Research Projects

 Research Interests
Statistical Inference, Statistical Analysis for Fuzzy Data, Applied Statistical
Methods, Bayesian Statistics, Modeling in Non-Precise Environments.
 Research Projects
[1] Research on some hydrological characteristics of the south west of Iran,
Isfahan University of Technology (Jehad-e Daneshgahi), 1987,2 - 1987,9.
[2] Research on the educational situation of Ferdowsi University students,
Ferdowsi University, 1992,9 - 1993,2.
[3] Research on c-fuzzy numbers, Isfahan University of Technology, 1994,9 -
1995,8.
[4] Research on fuzzy hypothesis testing (joint, with J. Behboodian), Isfahan
University of Technology, 2001,9 - 2002,8.
[5] Research on sequential approach on hypothesis testing with fuzzy data,
Isfahan University of Technology, 2002,9 - 2003,8.
[6] Research on the consumption of energy in Iranian households (joint with a
group of 5 researchers), Isfahan University of Technology and Ministry of
Energy, 2002,9 - 2003,5.
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[7] Research on extending pedotransfer functions by applying some fuzzy
regression models (joint with J. Mohammadi), University of Shahrekord,
2003,9 - 2004,8.
[8] Research on estimating the prevalence of a disease, subject to
misclassification (joint with A. Zeinal), Isfahan University of Technology,
2004,12 - 2005,6.
6. Publications (In English)
6.1 Journal Papers:
[1] Taheri, S.M., Behboodian, J. (1999), Neyman-Pearson Lemma for fuzzy
hypotheses testing, Metrika, 49: 3-17.
[2] Taheri, S.M., Behboodian, J. (2001), A Bayesian approach to fuzzy
hypotheses testing, Fuzzy Sets and Systems, 123: 39-48.
[3] Taheri, S.M., Behboodian, J. (2002), Fuzzy hypotheses testing with fuzzy
data: a Bayesian approach, Advances in Soft Computing (Lecture Notes in
Artificial Intelligence, No. 2275, Springer), pp. 527-533.
[4] Taheri, S.M. (2003), Trends in fuzzy statistics, Austrian J. Statistics, 32:
239-257.
[5] Zeinal, A., Taheri, S.M. (2003), Sample size determination for estimation
ratio, subject to misclassification, Journal of Science Teacher Training
University, 3: 99-108.
[6] Mohammadi, J., Taheri, S.M. (2004), Pedomodels fitting with fuzzy least
squares regression, Iranian Journal of Fuzzy Systems, 1: 45-61.
[7] Tavanai, H., Taheri, S.M., Nasiri, M. (2005), Modeling of colour yield in
polyethylene terephthalate dyeing with statistical and fuzzy regression, Iranian
Polymer Journal, 14: 954-967.
[8] Torabi, H., Behboodian, J., Taheri, S.M. (2006), Neyman-Pearson Lemma
for fuzzy hypotheses testing with vague data, Metrika, 64: 289-304.
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[9] Taheri, S.M., Azizi, R. (2007), On information energy of the image fuzzy
sets, Information Sciences, 177: 3871-3881.
[10] Taheri, S.M. (2008), C-fuzzy numbers and a dual of extension principle,
Information Sciences, 178: 827-835.
[11] Falsafain, A., Taheri, S.M., Mashinchi, M. (2008), Fuzzy estimation of
parameters in statistical models, International J. of Computational and
Mathematical Sciences, 2: 79-85.
[12] Taheri, S.M., Arefi, M. (2009), Testing fuzzy hypotheses based on fuzzy
test statistic, Soft Computing, 13: 617-625.
[13] Parchami, A., Taheri, S.M., Mashinchi, M. (2010), Fuzzy p-value in testing
fuzzy hypotheses with crisp data, Statistical Papers, 51: 209-226.
[14] Najafi., Z., Taheri, S.M., Mashinchi, M. (2010), Likelihood ratio test based
on fuzzy data, International J. Intelligent Technologies and Applied Statistics,
3: 285-301.
[15] Fattahi, S., Hoseini, S.A., Taheri, S.M. (2010), Cotton yarn engineering
using robust regression and criteria of Mallow’s Cp, Fibers and Polymers, 11:
1075-1082.
[16] Taheri, S.M., Zarei, R. (2011), Extension principle for vague sets and its
applications, Advances in Fuzzy Mathematics, 6: 17-26.
[17] Pourahmad, S., Ayatollahi, S.M.T., Taheri, S.M. (2011), Fuzzy logistic
regression: a new possibilistic model and its application in clinical vague
status, Iranian J. Fuzzy Systems, 8: 1-17.
[18] Arefi, M., Taheri, S.M. (2011), Testing fuzzy hypotheses using fuzzy data
based on fuzzy test statistic, Journal of Uncertain Systems, 5: 45-61.
[19] Taheri, S.M., Zarei, R. (2011), Bayesian system reliability assessment
under the vague environment, Applied Soft Computing, 11: 1614-1622.
[20] Arefi, M., Taheri, S.M. (2011), A fuzzy-based approach to testing
statistical hypotheses, International J. Intelligent Technologies and Applied
Statistics, 4: 1-23.
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[21] Chachi, J., Taheri, S.M. (2011), Fuzzy confidence intervals for mean of
Gaussian fuzzy random variables, Expert Systems with Applications, 38:
5240-5244.
[22] Taheri, S.M., Hesamian, G. (2011), Goodman-Kruskal measure of
association for fuzzy-categorized variables, Kybernetika, 47: 110-122.
[23] Falsafain, A., Taheri, S.M. (2011), On Buckley’s approach to fuzzy
estimation, Soft Computing, 15: 345-349.
[24] Fattahi, S., Hoseini, S.A., Taheri, S.M. (2011), Two-way prediction of
cotton yarn properties and fiber properties using multivariate multiple
regression, Journal of the Textile Institute, 102: 849-856.
[25] Pourahmad, S., Ayatollahi, S.M.T., Taheri, S.M., Z. Habib Agahi (2011),
Fuzzy Logistic Regression based on the least squares approach with
application in clinical studies, Computers and Mathematics with Applications,
62: 3353-3365.
[26] Fattahi, S., Taheri, S.M., Hoseini, S.A. (2012), Cotton yarn engineering
via fuzzy least squares regression, Fibers and Polymers, 13: 390-396.
[27] Arefi, M., Viertl, R., Taheri, S.M. (2012), Fuzzy density estimation,
Metrika, 75: 5-22.
[28] Taheri, S.M., Kelkinnama, M. (2012), Fuzzy linear regression based on
least absolutes deviations, Iranian J. Fuzzy Systems, 9: 121-140.
[29] Parchami, A., Taheri, S.M., Mashinchi, M. (2012), Testing fuzzy
hypotheses based on vague observations: a p-value approach, Statistical
Papers, 53: 469-484.
[30] Chachi, J. Taheri, S.M., Viertl, R. (2012), Testing statistical hypotheses
based on fuzzy confidence intervals, Austrian Journal of Statistics, 41: 267-
286.
[31] Kelkinnama, M., Taheri, S.M. (2012), Fuzzy least-absolutes regression
using shape preserving operations, Information Sciences, 214: 105-120.
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[32] Arefi, M., Taheri, S.M. (2013), A new approach for testing fuzzy
hypotheses based on fuzzy data, International Journal of Computational
Intelligence Systems, 6: 318-327.
[33] Hesamian, G., Taheri, S.M. (2013), Linear rank tests for two-sample fuzzy
data: A p-value approach, Journal of Uncertain Systems, 7: (to appear).
[34] Azizi, M.A., Malaek, S.M.B., Ashrafizadeh, M., Taheri, S.M., Aircraft
design cycle time reduction using artificial intelligence, Aerospace Science
and Technology, (to appear).
[35] Taheri, S.M., Hesamian, G., A generalization of the Wilcoxon signed-rank
test and its applications, Statistical Papers, (to appear), DOI 10.1007/s00362-
012-0443-4.
[36] Chachi, J. Taheri, S.M., A unified approach to similarity measure between
intuitionistic fuzzy sets, International Journal of Intelligent Systems, (to
appear).