Optimization of groundwater monitoring network using Ant Colony Optimization (ACO) algorithm

Document Type : Technical Report

Authors

Abstract
In this paper, using the one of the most robust optimization technique, Ant Colony Optimization Algorithm (ACO) the minimum number of required sampling points was determined in Hashtgerd plain. The ACO technique is based on the minimum distance between the food source and the ant nest. In Hashtgerd plain using ACO about ۳۰% of sampling point were reduced. In this aquifer, the number of sampling points for contamination research where in ۲۵ location and after the application of ACO technique results showed that only ۱۸ sampling points is enough and the ۷ number of sampling points is not necessary and introduced more expenses for the contamination study. In addition, the results of nitrate contamination contour plot before and after reducing the sampling points from ۲۵ to ۱۸ shows a small change in contour maps. The maximum RMSE after reduction ۷ sampling points is about ۰.۳۱۹۸ that shows the minimum error for optimized network. In this paper, using the one of the most robust optimization technique, Ant Colony Optimization Algorithm (ACO) the minimum number of required sampling points was determined in Hashtgerd plain. The ACO technique is based on the minimum distance between the food source and the ant nest. In Hashtgerd plain using ACO about ۳۰% of sampling point were reduced. In this aquifer, the number of sampling points for contamination research where in ۲۵ location and after the application of ACO technique results showed that only ۱۸ sampling points is enough and the ۷ number of sampling points is not necessary and introduced more expenses for the contamination study. In addition, the results of nitrate contamination contour plot before and after reducing the sampling points from ۲۵ to ۱۸ shows a small change in contour maps. The maximum RMSE after reduction ۷ sampling points is about ۰.۳۱۹۸ that shows the minimum error for optimized network. In this paper, using the one of the most robust optimization technique, Ant Colony Optimization Algorithm (ACO) the minimum number of required sampling points was determined in Hashtgerd plain. The ACO technique is based on the minimum distance between the food source and the ant nest. In Hashtgerd plain using ACO about ۳۰% of sampling point were reduced. In this aquifer, the number of sampling points for contamination research where in ۲۵ location and after the application of ACO technique results showed that only ۱۸ sampling points is enough and the ۷ number of sampling points is not necessary and introduced more expenses for the contamination study. In addition, the results of nitrate contamination contour plot before and after reducing the sampling points from ۲۵ to ۱۸ shows a small change in contour maps. The maximum RMSE after reduction ۷ sampling points is about ۰.۳۱۹۸ that shows the minimum error for optimized network. In this paper, using the one of the most robust optimization technique, Ant Colony Optimization Algorithm (ACO) the minimum number of required sampling points was determined in Hashtgerd plain. The ACO technique is based on the minimum distance between the food source and the ant nest. In Hashtgerd plain using ACO about ۳۰% of sampling point were reduced. In this aquifer, the number of sampling points for contamination research where in ۲۵ location and after the application of ACO technique results showed that only ۱۸ sampling points is enough and the ۷ number of sampling points is not necessary and introduced more expenses for the contamination study. In addition, the results of nitrate contamination contour plot before and after reducing the sampling points from ۲۵ to ۱۸ shows a small change in contour maps. The maximum RMSE after reduction ۷ sampling points is about ۰.۳۱۹۸ that shows the minimum error for optimized network. In this paper, using the one of the most robust optimization technique, Ant Colony Optimization Algorithm (ACO) the minimum number of required sampling points was determined in Hashtgerd plain. The ACO technique is based on the minimum distance between the food source and the ant nest. In Hashtgerd plain using ACO about ۳۰% of sampling point were reduced. In this aquifer, the number of sampling points for contamination research where in ۲۵ location and after the application of ACO technique results showed that only ۱۸ sampling points is enough and the ۷ number of sampling points is not necessary and introduced more expenses for the contamination study. In addition, the results of nitrate contamination contour plot before and after reducing the sampling points from ۲۵ to ۱۸ shows a small change in contour maps. The maximum RMSE after reduction ۷ sampling points is about ۰.۳۱۹۸ that shows the minimum error for optimized network.

Keywords


Volume 9, Issue 4 - Serial Number 19
Winter 2016
Pages 171-174

  • Receive Date 17 March 2012
  • Revise Date 30 August 2012
  • Accept Date 25 September 2012