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Fuzzy Orbit Irresolute Mappings
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Fuzzy 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. .

Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion
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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Mathematics In Operational Research
A single server fuzzy queues with priority and unequal service rates
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Publication Date
Mon May 16 2016
Journal Name
Far East Journal Of Mathematical Sciences (fjms)
MINIMIZING WAITING TIMES USING MULTIPLE FUZZY QUEUEING MODEL WITH SUPPLY PRIORITIES
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Generalizations of Fuzzy k-ideals in a KU-algebra with Semigroup
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Abstract<p>We present the notion of bipolar fuzzy k-ideals with thresholds (<italic>θ, λ</italic>) of a KU-algebra with semigroup and give some basic properties of this ideal. Also, we study some relations about a bipolar fuzzy k-ideal with thresholds (<italic>θ, λ</italic>) and a k-ideal of a KU-semigroup.</p>
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Publication Date
Mon Aug 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
comparing three estimators of fuzzy reliability for one scale parameter rayleigh distribution
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Statistical methods and statistical decisions making were used to arrange and analyze the primary data to get norms which are used with Geographic Information Systems (GIS) and spatial analysis programs to identify the animals production and poultry units in strategic nutrition channels, also the priorities of food insecurity through the local production and import when there is no capacity for production. The poultry production is one of the most important commodities that satisfy human body protein requirements, also the most important criteria to measure the development and prosperity of nations. The poultry fields of Babylon Governorate are located in Abi Ghareg and Al_Kifil centers according to many criteria or factors such as the popu

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Publication Date
Sat Jun 01 2013
Journal Name
Nahrain University, College Of Engineering Journal
Planned Reliability Improvement Calculation of Iraqi Super Grid Applying Fuzzy Logic Method
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Reliability is an essential measure and important component of all power system planning and operation procedures. It is one of the key design factors when designing complex, critical and expensive systems. This paper presents a fuzzy logic approach for reliability improvement planning purposes. Evaluating the reliability of the complex and large planned Iraqi super grid ;as Al- Khairat generating station with its tie set is intended to be compact to that grid; and determination of the given reliability improvement project are the major goals of the paper. Results show that the Iraqi super grid reliability is improved by 9.64%. In the proposed technique, fuzzy set theory is used to include imprecise indices of different components in normal

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Discussing Fuzzy Reliability Estimators of Function of Mixed Probability Distribution By Simulation
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This paper deals  with constructing mixed probability distribution  from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are (  .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β)  are estimated by three different methods, which are  maximum likelihood, and  Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Pairwise connectedness in $ check ${$text ${$C$}$$}$ $ ech fuzzy soft bi-closure spaces
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The concept of Cech fuzzy soft bi-closure space ( ˇ Cfs bi-csp) ( ˇ U, L1, L2, S) is initiated and studied by the authors in [6]. The notion of pairwise fuzzy soft separated sets in Cfs bi-csp is defined in this study, and various features of ˇ this notion are proved. Then, we introduce and investigate the concept of connectedness in both Cfs bi-csps and its ˇ associated fuzzy soft bitopological spaces utilizing the concept of pairwise fuzzy soft separated sets. Furthermore, the concept of pairwise feebly connected is introduced, and the relationship between pairwise connected and pairwise feebly connected is discussed. Finally, we provide various instances to further explain our findings.

Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Turbid of Water By Using Fuzzy C- Means and Hard K- Means
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In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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