The AUT Journal of Modeling and Simulation is one of the publishing journals at Amirkabir University of Technology. The journal has been running for more than 50 years, publishing numerous English original articles.

The reviewers of the journal comprise of university academics around the world. The review strategy of AJMS is single-blind, peer review, electronic and print, biannually publication. The editorial board members meet regularly to decide about the articles. The editorial board members are all senior researchers from different universities all over the world. All modeling and simulation fields are of interest to this Journal. Most research and experiments in the fields of science, engineering have been spending significant efforts to extract rules from various complicated phenomena by observations, recorded data, analytical or experimental derivations and so on (Modeling). The rules are normally formulated by quantitative expressions (quantitative models) or qualitative expressions (qualitative models). Identification and Simulation provides mechanisms to establish the models and Control provides mechanisms to improve the performance of system, represented by their models.

We, therefore, request all researchers and university lecturers to send their original scientific manuscripts to this journal.

Dear researchers, to view the records of the Amirkabir Scientific Research Journal by AJSR.AUT.AC.IR. 


 This journal is following of Committee on Publication Ethics (COPE) and complies with the highest ethical standards in accordance with ethical laws.


 

CC BY-NC: This license lets others remix, adapt, and build upon your work non-commercially, and although their new works must also acknowledge you and be non-commercial, they don’t have to license their derivative works on the same terms.


Access to articles from this site is free

This Journal allows the author(s) to hold the copyright without restrictions.

This Journal doesn't have any submission and article processing charges (APCs).


Current Issue: Volume 51, Issue 2, Summer and Autumn 2019, Pages 81-254 

Research Article

1. Robust Fault Detection on Boiler-turbine Unit Actuators Using Dynamic Neural Networks

Pages 83-90

10.22060/miscj.2019.16453.5158

Arash Daneshnia; Mohammad Bagher Menhaj; farshad barazandeh; Ali Kazemi


15. Statistical analysis of the association between rheological properties of blood and atherosclerosis

Pages 227-240

10.22060/miscj.2019.16590.5163

Majid Abbasian; Mehrzad Shams; Ziba Valizadeh; Abouzar Moshfegh; Ashkan Javadzadegan


Publication Information

Publisher

Director-in-Charge Editor-in-Chief Executive Manager
Print ISSN
2588-2953
Online ISSN
2588-2961

Indexing and Abstracting

Keywords Cloud