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Fuzzy orbit topological spaces
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Abstract<p>The concept of fuzzy orbit open sets under the mapping <italic>f</italic>:<italic>X</italic> → <italic>X</italic> in a fuzzy topological space (<italic>X</italic>,<italic>τ</italic>) was introduced by Malathi and Uma (2017). In this paper, we introduce some conditions on the mapping <italic>f</italic>, to obtain some properties of these sets. Then we employ these properties to show that the family of all fuzzy orbit open sets construct a new fuzzy topology, which we denoted by <italic>τ</italic> <sub> <italic>F0</italic> </sub> coarser than <italic>τ</italic>. As a result, a new fuzzy topological space (<italic>X</italic>, <italic>τ</italic> <sub> <italic>F0</italic> </sub>) is obtained. We refer to this topological space as a fuzzy orbit topological space. In addition, we define the notion of fuzzy orbit interior (closure) and study some of their properties. Finally, the category of fuzzy orbit topological spaces <inline-formula> <tex-math> <?CDATA ${\mathbb{F}}{\mathbb{O}}TOP$?> </tex-math> <math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mrow> <mi mathvariant="double-struck">F</mi> <mi mathvariant="double-struck">O</mi> <mi>T</mi> <mi>O</mi> <mi>P</mi> </mrow> </math> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MSE_571_1_012026_ieqn1.gif" xlink:type="simple"></inline-graphic> </inline-formula> is defined, and we prove it can be embedded in the category of fuzzy topological spaces <inline-formula> <tex-math> <?CDATA ${\mathbb{F}}TOP$?> </tex-math> <math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mrow> <mi mathvariant="double-struck">F</mi> <mi>T</mi> <mi>O</mi> <mi>P</mi> </mrow> </math> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MSE_571_1_012026_ieqn2.gif" xlink:type="simple"></inline-graphic> </inline-formula>.</p>
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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 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
Wed Jul 01 2015
Journal Name
The Sai 2015
An optimal defuzzification method for interval type-2 fuzzy logic control scheme
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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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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Solving Time-Cost Tradeoff Problem with Resource Constraint Using Fuzzy Mathematical Model
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Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the

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Crossref
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
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Solve travelling sales man problem by using fuzzy multi-objective linear programming
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   The main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits  of( FMOLP)   algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun

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Publication Date
Sat May 30 2020
Journal Name
Neuroquantology
Desertification Monitoring in the South-West of Iraqi Using Fuzzy Inference System
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In this research, the region in the south-west of Iraq is classified using a fuzzy inference system to estimate its desertification degree. Three land cover indices are used which are the Normalized Difference Vegetation Index, Normalized Multi-Band Drought Index and the top of atmosphere surface temperature to build a fuzzy decision about the desertification degree using eight decision roles. The study covers a temporal period of 38 years, where about every 10 years a sample is elected to verify the desertification status of the region, starting from 1990 to 2018. The results show that the desertification status varied every 10 years, wherein 2000 encountered the highest desertification in the south-west of Iraq.

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Publication Date
Fri Sep 29 2023
Journal Name
International Journal Of Applied Mechanics And Engineering
Fuzzy logic control of active suspension system equipped with a hydraulic actuator
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In this paper, the Active Suspension System (ASS) of road vehicles was investigated. In addition to the conventional stiffness and damper, the proposed ASS includes a fuzzy controller, a hydraulic actuator, and an LVDT position sensor. Furthermore, this paper presents a nonlinear model describing the operation of the hydraulic actuator as a part of the suspension system. Additionally, the detailed steps of the fuzzy controller design for such a system are introduced. A MATLAB/Simulink model was constructed to study the proposed ASS at different profiles of road irregularities. The results have shown that the proposed ASS has superior performance compared to the conventional Passive Suspension System (PSS), where the body displacemen

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