Search results for: Generalized trapezoidal fuzzy numbers
1487 A Fuzzy Predictive Filter for Sinusoidal Signals with Time-Varying Frequencies
Authors: X. Z. Gao, S. J. Ovaska, X. Wang
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Prediction of sinusoidal signals with time-varying frequencies has been an important research topic in power electronics systems. To solve this problem, we propose a new fuzzy predictive filtering scheme, which is based on a Finite Impulse Response (FIR) filter bank. Fuzzy logic is introduced here to provide appropriate interpolation of individual filter outputs. Therefore, instead of regular 'hard' switching, our method has the advantageous 'soft' switching among different filters. Simulation comparisons between the fuzzy predictive filtering and conventional filter bank-based approach are made to demonstrate that the new scheme can achieve an enhanced prediction performance for slowly changing sinusoidal input signals.Keywords: Predictive filtering, fuzzy logic, sinusoidal signals, time-varying frequencies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14781486 A Quadratic Approach for Generating Pythagorean Triples
Authors: P. K. Rahul Krishna, S. Sandeep Kumar, Jayanthi Sunder Raj
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The article explores one of the important relations between numbers-the Pythagorean triples (triplets) which finds its application in distance measurement, construction of roads, towers, buildings and wherever Pythagoras theorem finds its application. The Pythagorean triples are numbers, that satisfy the condition “In a given set of three natural numbers, the sum of squares of two natural numbers is equal to the square of the other natural number”. There are numerous methods and equations to obtain the triplets, which have their own merits and demerits. Here, quadratic approach for generating triples uses the hypotenuse leg difference method. The advantage is that variables are few and finally only three independent variables are present.
Keywords: Arithmetic progression, hypotenuse leg difference method, natural numbers, Pythagorean triplets, quadratic equation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8151485 Complex-Valued Neural Network in Signal Processing: A Study on the Effectiveness of Complex Valued Generalized Mean Neuron Model
Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy
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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17201484 Upper Bound of the Generalize p-Value for the Behrens-Fisher Problem with a Known Ratio of Variances
Authors: Rada Somkhuean, Suparat Niwitpong, Sa-aat Niwitpong
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This paper presents the generalized p-values for testing the Behrens-Fisher problem when a ratio of variance is known. We also derive a closed form expression of the upper bound of the proposed generalized p-value.
Keywords: Generalized p-value, hypothesis testing, ratio of variances, upper bound.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12191483 A Novel Modified Adaptive Fuzzy Inference Engine and Its Application to Pattern Classification
Authors: J. Hossen, A. Rahman, K. Samsudin, F. Rokhani, S. Sayeed, R. Hasan
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The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a novel Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data sets. A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and rules by the fuzzy c-means clustering and Apriori algorithm technique, respectively. The generated adaptive fuzzy inference engine is adjusted by the least-squares fit and a conjugate gradient descent algorithm towards better performance with a minimal set of rules. The proposed MAFIE is able to reduce the number of rules which increases exponentially when more input variables are involved. The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher-s Iris and Wisconsin breast cancer data sets and shown to be very competitive.Keywords: Apriori algorithm, Fuzzy C-means, MAFIE, TSK
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19231482 Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System
Authors: S. Gherbi, F. Bouchareb
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This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.
Keywords: Delayed systems, Fuzzy Immune PID, Optimization, Smith predictor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22101481 Evaluating Service Quality of Online Auction by Fuzzy MCDM
Authors: Wei-Hsuan Lee, Chien-Hua Wang, Chin-Tzong Pang
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This paper applies fuzzy set theory to evaluate the service quality of online auction. Service quality is a composition of various criteria. Among them many intangible attributes are difficult to measure. This characteristic introduces the obstacles for respondent in replying to the survey. So as to overcome this problem, we invite fuzzy set theory into the measurement of performance. By using AHP in obtaining criteria and TOPSIS in ranking, we found the most concerned dimension of service quality is Transaction Safety Mechanism and the least is Charge Item. Regarding to the most concerned attributes are information security, accuracy and information.Keywords: AHP, Fuzzy set theory, TOPSIS, Online auction, Servicequality
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17811480 Unsupervised Image Segmentation Based on Fuzzy Connectedness with Sale Space Theory
Authors: Yuanjie Zheng, Jie Yang, Yue Zhou
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In this paper, we propose an approach of unsupervised segmentation with fuzzy connectedness. Valid seeds are first specified by an unsupervised method based on scale space theory. A region is then extracted for each seed with a relative object extraction method of fuzzy connectedness. Afterwards, regions are merged according to the values between them of an introduced measure. Some theorems and propositions are also provided to show the reasonableness of the measure for doing mergence. Experiment results on a synthetic image, a color image and a large amount of MR images of our method are reported.Keywords: Image segmentation, unsupervised imagesegmentation, fuzzy connectedness, scale space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13301479 TS Fuzzy Controller to Stochastic Systems
Authors: Joabe Silva, Ginalber Serra
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This paper proposes the analysis and design of robust fuzzy control to Stochastic Parametrics Uncertaint Linear systems. This system type to be controlled is partitioned into several linear sub-models, in terms of transfer function, forming a convex polytope, similar to LPV (Linear Parameters Varying) system. Once defined the linear sub-models of the plant, these are organized into fuzzy Takagi- Sugeno (TS) structure. From the Parallel Distributed Compensation (PDC) strategy, a mathematical formulation is defined in the frequency domain, based on the gain and phase margins specifications, to obtain robust PI sub-controllers in accordance to the Takagi- Sugeno fuzzy model of the plant. The main results of the paper are based on the robust stability conditions with the proposal of one Axiom and two Theorems.Keywords: Fuzzy Systems; Robust Stability, Stochastic Control, Stochastic Process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16901478 Finding Fuzzy Association Rules Using FWFP-Growth with Linguistic Supports and Confidences
Authors: Chien-Hua Wang, Chin-Tzong Pang
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In data mining, the association rules are used to search for the relations of items of the transactions database. Following the data is collected and stored, it can find rules of value through association rules, and assist manager to proceed marketing strategy and plan market framework. In this paper, we attempt fuzzy partition methods and decide membership function of quantitative values of each transaction item. Also, by managers we can reflect the importance of items as linguistic terms, which are transformed as fuzzy sets of weights. Next, fuzzy weighted frequent pattern growth (FWFP-Growth) is used to complete the process of data mining. The method above is expected to improve Apriori algorithm for its better efficiency of the whole association rules. An example is given to clearly illustrate the proposed approach.Keywords: Association Rule, Fuzzy Partition Methods, FWFP-Growth, Apiroir algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16421477 Conventional and Fuzzy Logic Controllers at Generator Location for Low Frequency Oscillation Damping
Authors: K. Prasertwong, N. Mithulananthan
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This paper investigates and compares performance of various conventional and fuzzy logic based controllers at generator locations for oscillation damping. Performance of combination of conventional and fuzzy logic based controllers also studied by comparing overshoot on the active power deviation response for a small disturbance and damping ratio of the critical mode. Fuzzy logic based controllers can not be modeled in the state space form to get the eigenvalues and corresponding damping ratios of various modes of generators and controllers. Hence, a new method based on tracing envelop of time domain waveform is also presented and used in the paper for comparing performance of controllers. The paper also shows that if the fuzzy based controllers designed separately combining them could not lead to a better performance.Keywords: Automatic voltage regulator, damping ratio, fuzzylogic controller, power system stabilizer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20001476 Rule-Based Fuzzy Logic Controller with Adaptable Reference
Authors: Sheroz Khan, I. Adam, A. H. M. Zahirul Alam, Mohd Rafiqul Islam, Othman O. Khalifa
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This paper attempts to model and design a simple fuzzy logic controller with Variable Reference. The Variable Reference (VR) is featured as an adaptability element which is obtained from two known variables – desired system-input and actual system-output. A simple fuzzy rule-based technique is simulated to show how the actual system-input is gradually tuned in to a value that closely matches the desired input. The designed controller is implemented and verified on a simple heater which is controlled by PIC Microcontroller harnessed by a code developed in embedded C. The output response of the PIC-controlled heater is analyzed and compared to the performances by conventional fuzzy logic controllers. The novelty of this work lies in the fact that it gives better performance by using less number of rules compared to conventional fuzzy logic controllers.Keywords: Fuzzy logic controller, Variable reference, Adaptability, Rule-based.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13041475 A New Intelligent Strategy to Integrated Control of AFS/DYC Based on Fuzzy Logic
Authors: R. Karbalaei, A. Ghaffari, R. Kazemi, S. H. Tabatabaei
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An integrated vehicle dynamics control system is developed in this paper by a combination of active front steering (AFS) and direct yaw-moment control (DYC) based on fuzzy logic control. The control system has a hierarchical structure consisting of two layers. A fuzzy logic controller is used in the upper layer (yaw rate controller) to keep the yaw rate in its desired value. The yaw rate error and its rate of change are applied to the upper controlling layer as inputs, where the direct yaw moment control signal and the steering angle correction of the front wheels are the outputs. In the lower layer (fuzzy integrator), a fuzzy logic controller is designed based on the working region of the lateral tire forces. Depending on the directions of the lateral forces at the front wheels, a switching function is activated to adjust the scaling factor of the fuzzy logic controller. Using a nonlinear seven degrees of freedom vehicle model, the simulation results illustrate considerable improvements which are achieved in vehicle handling through the integrated AFS/DYC control system in comparison with the individual AFS or DYC controllers.
Keywords: Intelligent strategy, integrated control, fuzzy logic, AFS/DYC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23041474 A Fuzzy Decision Making Approach for Supplier Selection in Healthcare Industry
Authors: Zeynep Sener, Mehtap Dursun
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Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision methodology.
Keywords: Fuzzy decision making, fuzzy multiple objective programming, medical supply chain, supplier selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26631473 Solving of the Fourth Order Differential Equations with the Neumann Problem
Authors: Marziyeh Halimi, Roushanak Lotfikar, Simin Mansouri Borojeni
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In this paper we considered the Neumann problem for the fourth order differential equation. First we define the weighted Sobolev space 2 Wα and generalized solution for this equation. Then we consider the existence and uniqueness of the generalized solution, as well as give the description of the spectrum and of the domain of definition of the corresponding operator.Keywords: Neumann problem, weighted Sobolev spaces, generalized solution, spectrum of linear operators.2000 mathematic subject classification: 34A05, 34A30.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14191472 Improving Convergence of Parameter Tuning Process of the Additive Fuzzy System by New Learning Strategy
Authors: Thi Nguyen, Lee Gordon-Brown, Jim Peterson, Peter Wheeler
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An additive fuzzy system comprising m rules with n inputs and p outputs in each rule has at least t m(2n + 2 p + 1) parameters needing to be tuned. The system consists of a large number of if-then fuzzy rules and takes a long time to tune its parameters especially in the case of a large amount of training data samples. In this paper, a new learning strategy is investigated to cope with this obstacle. Parameters that tend toward constant values at the learning process are initially fixed and they are not tuned till the end of the learning time. Experiments based on applications of the additive fuzzy system in function approximation demonstrate that the proposed approach reduces the learning time and hence improves convergence speed considerably.Keywords: Additive fuzzy system, improving convergence, parameter learning process, unsupervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15031471 A Comparative Study on Fuzzy and Neuro-Fuzzy Enabled Cluster Based Routing Protocols for Wireless Sensor Networks
Authors: Y. Harold Robinson, E. Golden Julie
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Dynamic Routing in Wireless Sensor Networks (WSNs) has played a significant task in research for the recent years. Energy consumption and data delivery in time are the major parameters with the usage of sensor nodes that are significant criteria for these networks. The location of sensor nodes must not be prearranged. Clustering in WSN is a key methodology which is used to enlarge the life-time of a sensor network. It consists of numerous real-time applications. The features of WSNs are minimized the consumption of energy. Soft computing techniques can be included to accomplish improved performance. This paper surveys the modern trends in routing enclose fuzzy logic and Neuro-fuzzy logic based on the clustering techniques and implements a comparative study of the numerous related methodologies.Keywords: Wireless sensor networks, clustering, fuzzy logic, neuro-fuzzy logic, energy efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9811470 On Solving Single-Period Inventory Model under Hybrid Uncertainty
Authors: Madhukar Nagare, Pankaj Dutta
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Inventory decisional environment of short life-cycle products is full of uncertainties arising from randomness and fuzziness of input parameters like customer demand requiring modeling under hybrid uncertainty. Prior inventory models incorporating fuzzy demand have unfortunately ignored stochastic variation of demand. This paper determines an unambiguous optimal order quantity from a set of n fuzzy observations in a newsvendor inventory setting in presence of fuzzy random variable demand capturing both fuzzy perception and randomness of customer demand. The stress of this paper is in providing solution procedure that attains optimality in two steps with demand information availability in linguistic phrases leading to fuzziness along with stochastic variation. The first step of solution procedure identifies and prefers one best fuzzy opinion out of all expert opinions and the second step determines optimal order quantity from the selected event that maximizes profit. The model and solution procedure is illustrated with a numerical example.Keywords: Fuzzy expected value, Fuzzy random demand, Hybrid uncertainty, Optimal order quantity, Single-period inventory
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20071469 Existence and Stability Analysis of Discrete-time Fuzzy BAM Neural Networks with Delays and Impulses
Authors: Chao Wang, Yongkun Li
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In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.
Keywords: Discrete-time fuzzy BAM neural networks, ımpulses, global exponential stability, global asymptotical stability, equilibrium point.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14931468 Gain Tuning Fuzzy Controller for an Optical Disk Drive
Authors: Shiuh-Jer Huang, Ming-Tien Su
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Since the driving speed and control accuracy of commercial optical disk are increasing significantly, it needs an efficient controller to monitor the track seeking and following operations of the servo system for achieving the desired data extracting response. The nonlinear behaviors of the actuator and servo system of the optical disk drive will influence the laser spot positioning. Here, the model-free fuzzy control scheme is employed to design the track seeking servo controller for a d.c. motor driving optical disk drive system. In addition, the sliding model control strategy is introduced into the fuzzy control structure to construct a 1-D adaptive fuzzy rule intelligent controller for simplifying the implementation problem and improving the control performance. The experimental results show that the steady state error of the track seeking by using this fuzzy controller can maintain within the track width (1.6 μm ). It can be used in the track seeking and track following servo control operations.Keywords: Fuzzy control, gain tuning and optical disk drive.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15741467 Analysis of Periodic Solution of Delay Fuzzy BAM Neural Networks
Authors: Qianhong Zhang, Lihui Yang, Daixi Liao
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In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. These criteria are presented in terms of system parameters and have important leading significance in the design and applications of neural networks. Moreover an example is given to illustrate the effectiveness and feasible of results obtained.Keywords: Fuzzy BAM neural networks, Periodic solution, Global exponential stability, Time-varying delays
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15051466 Fuzzy Control of the Air Conditioning System at Different Operating Pressures
Authors: Mohanad Alata , Moh'd Al-Nimr, Rami Al-Jarrah
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The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.
Keywords: Air Conditioning, ANFIS, Fuzzy Control, Sugeno System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33551465 A Novel Fuzzy Logic Based Controller to Adjust the Brightness of the Television Screen with Respect to Surrounding Light
Authors: A. V. Sai Balasubramanian, N. Ravi Shankar, S. Subbaraman, R. Rengaraj
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One of the major cause of eye strain and other problems caused while watching television is the relative illumination between the screen and its surrounding. This can be overcome by adjusting the brightness of the screen with respect to the surrounding light. A controller based on fuzzy logic is proposed in this paper. The fuzzy controller takes in the intensity of light surrounding the screen and the present brightness of the screen as input. The output of the fuzzy controller is the grid voltage corresponding to the required brightness. This voltage is given to CRT and brightness is controller dynamically. For the given test system data, different de-fuzzifier methods have been implemented and the results are compared. In order to validate the effectiveness of the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time system. The simulations are performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time applications.Keywords: Fuzzy controller, Grid voltage
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27761464 Bio-Inspired Generalized Global Shape Approach for Writer Identification
Authors: Azah Kamilah Muda, Siti Mariyam Shamsuddin, Maslina Darus
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Writer identification is one of the areas in pattern recognition that attract many researchers to work in, particularly in forensic and biometric application, where the writing style can be used as biometric features for authenticating an identity. The challenging task in writer identification is the extraction of unique features, in which the individualistic of such handwriting styles can be adopted into bio-inspired generalized global shape for writer identification. In this paper, the feasibility of generalized global shape concept of complimentary binding in Artificial Immune System (AIS) for writer identification is explored. An experiment based on the proposed framework has been conducted to proof the validity and feasibility of the proposed approach for off-line writer identification.Keywords: Writer identification, generalized global shape, individualistic, pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12191463 Fuzzy Sliding Mode Speed Controller for a Vector Controlled Induction Motor
Authors: S. Massoum, A. Bentaallah, A. Massoum, F. Benaimeche, P. Wira, A. Meroufel
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This paper presents a speed fuzzy sliding mode controller for a vector controlled induction machine (IM) fed by a voltage source inverter (PWM). The sliding mode based fuzzy control method is developed to achieve fast response, a best disturbance rejection and to maintain a good decoupling. The problem with sliding mode control is that there is high frequency switching around the sliding mode surface. The FSMC is the combination of the robustness of Sliding Mode Control (SMC) and the smoothness of Fuzzy Logic (FL). To reduce the torque fluctuations (chattering), the sign function used in the conventional SMC is substituted with a fuzzy logic algorithm. The proposed algorithm was simulated by Matlab/Simulink software and simulation results show that the performance of the control scheme is robust and the chattering problem is solved.Keywords: IM, FOC, FLC, SMC, and FSMC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28001462 Fuzzy Boundary Layer Solution to Nonlinear Hydraulic Position Control Problem
Authors: Mustafa Resa Becan
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Sliding mode control with a fuzzy boundary layer is presented to hydraulic position control problem in this paper. A nonlinear hydraulic servomechanism which has an asymmetric cylinder is modeled and simulated first, then the proposed control scheme is applied to this model versus the conventional sliding mode control. Simulation results proved that the chattering free position control is achieved by tuning the fuzzy scaling factors properly.
Keywords: Hydraulic servomechanism, position control, sliding mode control, chattering, fuzzy boundary layer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18151461 The BGMRES Method for Generalized Sylvester Matrix Equation AXB − X = C and Preconditioning
Authors: Azita Tajaddini, Ramleh Shamsi
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In this paper, we present the block generalized minimal residual (BGMRES) method in order to solve the generalized Sylvester matrix equation. However, this method may not be converged in some problems. We construct a polynomial preconditioner based on BGMRES which shows why polynomial preconditioner is superior to some block solvers. Finally, numerical experiments report the effectiveness of this method.Keywords: Linear matrix equation, Block GMRES, matrix Krylov subspace, polynomial preconditioner.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8621460 Filteristic Soft Lattice Implication Algebras
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Applying the idea of soft set theory to lattice implication algebras, the novel concept of (implicative) filteristic soft lattice implication algebras which related to (implicative) filter(for short, (IF-)F-soft lattice implication algebras) are introduced. Basic properties of (IF-)F-soft lattice implication algebras are derived. Two kinds of fuzzy filters (i.e.(2, 2 _qk)((2, 2 _ qk))-fuzzy (implicative) filter) of L are introduced, which are generalizations of fuzzy (implicative) filters. Some characterizations for a soft set to be a (IF-)F-soft lattice implication algebra are provided. Analogously, this idea can be used in other types of filteristic lattice implication algebras (such as fantastic (positive implicative) filteristic soft lattice implication algebras).
Keywords: Soft set, (implicative) filteristic lattice implication algebras, fuzzy (implicative) filters, ((2, 2 _qk)) (2, 2 _ qk)-fuzzy(implicative) filters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16451459 Comparison between Optimized Passive Vehicle Suspension System and Semi Active Fuzzy Logic Controlled Suspension System Regarding Ride and Handling
Authors: Mehrdad N. Khajavi, Vahid Abdollahi
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The purpose of suspension system in automobiles is to improve the ride comfort and road handling. In this research the ride and handling performance of a specific automobile with passive suspension system is compared to a proposed fuzzy logic semi active suspension system designed for that automobile. The bodysuspension- wheel system is modeled as a two degree of freedom quarter car model. MATLAB/SIMULINK [1] was used for simulation and controller design. The fuzzy logic controller is based on two inputs namely suspension velocity and body velocity. The output of the fuzzy controller is the damping coefficient of the variable damper. The result shows improvement over passive suspension method.Keywords: Suspension System, Ride Comfort, Fuzzy Logic Controller, Passive and Semi Active System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35801458 Fuzzy Clustering Analysis in Real Estate Companies in China
Authors: Jianfeng Li, Feng Jin, Xiaoyu Yang
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This paper applies fuzzy clustering algorithm in classifying real estate companies in China according to some general financial indexes, such as income per share, share accumulation fund, net profit margins, weighted net assets yield and shareholders' equity. By constructing and normalizing initial partition matrix, getting fuzzy similar matrix with Minkowski metric and gaining the transitive closure, the dynamic fuzzy clustering analysis for real estate companies is shown clearly that different clustered result change gradually with the threshold reducing, and then, it-s shown there is the similar relationship with the prices of those companies in stock market. In this way, it-s great valuable in contrasting the real estate companies- financial condition in order to grasp some good chances of investment, and so on.
Keywords: Fuzzy clustering algorithm, data mining, real estate company, financial analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1902