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Showing 6 results for Taheri
A Parvardeh, M Taheri, S Kamkar,
Volume 14, Issue 2 (3-2010)
Abstract
S. Mahmoud Taheri,
Volume 22, Issue 2 (3-2018)
Abstract
There are two main approches to the fuzzy regression (more precisely: regression in fuzzy environment): the least of sum of distances (including two methods of least squared errors and least absolute errors) and the possibilistic method (the method of least whole vaguness under some restrictions). Beside, some heuristic methods have been proposed to deal with fuzzy regression. Some of them are based on a combination of two mentioned approaches. Some of them are based on computational algorithmes. A few of heuristic methods use the fuzzy inference systems. Also, there are some methods based on clustering, artificial neural networks, evolutionary algorithms, and nonparametric procedures.
In this paper, a history and basic ideas of the two main approaches to fuzzy regression are reveiwed, and some heuristic methods in this topic are investigated. Moreover, 10 criterion are proposed by which one can evaluate and compare fuzzy regression models.
S Mahmoud Taheri, , , ,
Volume 23, Issue 1 (9-2018)
Abstract
This study aims to use a method of systemic review, called meta-analysis, to analysis the results of studies carried out in Iran about the role of self-regulation learning on learners’ academic performance in the past decade. So far studies investigating the relationship between self-learning and academic achievement have been conducted mainly in the frame of classical statistical models, while the nature of these variables and the relationship between them are fuzzy so that. It is suitable, therefore, to employ a fuzzy method to analysis such data. To do this 50 accomplished researches about the role of self-regulation learning on learners’ academic performance, 31 researches were chosen for fuzzy meta-analysis. The obtained results show that there is a meaningful relationship between self-regulation learning and learners’ academic achievement and self-regulation learning cam explain 4-17 percent of variance of the academic achievement. The obtain results can be use to education program planning and effective learning them.
Hamieh Arzhangdamirchi, Reza Pourtaheri,
Volume 23, Issue 2 (3-2019)
Abstract
Many point process models have been proposed for studying variety of scientific disciplines, including geology, medicin, astronomy, forestry, ecology and ect. The assessment of fitting these models is important. Residuals-based methods are appropriate tools for evaluating good fit of spatial point of process models. In this paper, first, the concepts related to the Voronoi residuals are investigated. Then, after fitting a cluster point process to the data set of the position of the trees in the Guilan forest, the proposed model is evaluated using these residuals.
Mehrdad Tamiji, Dr. S. Mahmoud Taheri,
Volume 25, Issue 2 (3-2021)
Abstract
Methods of inferring the population structure, its applications in identifying disease models as well as foresighting the physical and mental situation of human beings have been finding ever-increasing importance. In this article, first, motivation and significance of studying the problem of population structure is explained. In the next section, the applications of inference of population structure in biology and the treatment of various diseases are described. Afterward, the methods of inferring the population structure as well as detecting the disease model correspond to each subpopulation, for populations whose members are admixture or not, are described separately. To this end, the methods of inferring the population structure through the Bayesian approach are emphasized and the reasons for the superiority of Bayesian methods are illustrated.
Ali Reza Taheriyoun, Gazelle Azadi,
Volume 26, Issue 1 (12-2021)
Abstract
Profile monitoring is usually faced by control charts and mostly the response variable is observable in those problems. We confront here with a similar problem where the values of the reward function are observed instead of the response variable vector and we use the dart model to make it easier to understand. Supposing there exists at most one change-point, a sequence of independent points resulted by darts throws is observed and the estimation of parameters and the change-point (if there exists any) are presented using the frequentist and Bayesian approaches. In both the approaches, two possible precision scalar and matrix are studied separately. The results are examined through a simulation study and the methods applied on a real data.
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