Logistic regression analysis is used to model categorical dependent variable. It is usually used in social sciences and clinical research. Human thoughts and disease diagnosis in clinical research contain vagueness. This situation leads researchers to combine fuzzy set and statistical theories. Fuzzy logistic regression analysis is one of the outcomes of this combination and it is used in situa...

Linear programming is one of the most important usages of operation research methods in real life, that includes of one objective function and one or several constraints which can be in the form of equality and inequality. Most of the problems in the real world are include of inconsistent and astute uncertainty, because of this reason we can’t obtain the optimal solution easily. In this paper, ...

The fixed charge transportation problem (FCTP) is a deployment of the classical transportation problem in which a fixed cost is incurred, independent of the amount transported, along with a variable cost that is proportional to the amount shipped. Since the problem is considered as an NP-hard, the computational time grows exponentially as the size of the problem increases. In this pape...

We introduce a new approach to distribution fitting, called Decision on Beliefs (DOB). The objective is to identify the probability distribution function (PDF) of a random variable X with the greatest possible confidence. It is known that f X is a member of = { , , }. 1 m S f L f To reach this goal and select X f from this set, we utilize stochastic dynamic programming and formulate this proble...

This paper takes a broad and novel approach to analysing the Iranian Jewish community of Iran, both as a distinct group and as a constituent part of Iran’s wider population sharing its national culture. The goal was to find a new way of addressing the topic, avoiding many ambiguities, and bringing all discourse back to its starting point: Iranian identity. If we identify Persian roots as the fo...

This paper presents a simple yet powerful original approach for approximating dispersivity in porous media. The key to this approach is both use of least-squares criterion and image processing technique. Two dimensional transparent models, including horizontal and vertical configurations, under different combinations of grain sizes and pore velocities, experimented. Concentration data were obta...

Buckling strength of composite latticed cylindrical shells is one of the important parameters for studying the failure of these structures. In this paper, new governing differential equations are derived for latticed cylindrical shells and their critical buckling axial loads. The nested structure under compressive axial buckling load was analyzed. Finite Element Method (FEM) was applied to mode...

Clustering is the process of dividing a set of input data into a number of subgroups. The members of each subgroup are similar to each other but different from members of other subgroups. The genetic algorithm has enjoyed many applications in clustering data. One of these applications is the clustering of images. The problem with the earlier methods used in clustering images was in selecting in...

  Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. In this paper we propose a novel app...