The aim of this paper is to introduce the notion of hyper fuzzy AT-ideals on hyper AT-algebra. Also, hyper fuzzy AT-subalgebras and fuzzy hyper AT-ideal of hyper AT-algebras are studied. We study on the fuzzy theory of hyper AT-subalgebras and hyper AT-ideal of hyper AT-algebras. Furthermore, the fuzzy set theory of the (weak, strong, s-weak) hyper fuzzy ATideals in hyper AT-algebras are applied and the relations among them are obtained.
This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.
The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin
... Show MoreIn this research for each positive integer integer and is accompanied by connecting that number with the number of Bashz Attabq result any two functions midwives to derive a positive integer so that there is a point
The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
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... Show MoreThe research deals with one of the urban problems facing cities, namely the existence of neglected urban spaces that need to be activated , These spaces give a negative image of the city, is not conducive to life and social interactions or the city has a one distinctive urban experience, leading to a reduction peoples' confidence in revisiting of those areas, hinder the rest of the activities in that region . Because these spaces are of the basic components of the city and give it its identity through the elements and entities that constitute it , The idea of research emerged in the reclaiming of these spaces within contemporary urban trends and the activation of flexible , short-term and inovation for that purpose with
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One of the important things provided by fuzzy model is to identify the membership functions. In the fuzzy reliability applications with failure functions of the kind who cares that deals with positive variables .There are many types of membership functions studied by many researchers, including triangular membership function, trapezoidal membership function and bell-shaped membership function. In I research we used beta function. Based on this paper study classical method to obtain estimation fuzzy reliability function for both series and parallel systems.