M
Maryam Mirakbari
Researcher at University of Tehran
Publications - 16
Citations - 327
Maryam Mirakbari is an academic researcher from University of Tehran. The author has contributed to research in topics: Copula (probability theory) & Climate change. The author has an hindex of 7, co-authored 15 publications receiving 200 citations. Previous affiliations of Maryam Mirakbari include Shiraz University.
Papers
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Regional Bivariate Frequency Analysis of Meteorological Droughts
TL;DR: In this article, a regional bivariate analysis is proposed for meteorological drought analysis based on time series analysis of 41 meteorological stations in Khuzestan province, southwest of Iran.
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Spatial and seasonal variations of sand-dust events and their relation to atmospheric conditions and vegetation cover in semi-arid regions of central Iran
TL;DR: In this article, the authors used Ridge Regression (RR) method to analyze the relationship between seasonal variations of precipitation, surface winds speed, air temperature, and Enhanced Vegetation Index (EVI) with Dust Storm Index (DSI) for two different periods (2001-2008 and 2009-2016).
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Evaluation of machine learning models for predicting the temporal variations of dust storm index in arid regions of Iran
TL;DR: In this paper, the applicability of nine machine learning (ML) models (including multivariate adaptive regression splines, least absolute shrinkage and selection operator, k-nearest neighbors, genetic programming, support vector machine, Cubist, artificial neural networks, extreme gradient boosting, random forest) and their average for predicting the seasonal dust storm index (DSI ) during 2000-2018 in arid regions of Iran.
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Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP)
Tayyebeh Mesbahzadeh,Maryam Mirakbari,Mohsen Mohseni Saravi,Farshad Soleimani Sardoo,Farshad Soleimani Sardoo,Mario Marcello Miglietta +5 more
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Spatial hydrological drought characteristics in Karkheh River basin, southwest Iran using copulas.
TL;DR: In this paper, a comparative analysis between the maximum likelihood parametric and non-parametric method of the Kendall estimation method for copulas parameter estimation was conducted to study joint severity-duration probability and recurrence intervals in Karkheh River basin.