Author = Ansari Ghojghar, Mohammad
Evaluating the efficiency of hybrid metamodels of machine learning and Box Jenkins in order to model dust storms (case study: Khuzestan province).

Articles in Press, Accepted Manuscript, Available Online from 03 September 2022


Mohammad Ansari ghojghar; javad bazrafshan; Shahab Araghinejad

Investigating the Interrelationships between Hydro-Social Parameters in the Asian Continent Using Data Mining Methods

Volume 52, Issue 3, May 2021, Pages 597-609


Mohammad Ansari Ghojghar; Sarvin Zmanzad-Ghavidel; fariba khodabakhshi; Masoud Pourgholam-Amiji; Shahab Araghinejad; Ali Salajegheh

Investigating the Relationship between Drought and Trend of the Frequency of Dust Storms in the West and Southwest of Iran

Volume 51, Issue 11, February 2021, Pages 2839-2852


Mohammad Ansari ghojghar; Masoud Pourgholam-Amiji; Shahab Araghinejad

Performance Evaluation of Genetic Algorithm and GA-SA Hybrid Method in Forecasting Dust Storms (Case Study: Khuzestan Province)

Volume 51, Issue 10, December 2020, Pages 2623-2639


Mohammad Ansari ghojghar; Masoud Pourgholam-Amiji; Javad Bazrafshan; Shahab Araghinejad; Abdolmajid Liaghat; Seyed-Mohammad Hosseini-Moghari

Performance Comparison of Statistical, Fuzzy and Perceptron Neural Network Models in Forecasting Dust Storms in Critical Regions in Iran

Volume 51, Issue 8, October 2020, Pages 2051-2063


Mohammad Ansari ghojghar; Masoud Pourgholam-Amiji; Javad Bazrafshan; Abdolmajid Liaghat; Shahab Araghinejad

Trend Analysis of Dusty Days Frequency and its Correlation with Climatic Variables (Case Study: Lorestan Province)

Volume 50, Issue 9, January 2020, Pages 2289-2301


Mohammad Ansari ghojghar; Shahab Araghinejad; javad Bazrafshan; A.H. Hoorfar