In this paper, we define the concept of soft -connected sets and soft -connected spaces by using the notion of soft -open sets in soft topological spaces. Several properties of these concepts are investigated.
This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others
In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
... Show MoreIn this paper we recall the definition of fuzzy length space on a fuzzy set after that we recall basic definitions and properties of fuzzy length. We define fuzzy bounded operator as an introduction to defined fuzzy length of an operator then we proved that the fuzzy length space FB ̃ ̃ consisting of all fuzzy bounded linear operators from a fuzzy length space ̃ into a fuzzy length space ̃ is fuzzy complete if ̃ is fuzzy complete. Also we proved that every finite dimensional fuzzy length space is fuzzy complete.
This research aims to estimate stock returns, according to the Rough Set Theory approach, test its effectiveness and accuracy in predicting stock returns and their potential in the field of financial markets, and rationalize investor decisions. The research sample is totaling (10) companies traded at Iraq Stock Exchange. The results showed a remarkable Rough Set Theory application in data reduction, contributing to the rationalization of investment decisions. The most prominent conclusions are the capability of rough set theory in dealing with financial data and applying it for forecasting stock returns.The research provides those interested in investing stocks in financial
... Show MoreThe concepts of nonlinear mixed summable families and maps for the spaces that only non-void sets are developed. Several characterizations of the corresponding concepts are achieved and the proof for a general Pietsch Domination-type theorem is established. Furthermore, this work has presented plenty of composition and inclusion results between different classes of mappings in the abstract settings. Finally, a generalized notation of mixing maps and their characteristics are extended to a more general setting.
In this paper, the linear system of Fredholm integral equations is solving using Open Newton-Cotes formula, which we use five different types of Open Newton-Cotes formula to solve this system. Compare the results of suggested method with the results of another method (closed Newton-Cotes formula) Finally, at the end of each method, algorithms and programs developed and written in MATLAB (version 7.0) and we give some numerical examples, illustrate suggested method
This paper is concerned with introducing and studying the new approximation operators based on a finite family of d. g. 'swhich are the core concept in this paper. In addition, we study generalization of some Pawlak's concepts and we offer generalize the definition of accuracy measure of approximations by using a finite family of d. g. 's.
Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we
... Show MoreThis paper deals with the blow-up properties of positive solutions to a parabolic system of two heat equations, defined on a ball in associated with coupled Neumann boundary conditions of exponential type. The upper bounds of blow-up rate estimates are derived. Moreover, it is proved that the blow-up in this problem can only occur on the boundary.
In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an
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