M Shaygan; Marzieh Mokarram
Abstract
Industrial activities and urban traffic contribute to increased air pollution in large cities, resulting in a rise in various diseases among the population. Consequently, studying and investigating polluted areas is crucial for effective city management. This study aims to examine the air pollution levels ...
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Industrial activities and urban traffic contribute to increased air pollution in large cities, resulting in a rise in various diseases among the population. Consequently, studying and investigating polluted areas is crucial for effective city management. This study aims to examine the air pollution levels in Tehran, Isfahan, and Qom cities, focusing on NO2, CO2, CO, and CH4 pollutants, during two distinct periods: pre-COVID-19 (2018-2019) and during COVID-19 (2020-2021), across all four seasons. By employing the Pearson correlation method and RBF neural networks (radial basis function neural network), the relationship between temperature and pollutants was explored. The findings reveal higher levels of air pollution in Tehran and Isfahan compared to other regions. Moreover, the study demonstrates a significant reduction in pollution during the COVID-19 era compared to the pre-COVID-19 period. Additionally, the regression analysis highlights a strong correlation between temperature increase and pollution levels (R2=0.981). Furthermore, the RBF method exhibits high accuracy in predicting air pollution levels (R2 = 0.85, RMSE = 0.08). In conclusion, this research underscores the urgent need for comprehensive measures to mitigate air pollution, particularly in highly polluted areas, and emphasizes the role of temperature as a crucial factor affecting pollution levels.
Mehran Shaygan; Marzieh Mokarram
Abstract
Due to the fact that droughts can affect both water quality and quantity, the purpose of this study is to determine the effect of droughts on water quality and quantity in Northern Fars province, Iran, based on drought indicators. The drought indices PCI, TVDI, and NDVI are used to study drought from ...
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Due to the fact that droughts can affect both water quality and quantity, the purpose of this study is to determine the effect of droughts on water quality and quantity in Northern Fars province, Iran, based on drought indicators. The drought indices PCI, TVDI, and NDVI are used to study drought from 2000 to 2020. Also, the kriging method is used to generate zoning maps of elements in water (Ca, Cl, EC, K, Na, Mg). Then, using the neural network (MLP) method, the amount of elements in the water is predicted based on drought indices. Based on the values of the drought indicators, the trend of drought changes in the region is increasing from 2000 to 2020, with the southern areas of the region experiencing a more acute drought than the rest of the region. In addition, the zoning map of the elements in water indicated that salt concentrations are higher in the southern parts than in the northern parts. Correlation between drought indices and the amounts of elements in water showed that Ca has a high correlation (R2= 0.820) with TVDI index, and also Cl, EC, K, Na, and Mg have significant correlations (R > 0.8) with the index. Using drought indicators, MLP results for predicting water quality status show that southern regions have more solutes and lower water quality. Furthermore, the R2 values of the model for predicting the elements Cl, EC, K, Na, Mg, TDS, TH using PCI index equal to 0.85 and for Ca using TVDI index equal to 0.71, which indicates high accuracy.
Mehran Shaygan; Marzieh Mokarram
Abstract
Fars province has a shortage of surface water resources due to its location in arid and semi-arid regions in Iran. Therefore, in order to exploit groundwater resources, determining water quality is very important. Due to the importance of the subject in this study, the aim is to determine the quality ...
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Fars province has a shortage of surface water resources due to its location in arid and semi-arid regions in Iran. Therefore, in order to exploit groundwater resources, determining water quality is very important. Due to the importance of the subject in this study, the aim is to determine the quality of the southern regions of Shiraz in Fars province. To prepare zoning maps of the sampled points, the Inverse distance weighting (IDW) method was used. Then, to homogenize each of the prepared layers, the fuzzy method was used. In this method, by defining the membership function for each of the zoning maps, the data were placed between zero and one based on the degree of importance they have for water quality. Finally, the analytic network process (ANP) method was used to weigh the layers and prepare the final water quality map. The results showed that about 80% of the study area has good water quality. While about 4% of the region (parts of the north and east) has poor quality in terms of drinking.
M Shaygan; M Mokarram
Abstract
The aim of this study was to use the attraction model to increase the spatial resolution of the Digital Elevation Model (DEM) and to use the genetic algorithm to predict stream network in the future and compare its results with stream of extraction of DEM with resolution of 30 m. In the quadrant neighborhood, ...
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The aim of this study was to use the attraction model to increase the spatial resolution of the Digital Elevation Model (DEM) and to use the genetic algorithm to predict stream network in the future and compare its results with stream of extraction of DEM with resolution of 30 m. In the quadrant neighborhood, a neighbor pixel is the only pixel in the same quadrant while in touching neighborhood a neighbor pixel that is the pixel, which physically touches a subpixel. In this method, the pixels were divided into a number of sub-pixels according to the values of the neighboring pixels. The results of the attraction model showed that Scale 2 with the Neighborhood model 2 is more accurate than other Neighborhoods for extracting DEM with higher resolution. The results showed that the predicted stream-network landscapes created using the GLE algorithm had the self-similar tree structure of natural stream networks. Also, the results of the genetic algorithm showed that a change in the degree of waterways in the study area over time compared to the current situation, so that the degree of number of first-class waterways in the future will change to grade 3 due to erosion in upper lands. Therefore, using these models, the condition of waterways can be predicted in the future and better management can be adopted for watersheds.
Volume 7, Issue 1 , December 2015, , Pages 39-57
Abstract
With the increase in population and consequent increasing needs of society, land use planning is of particular importance. Land use planningdue to being involved with several conflicting aims, multi- objective evolutionary algorithm would be a useful tool to solve land use planning. But use of these ...
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With the increase in population and consequent increasing needs of society, land use planning is of particular importance. Land use planningdue to being involved with several conflicting aims, multi- objective evolutionary algorithm would be a useful tool to solve land use planning. But use of these algorithms should be examined according to the type of issues. In the study, addition to introducing a model to optimize land use, effective solution for the application of multi- objective genetic algorithm on a variety of problems related to land use planning was presented. In order to land uses optimization in the study, the algorithm NSGA-II was use in the model. Output of the model might be introduced patterns for reduction of erosion to an acceptable level and enhancing the economic benefits. This will be skillfully carried out while the land use adaptation is in the highest level and land use changes are easy with high level of continuity.An innovative operator which producing the initial population and an innovative operator with an appropriate Crossover of land use planning issues were developed.The developed model in the study was implemented in Kerman-Rodbar watershed. Evaluation results show that the model is able to suggest patterns to land use planning that reduce erosion about 30 to 35%. While the economic benefits of the changes will be about 40 to 50 %. Furthermore all models have a high consistency and low difficulty to change. These operators have had a significant impact on problem solving. Keywords: Multi- objective optimization, NSGA-II algorithm, Innovative Operators, Land use planning, Ecological potentiality
