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Landfill Site Selection Using Simple Additive Weighting (SAW) Method and Artificial Neural Network Method; A Case Study from Lorestan Province, Iran

Author

Listed:
  • E Mokhtari
  • M Khamehchian
  • G Montazer
  • M Nikudel

Abstract

The selection of a site for landfill is one of the most difficult steps in landfilling process. Several techniques and methods have been used in a sanitary landfill site selection in the literature. In this paper two methods consist of a method based on the artificial neural network method and simple additive weighting (SAW) method have been used to landfill site selection in Lorestan province, IRAN and the results of two methods compare to each other. The input data of the research consist of 9 digitized data layers including geology, faults, slope, vegetation, residential areas, road and railways, groundwater resources, dams, drainage network maps. The land suitability map prepared by means of SAW method has been grouped in five categories with 0.5 intervals (Ai: 0 to 2.5). Derived map from the neural network modeling exhibit a gradual suitability for a landfill site. With SAW method that was used in the first step of the research, most of the area is considered unsuitable, while by the neural network method, the area with high suitability covers different parts of the study area. One of the most characteristics of the neural network methods is flexibility. The maps that are provided by these methods help the decision makers to select areas with a high suitability value and then proceed to field investigations according to the level of enforcement of the other policies.

Suggested Citation

  • E Mokhtari & M Khamehchian & G Montazer & M Nikudel, 2016. "Landfill Site Selection Using Simple Additive Weighting (SAW) Method and Artificial Neural Network Method; A Case Study from Lorestan Province, Iran," International Journal of Geography and Geology, Conscientia Beam, vol. 5(10), pages 209-223.
  • Handle: RePEc:pkp:ijogag:v:5:y:2016:i:10:p:209-223:id:1966
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