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safarian zengir V, zenali B, Jafari hasi Kennedy Y, jafarzadeh L. Investigation of dust and evaluation of its prediction in Ardebil province using ANFIS model. Journal of Spatial Analysis Environmental Hazards 2018; 5 (2) :107-124
URL: http://jsaeh.khu.ac.ir/article-1-2771-en.html
1- University of Mohaghegh Ardabili , Safariyan.vahid@gmail.com
2- University of Mohaghegh Ardabili
3- Azad University of Ardabil
Abstract:   (5193 Views)
Investigation and evaluation of dust and microstrip phenomena is one of the important values ​​in the management of climate and environmental hazards in the Middle East, especially in the arid, western, southern and central parts of Iran. Methods and plans for studying this phenomenon and its management are of great importance and great value. According to studies on dust phenomena based on predictive methods with low error, contradictory and low, the evaluation of the characteristics of dust and its prediction will reduce the irreparable damage that results from it. To do this, in this research, dust monitoring and assessment of its prediction in Ardebil province was performed using the ANFIS model. The data used in this study is the amount of dust in the relevant statistical period to each station from its inception until 2016. The dust phenomenon was used in the observed and predicted time intervals to assess the dust and the ANFIS model for predicting dust phenomena. According to the findings of this study, in the monitoring and prediction of dust situation, the frequency of occurrence in observed years in the maximum amount of dust in Ardabil station with 74% and the lowest in Mashgin is 8%. In the years to come, the maximum amount of dust at Khalkhal Station was 61.67% and the lowest was 10% in Mashgin. In terms of amount of dust, the Ardebil station is more intense than the rest of the stations. In terms of the severity of drought that has been studied, each of the 5 stations studied has a dust concentration of more than 74%. For the 5 stations studied for the next 18 years using manually generated codes, the stations were divided in time series, with the highest average error of training at Pars-Abad Moghan Station with 0.091% and less The highest value was obtained at the Grammy station with a value of 0.001%.
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Type of Study: Research | Subject: Special
Received: 2017/10/15 | Accepted: 2018/05/25 | Published: 2018/09/22

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