Search results for: the theory of fuzzy sets.
2416 Fuzzy Logic Controlled Shunt Active Power Filter for Three-phase Four-wire Systems with Balanced and Unbalanced Loads
Authors: Ahmed A. Helal, Nahla E. Zakzouk, Yasser G. Desouky
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This paper presents a fuzzy logic controlled shunt active power filter used to compensate for harmonic distortion in three-phase four-wire systems. The shunt active filter employs a simple method for the calculation of the reference compensation current based of Fast Fourier Transform. This presented filter is able to operate in both balanced and unbalanced load conditions. A fuzzy logic based current controller strategy is used to regulate the filter current and hence ensure harmonic free supply current. The validity of the presented approach in harmonic mitigation is verified via simulation results of the proposed test system under different loading conditions.Keywords: Active power filters, Fuzzy logic controller, Power quality
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Authors: C. Senanayake, S. Veera Ragavan
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Warehousing is commonly used in factories for the storage of products until delivery of orders. As the amount of products stored increases it becomes tedious to be carried out manually. In recent years, the manual storing has converted into fully or partially computer controlled systems, also known as Automated Storage and Retrieval Systems (AS/RS). This paper discusses an ASRS system, which was designed such that the best storage location for the products is determined by utilizing a fuzzy control system. The design maintains the records of the products to be/already in store and the storage/retrieval times along with the availability status of the storage locations. This paper discusses on the maintenance of the above mentioned records and the utilization of the concept of fuzzy logic in order to determine the optimum storage location for the products. The paper will further discuss on the dynamic splitting and merging of the storage locations depending on the product sizes.Keywords: ASRS, fuzzy control systems, MySQL database, dynamic splitting and merging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21422414 Software Effort Estimation Using Soft Computing Techniques
Authors: Parvinder S. Sandhu, Porush Bassi, Amanpreet Singh Brar
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Various models have been derived by studying large number of completed software projects from various organizations and applications to explore how project sizes mapped into project effort. But, still there is a need to prediction accuracy of the models. As Neuro-fuzzy based system is able to approximate the non-linear function with more precision. So, Neuro-Fuzzy system is used as a soft computing approach to generate model by formulating the relationship based on its training. In this paper, Neuro-Fuzzy technique is used for software estimation modeling of on NASA software project data and performance of the developed models are compared with the Halstead, Walston-Felix, Bailey-Basili and Doty Models mentioned in the literature.
Keywords: Effort Estimation, Neural-Fuzzy Model, Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20752413 Retrieving Similar Segmented Objects Using Motion Descriptors
Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou
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The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.
Keywords: Fuzzy Object, Fuzzy Image Segmentation, Motion Descriptors, MRI Imaging, Object-Based Image Retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23022412 Segmentation of Cardiac Images by the Force Field Driven Speed Term
Authors: Renato Dedic, Madjid Allili, Roger Lecomte, Adbelhamid Benchakroun
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The class of geometric deformable models, so-called level sets, has brought tremendous impact to medical imagery. In this paper we present yet another application of level sets to medical imaging. The method we give here will in a way modify the speed term in the standard level sets equation of motion. To do so we build a potential based on the distance and the gradient of the image we study. In turn the potential gives rise to the force field: F~F(x, y) = P ∀(p,q)∈I ((x, y) - (p, q)) |ÔêçI(p,q)| |(x,y)-(p,q)| 2 . The direction and intensity of the force field at each point will determine the direction of the contour-s evolution. The images we used to test our method were produced by the Univesit'e de Sherbrooke-s PET scanners.Keywords: PET, Cardiac, Heart, Mouse, Geodesic, Geometric, Level Sets, Deformable Models, Edge Detection, Segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12112411 A Two-Stage Expert System for Diagnosis of Leukemia Based on Type-2 Fuzzy Logic
Authors: Ali Akbar Sadat Asl
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Diagnosis and deciding about diseases in medical fields is facing innate uncertainty which can affect the whole process of treatment. This decision is made based on expert knowledge and the way in which an expert interprets the patient's condition, and the interpretation of the various experts from the patient's condition may be different. Fuzzy logic can provide mathematical modeling for many concepts, variables, and systems that are unclear and ambiguous and also it can provide a framework for reasoning, inference, control, and decision making in conditions of uncertainty. In systems with high uncertainty and high complexity, fuzzy logic is a suitable method for modeling. In this paper, we use type-2 fuzzy logic for uncertainty modeling that is in diagnosis of leukemia. The proposed system uses an indirect-direct approach and consists of two stages: In the first stage, the inference of blood test state is determined. In this step, we use an indirect approach where the rules are extracted automatically by implementing a clustering approach. In the second stage, signs of leukemia, duration of disease until its progress and the output of the first stage are combined and the final diagnosis of the system is obtained. In this stage, the system uses a direct approach and final diagnosis is determined by the expert. The obtained results show that the type-2 fuzzy expert system can diagnose leukemia with the average accuracy about 97%.
Keywords: Expert system, leukemia, medical diagnosis, type-2 fuzzy logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10532410 Sociological Impact on Education An Analytical Approach Through Artificial Neural network
Authors: P. R. Jayathilaka, K.L. Jayaratne, H.L. Premaratne
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This research presented in this paper is an on-going project of an application of neural network and fuzzy models to evaluate the sociological factors which affect the educational performance of the students in Sri Lanka. One of its major goals is to prepare the grounds to device a counseling tool which helps these students for a better performance at their examinations, especially at their G.C.E O/L (General Certificate of Education-Ordinary Level) examination. Closely related sociological factors are collected as raw data and the noise of these data are filtered through the fuzzy interface and the supervised neural network is being utilized to recognize the performance patterns against the chosen social factors.Keywords: Education, Fuzzy, neural network, prediction, Sociology
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16392409 Model Order Reduction of Discrete-Time Systems Using Fuzzy C-Means Clustering
Authors: Anirudha Narain, Dinesh Chandra, Ravindra K. S.
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A computationally simple approach of model order reduction for single input single output (SISO) and linear timeinvariant discrete systems modeled in frequency domain is proposed in this paper. Denominator of the reduced order model is determined using fuzzy C-means clustering while the numerator parameters are found by matching time moments and Markov parameters of high order system.
Keywords: Model Order reduction, Discrete-time system, Fuzzy C-Means Clustering, Padé approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28132408 Low Cost Chip Set Selection Algorithm for Multi-way Partitioning of Digital System
Authors: Jae Young Park, Soongyu Kwon, Kyu Han Kim, Hyeong Geon Lee, Jong Tae Kim
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This paper considers the problem of finding low cost chip set for a minimum cost partitioning of a large logic circuits. Chip sets are selected from a given library. Each chip in the library has a different price, area, and I/O pin. We propose a low cost chip set selection algorithm. Inputs to the algorithm are a netlist and a chip information in the library. Output is a list of chip sets satisfied with area and maximum partitioning number and it is sorted by cost. The algorithm finds the sorted list of chip sets from minimum cost to maximum cost. We used MCNC benchmark circuits for experiments. The experimental results show that all of chip sets found satisfy the multiple partitioning constraints.Keywords: lowest cost chip set, MCNC benchmark, multi-way partitioning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15032407 Stabilization of the Lorenz Chaotic Equations by Fuzzy Controller
Authors: Behrooz Rezaie, Zahra Rahmani Cherati, Mohammad Reza Jahed Motlagh, Mohammad Farrokhi
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In this paper, a fuzzy controller is designed for stabilization of the Lorenz chaotic equations. A simple Mamdani inference method is used for this purpose. This method is very simple and applicable for complex chaotic systems and it can be implemented easily. The stability of close loop system is investigated by the Lyapunov stabilization criterion. A Lyapunov function is introduced and the global stability is proven. Finally, the effectiveness of this method is illustrated by simulation results and it is shown that the performance of the system is improved.Keywords: Chaotic system, Fuzzy control, Lorenz equation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20292406 The Countabilities of Soft Topological Spaces
Authors: Weijian Rong
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Soft topological spaces are considered as mathematical tools for dealing with uncertainties, and a fuzzy topological space is a special case of the soft topological space. The purpose of this paper is to study soft topological spaces. We introduce some new concepts in soft topological spaces such as soft first-countable spaces, soft second-countable spaces and soft separable spaces, and some basic properties of these concepts are explored.
Keywords: soft sets, soft first-countable spaces, soft second countable spaces, soft separable spaces, soft Lindelöf.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24152405 A Novel Fuzzy-Neural Based Medical Diagnosis System
Authors: S. Moein, S. A. Monadjemi, P. Moallem
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In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and applied to a MLP neural network. The results of the experiments and also the advantages of using a fuzzy approach were discussed as well. Outcomes suggest the role of effective symptoms selection and the advantages of data fuzzificaton on a neural networks-based automatic medical diagnosis system.Keywords: Artificial Neural Networks, Fuzzy Logic, MedicalDiagnosis, Symptoms, Fuzzification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22602404 Approach Based on Fuzzy C-Means for Band Selection in Hyperspectral Images
Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge
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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.
Keywords: Band selection, fuzzy C-means, K-means, hyperspectral image.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18152403 Optimal Data Compression and Filtering: The Case of Infinite Signal Sets
Authors: Anatoli Torokhti, Phil Howlett
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We present a theory for optimal filtering of infinite sets of random signals. There are several new distinctive features of the proposed approach. First, we provide a single optimal filter for processing any signal from a given infinite signal set. Second, the filter is presented in the special form of a sum with p terms where each term is represented as a combination of three operations. Each operation is a special stage of the filtering aimed at facilitating the associated numerical work. Third, an iterative scheme is implemented into the filter structure to provide an improvement in the filter performance at each step of the scheme. The final step of the concerns signal compression and decompression. This step is based on the solution of a new rank-constrained matrix approximation problem. The solution to the matrix problem is described in this paper. A rigorous error analysis is given for the new filter.
Keywords: stochastic signals, optimization problems in signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12802402 Generic Filtering of Infinite Sets of Stochastic Signals
Authors: Anatoli Torokhti, Phil Howlett
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A theory for optimal filtering of infinite sets of random signals is presented. There are several new distinctive features of the proposed approach. First, a single optimal filter for processing any signal from a given infinite signal set is provided. Second, the filter is presented in the special form of a sum with p terms where each term is represented as a combination of three operations. Each operation is a special stage of the filtering aimed at facilitating the associated numerical work. Third, an iterative scheme is implemented into the filter structure to provide an improvement in the filter performance at each step of the scheme. The final step of the scheme concerns signal compression and decompression. This step is based on the solution of a new rank-constrained matrix approximation problem. The solution to the matrix problem is described in this paper. A rigorous error analysis is given for the new filter.Keywords: Optimal filtering, data compression, stochastic signals.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13212401 Performance Analysis of Brain Tumor Detection Based On Image Fusion
Authors: S. Anbumozhi, P. S. Manoharan
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Medical Image fusion plays a vital role in medical field to diagnose the brain tumors which can be classified as benign or malignant. It is the process of integrating multiple images of the same scene into a single fused image to reduce uncertainty and minimizing redundancy while extracting all the useful information from the source images. Fuzzy logic is used to fuse two brain MRI images with different vision. The fused image will be more informative than the source images. The texture and wavelet features are extracted from the fused image. The multilevel Adaptive Neuro Fuzzy Classifier classifies the brain tumors based on trained and tested features. The proposed method achieved 80.48% sensitivity, 99.9% specificity and 99.69% accuracy. Experimental results obtained from fusion process prove that the use of the proposed image fusion approach shows better performance while compared with conventional fusion methodologies.
Keywords: Image fusion, Fuzzy rules, Neuro-fuzzy classifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30582400 Evaluation of Electronic Payment Systems Using Fuzzy Multi-Criteria Decision Making Approach
Authors: Gülfem Alptekin, S. Emre Alptekin
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Global competitiveness has recently become the biggest concern of both manufacturing and service companies. Electronic commerce, as a key technology enables the firms to reach all the potential consumers from all over the world. In this study, we have presented commonly used electronic payment systems, and then we have shown the evaluation of these systems in respect to different criteria. The payment systems which are included in this research are the credit card, the virtual credit card, the electronic money, the mobile payment, the credit transfer and the debit instruments. We have realized a systematic comparison of these systems in respect to three main criteria: Technical, economical and social. We have conducted a fuzzy multi-criteria decision making procedure to deal with the multi-attribute nature of the problem. The subjectiveness and imprecision of the evaluation process are modeled using triangular fuzzy numbers.Keywords: Electronic payment systems, fuzzy multi-criteriadecision making, analytical hierarchy process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19312399 Performance Analysis of Deterministic Stable Election Protocol Using Fuzzy Logic in Wireless Sensor Network
Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar
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In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.
Keywords: Deterministic stable election protocol, energy model, fuzzy logic, wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9772398 Design of Robust Fuzzy Logic Power System Stabilizer
Authors: S. A. Taher, A. Shemshadi
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Power system stabilizers (PSS) must be capable of providing appropriate stabilization signals over a broad range of operating conditions and disturbance. Traditional PSS rely on robust linear design method in an attempt to cover a wider range of operating condition. Expert or rule-based controllers have also been proposed. Recently fuzzy logic (FL) as a novel robust control design method has shown promising results. The emphasis in fuzzy control design center is around uncertainties in the system parameters & operating conditions. In this paper a novel Robust Fuzzy Logic Power System Stabilizer (RFLPSS) design is proposed The RFLPSS basically utilizes only one measurable Δω signal as input (generator shaft speed). The speed signal is discretized resulting in three inputs to the RFLPSS. There are six rules for the fuzzification and two rules for defuzzification. To provide robustness, additional signal namely, speed are used as inputs to RFLPSS enabling appropriate gain adjustments for the three RFLPSS inputs. Simulation studies show the superior performance of the RFLPSS compared with an optimally designed conventional PSS and discrete mode FLPSS.Keywords: Controller design, Fuzzy Logic, PID, Power SystemStabilizer, Robust control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21362397 Adaptive Fuzzy Routing in Opportunistic Network (AFRON)
Authors: Payam Nabhani, Sima Radmanesh
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Opportunistic network is a kind of Delay Tolerant Networks (DTN) where the nodes in this network come into contact with each other opportunistically and communicate wirelessly and, an end-to-end path between source and destination may have never existed, and disconnection and reconnection is common in the network. In such a network, because of the nature of opportunistic network, perhaps there is no a complete path from source to destination for most of the time and even if there is a path; the path can be very unstable and may change or break quickly. Therefore, routing is one of the main challenges in this environment and, in order to make communication possible in an opportunistic network, the intermediate nodes have to play important role in the opportunistic routing protocols. In this paper we proposed an Adaptive Fuzzy Routing in opportunistic network (AFRON). This protocol is using the simple parameters as input parameters to find the path to the destination node. Using Message Transmission Count, Message Size and Time To Live parameters as input fuzzy to increase delivery ratio and decrease the buffer consumption in the all nodes of network.
Keywords: Opportunistic Routing, Fuzzy Routing, Opportunistic Network, Message Routing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15372396 The Imaging Methods for Classifying Crispiness of Freeze-Dried Durian using Fuzzy Logic
Authors: Sitthichon Kanitthakun, Pinit Kumhom, Kosin Chamnongthai
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In quality control of freeze-dried durian, crispiness is a key quality index of the product. Generally, crispy testing has to be done by a destructive method. A nondestructive testing of the crispiness is required because the samples can be reused for other kinds of testing. This paper proposed a crispiness classification method of freeze-dried durians using fuzzy logic for decision making. The physical changes of a freeze-dried durian include the pores appearing in the images. Three physical features including (1) the diameters of pores, (2) the ratio of the pore area and the remaining area, and (3) the distribution of the pores are considered to contribute to the crispiness. The fuzzy logic is applied for making the decision. The experimental results comparing with food expert opinion showed that the accuracy of the proposed classification method is 83.33 percent.Keywords: Durian, crispiness, freeze drying, pore, fuzzy logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19702395 A Review of Existing Turnover Intention Theories
Authors: Pauline E. Ngo-Henha
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Existing turnover intention theories are reviewed in this paper. This review was conducted with the help of the search keyword “turnover intention theories” in Google Scholar during the month of July 2017. These theories include: The Theory of Organizational Equilibrium (TOE), Social Exchange Theory, Job Embeddedness Theory, Herzberg’s Two-Factor Theory, the Resource-Based View, Equity Theory, Human Capital Theory, and the Expectancy Theory. One of the limitations of this review paper is that data were only collected from Google Scholar where many papers were sometimes not freely accessible. However, this paper attempts to contribute to the research in clarifying the distinction between theories and models in the context of turnover intention.
Keywords: Job embeddedness theory, theory of organizational equilibrium (TOE), Herzberg’s two-factor theory, turnover intention theories, theories and models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 227792394 Detection of Black Holes in MANET Using Collaborative Watchdog with Fuzzy Logic
Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji
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Mobile ad hoc network (MANET) is a self-configuring network of mobile node connected without wires. A Fuzzy Logic Based Collaborative watchdog approach is used to reduce the detection time of misbehaved nodes and increase the overall truthfulness. This methodology will increase the secure efficient routing by detecting the Black Holes attacks. The simulation results proved that this method improved the energy, reduced the delay and also improved the overall performance of the detecting black hole attacks in MANET.
Keywords: MANET, collaborative watchdog, fuzzy logic, AODV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13512393 A New Class F2 (M, 0, N)L„ p)F of The Double Difference Sequences of Fuzzy Numbers
Authors: N. Subramanian, C. Murugesan
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The double difference sequence space I2 (M, of fuzzy numbers for both 1 < p < oo and 0 < p < 1, is introduced. Some general properties of this sequence space are studied. Some inclusion relations involving this sequence space are obtained.
Keywords: Orlicz function, solid space, metric space, completeness
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10142392 Multimodal Biometric Authentication Using Choquet Integral and Genetic Algorithm
Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara
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The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.
Keywords: Multimodal biometrics, data fusion, Choquet integral, fuzzy measures, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25162391 Comparative Study of Intuitionistic and Generalized Neutrosophic Soft Sets
Authors: Debabrata Mandal
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The aim of this paper is to define several operations such as Intersection, Union, OR, AND operations of intuitionistic (resp. generalized) neutrosophic soft sets in the sense of Maji and compare these with intuitionistic (resp. generalized) neutrosophic soft sets in the sense of Said et al via examples. At the end of the paper, a new concept - extension is introduced, which can be used to refine our choices in case of decision making.
Keywords: AND, OR, Union, Intersection, Extension, Decision making.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16972390 An Efficient Technique for Extracting Fuzzy Rulesfrom Neural Networks
Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu
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Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.
Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15812389 Medical Image Edge Detection Based on Neuro-Fuzzy Approach
Authors: J. Mehena, M. C. Adhikary
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Edge detection is one of the most important tasks in image processing. Medical image edge detection plays an important role in segmentation and object recognition of the human organs. It refers to the process of identifying and locating sharp discontinuities in medical images. In this paper, a neuro-fuzzy based approach is introduced to detect the edges for noisy medical images. This approach uses desired number of neuro-fuzzy subdetectors with a postprocessor for detecting the edges of medical images. The internal parameters of the approach are optimized by training pattern using artificial images. The performance of the approach is evaluated on different medical images and compared with popular edge detection algorithm. From the experimental results, it is clear that this approach has better performance than those of other competing edge detection algorithms for noisy medical images.Keywords: Edge detection, neuro-fuzzy, image segmentation, artificial image, object recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12822388 Edge Detection in Digital Images Using Fuzzy Logic Technique
Authors: Abdallah A. Alshennawy, Ayman A. Aly
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The fuzzy technique is an operator introduced in order to simulate at a mathematical level the compensatory behavior in process of decision making or subjective evaluation. The following paper introduces such operators on hand of computer vision application. In this paper a novel method based on fuzzy logic reasoning strategy is proposed for edge detection in digital images without determining the threshold value. The proposed approach begins by segmenting the images into regions using floating 3x3 binary matrix. The edge pixels are mapped to a range of values distinct from each other. The robustness of the proposed method results for different captured images are compared to those obtained with the linear Sobel operator. It is gave a permanent effect in the lines smoothness and straightness for the straight lines and good roundness for the curved lines. In the same time the corners get sharper and can be defined easily.Keywords: Fuzzy logic, Edge detection, Image processing, computer vision, Mechanical parts, Measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47682387 Granulation using Clustering and Rough Set Theory and its Tree Representation
Authors: Girish Kumar Singh, Sonajharia Minz
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Granular computing deals with representation of information in the form of some aggregates and related methods for transformation and analysis for problem solving. A granulation scheme based on clustering and Rough Set Theory is presented with focus on structured conceptualization of information has been presented in this paper. Experiments for the proposed method on four labeled data exhibit good result with reference to classification problem. The proposed granulation technique is semi-supervised imbibing global as well as local information granulation. To represent the results of the attribute oriented granulation a tree structure is proposed in this paper.Keywords: Granular computing, clustering, Rough sets, datamining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1719