Fuzzy regression is considered one of the most important regression models, and recently the fuzzy regression model has become a powerful tool for conducting statistical operations, however, the above model also faces some problems and violations, including (when the data is skewed, or no-normal, .....) and thus leads to incorrect results, so it is necessary to find a model to deal with such violations and problems suffered by the regular fuzzy regression models and at the same time be more powerful and immune than the fuzzy regression model called the semi-parametric fuzzy quantile regression. This model is characterized by containing two parts, the first is the fuzzy parametric part (fuzzy inputs and crisp parameters) and the second is the fuzzy nonparametric part for fuzzy triangular numbers, and the semiparametric fuzzy quantile regression is estimated. To demonstrate the effectiveness of our combining model, we will utilize the following Akbari and Hesamian (2019) dataset that was used as a reference case study. Estimate Fuzzy Quantile Regression Model: (FQRM), Fuzzy semi-parametric quantile regression: (FSPQRM), Fuzzy Support Vector Machine: (FSVM), Combining FQRM-FSVR (Comb), Combining FSPQRM-FSVR. Using a new metric measure Jensen–Shannon Distance: (JS) based on fuzzy belonging functions. Two criteria MSM and G1 were used in comparison.
This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro
... Show MoreThe research demonstrates new species of the games by applying separation axioms via sets, where the relationships between the various species that were specified and the strategy of winning and losing to any one of the players, and their relationship with the concepts of separation axioms via sets have been studied.
In this article, the notions are introduced by using soft ideal and soft semi-open sets, which are - - - -closed sets " -closed" where many of the properties of these sets are clarified. Some games by using soft- -semi, soft separation axioms: like ( 0 ( 0 Using many figures and proposition to study the relationships among these kinds of games with some examples are explained.
The significance of the work is to introduce the new class of open sets, which is said Ǥ- -open set with some of properties. Then clarify how to calculate the boundary area for these sets using the upper and lower approximation and obtain the best accuracy.
The attribute quality control charts are one of the main useful tools to use in control of quality product in companies. In this paper utilizing the statistical procedures to find the attribute quality control charts for through fuzzified the real data which we got it from Baghdad Soft Drink Company in Iraq, by using triangular membership function to obtain the fuzzy numbers then employing the proposed ranking function to transform to traditional sample. Then, compare between crisp and fuzzy attribute quality control.
In this article, we aim to define a universal set consisting of the subscripts of the fuzzy differential equation (5) except the two elements and , subsets of that universal set are defined according to certain conditions. Then, we use the constructed universal set with its subsets for suggesting an analytical method which facilitates solving fuzzy initial value problems of any order by using the strongly generalized H-differentiability. Also, valid sets with graphs for solutions of fuzzy initial value problems of higher orders are found.