Although most dust storms, especially those prevailing in Iran, are often regional in nature, But local centers dust, the dust belt and specifically in Iran, played a significant role. One of the origins of local dust in this belt is Yazd city and salt domes northeast of Ardakan. Understanding the characteristics of dust storms is important in terms of type, frequency, location and time of occurrence. Due to the dry climatic conditions and strong and erosive winds on it, the city of Yazd is faced with various dust events every year, which causes significant damage to the economic and biological resources of the city. In addition to climatic parameters and indicators, some indicators reveal that climate change can also affect the course of changes in dust occurrence. In addition to climatic parameters and indicators, some indicators reveal that climate change can also affect the process of change in the occurrence of dust in order to identify these indicators from the software ClimPACT is based on RClimDEX software and runs in R 2.10 software environment. In addition to identifying the trend of dust changes, the purpose of this study is to determine the importance of each factor affecting the occurrence of dust in Yazd. For this purpose, analysis and comparison of different functions of neural network, multilayer perceptron was used and finally the model with the least error rate and the highest correlation coefficient, as the optimal model to investigate the share of climatic factors affecting the occurrence of dust originating around and outside the station was estimated based on the optimal model. The occurrence of internal and external dust (dependent variable) was modeled and analyzed and the most important determining factors in the occurrence of internal and external dust were determined
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