Application of hierarchy-fuzzy analysis models and artificial neural networks in locating urban waste burial (Case Study: Lali city)
Article Type:
Research/Original Article (بدون رتبه معتبر)
Background and objective

 Today, waste burial is the most common method in many countries due to its lower cost and acceptance of a wider range of waste. In locating the waste landfill, various parameters such as the needs of urban communities, government, and environmental laws, and a large number of quantitative and qualitative criteria are evaluated. For this purpose, several multi-criteria decision-making methods are used in prioritizing suitable places.

Materials and methods

  This study aims to investigate the suitable places to bury urban wastes in Lali city using a hierarchical-fuzzy analysis process (FAHP) along with a spatial information system and artificial neural network. For this purpose, data such as slope, slope direction, geology, land use, fault, precipitation, soil science, topography, vegetation, communication lines, hydrographic networks, wind, underground water level, and population centers as Information layers were used to locate the waste burial. After standardizing and preparing the maps, the steps related to the weighting of the desired layers were carried out to achieve the weight and importance of each in the positioning process. Then, pairwise comparisons were made between the indicators based on fuzzy numbers and using the FAHP technique.

Results and conclusion

 Considering all the effective factors in locating and weighting each of the criteria and sub-criteria and combining the data with GIS and artificial neural networks, the proposed areas for landfilling according to the direction of the prevailing winds in the region, in the southeast part of the range Studies were considered that the city has the least development in this direction. Whereas, the location of the current waste burial site is located in an inappropriate place in the north of the city and a tourist area.

Journal of Nature and Spatial Sciences, Volume:3 Issue: 1, Winter and Spring 2023
38 to 49  
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