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Robust Control of Dc Motor Using Fuzzy Sliding Mode Control with Fractional Pid Compensator
Robust Control of Dc Motor Using Fuzzy Sliding Mode Control with Fractional Pid Compensator
en
en
This paper presents a robust fuzzy sliding mode control scheme and the additional compensator. The additional compensator relaying on the sliding-mode theory is used to improve the dynamical characteristics of the drive system. Sliding mode control method is studied for controlling DC motor because of its robustness against model uncertainties and external disturbances. In this method, using high control gain to overcome uncertainties lead to occur chattering phenomena in control law which can excite unmodeled dynamics and maybe harm the plant. In order to enhancement the sliding mode controller performance, we have used fuzzy logic. For this purpose, we have used a Fractional PID outer loop in the control law then the gains of the sliding term and Fractional PID term are tuned on-line by a fuzzy system, so the chattering is avoided and response of the system is improved against external load torque here. Presented implementation results on a DC motor confirm the above claims and demonstrate the performance improvement in this case.
238
246
Yaghoub
Heidari
Abolfazl
Ranjbar Noee
Heydar Ali
Shayanfar
Soheil
Salehi
Fuzzy logic
Fractional PID
sliding mode
DC motor.
Article.1.pdf
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Y. J. Huang, T. C. Kuo, Robust position control of DC servomechanism with output measurement noise, Electrical Engineering, 88 (2006), 223-238
##[9]
P. Guan, X. J. Liu, J. Z. Liu, Adaptive fuzzy sliding mode control for flexible satellite, Eng. Appl. Artif. Intell., 18 (2005), 451-459
##[10]
H. S. Choi, Y. H. Park, Y. S. Cho, M. Lee, Global sliding-mode control. Improved design for a brushless DC motor, IEEE Control Systems Magazine, 21 (2001), 27-35
##[11]
A. J. Koshkouei, A. S. I. Zinober, Sliding mode controller-observer design for SISO linear systems, Int. J. Syst. Sci., 29 (1998), 1363-1373
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S. V. Drakunov, V. I. Utkin, Sliding mode control in dynamic systems, Internat. J. Control, 55 (1992), 1029-1037
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M. G. Sarwer, M. A. Rafiq, B. C. Ghosh, Sliding Mode Speed Controller of a D.C Motor Drive, J. Elec. Engg., 31 (2004), 45-49
##[15]
A. J. Koshkouei, K. J. Burnham, Control of DC motors using proportional integral sliding mode, Control Theory and Applications Centre (Coventry University), Coventry (2006)
##[16]
B. Mrozek, Z. Mrozek, Modelling and Fuzzy Control of DC Drive, Proceedings of 14th European Simulation Multi conference, 2000 (2000), 186-190
##[17]
K. Nouri, R. Dhaouadi, N. B. Braiek, Adaptive control of a nonlinear dc motor drive using recurrent neural networks, Appl. Soft Comput., 8 (2008), 371-382
]
Automatic Train Control Based on the Multi-agent Control of Cooperative Systems
Automatic Train Control Based on the Multi-agent Control of Cooperative Systems
en
en
The growing traffic intensity and complexity of the railway systems as well as the demand for higher speed need to new Automatic Train Control (ATC) methods. The conventional ATC system has some problems and in recent years new ATC methods like the Decentralized ATC (D-ATC) and autonomous decentralized ATC are developed which have some advantages. In this paper, an Intelligent Decentralized ATC (ID-ATC) approach based on the Multi-Agent systems theory is developed which can provide high transportation capacity, high-safety and high-reliability. In this method we combine the Voronoi concept of cooperative systems theory with Multi-Agent control theory by using of fuzzy control logic. The control algorithms are presented and by using of simulation results the effectiveness of the method is demonstrated.
247
257
Ali
Siahvashi
Bijan
Moaveni
Automatic Train Control
Multi-Agent Control Systems
Cooperative systems
Fuzzy control
Voronoi Algorithm.
Article.2.pdf
[
[1]
H. Dong, B. Ning, B. Cai, Z. Hou, Automatic Train Control System Development and Simulation for High-Speed Railways, IEEE Circuits Syst. Mag., 10 (2010), 6-18
##[2]
M. Matsumoto, The revolution of train control System in Japan, Proceeding of IEEE International Conference Autonomous Decentralized Systems (ISADS), 2005 (2005), 599-606
##[3]
M. Matsumoto, M. Sato, S. Kitamura, T. Shigeta, N. Amiya, Development of autonomous decentralized ATC system, Proceeding of the 2nd International Workshop on Autonomous Decentralized System, 2002 (2002), 310-315
##[4]
D. A. El-Kebbe, M. Gotz, Distributed Real-Time Control of Railway Crossings Using Multi-Agent Technology, Proceeding of the International Conference on Computational Intelligence for Modeling, Control and Automation, 2005 (2005), 768-772
]
Comparing Fuzzy Charts with Probability Charts and Using Them in a Textile Company
Comparing Fuzzy Charts with Probability Charts and Using Them in a Textile Company
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en
In this article it has been tried to show that fuzzy theory performs better than probability theory in monitoring the product quality. A method that uses statistical techniques to monitor and control product quality is called statistical process control (SPC), where control charts are test tools frequently used for monitoring the manufacturing process. In this study, statistical quality control and the fuzzy set theory are aimed to combine. As known, fuzzy sets and fuzzy logic are powerful mathematical tools for modeling uncertain systems in industry, nature and humanity; and facilitators for common-sense reasoning in decision making in the absence of complete and precise information. In this basis for a textile firm for monitoring the yarn quality, control charts according to fuzzy theory by considering the quality in terms of grades of conformance as opposed to absolute conformance and nonconformance. And then with the same data for a textile factory, the control chart based on probability theory is constructed. The results of control charts based on two different approaches are compared. It’s seen that fuzzy theory performs better than probability theory in monitoring the product quality.
258
272
Hamid Reza
Feili
Pooyan
Fekraty
Quality Control Charts
Fuzzy Set Theory
Fuzzy Control Charts
Statistical Process Control
Textile
Article.3.pdf
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]
Chaos Synchronization of Two Uncertain Chaotic System Using Genetic Based Fuzzy Adaptive Pid Controller
Chaos Synchronization of Two Uncertain Chaotic System Using Genetic Based Fuzzy Adaptive Pid Controller
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en
A Genetic based Fuzzy PID controller has been proposed to synchronization task of
chaotic systems in which one system has been considered as "master" whilst the other
system has been treated as "slave" (a perturbed system with uncertainty and
disturbance). Three PID control gains \(k_p , k_i\) , and \(k_d\) , will be updated online. An
adequate adaptation mechanism is used to minimize the sliding surface error with
appropriate adaptive law. Using the gradient method, coefficients of the PID controller
are updated. A supervisory controller has also been used to provide the stability. The
proposed method has been found with a significant performance when it was
implemented on the Van Der Pol oscillator chaotic equations.
273
286
Yaghoub
Heidari
Soheil
Salehi Alashti
Rouhollah
Maghsoudi
Fuzzy
Chaos synchronization
supervisory controller
Van der Pol
Adaptive Control.
Article.4.pdf
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]
Investigate of Fuzzy Semi-simple Lie Algebra
Investigate of Fuzzy Semi-simple Lie Algebra
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en
In this paper we have tried apply the concepts of fuzzy set to lie algebras and fuzzy ideals of lie algebras in order to provide suitable conditions to introduce the solvable fuzzy ideals, we use zadeh’s extension principle the aim of this paper is to introduce and study new definition for fuzzy lie algebras and fuzzy semi-simple of lie algebras.
287
292
A.
Taleshian
F.
Khaniani
A. A.
Hosseinzadeh
Fuzzy algebra
Lie algebra
Fuzzy ideal
solvable Fuzzy ideal
Fuzzy semi-simple.
Article.5.pdf
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]
Simulating a State of the Art Agent Based System with Fuzzy Reasoning for Supply Chain Coordination
Simulating a State of the Art Agent Based System with Fuzzy Reasoning for Supply Chain Coordination
en
en
With the emergence of high speed wireless networks and parallel advancements in Internet based technologies such as the Semantic Web, Web Services, Multi Agent Systems, and Context Awareness, the realization of the vision of the intelligent wireless web (IWW) has become a possibility. On the other side, recent developments in the field of multi criteria decision making, have led us to more accurate and applicable algorithms. In this paper, we are going to summarize the details and results of a multidisciplinary agent based software, namely SWESS that enables real-time supply chain coordination through taking advantage of different methods of different scientific areas such as computer science, supply chain management and multi criteria decision making.
293
304
A.
Shemshadi
H.
Shirazi
M. J.
Tarokh
Supply chain coordination
supply chain management
multi-criteria decision making
multi agent systems
artificial intelligence
Article.6.pdf
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M. J. Tarokh, J. Soroor, Supply Chain Management Information Systems Critical Failure Factors, European Management & Technology Conference of Technology Research Institute of Florida, 2005 (2005), 425-431
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X. H. Li, Q. Wang, Coordination mechanisms of supply chain systems, Eur. J. Oper. Res., 179 (2006), 1-16
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##[8]
J. Soroor, M. J. Tarokh, A. Shemshadi, Initiating a state of the art system for real-time supply chain coordination, Eur. J. Oper. Res., 196 (2009), 635-650
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]
Gravitational Attraction Search with Virtual Mass Gasvm to Solve Static Grid Job Scheduling Problem
Gravitational Attraction Search with Virtual Mass Gasvm to Solve Static Grid Job Scheduling Problem
en
en
Achieving the most grid computing efficiency requires optimized job scheduling, that is a problem with vast search space and Attaining optimal solutions using deterministic algorithm is extremely difficult or impossible. Besides, Falling in the trap of local minima is considered to be one of the problems existing in gravitational attraction search. GASVM proposed two modifications. First, defining virtual mass (VM) for K best solutions. For each solution, VM is defined depends on mass and ranking in the sorted list of solutions. VMs will increase gravitational mass of proper solutions and attract others to them.
Second, we calculate gravitational force of just K proper solutions on the others to prevent current good solutions, more searching about, and attracting other solutions in the direction of them. In each modification, we obtain K by using roulette wheel algorithm. Analyzing the results of GASVM executions shows that the proposed algorithm is able to achieve its intended aims to modify gravitational attraction search algorithm.
305
312
Amin
Jula
Narjes Khatoon
Naseri
Amir Masood
Rahmani
gravitational attraction search algorithm
static job scheduling in grid
Newton's gravitational law.
Article.7.pdf
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]
A New Approach to Solve Multi-objective Linear Bilevel Programming Problems
A New Approach to Solve Multi-objective Linear Bilevel Programming Problems
en
en
Many problems in sciences and industry such as signal optimization, traffic assignment, economic market,… have been modeled, or their mathematical models can be approximated, by linear bilevel programming (LBLP) problems, where in each level one must optimize some objective functions. In this paper, we use fuzzy set theory and fuzzy programming to convert the multi-objective linear bilevel programming (MOLBLP) problem to a linear bilevel programming problem, then we extend the Kth-best method to solve the final LBLP problem. The existence of optimal solution, and the convergence of this approach, are important issues that are considered in this article. A numerical example is illustrated to show the efficiency of the new approach.
313
320
M. H.
Farahi
E.
Ansari
Linear bilevel programming
Multi-objective linear bilevel programming
Fuzzy set theory
Fuzzy programming
Kth-best algorithm.
Article.8.pdf
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]
Fuzzy Demand Consideration in a Multi-objective Dynamic Cell Formation Problem Using a Robust Scatter Search
Fuzzy Demand Consideration in a Multi-objective Dynamic Cell Formation Problem Using a Robust Scatter Search
en
en
This paper presents a multi-objective cell formation problem considering alternative process routes and machine utilization with fuzzy demand. Two conflicting objectives include the total cell load variation and sum of the other costs consisting machine cost, inter-cell material handling cost, parts purchasing, operation, maintenance, and reconfiguration of machines cost are to be minimized simultaneously. Moreover, we consider demand in fuzzy condition, because it is more realistic to take into account the inexact and uncertain nature of demand. Due to the complexity of this problem, we develop a scatter search algorithm. Also by using the Taguchi as a robust parameter design method, we tune the effective factors of the developed algorithm on two sizes of benchmark problems that are generated randomly. NSGAII and Scatter Search evaluated and the related results confirm the efficiency and the effectiveness of our proposed Scatter Search provides good output according to some quality measures, especially for large-sized problems.
321
332
Hossein
Amoozad-Khalili
Mehdi
Ranjbar-Bourani
S. M. Javad Mirzapour
Ale-Hashem
Cell formation problem
fuzzy demand
scatter search
Taguchi design
Article.9.pdf
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A. J. Vakharia, B. K. Kaku, Redesigning a cellular manufacturing system to handle long-term demand changes: A methodology and investigation, Decision Sciences, 24 (1993), 909-930
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G. Harhalaks, R. Nagi, J. Proth, An efficient heuristic in manufacturing cell formation to group technology applications, Int. J. Prod. Res.., 1990 (28), 185-198
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M. Chen, A mathematical programming model for systems reconfiguration in a dynamic cell formation condition, Ann. Oper. Res., 77 (1998), 109-128
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J. Balakrishnan, C. H. Cheng, , Dynamic cellular manufacturing under multi-period planning horizons, Journal of Manufacturing Technology Management, 16 (2005), 516-530
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R. Tavakkoli-Moghaddam, N. Safaei , A generalized dynamic cell formation problem with fuzzy demand and unreliable facilities, Proceeding of the 3rd International Conference on Group Technology/Cellular Manufacturing (Groningen), 2006 (2006), 349-356
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F. M. Defersha, M. Chen , A comprehensive mathematical model for the design of cellular manufacturing system, Int. J. Prod. Econ., 103 (2006), 767-783
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N. Safaei, M. Saidi-Mehrabad, R. Tavakkoli-Moghaddam, F. Sassani, A fuzzy programming approach to a cell formation problem with dynamic and uncertain conditions, Fuzzy Sets and Systems, 159 (2008), 215-236
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S. A. Torabi, E. Hassini,, An interactive possibilistic programming approach for multiple objective supply chain master planning, Fuzzy Sets and Systems, 159 (2008), 193-214
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H. Seifoddini, A probabilistic model for machine cell formation, J. Manuf. Syst., 9 (1990), 69-75
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R. Tavakkoli-Moghaddam, N. Safaei, M. Babakhani, Solving a dynamic cell formation problem with machine cost and alternative process plan by memetic algorithms, Lect. Notes Comput. Sci., 3777 (2005), 213-227
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R. Tavakkoli-Moghaddam, M. B. Aryanezhad, N. Safaei, M. Vasei, A. Azaron, A new approach for the cellular manufacturing problem in fuzzy dynamic conditions by a genetic algorithm, J. Intell. Fuzzy. Syst., 18 (2007), 363-376
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R. Tavakkoli-Moghaddam, N. Safaei, , A generalized dynamic cell formation problem with fuzzy demand and unreliable facilities, Proceeding of the 3rd International Conference on Group Technology/Cellular Manufacturing (Groningen), 2006 (2006), 349-356
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]
Fuzzy Material Requirements Planning
Fuzzy Material Requirements Planning
en
en
Various modeling techniques based on possibility distribution function has been applied successfully in a wide range of issues related to production planning. However, the possibility distribution function derived from the records recorded in the organization are not always available or changes in production environment may cause a variety of changes and volatilities in model and make it unreliable; changes such as: market demand, changes in types of production costs, capacity, resources, and administrative constraints. In this study fuzzy sets theory has been combined with material requirements planning (MRP). It is noteworthy that material requirements planning (MRP) is one of the most commonly used subdivision of production planning that combining it with fuzzy theory can be applied to develop decision making systems and make them more efficient. In addition, the uncertainties of industrial environments can be exerted properly into the production decision-making.
333
338
Hamid Reza
Feili
Mahzad
Shakeri Moghaddam
Rezvan
Zahmatkesh
Production Planning
Material Requirements Planning
Uncertainty
Fuzzy
Article.10.pdf
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]
Fuzzy Logic Applications in Chemical Processes
Fuzzy Logic Applications in Chemical Processes
en
en
Fuzzy logic a new approach was intended to emulate human reasoning using calculations and operations with fuzzy groups and linguistic variables. Fuzzy variables describe qualitative expressions such as very slow, slow, fast, very fast, and so on. The application of fuzzy logic techniques has been increasing rapidly in the last few years. Fuzzy logic is used in target tracking, pattern recognition, robotics, power systems, controller design, chemical engineering, biomedical engineering, vehicular technology, economy management and decision making, aerospace applications, communications and networking, electronic engineering, and civil engineering. In many chemical engineering systems, the classification of product quality characteristics is performed by human experts, due to the absence of measuring devices. The development of mathematical models for such systems is a rather difficult task, since no equations based on first principles can be written. Chemical engineering has employed fuzzy logic in the detection of chemical agents as well as gas recognition. It has also been applied to processes control, batch distillation column, separation process, and kinetics. In this research, we investigate these applications in more detail.
339
348
M. R. Sarmasti
Emami
Chemical
Process
Fuzzy Logic
System
Article.11.pdf
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P. B. Osofisan, O. J. Obafaiye, Fuzzy Logic Modeling of the Fluidized Catalytic Cracking Unit of a Petrochemical Refinery, Pac. j. sci. technol., 8 (2007), 59-67
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H. Taskin, K. Cemalettin, O. Uygun, S. Arslankaya , Fuzzy logic control of a fluid catalytic cracking unit (FCCU) to improve dynamic performance, Comput. Chem. Eng., 30 (2006), 850-863
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A. Ghadimi, M. Sadrzadeh, T. Mohammadi, Prediction of ternary gas permeation through synthesized PDMS membranes by using Principal Component Analysis (PCA) and fuzzy logic (FL), J. Memb. Sci., 360 (2010), 509-521
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R. F. Liao, C. W. Chan, J. Hromek, G. H. Huang, L. He , Fuzzy logic control for a petroleum separation process, Eng. Appl. Artif. Intell., 21 (2008), 835-845
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]
A Fuzzy Heuristic Algorithm for the Flow Shop Scheduling Problem
A Fuzzy Heuristic Algorithm for the Flow Shop Scheduling Problem
en
en
The two-machine flow shop problem with the objective of minimizing makespan that is known as Johnson problem is now standard fundamental in the theory of scheduling. We generalize Johnson’s results for more than two machine problems, using a fuzzy heuristic algorithm. Performance of the new algorithm is analyzed with some numerical examples. To evaluate the performance of the proposed heuristic, we have used it on some small size problems and the results are compared with optimum scheduling. Notice that scheduling the problems with large sizes, is NP hard.
349
354
Mehdi
Heydari
Emran
Mohammadi
Scheduling
Fuzzy heuristic algorithm
Membership function
Flow shop
Article.12.pdf
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[1]
S. M. Johnson, Optimal two‐ and three‐stage production schedules with setup times included, Naval Research Logistics, 1 (1954), 69-81
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]
A Hybrid Fuzzy MCDM Approach to Thesis Subject Selection
A Hybrid Fuzzy MCDM Approach to Thesis Subject Selection
en
en
One of the most significant decisions that a doctoral student may make in the beginning of his/her research career is the selection of a thesis subject. There are also a number of conflicting criteria, including supervisor reputation, convergence of interest, student’s interest and motivation, etc, which should be considered as a part of the appropriate thesis subject selection process. For this purpose, multiple criteria decision making (MCDM) methods have been found to be useful approaches to solve this kind of problem. This paper devises a fuzzy hybrid analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach to the problem of thesis subject selection. Fuzzy AHP is used to calculate the weight of each criterion, and fuzzy TOPSIS is proposed to prioritize thesis subjects from the best to the worst ones. The application of fuzzy set theory allows incorporating the vague and imprecise linguistic terms into the decision process.
355
365
Mohammad Hasan
Aghdaie
Majid
Behzadian
Thesis subject
Fuzzy TOPSIS
Fuzzy AHP
Article.13.pdf
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F. T. Bozbura, A. Beskese, C. Kahraman, Prioritization of human capital measurement indicators using fuzzy AHP, Expert Syst Appl., 32 (2007), 1100-1112
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S. Önüt, S. S. Kara, T. Efendigil, A hybrid fuzzy MCDM approach to machine tool selection, J. Intell. Manuf., 19 (2008), 443-453
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E. M. Phillips, D. S. Pugh , How to get a PhD: A handbook for students and their supervisors (4th ed.), Open University Press, Berkshire (2005)
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F. T. Bozbura, A. Beskese, C. Kahraman, Prioritization of human capital measurement indicators using fuzzy AHP, Expert Syst. Appl., 32 (2007), 1100-1112
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S. Ray, Selecting a Doctoral Dissertation Supervisor:Analytical Hierarchy Approach to the Multiple Criteria Problem, International Journal of Doctoral Studies, 2 (2007), 23-32
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]
Fuzzy FMEA Analysis for Identification and Control of Failure Preferences in ERP Implementation
Fuzzy FMEA Analysis for Identification and Control of Failure Preferences in ERP Implementation
en
en
ERP began in the 1960s as material requirements planning, an outgrowth of early efforts in bill of material processing. However ERP Implementing as a new set of decision-making processes is a major undertaking involving member throughout the company, there are many barriers to implement ERP successfully. Organizations can reduce the effect of failure through identifying their strengths and weaknesses. One of the most significant methods for defect prevention is FMEA. Fuzzy logic as complementation of FMEA measures the degree of membership in a class instead of arguing over inclusion or exclusion. Fuzzy-FMEA is used as a preventive technique to decrease the failure rate in ERP implementation. The proposed Fuzzy-FMEA also identifies the major failure causes and effect of potential defects in ERP implementation by using fuzzy number. Then failure preferences can be characterized by the severity, occurrence and detection fuzzy values and overall fuzzy risk priority number.
366
376
Hadi
Shirouyehzad
Mostafa
Badakhshian
Reza
Dabestani
Hamidreza
Panjehfouladgaran
Failure Mode and Effect Analysis
Fuzzy Logic
Enterprise Resource Planning
Critical Failure Factors.
Article.14.pdf
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[1]
A. Teltumbde, A framework for evaluating ERP projects, Int. J. Prod. Res., 38 (2000), 4507-4520
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E. W. T. Ngai, C. C. H. Law, F. K. T. Wat, Examining the critical success factors in the adoption of enterprise resource planning, Computers in Industry, 59 (2008), 548-564
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L. M. Hitt, D. J. Wu, X. Zhou, Investment in Enterprise Resource Planning: business impact and productivity measures, J. Manage. Inform. Syst., 2002 (19), 71-98
##[4]
E. L. Wagner, S. Newell , Repairing ERP: producing social order to create a working information system, J. Appl. Behav. Sci., 42 (2006), 40-57
##[5]
M. Pozzebon, Combining a structuration approach with a behavioral-based model to investigate ERP usage, AMCIS 2000 Proceedings, 2000 (2000), 1015-1021
##[6]
L. Wah, Give ERP a chance, Management Review, 89 (2000), 20-24
##[7]
R. R. Nelson, P. H. Cheney, Training end users: an exploratory study, MIS Quarterly, 11 (1987), 547-559
##[8]
J. R. Muscatello, D. H. Parente , Enterprise Resource Planning (ERP): A post implementation cross-case analysis, Information Resource Management, 19 (2006), 61-80
##[9]
R. R. Nelson, IT project management: infamous failures, classic mistakes, and best practices, MIS Quart Executive, 6 (2007), 67-78
##[10]
T. H. Davenport, Putting the enterprise into the enterprise system, Harvard Business Review, 76 (1998), 121-131
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J. Luftman, R. Kempaiah, E. Nash , Key issues for IT executives, MIS Quart Executive, 5 (2005), 81-99
##[12]
J. Bradley, Management based critical success factors in the implementation of Enterprise Resource Planning systems, Int. J. Accounting Inform. Syst., 9 (2008), 175-200
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Y. Kim, Z. Lee, S. Gosain , Impediments to successful ERP implementation process, Business Process Management Journal, 11 (2005), 158-170
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F. F. H. Nah, K. M. Zuckweiler, J. L. S. Lau, ERP Implementation: Chief Information Officers’ Perceptions of Critical Success Factors, Int. J. Hum. Comput. Interact., 16 (2003), 5-22
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D. Aloini, R. Dulmin, V. Mininno , Risk management in ERP project introduction: Review of the literature, Information and Management, 44 (2007), 547-567
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S. M. Huang, I. C. Chang, S. H. Li, M. T. Lin , Assessing risk in ERP projects: identify and prioritize the factors, Ind. Manage. Data Syst., 104 (2004), 681-688
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A. Segismundo, P. A. C. Miguel , Failure mode and effects analysis (FMEA) in the context of risk management in new product development, Int. J. Qual. Reliab. Manag., 25 (2008), 899-912
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E. P. Zafiropoulos, E. N. Dialynas , Reliability prediction and failure mode effects and criticality analysis of electronic devices using fuzzy logic, Int. J. Qual. Reliab. Manag., 22 (2005), 183-200
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A.V. Ahsen, Cost-oriented failure mode and effects analysis, Int. J. Qual. Reliab. Manag., 25 (2008), 466-476
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, MatLab 6 Users Guide of the Fuzzy Logic Toolbox, , U.S.A. (2000)
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H. Shirouyehzad, M. Badakhshian, R. Dabestani , The Identification and Control of Failure Preferences in ERP Implementation Using FMEA, Proceeding of 13th WMCSCI, 2009 (2009), 232-237
]
Application of Homotopy Perturbation Method for Fuzzy Integral Equations
Application of Homotopy Perturbation Method for Fuzzy Integral Equations
en
en
In this paper, an application of homotopy perturbation method (HPM) is applied to solve linear fuzzy Fredholm integral equation. Comparison are made between the exact solution and solution of homotopy perturbation method. The results reveal that the homotopy analysis method is very effective and simple.
377
385
Mashallah
Matinfar
Mohammad
Saeidy
Fuzzy number
Fredholm integral equation
Homotopy perturbation method.
Article.15.pdf
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E. Babolian, H. Sadeghi Goghary, S. Abbasbandy, Numerical solution of linear Fredholm fuzzy integral equations of the second kind by Adomian method, Appl. Math. Comput., 161 (2005), 733-744
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]
PID Control of DC Motor Using Particle Swarm Optimization (PSO) Algorithm
PID Control of DC Motor Using Particle Swarm Optimization (PSO) Algorithm
en
en
Wide amplitude, DC motor's speed and their facile control cause its great application in industries. Generally the DC motors gain speed by armature voltage control or field control. The suggestion method in this paper is using PSO Algorithm for regulation parameter PID control of DC motors. The Algorithm PSO using by defining the fitness functions so that the minimum error and overshoot design is easy to implement.
386
391
Mahbubeh
Moghaddas
Mohamadreza
Dastranj
Nemat
Changizi
Modjtaba
Rouhani
nonlinear
optimal
classical PID controller
DC motor
PSO Algorithm
Article.16.pdf
[
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P.-I-H. Lin, S. Hwang, J. Chou, Comparison on fuzzy logic and PID controls for a DC motor position controller, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting, 1994 (1994), 1930-1935
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J. Tang, R. Chassaing, PID Controller Using theTMS320C31 DSK for Real-Time DC Motor Control, Proceedings of the 1999 Texas Instruments DSPS Fest (Houston), 1999 (1999), -
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Y. P. Yang, C. H. Cheung, S. W. Wu, J. P. Wang, Optimal design and control of axial-flux brushless dc wheel motor for electrical vehicles, Proceedings of the 10th Mediterranean Conference on Control and Automation-MED2002 (Lisbon), 2002 (2002), 9-12
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H. C. Cho, K. S. Lee, S. M. Fadali, Real-time adaptive speed control of dc motors with bounded periodic random disturbance, Int. J. Innov. Comput. I, 5 (2009), 2575-2584
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M. Fallahi, S. Azadi, Adaptive Control of a DC Motor Using Neural Network Sliding Mode Control, Proceedings of the International Multi Conference of Engineers and Computer Scientists (Hong Kong), 2009 (2009), 1-5
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B. Allaoua, A. Laoufi, B. Gasbaoui, A. Abderrahmani, Neuro-fuzzy DC motor speed control using particle swarm optimization, Leonardo El. J. Pract. Technol., 15 (2009), 1-18
##[8]
M. Fallahi, S. Azadi, Robust Control of DC Motor Using Fuzzy Sliding Mode Control with PID Compensator, Proceedings of the International Multi Conference of Engineers and Computer Scientists (Hong Kong), 2009 (2009), 1-5
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J. Kennedy, R. Eberhart, Particle Swarm Optimization, IEEE International Conference on Neural Networks (Perth, Australia), 1995 (1995), 1942-1948
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R. C. Eberhart, Y. Shi, Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization, Proceedings of the 2000 Congress on Evolutionary Computation, 2000 (2000), 84-88
]
Sequential Sampling Plan by Variable with Fuzzy Parameters
Sequential Sampling Plan by Variable with Fuzzy Parameters
en
en
In this present paper we have proposed a method for designing sequential sampling plans (SSP) by variable when the acceptable quality levels (AQL) and the rejectable quality levels (RQL) are fuzzy number. We are calculated decision criteria in the fuzzy SSP by variable. This plan is well defined since if two quality levels are crisp, it changes to classical plan by variable. For such a plan, a particular table of rejection and acceptance is calculated and compared with the classical one.
392
401
Ezzatallah
Baloui Jamkhaneh
Bahram
Sadeghpour Gildeh
Statistical quality control
sequential sampling plan
fuzzy number
acceptable quality level
lot tolerance percent defective.
Article.17.pdf
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E. Baloui Jamkhaneh, A. N. Ghara, Testing statistical hypotheses for compare means with vague data, International Mathematical Forum, 5 (2010), 615-620
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E. Baloui Jamkhaneh, A. N. Ghara, Testing Statistical Hypotheses with Fuzzy Data, Proceedings of International Conference on Intelligent Computing and Cognitive Informatics, 2010 (2010), 86-89
##[5]
E. Baloui Jamkhaneh, B. Sadeghpour Gildeh, G. Yari , Acceptance single sampling plan with fuzzy parameter, Iran. J. Fuzzy Syst., 8 (2011), 47-55
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E. Baloui Jamkhaneh, B. Sadeghpour Gildeh, G. Yari, Inspection Error and its Effects on Single Sampling Plans with Fuzzy Parameters, Struct. Multidisc. Optim., 43 (2011), 555-560
##[7]
E. Baloui Jamkhaneh, B. Sadeghpour Gildeh, AOQ and ATI for double sampling plan with using fuzzy binomial distribution, International Conference on Intelligent Computing and Cognitive Informatics, 2010 (2010), 45-49
##[8]
E. Baloui Jamkhaneh, B. Sadeghpour Gildeh, G. Yari, Important Criteria of Rectifying Inspection for Single Sampling Plan with Fuzzy Parameter, Int. J. Contemp. Math. Sci., 4 (2009), 1791-1801
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B. Sadeghpour Gildeh, G. Yari, E. Baloui Jamkhaneh, Acceptance double sampling plan with fuzzy parameter, Proceedings of the 11th joint conference on information science (Shenzhen, China), 2008 (2008), -
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H. Torabi, J. Behboodian, S. M. Taheri, Neyman-Pearson lemma for fuzzy hypotheses testing with vague data, Metrika, 64 (2006), 289-304
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H. Torabi, S. M. Mirhosseini, Sequential probability ratio tests for fuzzy hypotheses testing, Appl. Math. Sci. (Ruse), 3 (2009), 1609-1618
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]
The Application of Fuzzy Analysis on Modeling Behavioral Constructs Appraisal of Informal Learning and Psychological Empowerment Among Employees
The Application of Fuzzy Analysis on Modeling Behavioral Constructs Appraisal of Informal Learning and Psychological Empowerment Among Employees
en
en
In the current ever-changing business world, organizations need to emphasize on employees as key element of acquiring competitive advantage. As managerial strategy, psychological empowerment has been less in consideration. In this context, authors investigated effects of informal learning on psychological empowerment. Both mentioned variables have been formed in individual context and led to organizational results in collective context. The contribution of this paper is the application of fuzzy logic on construct of appraisement model in better explaining of employee's behavior. It considers two important aspects of dynamic environment of organizations; first, uncertain environment of organizations and second, complexity of human behaviors which are ill-defined. The proposed model can be led to a better strategic planning of organization's social capital and can be applied to other contexts and would guide organizations to realistic appraisement of environmental factors. Authors have applied the proposed fuzzy-model in "Agricultural Jahad" organization and results are discussed.
402
412
Peyman
Mohammady
Alireza
Bolhari
Mohsen
Rajabi
fuzzy expert system
fuzzy hypothesis analysis
individual development
informal learning
psychological empowerment
Article.18.pdf
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V. J. Marsick, M. Volpe, The nature and need for informal learning, Advances in Developing Human Resources, 1 (1999), 1-9
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K. Thomas, S. Allen, The learning organization: a meta-analysis of themes in literature, The Learning Organization, 13 (2006), 123-139
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A. L. Kremer, Predictors of Participation in Formal and Informal Workplace Learning: Demographic, Situational,Motivational, and Deterrent Factors, PhD Dissertation (George Mason University), 2006 (2006), 3893-3893
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M. Lee, J. Koh, Is empowerment really a new concept?, Int. J. Hum. Resour. Man., 12 (2001), 684-695
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]
Integrated Fuzzy VIKOR and Fuzzy AHP Model for Supplier Selection in an Agile and Modular Virtual Enterprise Application of FMCDM on Service Companies
Integrated Fuzzy VIKOR and Fuzzy AHP Model for Supplier Selection in an Agile and Modular Virtual Enterprise Application of FMCDM on Service Companies
en
en
In this ever-changing world, organizations need to Outsource parts of their processes for having agile response to market's needs and varying demands. Because of temporal nature of virtual enterprises(VE's), the situation of outsourcing process in this kind of organizations is a vital situation. The main aim of this paper is to present a decision-making framework for specific area that is appropriated for complex states. The contribution of this paper is developing of fuzzy VIKOR method and combining it with fuzzy AHP. This extension suitable for decision-making situations whichbe face with mixture appraisement that simultaneously regarded to both "group utility" or majority and "individual regret" of the opponent. The Integrated and developed model is suitable for inconsistent conditions that we face to collection of criterias and sub criterias that should satisfy some of them collectively and simultaneously and in other attainment of some individual criterias is desirable. This framework then extended to a case study with varied criterias for outsourcing process.
413
434
Peyman
Mohammady
Amin
Amid
Fuzzy AHP
Fuzzy VIKOR
Multicriteria decision-making
Virtual Enterprises
Article.19.pdf
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L. M. Camarinha-Matos, H. Afsarmanesh, C. Garita, Towards an architecture for virtual enterprises, J. Intell. Manuf., 9 (1998), 189-199
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H. W. M. Gazendam, Semiotics, Virtual Organisations, and Information Systems, in: Information, Organisation and Technology: Studies in Organisational Semiotics, 2001 (2001), 1-48
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G. D. Putnik, M. M. Cunha, R. Sousa, P. Avila, Virtual Enterprise Integration: Challenges of a New Paradigm, in: Virtual Enterprise Integration: Technological and Organizational Perspectives, 2005 (2005), 1-31
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H. Sharifi, Z. Zhang, A methodology for achieving agility in manufacturing organization: An introduction, Int. J. Prod. Econ., 62 (1999), 7-22
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Y. Y. Yusuf, M. Sarhadi, A. Gunasekaran, Agile manufacturing: The drivers, concepts and attributes, Int. J. Prod. Econ., 62 (1999), 33-43
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S. L. Goldman, R. N. Nagel, K. Preiss, Agile Competitors and Virtual Organizations: Strategies for Enriching the Customer, Van Nostrand Reinhold, New York (1995)
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P. T. Kidd, Agile Manufacturing: Forging New Frontiers, Addison-Wesley, London (1994)
##[8]
H. Sharifi, Z. Zhang, Agile manufacturing in practice-application of a methodology, Int. J. Oper. Prod. Man., 21 (2001), 772-794
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T. Y. Kim, S. Lee, K. Kim, C. H. Kim, A modeling framework for agile and interoperable virtual enterprises, Computers in Industry, 57 (2006), 204-217
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D. M. Anderson, Agile Product Development For Mass Customization: How to Develop and Deliver Products for Mass Customization, Niche Markets, JIT, Build-To-Order and Flexible Manufacturing, Irwin Professional Pub., Chicago (1997)
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A. K. W. Lau, R. C. M. Yam, E. P. Y. Tang, Supply chain product co-development, product modularity and product performance: Empirical evidence from Hong Kong manufacturers, Industrial Management & Data Systems, 107 (2007), 1036-1065
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C. H. Fine, Clockspeed: Winning Industry Control in the Age of Temporary Advantage, Perseus Books, U.S.A. (1999)
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V. Corvello, P. Migliarese, Virtual forms for the organization of production: A comparative analysis, Int. J. Prod. Econ., 110 (2007), 5-15
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C. Y. Baldwin, K. B. Clark, Managing in an Age of Modularity, Harvard Business Review, 75 (1997), 84-93
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D. R. Towill, The seamless supply chain - the predators strategic advantage, International Journal of the Techniques of Manufacturing, 13 (1997), 37-56
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N. Aissaoui, M. Haouari, E. Hassini, Supplier selection and order lot sizing modeling: A review, Comput. Oper. Res., 34 (2007), 3516-3540
##[17]
A. Q. Gill, B. Henderson-Sellers, Measuring agility and adaptability of agile methods: a 4- Dimensional Analytical Tool, Proceeding of IADIS International Conference Applied Computing, IADIS Press, 2006 (2006), 503-507
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M. A. Schilling, Modularity in multiple disciplines, in: Managing in the Modular Age: Architectures, Networks and Organizations, 2003 (2003), 203-214
##[19]
S. Opricovic, Multicriteria optimization of civil engineering systems, PhD Thesis (Faculty of Civil Engineering), Belgrade (1998)
##[20]
S. Opricovic, G. H. Tzeng, Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, Eur. J. Oper. Res., 156 (2004), 445-455
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T. L. Saaty , The Analytic Hierarchy Process, McGraw-Hill, New York (1980)
##[22]
C. C. Yang, B. S. Chen, Key quality performance evaluation using Fuzzy AHP, Journal of the Chinese Institute of Industrial Engineers, 21 (2004), 543-550
##[23]
C.-C. Sun, A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods, Expert Systems with Applications, 37 (2010), 7745-7754
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F. Torfi, R. Z. Farahani, S. Rezapour, Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives, Applied Soft Computing, 10 (2010), 520-528
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J. Wang, K. Fan, W. Wang, Integration of fuzzy AHP and FPP with TOPSIS methodology for aeroengine health assessment, Expert Systems with Applications, 37 (2010), 8516-8526
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L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning, Information Science, 8 (1975), 199-249
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S. J. Chen, C. L. Hwang, Fuzzy Multiple Attribute Decision Making : Methods and Applications, Springer, New York (1992)
]
A New Method for Solving Fuzzy Mcdm Problems
A New Method for Solving Fuzzy Mcdm Problems
en
en
Solving multi-criteria fuzzy decision making problems is one of the most important objects that scolars deal with. In situations that the information about criteria weights for alternatives is completely unknown, choosing the best alternative is more difficult. In this paper, by using of intuitionistic fuzzy sets(IFSs), we combine the concepts of entropy, correlation coefficient of two IFSs and ideal solution to determine the criteria weights and then evaluate the weighted correlation coefficient between an alternative and the ideal solution. According to this value, the alternatives can be ranked. Practicality and effectiveness of this technique, in comparison with other similar methods, persuade the decision makers to use of it.
435
438
Reza
Khalesi
Hamidreza
Maleki
fuzzy decision making
correlation coefficient
intuitionistic fuzzy.
Article.20.pdf
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[1]
K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20 (1986), 87-96
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W.-L. Hung, Using statistical viewpoint in developing correlation of intuitionistic fuzzy sets, Internat. J. Uncertain. Fuzziness Knowledge-Based Systems, 9 (2001), 509-516
##[3]
P. Burillo, H. Bustince, Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets, Fuzzy Sets and Systems, 19 (1996), 305-316
##[4]
H. W. Liu, G. J. Wang, Multi-criteria decision-making methods based on intuitionistic fuzzy sets, Eur. J. Oper. Res., 179 (2007), 220-233
##[5]
J. Ye, Multicriteria fuzzy decision-making method based on a novel accuracy function under interval-valued intuitionistic fuzzy environment, Expert Systems with Applications, 36 (2009), 6899-6902
##[6]
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]