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دکتر فريد صابري موحد (استادیار )
دانشکده علوم و فناوری های نوین / گروه آموزشي رياضي
  • رشته: آنالیزعددی _ جبرخطی عددی
  • شماره اتاق: 202
  • تلفن : 3421
 

انگلیسی

  1. F. Saberi-Movahed, M. Mohammadifard, A. Mehrpooya, M. Rezaei-Ravari, K. Berahmand, M. Rostami, S. Karami, M. Najafzadeh, D. Hajinezhad, M. Jamshidi, F. Abedi, M. Mohammadifard, E. Farbod, F. Safavi, M. Dorvash, N. Mottaghi-Dastjerdi, S. Vahedi, M. Eftekhari, F. SaberiMovahed, H. Alinejad-Rokny, S. S Band, I. Tavassoly, Decoding Clinical Biomarker Space of Covid-19: Exploring Matrix Factorization-based Feature Selection Methods, Computers in Biology and Medicine, 5 April 2022, 105426, https://doi.org/10.1016/j.compbiomed.2022.105426.

  2. F. Saberi-Movahed , A. Tajaddini, M. Heyouni, L. Elbouyahyaoui, Some iterative approaches for Sylvester tensor equations, Part II: A tensor format of Simpler variant of GCRO-based methods, Applied Numerical Mathematics, 172, 413-427, 2022, https://doi.org/10.1016/j.apnum.2021.10.022.

  3. F. Saberi-Movahed , A. Tajaddini, M. Heyouni, L. Elbouyahyaoui, Some iterative approaches for Sylvester tensor equations, Part I: A tensor format of truncated Loose Simpler GMRES, Applied Numerical Mathematics, 172, 428-445, 2022, https://doi.org/10.1016/j.apnum.2021.10.020.

  4. M. Mokhtia, M. Eftekhari, F. Saberi-Movahed , Dual-manifold regularized regression models for feature selection based on hesitant fuzzy correlation, Knowledge-Based Systems, Volume 229, 11 October 2021, 107308, https://doi.org/10.1016/j.knosys.2021.107308.

  5. A. Mehrpooya, F. Saberi-Movahed, N. Azizizadeh, M. Rezaei-Ravari, F. Saberi-Movahed, M. Eftekhari, I. Tavassoly, High dimensionality reduction by matrix factorization for systems pharmacology, Briefings in Bioinformatics, 23(1), bbab410, 2022, https://doi.org/10.1093/bib/bbab410.

  6. A. Tajaddini, G. Wu, F. Saberi-Movahed , N. Azizi-Zadeh, Two new variants of the simpler block GMRES method with vector deflation and eigenvalue deflation for multiple linear systems, Journal of Scientific Computing, 86, 9 (2021). https://doi.org/10.1007/s10915- 020-01376-w.

  7. M. Rezaei, M. Eftekhari, F. Saberi-Movahed , Regularizing extreme learning machine by dual locally linear embedding manifold learning for training multi-label neural network classifiers, Engineering Applications of Artificial Intelligence, Volume 97, January 2021, 104062.

  8. L. Elbouyahyaoui, M. Heyouni, A. Tajaddini, F. Saberi-Movahed , On restarted and deflated block FOM and GMRES methods for sequences of shifted linear systems, Numerical Algorithms, 87, 1257–1299, 2021, https://doi.org/10.1007/s11075-020-01007-3.

  9. M. Rezaei, M. Eftekhari, F. Saberi-Movahed , ML-CK-ELM: An efficient Multi-layer Extreme Learning Machine using Combined Kernels for Multi-label classification, Scientia Iranica, 27 (6), 3005–3018, 2020, https://doi.org/10.24200/sci.2020.53490.3263.

  10. M. Mokhtia, M. Eftekhari, F. Saberi-Movahed, Feature selection based on regularization of sparsity based regression models by hesitant fuzzy correlation, Applied Soft Computing, Volume 91, June 2020, 106255.

  11. M. Heyouni, F. Saberi-Movahed, A. Tajaddini, A tensor format for the generalized Hessenberg method for solving Sylvester tensor equations, Journal of Computational and Applied Mathematics, Volume 377, 15 October 2020, 112878.

  12. M. Mokhtia, M. Eftekhari, F. Saberi-Movahed, Proposing a method for regression based on feature extraction and hesitant fuzzy sets, Electronic Industries, 10 (4), 85-96, 2020. (ISC, Verified by Ministry of Science, Research and Technology, In Persian)

  13. F. Saberi-Movahed, M. Najafzadeh, A. Mehrpooya, Receiving more accurate predictions for Longitudinal Dispersion Coefficients in water pipelines: Training Group Method of Data Handling using Extreme Learning Machine conceptions, Water Resources Management, 34, 529-561, 2020.

  14. F. Saberi-Movahed, M. Eftekhari, M. Mohtashami, Supervised feature selection by constituting a basis for the original space of features and matrix factorization, International Journal of Machine Learning and Cybernetics, 11, 1405-1421, 2020.

  15. M. Dehtaghi Zadeh, F. Saberi-Movahed, M. Eftekhari, Feature selection method based on subspace learning and factorization of basis matrix for DNA micro-array datasets, Iranian Journal of Biomedical Engineering, 13 (3), 331-340, 2019. (ISC, Verified by Ministry of Science, Research and Technology, In Persian)

  16. M. Heyouni, F. Saberi-Movahed, A. Tajaddini, On global Hessenberg based methods for solving Sylvester matrix equations, Computers & Mathematics with Applications, 77, 77–92, 2019.

  17. M. Najafzadeh, F. Saberi-Movahed, GMDH-GEP to predict free span expansion rates below pipelines under waves, Marine Georesources & Geotechnology, 37 (3), 375–392, 2019.

  18. M. Najafzadeh, F. Saberi-Movahed, S. Sarkamaryan, NF-GMDH based self-organized systems to predict bridge pier scour depth under debris flow effects, Marine Georesources & Geotechnology, 36 (5), 589–602, 2018.

  19. F. Beik, F. Saberi-Movahed, S. Ahmadi, On the Krylov subspace methods based on tensor format for positive definite Sylvester tensor equations, Numerical linear algebra with applications, 23, 444–466, 2016.

  20. M. Mohseni Moghadam, A. Rivaz, A. Tajaddini, F. Saberi-Movahed, Convergence analysis of the global FOM and GMRES methods for solving matrix equations AXB = C with SPD coefficients, Bulletin of the Iranian Mathematical Society, 14, 981–1001, 2015.

فارسی

    اطلاعاتی درج نشده است

انگلیسی

  1. M. Eftekhari, F. Saberi-Movahed, A. Mehrpooya, Supervised feature selection via information gain, maximum projection and minimum redundancy, in Proceeding of the 10th Seminar on Linear Algebra and its Applications, Shahid Bahonar University of Kerman, Kerman, 2020.

    فایل مقاله فایل ارائه
  2. B. Ebrahimi, M. Eftekhari, F. Saberi-Movahed, Multi-label feature selection via feature correlation, minimum redundancy and sparsity regularization, Bojnourd, Iran, 2019.

  3. M. Mohseni Moghadam, A. Rivaz, A. Tajaddini, F. Saberi-Movahed, New convergence results for the Conjugate Gradient method, 7th Seminar of Numerical analysis and its applications, Kerman, Iran, 2018.

  4. F. Beik, F. Saberi-Movahed, FOM-BTF: Full orthogonalization method based on tensor format, 5th Seminar of Numerical analysis and its applications, Rafsanjan, Iran, 2014.

  5. F. Saberi-Movahed, A. Tajaddini, Convergence results for generalized Conjugate Gradient method for the matrix equation AXB = C, 7th Seminar on Linear Algebra and its Applications, Mashhad, Iran, 2014.

  6. A. Rivaz, F. Saberi-Movahed, Some applications of T-matrices in symmetric positive definite matrices, 6th Seminar on Linear Algebra and its Applications, Arak, Iran, 2011.

  7. F. Saberi-Movahed, M. Neyestani, M.A. Yaghoubi, Combining a feasible method with the penalty function in PSO algorithm and its application in constrained optimization problems, 6th Seminar on Linear Algebra and its Applications, 40th Annual Iranian Mathematics conference, Sharif University of technology, Tehran, Iran, 2008.

فارسی

    اطلاعاتی درج نشده است

انگلیسی

  1. 1.M. Eftekhari, A. Mehrpooya, F. Saberi-Movahed, V. Torra, How Fuzzy Concepts Contribute to Machine Learning, Studies in Fuzziness and Soft Computing, Springer Cham, 2022, https://doi.org/10.1007/978-3-030-94066-9.

فارسی

    اطلاعاتی درج نشده است