Search results for: Intuitionistic fuzzy group
2256 An Innovative Fuzzy Decision Making Based Genetic Algorithm
Authors: M. A. Sharbafi, M. Shakiba Herfeh, Caro Lucas, A. Mohammadi Nejad
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Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of GA to obtain fuzzy rules and application of fuzzy logic in optimization of GA). In this paper, we suggest a new method in which fuzzy decision making is used to improve the performance of genetic algorithm. In the suggested method, we determine the alleles that enhance the fitness of chromosomes and try to insert them to the next generation. In this algorithm we try to present an innovative vaccination in the process of reproduction in genetic algorithm, with considering the trade off between exploration and exploitation.Keywords: Genetic Algorithm, Fuzzy Decision Making.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15982255 Dependent Weighted Aggregation Operators of Hesitant Fuzzy Numbers
Authors: Jing Liu
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In this paper, motivated by the ideas of dependent weighted aggregation operators, we develop some new hesitant fuzzy dependent weighted aggregation operators to aggregate the input arguments taking the form of hesitant fuzzy numbers rather than exact numbers, or intervals. In fact, we propose three hesitant fuzzy dependent weighted averaging(HFDWA) operators, and three hesitant fuzzy dependent weighted geometric(HFDWG) operators based on different weight vectors, and the most prominent characteristic of these operators is that the associated weights only depend on the aggregated hesitant fuzzy numbers and can relieve the influence of unfair hesitant fuzzy numbers on the aggregated results by assigning low weights to those “false” and “biased” ones. Some examples are given to illustrated the efficiency of the proposed operators.
Keywords: Hesitant fuzzy numbers, hesitant fuzzy dependent weighted averaging(HFDWA) operators, hesitant fuzzy dependent weighted geometric(HFDWG) operators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17672254 Simplex Method for Fuzzy Variable Linear Programming Problems
Authors: S.H. Nasseri, E. Ardil
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Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.
Keywords: Fuzzy variable linear programming, fuzzy number, ranking function, simplex method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33412253 Sensitizing Rules for Fuzzy Control Charts
Authors: N. Pekin Alakoç, A. Apaydın
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Quality control charts indicate out of control conditions if any nonrandom pattern of the points is observed or any point is plotted beyond the control limits. Nonrandom patterns of Shewhart control charts are tested with sensitizing rules. When the processes are defined with fuzzy set theory, traditional sensitizing rules are insufficient for defining all out of control conditions. This is due to the fact that fuzzy numbers increase the number of out of control conditions. The purpose of the study is to develop a set of fuzzy sensitizing rules, which increase the flexibility and sensitivity of fuzzy control charts. Fuzzy sensitizing rules simplify the identification of out of control situations that results in a decrease in the calculation time and number of evaluations in fuzzy control chart approach.Keywords: Fuzzy set theory, Quality control charts, Run Rules, Unnatural patterns.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35312252 Auto Regressive Tree Modeling for Parametric Optimization in Fuzzy Logic Control System
Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao
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The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13842251 A Note on Characterization of Regular Γ-Semigroups in terms of (∈,∈ ∨q)-Fuzzy Bi-ideal
Authors: S.K.Sardar, B.Davvaz, S.Kayal, S.K.Majumdar
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The purpose of this note is to obtain some properties of (∈,∈ ∨q)- fuzzy bi-ideals in a Γ-semigroup in order to characterize regular and intra-regular Γ-semigroups.Keywords: Regular Γ-semigroup, belong to or quasi-coincident, (∈, ∈ ∨q)-fuzzy subsemigroup, (∈, ∈ ∨q)-fuzzy bi-ideals.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22152250 Some Equalities Connected with Fuzzy Soft Matrices
Authors: D. R. Jain
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The aim of this paper is to use matrix representation of Fuzzy soft sets for proving some equalities connected with Fuzzy soft sets based on set-operations.
Keywords: Equality, Fuzzy soft matrix, Fuzzy soft sets, operations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17772249 Fuzzy Shortest Paths Approximation for Solving the Fuzzy Steiner Tree Problem in Graphs
Authors: Miloš Šeda
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In this paper, we deal with the Steiner tree problem (STP) on a graph in which a fuzzy number, instead of a real number, is assigned to each edge. We propose a modification of the shortest paths approximation based on the fuzzy shortest paths (FSP) evaluations. Since a fuzzy min operation using the extension principle leads to nondominated solutions, we propose another approach to solving the FSP using Cheng's centroid point fuzzy ranking method.Keywords: Steiner tree, single shortest path problem, fuzzyranking, binary heap, priority queue.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16872248 Ranking Fuzzy Numbers Based On Epsilon-Deviation Degree
Authors: Vincent F. Yu, Ha Thi Xuan Chi
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Nejad and Mashinchi (2011) proposed a revision for ranking fuzzy numbers based on the areas of the left and the right sides of a fuzzy number. However, this method still has some shortcomings such as lack of discriminative power to rank similar fuzzy numbers and no guarantee the consistency between the ranking of fuzzy numbers and the ranking of their images. To overcome these drawbacks, we propose an epsilon-deviation degree method based on the left area and the right area of a fuzzy number, and the concept of the centroid point. The main advantage of the new approach is the development of an innovative index value which can be used to consistently evaluate and rank fuzzy numbers. Numerical examples are presented to illustrate the efficiency and superiority of the proposed method.
Keywords: Ranking fuzzy numbers, Centroid, Deviation degree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15792247 Design of Gain Scheduled Fuzzy PID Controller
Authors: Leehter Yao, Chin-Chin Lin
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An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS_FPID) controller consists of both fuzzy PI-like controller and fuzzy PD-like controller. Both of fuzzy PI-like and PD-like controllers are weighted through adaptive gain scheduling, which are also determined by fuzzy logic inference. A modified genetic algorithm called accumulated genetic algorithm is designed to learn the parameters of fuzzy inference system. In order to learn the number of fuzzy rules required for the TSK model, the fuzzy rules are learned in an accumulated way. In other words, the parameters learned in the previous rules are accumulated and updated along with the parameters in the current rule. It will be shown that the proposed GS_FPID controllers learned by the accumulated GA perform well for not only the regular linear systems but also the higher order and time-delayed systems.
Keywords: Gain scheduling, fuzzy PID controller, adaptive control, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40532246 Takagi-Sugeno Fuzzy Control of Induction Motor
Authors: Allouche Moez, Souissi Mansour, Chaabane Mohamed, Mehdi Driss
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This paper deals with the synthesis of fuzzy state feedback controller of induction motor with optimal performance. First, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy controller is designed to stabilise the induction motor and guaranteed a minimum disturbance attenuation level for the closed-loop system. The gains of fuzzy control are obtained by solving a set of Linear Matrix Inequality (LMI). Finally, simulation results are given to demonstrate the controller-s effectiveness.
Keywords: Rejection disturbance, fuzzy modelling, open-loop control, Fuzzy feedback controller, fuzzy observer, Linear Matrix Inequality (LMI)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19032245 Prime(Semiprime) Fuzzy h-ideal in Γ-hemiring
Authors: Sujit Kumar Sardar, Debabrata Mandal
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The notions of prime(semiprime) fuzzy h-ideal(h-biideal, h-quasi-ideal) in Γ-hemiring are introduced and some of their characterizations are obtained by using "belongingness(∈)" and "quasi - coincidence(q)". Cartesian product of prime(semiprime) fuzzy h-ideals of Γ-hemirings are also investigated.Keywords: Γ-hemiring, Fuzzy h-ideals, Prime fuzzy left h-ideal, Prime(semiprime) (∈, ∈ ∨q)-fuzzy left h-bi-ideal(h-ideal, h-quasiideal), Cartesian product
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27672244 On the Fuzzy Difference Equation xn+1 = A +
Authors: Qianhong Zhang, Lihui Yang, Daixi Liao,
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In this paper, we study the existence, the boundedness and the asymptotic behavior of the positive solutions of a fuzzy nonlinear difference equations xn+1 = A + k i=0 Bi xn-i , n= 0, 1, · · · . where (xn) is a sequence of positive fuzzy numbers, A,Bi and the initial values x-k, x-k+1, · · · , x0 are positive fuzzy numbers. k ∈ {0, 1, 2, · · ·}.
Keywords: Fuzzy difference equation, boundedness, persistence, equilibrium point, asymptotic behaviour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16062243 Comparative Study of Some Adaptive Fuzzy Algorithms for Manipulator Control
Authors: Sudeept Mohan, Surekha Bhanot
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The problem of manipulator control is a highly complex problem of controlling a system which is multi-input, multioutput, non-linear and time variant. In this paper some adaptive fuzzy, and a new hybrid fuzzy control algorithm have been comparatively evaluated through simulations, for manipulator control. The adaptive fuzzy controllers consist of self-organizing, self-tuning, and coarse/fine adaptive fuzzy schemes. These controllers are tested for different trajectories and for varying manipulator parameters through simulations. Various performance indices like the RMS error, steady state error and maximum error are used for comparison. It is observed that the self-organizing fuzzy controller gives the best performance. The proposed hybrid fuzzy plus integral error controller also performs remarkably well, given its simple structure.Keywords: Hybrid fuzzy, Self-organizing, Self-tuning, Trajectory tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14782242 On Weakly Prime and Weakly Quasi-Prime Fuzzy Left Ideals in Ordered Semigroups
Authors: Jian Tang
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In this paper, we first introduce the concepts of weakly prime and weakly quasi-prime fuzzy left ideals of an ordered semigroup S. Furthermore, we give some characterizations of weakly prime and weakly quasi-prime fuzzy left ideals of an ordered semigroup S by the ordered fuzzy points and fuzzy subsets of S.
Keywords: Ordered semigroup, ordered fuzzy point, weakly prime fuzzy left ideal, weakly quasi-prime fuzzy left ideal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16342241 Compromise Ratio Method for Decision Making under Fuzzy Environment using Fuzzy Distance Measure
Authors: Debashree Guha, Debjani Chakraborty
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The aim of this paper is to adopt a compromise ratio (CR) methodology for fuzzy multi-attribute single-expert decision making proble. In this paper, the rating of each alternative has been described by linguistic terms, which can be expressed as triangular fuzzy numbers. The compromise ratio method for fuzzy multi-attribute single expert decision making has been considered here by taking the ranking index based on the concept that the chosen alternative should be as close as possible to the ideal solution and as far away as possible from the negative-ideal solution simultaneously. From logical point of view, the distance between two triangular fuzzy numbers also is a fuzzy number, not a crisp value. Therefore a fuzzy distance measure, which is itself a fuzzy number, has been used here to calculate the difference between two triangular fuzzy numbers. Now in this paper, with the help of this fuzzy distance measure, it has been shown that the compromise ratio is a fuzzy number and this eases the problem of the decision maker to take the decision. The computation principle and the procedure of the compromise ratio method have been described in detail in this paper. A comparative analysis of the compromise ratio method previously proposed [1] and the newly adopted method have been illustrated with two numerical examples.
Keywords: Compromise ratio method, Fuzzy multi-attributesingle-expert decision making, Fuzzy number, Linguistic variable
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14052240 Fuzzy Scan Method to Detect Clusters
Authors: Laureano Rodríguez, Gladys Casas, Ricardo Grau, Yailen Martínez
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The classical temporal scan statistic is often used to identify disease clusters. In recent years, this method has become as a very popular technique and its field of application has been notably increased. Many bioinformatic problems have been solved with this technique. In this paper a new scan fuzzy method is proposed. The behaviors of classic and fuzzy scan techniques are studied with simulated data. ROC curves are calculated, being demonstrated the superiority of the fuzzy scan technique.Keywords: Scan statistic, fuzzy scan, simulating study
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13862239 Adaptation of Iterative Methods to Solve Fuzzy Mathematical Programming Problems
Authors: Ricardo C. Silva, Luiza A. P. Cantao, Akebo Yamakami
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Based on the fuzzy set theory this work develops two adaptations of iterative methods that solve mathematical programming problems with uncertainties in the objective function and in the set of constraints. The first one uses the approach proposed by Zimmermann to fuzzy linear programming problems as a basis and the second one obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. We outline similarities between the two iterative methods studied. Selected examples from the literature are presented to validate the efficiency of the methods addressed.Keywords: Fuzzy Theory, Nonlinear Optimization, Fuzzy Mathematics Programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16152238 Comparison Results of Two-point Fuzzy Boundary Value Problems
Authors: Hsuan-Ku Liu
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This paper investigates the solutions of two-point fuzzy boundary value problems as the form x = f(t, x(t)), x(0) = A and x(l) = B, where A and B are fuzzy numbers. There are four different solutions for the problems when the lateral type of H-derivative is employed to solve the problems. As f(t, x) is a monotone function of x, these four solutions are reduced to two different solutions. As f(t, x(t)) = λx(t) or f(t, x(t)) = -λx(t), solutions and several comparison results are presented to indicate advantages of each solution.
Keywords: Fuzzy derivative, lateral type of H-derivative, fuzzy differential equations, fuzzy boundary value problems, boundary value problems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15252237 On λ− Summable of Orlicz Space of Gai Sequences of Fuzzy Numbers
Authors: N.Subramanian, S.Krishnamoorthy, S. Balasubramanian
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In this paper the concept of strongly (λM)p - Ces'aro summability of a sequence of fuzzy numbers and strongly λM- statistically convergent sequences of fuzzy numbers is introduced.Keywords: Fuzzy numbers, statistical convergence, Orlicz space, gai sequence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19462236 Estimating Development Time of Software Projects Using a Neuro Fuzzy Approach
Authors: Venus Marza, Amin Seyyedi, Luiz Fernando Capretz
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Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of Magnitude of Relative Error) applying neuro-fuzzy was substantially lower than MMRE applying fuzzy logic and neural network.Keywords: Artificial Neural Network, Fuzzy Logic, Neuro-Fuzzy, Software Estimation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16552235 A Fuzzy MCDM Approach for Health-Care Waste Management
Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi
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The management of the health-care wastes is one of the most important problems in Istanbul, a city with more than 12 million inhabitants, as it is in most of the developing countries. Negligence in appropriate treatment and final disposal of the healthcare wastes can lead to adverse impacts to public health and to the environment. This paper employs a fuzzy multi-criteria group decision making approach, which is based on the principles of fusion of fuzzy information, 2-tuple linguistic representation model, and technique for order preference by similarity to ideal solution (TOPSIS), to evaluate health-care waste (HCW) treatment alternatives for Istanbul. The evaluation criteria are determined employing nominal group technique (NGT), which is a method of systematically developing a consensus of group opinion. The employed method is apt to manage information assessed using multigranularity linguistic information in a decision making problem with multiple information sources. The decision making framework employs ordered weighted averaging (OWA) operator that encompasses several operators as the aggregation operator since it can implement different aggregation rules by changing the order weights. The aggregation process is based on the unification of information by means of fuzzy sets on a basic linguistic term set (BLTS). Then, the unified information is transformed into linguistic 2-tuples in a way to rectify the problem of loss information of other fuzzy linguistic approaches.Keywords: Group decision making, health care waste management, multi-criteria decision making, OWA, TOPSIS, 2-tuple linguistic representation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23962234 Unmanned Combat Aircraft Selection using Fuzzy Proximity Measure Method in Multiple Criteria Group Decision Making
Authors: C. Ardil
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The decision to select an unmanned combat aircraft is complicated since several options and conflicting criteria must be considered at simultaneously. When making multiple criteria decision, it is important to consider the selected evaluation criteria, including priceability, payloadability, stealthability, speedability , and survivability. The fundamental goal of the study is to select the best unmanned combat aircraft by taking these evaluation criteria into account. The optimal aircraft was chosen using the fuzzy proximity measure method, which enables decision-makers to designate preferences as standard fuzzy set numbers during the multiple criteria decision-making process. To assess the applicability of the proposed approach, a numerical example is provided. Finally, by comparing determined unmanned combat aircraft, the proposed method produced a successful application, and the best aircraft was selected.
Keywords: standard fuzzy sets (SFS), unmanned combat aircraft selection, multiple criteria decision making (MCDM), multiple criteria group decision making (MCGDM), proximity measure method (PMM)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4132233 Identification of MIMO Systems Using Neuro-Fuzzy Models with a Shuffled Frog Leaping Algorithm
Authors: Sana Bouzaida, Anis Sakly, Faouzi M'Sahli
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In this paper, a TSK-type Neuro-fuzzy Inference System that combines the features of fuzzy sets and neural networks has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA).Keywords: Identification, Shuffled frog Leaping Algorithm (SFLA), TSK-type neuro-fuzzy model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17642232 Generalized Measures of Fuzzy Entropy and their Properties
Authors: K.C. Deshmukh, P.G. Khot, Nikhil
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In the present communication, we have proposed some new generalized measure of fuzzy entropy based upon real parameters, discussed their and desirable properties, and presented these measures graphically. An important property, that is, monotonicity of the proposed measures has also been studied.Keywords: Fuzzy numbers, Fuzzy entropy, Characteristicfunction, Crisp set, Monotonicity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14622231 Fuzzy Group Decision Making for the Assessment of Health-Care Waste Disposal Alternatives in Istanbul
Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi
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Disposal of health-care waste (HCW) is considered as an important environmental problem especially in large cities. Multiple criteria decision making (MCDM) techniques are apt to deal with quantitative and qualitative considerations of the health-care waste management (HCWM) problems. This research proposes a fuzzy multi-criteria group decision making approach with a multilevel hierarchical structure including qualitative as well as quantitative performance attributes for evaluating HCW disposal alternatives for Istanbul. Using the entropy weighting method, objective weights as well as subjective weights are taken into account to determine the importance weighting of quantitative performance attributes. The results obtained using the proposed methodology are thoroughly analyzed.Keywords: Entropy weighting method, group decision making, health-care waste management, hierarchical fuzzy multi-criteriadecision making
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16812230 Improving Digital Image Edge Detection by Fuzzy Systems
Authors: Begol, Moslem, Maghooli, Keivan
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Image Edge Detection is one of the most important parts of image processing. In this paper, by fuzzy technique, a new method is used to improve digital image edge detection. In this method, a 3x3 mask is employed to process each pixel by means of vicinity. Each pixel is considered a fuzzy input and by examining fuzzy rules in its vicinity, the edge pixel is specified and by utilizing calculation algorithms in image processing, edges are displayed more clearly. This method shows significant improvement compared to different edge detection methods (e.g. Sobel, Canny).Keywords: Fuzzy Systems, Edge Detection, Fuzzy edgedetection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20792229 Fuzzy Mathematical Morphology approach in Image Processing
Authors: Yee Yee Htun, Dr. Khaing Khaing Aye
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Morphological operators transform the original image into another image through the interaction with the other image of certain shape and size which is known as the structure element. Mathematical morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been applied widely too many applications such as edge detection, objection segmentation, noise suppression and so on. Fuzzy Mathematical Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations such as fuzzy erosion, dilation, opening and closing, a general method based upon fuzzy implication and inclusion grade operators is introduced. The fuzzy morphological operations extend the ordinary morphological operations by using fuzzy sets where for fuzzy sets, the union operation is replaced by a maximum operation, and the intersection operation is replaced by a minimum operation. In this work, it consists of two articles. In the first one, fuzzy set theory, fuzzy Mathematical morphology which is based on fuzzy logic and fuzzy set theory; fuzzy Mathematical operations and their properties will be studied in details. As a second part, the application of fuzziness in Mathematical morphology in practical work such as image processing will be discussed with the illustration problems.Keywords: Binary Morphological, Fuzzy sets, Grayscalemorphology, Image processing, Mathematical morphology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32402228 Assessment the Quality of Telecommunication Services by Fuzzy Inferences System
Authors: Oktay Nusratov, Ramin Rzaev, Aydin Goyushov
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Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IPprotocol. To implement the main features and functions of the fuzzy control system of quality telecommunication services it is used multilayer feedforward neural network.
Keywords: Quality of communication, IP-telephony, Fuzzy set, Fuzzy implication, Neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23412227 Fuzzy Hierarchical Clustering Applied for Quality Estimation in Manufacturing System
Authors: Y. Q. Lv, C.K.M. Lee
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This paper develops a quality estimation method with the application of fuzzy hierarchical clustering. Quality estimation is essential to quality control and quality improvement as a precise estimation can promote a right decision-making in order to help better quality control. Normally the quality of finished products in manufacturing system can be differentiated by quality standards. In the real life situation, the collected data may be vague which is not easy to be classified and they are usually represented in term of fuzzy number. To estimate the quality of product presented by fuzzy number is not easy. In this research, the trapezoidal fuzzy numbers are collected in manufacturing process and classify the collected data into different clusters so as to get the estimation. Since normal hierarchical clustering methods can only be applied for real numbers, fuzzy hierarchical clustering is selected to handle this problem based on quality standards.Keywords: Quality Estimation, Fuzzy Quality Mean, Fuzzy Hierarchical Clustering, Fuzzy Number, Manufacturing system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1660