fuzzy logic

The aim of localization of rangeland species plantation is to predict the potentials and limitations of rangelands for plantation. Aellenia subaphylla is resistant to drought and salinity. It produces considerable forage in winter rangelands. In this research, the geographic information system and two methods of classic and fuzzy logic were used to locate this species in winter rangelands of Golestan province in 2018. At first, the needed information and layers were collected, and the required maps were prepared. Then, according to the ecological requirements of A. subaphylla, the layers for the classic method were classified into two appropriate and inappropriate classes, while for the fuzzy method classified into inappropriate, proportionate, appropriate and perfectly suitable classes. Then, by combining the classifieds layers, the final maps were obtained using Boolean and fuzzy logic method. Localization of A.subaphylla using classic logic indicated that 47.5% of the winter rangelands of Golestan province are suitable and 52.5% are notsuitable for plantation of A.subaphylla. However, the fuzzy logic demonstrated that 15.8% of the studied rangelands are highly suitable, 13.8% are suitable, 26.2% are moderately suitable and 44.2% are notsuitable for A.subaphylla plantation. The results demonstrated that high soil salinity, soil acidity and temperature conditions are limiting factors for A.subaphylla plantation in degraded winter rangeland of Golestan province. It was found that the fuzzy logic gives better and more accurate results than the classic method, so it is recommended to localization of suitable areas for rangeland species plantation.

This study was conducted aimed to identify the potential of lands in Lorestan Province for the second cultivation of forage millet using Geographic Information System(GIS), Network Analysis Process(ANP) and fuzzy logic.In order to identify the potential of lands, first the raster layer of environmental factors affecting forage millet cultivation including the minimum, maximum and mean temperature, elevation, slope, pH, texture, organic matter, total nitrogen, potassium and phosphorus available in GIS was prepared. Then, using fuzzy functions, the map of each factor was standardized. The weight of each factor was determined by ANP. By combining the weighted layers, the final layers were produced and zoned into four highly suitable, suitable, marginally suitable and unsuitable classes based on fuzzy logic.The results showed that fuzzy value of agricultural lands for forage millet was between 0.35 and 0.88. The highest study area level belonged to the suitable class(60.42%) and the lowest study area level belonged to the highly suitable class(16.35%). Investigation of climatic suitability, topography and soil fertility maps showed that these factors caused severe limitations in 38.27, 38.15 and 7.44% of lands, respectively. Evaluation of climatic maps, topographic and soil factors showed that except for soil pH, all other factors in a part of the study area caused limitations for forage millet cultivation.Investigation of the land suitability final map showed that about 77% of the study area are highly suitable and suitable and cold regions, especially the east. Northeast of the province, are marginally suitable for forage millet double cropping.

The increasing demand for water has led to the development of various methods for water resources management. Some structural methods include the construction of barriers in the path of surface flows and make water reservoirs, which earth-fill dams are in this category. Efficiency and productivity of a dam depend on many factors, most importantly, the suitable areas for the construction of these dams. This research was conducted with the aim of developing a decision support system based on RS and GIS techniques and identifying and prioritizing suitable areas for the construction of earth-fill dams in the Beheshtabad watershed of the North Karun watershed. For this purpose, previous studies in this field were reviewed and effective criteria in locating the earth fill dams were selected. After selecting the set of criteria, a pairwise comparison questionnaire was made and provided to relevant experts. Then, using the Analytic Hierarchy Process (AHP), prioritization and determination of the relative weight of these criteria were performed. Maps of each factor were prepared and standardized; then weights obtained by AHP method was then applied to them. Finally, the map was prepared with three categories of inappropriate, good, and very good for the construction of the earth-fill dam in the region. The results show that geomorphologic and geological criteria with the highest weight are the most important in determining the suitable location for earth-fill dam construction. This criterion composes of four sub-criteria: Karst, Fault, Landslide and Erosion. After this criterion, topography, investment, land use, distance from groundwater sources, distance from road and soil depth were ranked in order of importance. It was also found that more than four kilometers of the hydrological network of this watershed have a very good capability for the construction of short earth-fill dams in order to manage water resources.

In recent decades, increasing of population and development of technology and, consequently, intense agricultural and industrial activities have exposed groundwater resources to a variety of pollutants. Ajabshir plain, located in the southwest of East Azarbaijan province and southeast of Urmia Lake, is one of the areas that has faced groundwater contamination and needs more qualitative studies. In this study, first, the conventional drastic method was used to investigate the potential of nitrate contamination in Ajabshir plain, and then the optimization process was performed using the methods of genetic algorithm and fuzzy logic (Sugeno). The index values in the conventional drastic method were obtained from 87 to 145, as well as the drastic index values obtained by considering the weights of the genetic algorithm and optimization with fuzzy logic, from 47 to 74 and 0.01 to 0.6, respectively. According to the allergy classification the ordinary drastic is located in low, low to medium, and medium to high ranges, in which areas from the north of the plain and the north of Ajabshir city had moderate to high vulnerability index. Also, the optimized variables with genetic algorithm and fuzzy logic are in the safe zone in terms of contamination potential due to lower index values than 79. The normal drastic correlation coefficient, genetic algorithm, and fuzzy logic method with nitrate concentration were 0.2,73, 0.57, and 0.796, respectively. Therefore, the results show the superiority of the fuzzy logic method over other methods.

Finding an appropriate land to implement an activity in a particular geographical region became a significant phase of project implementation process especially in regional and national levels. One of the most useful tools in finding the susceptive locations of desert revival is utilization of computerized models. Finding the locations using Fuzzy Logic and Geographical Information Systems has been utilized in various special fields. This research aimed to determine the appropriate locations of desert revival with the risk degree by using of this model. This research adopted a method based on inspecting and grouping of environmental parameters affecti on preventing desertification. The method is accomplished using available parameters in the region and mapping of these resources were done by using Kriging and IDW methods; and ultimately specifying a simple model by valuation of Fuzzy Logic. Results showed that the Fuzzy model Gamma 0.8 had the best compatibility for recognizing the deserts and the susceptive places for combating desertification with high success rate or desert revival risk.