Zadah in [1] introduced the notion of a fuzzy subset A of a nonempty set S as a mapping from S into [0,1], Liu in [2] introduced the concept of a fuzzy ring, Martines [3] introduced the notion of a fuzzy ideal of a fuzzy ring. A non zero proper ideal I of a ring R is called an essential ideal if I  J  (0), for any non zero ideal J of R, [4]. Inaam in [5] fuzzified this concept to essential fuzzy ideal of fuzzy ring and gave its basic properties. Nada in [6] introduced and studied notion of semiessential ideal in a ring R, where a non zero ideal I of R is called semiessential if I  P  (0) for all non zero prime ideals of R, [4]. A ring R is called uniform if every ideal of R is essential. Nada in [6] introduced and studied the notion semiuniform ring where a ring R is called semiuniform ring if every ideal of R is semiessential ideal. In this paper we fuzzify the concepts semiessential ideal of a ring, uniform ring and semiuniform ring into semiessential fuzzy ideal of fuzzy ring, uniform fuzzy ring and semiuniform fuzzy ring. Where a fuzzy ideal A of a fuzzy ring X is semiessential if I  P  (0) for any prime fuzzy ideal P of X. A fuzzy ring X is called uniform (semiuniform) if every fuzzy ideal of X is essential (semiessential) respectively. In S.1, some basic definitions and results are collected. In S.2, we study semiesential fuzzy ideals of fuzzy ring, we give some basic properties about this concept. In S.3, we study the notion of uniform fuzzy rings and semiuniform fuzzy rings. Several properties about them are given. Throughout this paper, R is commutative ring with unity, and X(0) = 1, for any fuzzy ring.
In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better
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In this paper, we proved the existence and uniqueness of the solution of nonlinear Volterra fuzzy integral equations of the second kind.
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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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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To damp the low-frequency oscillations which occurred due to the disturbances in the electrical power system, the generators are equipped with Power System Stabilizer (PSS) that provide supplementary feedback stabilizing signals. The low-frequency oscillations in power system are classified as local mode oscillations, intra-area mode oscillation, and interarea mode oscillations. A suitable PSS model was selected considering the low frequencies oscillation in the inter-area mode based on conventional PSS and Fuzzy Logic Controller. Two types of (FIS) Mamdani and suggeno were considered in this paper. The software of the methods was executed using MATLAB R2015a package.
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Applications of nonlinear, time variant, and variable parameters represent a big challenge in a conventional control systems, the control strategy of the fuzzy systems may be represents a simple, a robust and an intelligent solution for such applications.
This paper presents a design of fuzzy control system that consists of three sub controllers; a fuzzy temperature controller (FC_T), a fuzzy humidity controller (FC_H) and a ventilation control system; to control the complicate environment of the greenhouse (GH) using a proposed multi-choice control system approach. However, to reduce the cost of the crop production in the GH, the first choice is using the ventilation system to control the temperature and humidit
... Show MoreIn this paper the definition of fuzzy anti-normed linear spaces and its basic properties are used to prove some properties of a finite dimensional fuzzy anti-normed linear space.
FUZZY CONTROLLERS F'OR SINGLE POINT CONTROLLER-I (SPC-l) SYSTEMS
The Assignment model is a mathematical model that aims to express a real problem facing factories and companies which is characterized by the guarantee of its activity in order to make the appropriate decision to get the best allocation of machines or jobs or workers on machines in order to increase efficiency or profits to the highest possible level or reduce costs or time To the extent possible, and in this research has been using the method of labeling to solve the problem of the fuzzy assignment of real data has been approved by the tire factory Diwaniya, where the data included two factors are the factors of efficiency and cost, and was solved manually by a number of iterations until reaching the optimization solution,
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