat. Ponds are habitats which cannot be replaced and this makes it necessary to investigate their changes in order to save these valuable ecosystems. The present research aims to investigate and evaluate the trend of variations in Anzali Pond using meteorological data between 1991-2010 by means of GMDH, which is based upon genetic algorithm and is a powerful technique in modeling complex dynamic non-linear systems, and linear regression technique. Input variables of both methodsinclude all factors (inside system and outside system factors) which affect variations in Anzali Pond. Exactness of linear regression method was 78% and exactness of GMDH neural network method was more than 97%. As as result, exactness of GMDH neural network method is significantly better than regression model.
Keywords
Anzali Pond, Regression Analysis, GMDH Neural Network
To cite this article
Farshad Parhizkar Miandehi, Erfan Zidehsaraei, Mousa Doostdar, Modeling and Prediction of Changes in Anzali Pond Using Multiple Linear Regression and Neural Network, International Journal of Intelligent Information Systems. Special Issue: Research and Practices in Information Systems and Technologies in Developing Countries. Vol. 3, No. 6-1, 2014, pp. 103-108. doi: 10.11648/j.ijiis.s.2014030601.29
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