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.
Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse
... Show MoreFuzzy orbit topological space is a new structure very recently given by [1]. This new space is based on the notion of open fuzzy orbit sets. The aim of this paper is to provide applications of open fuzzy orbit sets. We introduce the notions of fuzzy orbit irresolute mappings and fuzzy orbit open (resp. irresolute open) mappings and studied some of their properties. .
Let R be a Г-ring, and σ, τ be two automorphisms of R. An additive mapping d from a Γ-ring R into itself is called a (σ,τ)-derivation on R if d(aαb) = d(a)α σ(b) + τ(a)αd(b), holds for all a,b ∈R and α∈Γ. d is called strong commutativity preserving (SCP) on R if [d(a), d(b)]α = [a,b]α(σ,τ) holds for all a,b∈R and α∈Γ. In this paper, we investigate the commutativity of R by the strong commutativity preserving (σ,τ)-derivation d satisfied some properties, when R is prime and semi prime Г-ring.
Background: This in vitro study measure and compare the effect of light curing tip distance on the depth of cure by measuring vickers microhardness value on two recently launched bulk fill resin based composites Tetric EvoCeram Bulk Fill and Surefil SDR Flow with 4 mm thickness in comparison to Filtek Z250 Universal Restorative with 2 mm thickness. In addition, measure and compare the bottom to top microhardness ratio with different light curing tip distances. Materials and Method: One hundred fifty composite specimens were obtained from two cylindrical plastic molds the first one for bulk fill composites (Tetric EvoCeram Bulk Fill and Surefil SDR Flow) with 4 mm diameter and 4 mm depth, the second one for Filtek Z250 Universal Restorative
... Show MoreMultivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data. This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −
In the spreading of the Internet, mobile smart devices, and interactive websites such as YouTube, the educational video becomes more widespread and deliberative among users. The reasons for its spread are the prevalence of technologies, cheap cost, and easy to use. However, these products often lack to the distinction in video production. By following videos of an educational channel on YouTube, some comments found to discuss the lack of the content presented to motivate the learners, which lead to reduce the viewers of the videos. Therefore, there is an important decision to find general standards for the design and production of educational videos. A list of standards has been drawn up to help those interested in producing educational
... Show MoreIn the spreading of the Internet, mobile smart devices, and interactive websites such as YouTube, the educational video becomes more widespread and deliberative among users. The reasons for its spread are the prevalence of technologies, cheap cost, and easy to use. However, these products often lack to the distinction in video production. By following videos of an educational channel on YouTube, some comments found to discuss the lack of the content presented to motivate the learners, which lead to reduce the viewers of the videos. Therefore, there is an important decision to find general standards for the design and production of educational videos. A list of standards has been drawn up to help those interested in producing educational
... Show MoreIn this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients
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Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s
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