Search results for: rough fuzzy .
660 Fuzzy Approach for Ranking of Motor Vehicles Involved in Road Accidents
Authors: Lazim Abdullah, N orhanadiah Zam
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Increasing number of vehicles and lack of awareness among road users may lead to road accidents. However no specific literature was found to rank vehicles involved in accidents based on fuzzy variables of road users. This paper proposes a ranking of four selected motor vehicles involved in road accidents. Human and non-human factors that normally linked with road accidents are considered for ranking. The imprecision or vagueness inherent in the subjective assessment of the experts has led the application of fuzzy sets theory to deal with ranking problems. Data in form of linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. The Multi Criteria Decision Making, fuzzy TOPSIS was applied in computational procedures. From the analysis, it shows that motorcycles vehicles yielded the highest closeness coefficient at 0.6225. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the motorcycles recorded the first rank.
Keywords: Road accidents, decision making, closeness coefficient, fuzzy number
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1532659 An Edge Detection and Filtering Mechanism of Two Dimensional Digital Objects Based on Fuzzy Inference
Authors: Ayman A. Aly, Abdallah A. Alshnnaway
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The general idea behind the filter is to average a pixel using other pixel values from its neighborhood, but simultaneously to take care of important image structures such as edges. The main concern of the proposed filter is to distinguish between any variations of the captured digital image due to noise and due to image structure. The edges give the image the appearance depth and sharpness. A loss of edges makes the image appear blurred or unfocused. However, noise smoothing and edge enhancement are traditionally conflicting tasks. Since most noise filtering behaves like a low pass filter, the blurring of edges and loss of detail seems a natural consequence. Techniques to remedy this inherent conflict often encompass generation of new noise due to enhancement. In this work a new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of three stages. (1) Define fuzzy sets in the input space to computes a fuzzy derivative for eight different directions (2) construct a set of IFTHEN rules by to perform fuzzy smoothing according to contributions of neighboring pixel values and (3) define fuzzy sets in the output space to get the filtered and edged image. Experimental results are obtained to show the feasibility of the proposed approach with two dimensional objects.Keywords: Additive noise, edge preserving filtering, fuzzy image filtering, noise reduction, two dimensional mechanical images.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1555658 Improved BEENISH Protocol for Wireless Sensor Networks Based Upon Fuzzy Inference System
Authors: Rishabh Sharma, Renu Vig, Neeraj Sharma
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The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.
Keywords: Wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 458657 Stability Analysis of Impulsive Stochastic Fuzzy Cellular Neural Networks with Time-varying Delays and Reaction-diffusion Terms
Authors: Xinhua Zhang, Kelin Li
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In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural networks with timevarying delays and reaction-diffusion is considered. By utilizing suitable Lyapunov-Krasovskii funcational, the inequality technique and stochastic analysis technique, some sufficient conditions ensuring global exponential stability of equilibrium point for impulsive stochastic fuzzy cellular neural networks with time-varying delays and diffusion are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of fuzzy neural networks. An example is given to show the effectiveness of the obtained results.
Keywords: Exponential stability, stochastic fuzzy cellular neural networks, time-varying delays, impulses, reaction-diffusion terms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1365656 Micropower Fuzzy Linguistic-Hedges Circuit in Current-Mode Approach
Authors: E. Farshidi
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In this paper, based on a novel synthesis, a set of new simplified circuit design to implement the linguistic-hedge operations for adjusting the fuzzy membership function set is presented. The circuits work in current-mode and employ floating-gate MOS (FGMOS) transistors that operate in weak inversion region. Compared to the other proposed circuits, these circuits feature severe reduction of the elements number, low supply voltage (0.7V), low power consumption (<200nW), immunity from body effect and wide input dynamic range (>60dB). In this paper, a set of fuzzy linguistic hedge circuits, including absolutely, very, much more, more, plus minus, more or less and slightly, has been implemented in 0.18 mm CMOS process. Simulation results by Hspice confirm the validity of the proposed design technique and show high performance of the circuits.
Keywords: Current-mode, Linguistic-Hedge, Fuzzy Logic, lowpower
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1755655 A Trust Model using Fuzzy Logic in Wireless Sensor Network
Authors: Tae Kyung Kim, Hee Suk Seo
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Adapting various sensor devices to communicate within sensor networks empowers us by providing range of possibilities. The sensors in sensor networks need to know their measurable belief of trust for efficient and safe communication. In this paper, we suggested a trust model using fuzzy logic in sensor network. Trust is an aggregation of consensus given a set of past interaction among sensors. We applied our suggested model to sensor networks in order to show how trust mechanisms are involved in communicating algorithm to choose the proper path from source to destination.Keywords: Fuzzy, Sensor Networks, Trust.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3539654 Development of Risk Assessment and Occupational Safety Management Model for Building Construction Projects
Authors: Preeda Sansakorn, Min An
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In order to be capable of dealing with uncertainties, subjectivities, including vagueness arising in building construction projects, the application of fuzzy reasoning technique based on fuzzy set theory is proposed. This study contributes significantly to the development of a fuzzy reasoning safety risk assessment model for building construction projects that could be employed to assess the risk magnitude of each hazardous event identified during construction, and a third parameter of probability of consequence is incorporated in the model. By using the proposed safety risk analysis methodology, more reliable and less ambiguities, which provide the safety risk management project team for decision-making purposes.
Keywords: Safety risks assessment, building construction safety, fuzzy reasoning, construction risk assessment model, building construction projects.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2328653 Fuzzy based Security Threshold Determining for the Statistical En-Route Filtering in Sensor Networks
Authors: Hae Young Lee, Tae Ho Cho
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In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false reports during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and overhead. In this paper, we propose a fuzzy logic for determining a security threshold value in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the number of partitions in a global key pool, the number of compromised partitions, and the energy level of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.
Keywords: Fuzzy logic, security, sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1564652 Multisensor Agent Based Intrusion Detection
Authors: Richard A. Wasniowski
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In this paper we propose a framework for multisensor intrusion detection called Fuzzy Agent-Based Intrusion Detection System. A unique feature of this model is that the agent uses data from multiple sensors and the fuzzy logic to process log files. Use of this feature reduces the overhead in a distributed intrusion detection system. We have developed an agent communication architecture that provides a prototype implementation. This paper discusses also the issues of combining intelligent agent technology with the intrusion detection domain.Keywords: Intrusion detection, fuzzy logic, agents, networksecurity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1908651 Solution of Fuzzy Differential Equation under Generalized Differentiability by Genetic Programming
Authors: N. Kumaresan, J. Kavikumar, M. Kumudthaa, Kuru Ratnavelu
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In this paper, solution of fuzzy differential equation under general differentiability is obtained by genetic programming (GP). The obtained solution in this method is equivalent or very close to the exact solution of the problem. Accuracy of the solution to this problem is qualitatively better. An illustrative numerical example is presented for the proposed method.Keywords: Fuzzy differential equation, Generalized differentiability, Genetic programming and H-difference.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2231650 A Single-Period Inventory Problem with Resalable Returns: A Fuzzy Stochastic Approach
Authors: Oshmita Dey, Debjani Chakraborty
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In this paper, a single period inventory model with resalable returns has been analyzed in an imprecise and uncertain mixed environment. Demand has been introduced as a fuzzy random variable. In this model, a single order is placed before the start of the selling season. The customer, for a full refund, may return purchased products within a certain time interval. Returned products are resalable, provided they arrive back before the end of the selling season and are found to be undamaged. Products remaining at the end of the season are salvaged. All demands not met directly are lost. The probabilities that a sold product is returned and that a returned product is resalable, both imprecise in a real situation, have been assumed to be fuzzy in nature.
Keywords: Fuzzy random variable, Modified graded meanintegration, Internet mail order, Inventory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1517649 Assessment of Mortgage Applications Using Fuzzy Logic
Authors: Swathi Sampath, V. Kalaichelvi
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The assessment of the risk posed by a borrower to a lender is one of the common problems that financial institutions have to deal with. Consumers vying for a mortgage are generally compared to each other by the use of a number called the Credit Score, which is generated by applying a mathematical algorithm to information in the applicant’s credit report. The higher the credit score, the lower the risk posed by the candidate, and the better he is to be taken on by the lender. The objective of the present work is to use fuzzy logic and linguistic rules to create a model that generates Credit Scores.
Keywords: Credit scoring, fuzzy logic, mortgage, risk assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2731648 Influence of Artificial Roughness on Heat Transfer in the Rotating Flow
Authors: T. Magrakvelidze, N. Bantsadze, N. Lekveishvili, Kh. Lomidze
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The results of an experimental study of the process of convective and boiling heat transfer in the vessel with stirrer for smooth and rough ring-shaped pipes are presented. It is established that creation of two-dimensional artificial roughness on the heated surface causes the essential (~100%) intensification of convective heat transfer. In case of boiling the influence of roughness appears on the initial stage of boiling and in case of fully developed nucleate boiling there was no intensification of heat transfer. The similitude equation for calculating convective heat transfer coefficient, which generalizes well experimental data both for the smooth and the rough surfaces is proposed.Keywords: boiling, heat transfer, roughness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1859647 Application of Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA
Authors: Eleftherios Giovanis
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In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms significant the Logit and Probit models in the out-of sample period. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.Keywords: ANFIS, discrete choice models, financial crisis, USeconomy
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1596646 Extended Intuitionistic Fuzzy VIKOR Method in Group Decision Making: The Case of Vendor Selection Decision
Authors: Nastaran Hajiheydari, Mohammad Soltani Delgosha
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Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated.
Keywords: Group decision making, intuitionistic fuzzy entropy measure, intuitionistic fuzzy set, vendor selection VIKOR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 719645 Some Clopen Sets in the Uniform Topology on BCI-algebras
Authors: A. Hasankhani, H. Saadat, M. M. Zahedi
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In this paper some properties of the uniformity topology on a BCI-algebras are discussed.
Keywords: (Fuzzy) ideal, (Fuzzy) subalgebra, Uniformity, clopen sets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1646644 Design of Liquids Mixing Control System using Fuzzy Time Control Discrete Event Model for Industrial Applications
Authors: M.Saleem Khan, Khaled Benkrid
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This paper presents a time control liquids mixing system in the tanks as an application of fuzzy time control discrete model. The system is designed for a wide range of industrial applications. The simulation design of control system has three inputs: volume, viscosity, and selection of product, along with the three external control adjustments for the system calibration or to take over the control of the system autonomously in local or distributed environment. There are four controlling elements: rotatory motor, grinding motor, heating and cooling units, and valves selection, each with time frame limit. The system consists of three controlled variables measurement through its sensing mechanism for feed back control. This design also facilitates the liquids mixing system to grind certain materials in tanks and mix with fluids under required temperature controlled environment to achieve certain viscous level. Design of: fuzzifier, inference engine, rule base, deffuzifiers, and discrete event control system, is discussed. Time control fuzzy rules are formulated, applied and tested using MATLAB simulation for the system.Keywords: Fuzzy time control, industrial application and timecontrol systems, adjustment of Fuzzy system, liquids mixing system, design of fuzzy time control DEV system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2536643 Noise Reduction in Image Sequences using an Effective Fuzzy Algorithm
Authors: Mahmoud Saeidi, Khadijeh Saeidi, Mahmoud Khaleghi
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In this paper, we propose a novel spatiotemporal fuzzy based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership functions. In this algorithm median filter is used to suppress noise. Experimental results show when the images are corrupted by highdensity Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.Keywords: Image Sequences, Noise Reduction, fuzzy algorithm, triangular membership function
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1864642 Amelioration of Cardiac Arrythmias Classification Performance Using Artificial Neural Network, Adaptive Neuro-Fuzzy and Fuzzy Inference Systems Classifiers
Authors: Alexandre Boum, Salomon Madinatou
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This paper aims at bringing a scientific contribution to the cardiac arrhythmia biomedical diagnosis systems; more precisely to the study of the amelioration of cardiac arrhythmia classification performance using artificial neural network, adaptive neuro-fuzzy and fuzzy inference systems classifiers. The purpose of this amelioration is to enable cardiologists to make reliable diagnosis through automatic cardiac arrhythmia analyzes and classifications based on high confidence classifiers. In this study, six classes of the most commonly encountered arrhythmias are considered: the Right Bundle Branch Block, the Left Bundle Branch Block, the Ventricular Extrasystole, the Auricular Extrasystole, the Atrial Fibrillation and the Normal Cardiac rate beat. From the electrocardiogram (ECG) extracted parameters, we constructed a matrix (360x360) serving as an input data sample for the classifiers based on neural networks and a matrix (1x6) for the classifier based on fuzzy logic. By varying three parameters (the quality of the neural network learning, the data size and the quality of the input parameters) the automatic classification permitted us to obtain the following performances: in terms of correct classification rate, 83.6% was obtained using the fuzzy logic based classifier, 99.7% using the neural network based classifier and 99.8% for the adaptive neuro-fuzzy based classifier. These results are based on signals containing at least 360 cardiac cycles. Based on the comparative analysis of the aforementioned three arrhythmia classifiers, the classifiers based on neural networks exhibit a better performance.
Keywords: Adaptive neuro-fuzzy, artificial neural network, cardiac arrythmias, fuzzy inference systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 690641 Fuzzy Control of a Three Phase ThyristorizedInduction Motor
Authors: Abolfazl Jalilvand, Mohammad Reza Feyzi, Sohrab Khanmohammad, Mohammad Bagher Bana Sharifian, Ali Sajjadi
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Nowadays the control of stator voltage at a constant frequency is one of the traditional and low expense methods in order to control the speed of induction motors near its nominal speed. The torque of induction motor is a nonlinear function of the firing angle, phase angle and speed. In this paper the speed control of induction motor regarding various load torque and under different conditions will be investigated based on a fuzzy controller with inverse training.
Keywords: Three phase induction motor, AC converter, speedcontrol, fuzzy control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1781640 A Study on Fuzzy Adaptive Control of Enteral Feeding Pump
Authors: Seungwoo Kim, Hyojune Chae, Yongrae Jung, Jongwook Kim
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Recent medical studies have investigated the importance of enteral feeding and the use of feeding pumps for recovering patients unable to feed themselves or gain nourishment and nutrients by natural means. The most of enteral feeding system uses a peristaltic tube pump. A peristaltic pump is a form of positive displacement pump in which a flexible tube is progressively squeezed externally to allow the resulting enclosed pillow of fluid to progress along it. The squeezing of the tube requires a precise and robust controller of the geared motor to overcome parametric uncertainty of the pumping system which generates due to a wide variation of friction and slip between tube and roller. So, this paper proposes fuzzy adaptive controller for the robust control of the peristaltic tube pump. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good control performance, accurate dose rate and robust system stability, of the developed feeding pump is confirmed through experimental and clinic testing.
Keywords: Enteral Feeding Pump, Peristaltic Tube Pump, Fuzzy Adaptive Control, Fuzzy Multi-layered Controller, Look-up Table..
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1635639 Genetic Algorithm based Optimization approach for MR Dampers Fuzzy Modeling
Authors: Behnam Mehrkian, Arash Bahar, Ali Chaibakhsh
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Magneto-rheological (MR) fluid damper is a semiactive control device that has recently received more attention by the vibration control community. But inherent hysteretic and highly nonlinear dynamics of MR fluid damper is one of the challenging aspects to employ its unique characteristics. The combination of artificial neural network (ANN) and fuzzy logic system (FLS) have been used to imitate more precisely the behavior of this device. However, the derivative-based nature of adaptive networks causes some deficiencies. Therefore, in this paper, a novel approach that employ genetic algorithm, as a free-derivative algorithm, to enhance the capability of fuzzy systems, is proposed. The proposed method used to model MR damper. The results will be compared with adaptive neuro-fuzzy inference system (ANFIS) model, which is one of the well-known approaches in soft computing framework, and two best parametric models of MR damper. Data are generated based on benchmark program by applying a number of famous earthquake records.Keywords: Benchmark program, earthquake record filtering, fuzzy logic, genetic algorithm, MR damper.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2107638 Applying Fuzzy Decision Making Approach to IT Outsourcing Supplier Selection
Authors: Gülcin Büyüközkan, Mehmet Sakir Ersoy
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The decision of information technology (IT) outsourcing requires close attention to the evaluation of supplier selection process because the selection decision involves conflicting multiple criteria and is replete with complex decision making problems. Selecting the most appropriate suppliers is considered an important strategic decision that may impact the performance of outsourcing engagements. The objective of this paper is to aid decision makers to evaluate and assess possible IT outsourcing suppliers. An axiomatic design based fuzzy group decision making is adopted to evaluate supplier alternatives. Finally, a case study is given to demonstrate the potential of the methodology. KeywordsIT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic.Keywords: IT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1941637 Automatic Generation Control of Interconnected Power System with Generation Rate Constraintsby Hybrid Neuro Fuzzy Approach
Authors: Gayadhar Panda, Sidhartha Panda, C. Ardil
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The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the proposed approach is faster than conventional controllers. The performance of HNF controller has been compared with that of both conventional Proportional Integral (PI) controller as well as Fuzzy Logic Controller (FLC) both in the absence and presence of Generation Rate Constraint (GRC). System performance is examined considering disturbance in each area of interconnected power system.
Keywords: Automatic Generation Control (AGC), Dynamic Response, Generation Rate Constraint (GRC), Proportional Integral(PI) Controller, Fuzzy Logic Controller (FLC), Hybrid Neuro-Fuzzy(HNF) Control, MATLAB/SIMULINK.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4119636 Solutions of Fuzzy Transportation Problem Using Best Candidates Method and Different Ranking Techniques
Authors: M. S. Annie Christi
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Transportation Problem (TP) is based on supply and demand of commodities transported from one source to the different destinations. Usual methods for finding solution of TPs are North-West Corner Rule, Least Cost Method Vogel’s Approximation Method etc. The transportation costs tend to vary at each time. We can use fuzzy numbers which would give solution according to this situation. In this study the Best Candidate Method (BCM) is applied. For ranking Centroid Ranking Technique (CRT) and Robust Ranking Technique have been adopted to transform the fuzzy TP and the above methods are applied to EDWARDS Vacuum Company, Crawley, in West Sussex in the United Kingdom. A Comparative study is also given. We see that the transportation cost can be minimized by the application of CRT under BCM.
Keywords: Best candidates method, centroid ranking technique, robust ranking technique, transportation problem, fuzzy transportation problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1561635 On the Noise Distance in Robust Fuzzy C-Means
Authors: M. G. C. A. Cimino, G. Frosini, B. Lazzerini, F. Marcelloni
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In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is certainly one of the most known among these algorithms. In robust-FCM, noise is modeled as a separate cluster and is characterized by a prototype that has a constant distance δ from all data points. Distance δ determines the boundary of the noise cluster and therefore is a critical parameter of the algorithm. Though some approaches have been proposed to automatically determine the most suitable δ for the specific application, up to today an efficient and fully satisfactory solution does not exist. The aim of this paper is to propose a novel method to compute the optimal δ based on the analysis of the distribution of the percentage of objects assigned to the noise cluster in repeated executions of the robust-FCM with decreasing values of δ . The extremely encouraging results obtained on some data sets found in the literature are shown and discussed.Keywords: noise prototype, robust fuzzy clustering, robustfuzzy C-means
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1808634 Adaptive Fuzzy Control for Air-Fuel Ratio of Automobile Spark Ignition Engine
Authors: Ali Ghaffari, A. Hosein Shamekhi, Akbar Saki, Ehsan Kamrani
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In order to meet the limits imposed on automotive emissions, engine control systems are required to constrain air/fuel ratio (AFR) in a narrow band around the stoichiometric value, due to the strong decay of catalyst efficiency in case of rich or lean mixture. This paper presents a model of a sample spark ignition engine and demonstrates Simulink-s capabilities to model an internal combustion engine from the throttle to the crankshaft output. We used welldefined physical principles supplemented, where appropriate, with empirical relationships that describe the system-s dynamic behavior without introducing unnecessary complexity. We also presents a PID tuning method that uses an adaptive fuzzy system to model the relationship between the controller gains and the target output response, with the response specification set by desired percent overshoot and settling time. The adaptive fuzzy based input-output model is then used to tune on-line the PID gains for different response specifications. Experimental results demonstrate that better performance can be achieved with adaptive fuzzy tuning relative to similar alternative control strategies. The actual response specifications with adaptive fuzzy matched the desired response specifications.Keywords: Modelling, Air–fuel ratio control, SI engine, Adaptive fuzzy Control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2510633 A Group Based Fuzzy MCDM for Selecting Knowledge Portal System
Authors: Amir Sanayei, Seyed Farid Mousavi, Catherine Asadi Shahmirzadi
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Despite of many scholars and practitioners recognize the knowledge management implementation in an organizations but insufficient attention has been paid by researchers to select suitable knowledge portal system (KPS) selection. This study develops a Multi Criteria Decision making model based on the fuzzy VIKOR approach to help organizations in selecting KPS. The suitable portal is the critical influential factors on the success of knowledge management (KM) implementation in an organization.Keywords: Knowledge management, Knowledge portal system, Fuzzy VIKOR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1829632 Magnetic Fluid Based Squeeze Film in Rough Rotating Curved Porous Annular Plates: Deformation Effect
Authors: M. E. Shimpi, G. M. Deheri
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This article aims to investigate the performance of a magnetic fluid based squeeze film between rotating transversely rough curved porous annular plates incorporating the effect of elastic deformation. The associated stochastically averaged Reynolds type equation is solved to obtain the pressure distribution leading to the calculation of the load carrying capacity. The results suggest that the transverse roughness of the bearing surfaces affects the performance adversely although the bearing systems register a relatively improved performance due to the magnetization. The deformation causes reduced the load carrying capacity while the curvature parameters tend to nominally increase the load carrying capacity. Besides, the adverse effect of porosity, deformation and standard deviation can be minimized to some extent by the positive effect of the magnetization and the curvature parameters in the case of negatively skewed roughness by suitably choosing the rotational inertia and the aspect ratio, which becomes significant when negative variance occurs.
Keywords: Annular plates curved rough surface, deformation, load carrying capacity, rotational inertia, magnetic fluid, squeeze film.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1814631 An Enhanced Associativity Based Routing with Fuzzy Based Trust to Mitigate Network Attacks
Authors: K. Geetha, P. Thangaraj
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Mobile Ad Hoc Networks (MANETs) is a collection of mobile devices forming a communication network without infrastructure. MANET is vulnerable to security threats due to network’s limited security, dynamic topology, scalability and the lack of central management. The Quality of Service (QoS) routing in such networks is limited by network breakage caused by node mobility or nodes energy depletions. The impact of node mobility on trust establishment is considered and its use to propagate trust through a network is investigated in this paper. This work proposes an enhanced Associativity Based Routing (ABR) with Fuzzy based Trust (Fuzzy- ABR) routing protocol for MANET to improve QoS and to mitigate network attacks.Keywords: Mobile Ad hoc Networks (MANET), Associativity Based Routing (ABR), Fuzzy based Computed Trust.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2546