Search results for: robust fuzzy clustering
1039 Development of a Project Selection Method on Information System Using ANP and Fuzzy Logic
Authors: Ingu Kim, Shangmun Shin, Yongsun Choi, Nguyen Manh Thang, Edwin R. Ramos, Won-Joo Hwang
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Project selection problems on management information system (MIS) are often considered a multi-criteria decision-making (MCDM) for a solving method. These problems contain two aspects, such as interdependencies among criteria and candidate projects and qualitative and quantitative factors of projects. However, most existing methods reported in literature consider these aspects separately even though these two aspects are simultaneously incorporated. For this reason, we proposed a hybrid method using analytic network process (ANP) and fuzzy logic in order to represent both aspects. We then propose a goal programming model to conduct an optimization for the project selection problems interpreted by a hybrid concept. Finally, a numerical example is conducted as verification purposes.Keywords: Analytic Network Process (ANP), Multi-Criteria Decision-Making (MCDM), Fuzzy Logic, Information System Project Selection, Goal Programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20881038 Application of Fuzzy Logic Approach for an Aircraft Model with and without Winglet
Authors: Altab Hossain, Ataur Rahman, Jakir Hossen, A.K.M. P. Iqbal, SK. Hasan
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The measurement of aerodynamic forces and moments acting on an aircraft model is important for the development of wind tunnel measurement technology to predict the performance of the full scale vehicle. The potentials of an aircraft model with and without winglet and aerodynamic characteristics with NACA wing No. 65-3- 218 have been studied using subsonic wind tunnel of 1 m × 1 m rectangular test section and 2.5 m long of Aerodynamics Laboratory Faculty of Engineering (University Putra Malaysia). Focusing on analyzing the aerodynamic characteristics of the aircraft model, two main issues are studied in this paper. First, a six component wind tunnel external balance is used for measuring lift, drag and pitching moment. Secondly, Tests are conducted on the aircraft model with and without winglet of two configurations at Reynolds numbers 1.7×105, 2.1×105, and 2.5×105 for different angle of attacks. Fuzzy logic approach is found as efficient for the representation, manipulation and utilization of aerodynamic characteristics. Therefore, the primary purpose of this work was to investigate the relationship between lift and drag coefficients, with free-stream velocities and angle of attacks, and to illustrate how fuzzy logic might play an important role in study of lift aerodynamic characteristics of an aircraft model with the addition of certain winglet configurations. Results of the developed fuzzy logic were compared with the experimental results. For lift coefficient analysis, the mean of actual and predicted values were 0.62 and 0.60 respectively. The coreelation between actual and predicted values (from FLS model) of lift coefficient in different angle of attack was found as 0.99. The mean relative error of actual and predicted valus was found as 5.18% for the velocity of 26.36 m/s which was found to be less than the acceptable limits (10%). The goodness of fit of prediction value was 0.95 which was close to 1.0.Keywords: Wind tunnel; Winglet; Lift coefficient; Fuzzy logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19031037 Sway Reduction on Gantry Crane System using Delayed Feedback Signal and PD-type Fuzzy Logic Controller: A Comparative Assessment
Authors: M.A. Ahmad
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This paper presents the use of anti-sway angle control approaches for a two-dimensional gantry crane with disturbances effect in the dynamic system. Delayed feedback signal (DFS) and proportional-derivative (PD)-type fuzzy logic controller are the techniques used in this investigation to actively control the sway angle of the rope of gantry crane system. A nonlinear overhead gantry crane system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. A complete analysis of simulation results for each technique is presented in time domain and frequency domain respectively. Performances of both controllers are examined in terms of sway angle suppression and disturbances cancellation. Finally, a comparative assessment of the impact of each controller on the system performance is presented and discussed.Keywords: Gantry crane, anti-sway control, DFS controller, PD-type Fuzzy Logic Controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21501036 A Fuzzy-Rough Feature Selection Based on Binary Shuffled Frog Leaping Algorithm
Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn
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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.Keywords: Binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7301035 A New Approach for Network Reconfiguration Problem in Order to Deviation Bus Voltage Minimization with Regard to Probabilistic Load Model and DGs
Authors: Mahmood Reza Shakarami, Reza Sedaghati
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Recently, distributed generation technologies have received much attention for the potential energy savings and reliability assurances that might be achieved as a result of their widespread adoption. The distribution feeder reconfiguration (DFR) is one of the most important control schemes in the distribution networks, which can be affected by DGs. This paper presents a new approach to DFR at the distribution networks considering wind turbines. The main objective of the DFR is to minimize the deviation of the bus voltage. Since the DFR is a nonlinear optimization problem, we apply the Adaptive Modified Firefly Optimization (AMFO) approach to solve it. As a result of the conflicting behavior of the single- objective function, a fuzzy based clustering technique is employed to reach the set of optimal solutions called Pareto solutions. The approach is tested on the IEEE 32-bus standard test system.
Keywords: Adaptive Modified Firefly Optimization (AMFO), Pareto solutions, feeder reconfiguration, wind turbines, bus voltage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20161034 Generating Normally Distributed Clusters by Means of a Self-organizing Growing Neural Network– An Application to Market Segmentation –
Authors: Reinhold Decker, Christian Holsing, Sascha Lerke
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This paper presents a new growing neural network for cluster analysis and market segmentation, which optimizes the size and structure of clusters by iteratively checking them for multivariate normality. We combine the recently published SGNN approach [8] with the basic principle underlying the Gaussian-means algorithm [13] and the Mardia test for multivariate normality [18, 19]. The new approach distinguishes from existing ones by its holistic design and its great autonomy regarding the clustering process as a whole. Its performance is demonstrated by means of synthetic 2D data and by real lifestyle survey data usable for market segmentation.Keywords: Artificial neural network, clustering, multivariatenormality, market segmentation, self-organization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11981033 Contourlet versus Wavelet Transform for a Robust Digital Image Watermarking Technique
Authors: Ibrahim A. El rube, Mohamad Abou El Nasr , Mostafa M. Naim, Mahmoud Farouk
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In this paper, a watermarking algorithm that uses the wavelet transform with Multiple Description Coding (MDC) and Quantization Index Modulation (QIM) concepts is introduced. Also, the paper investigates the role of Contourlet Transform (CT) versus Wavelet Transform (WT) in providing robust image watermarking. Two measures are utilized in the comparison between the waveletbased and the contourlet-based methods; Peak Signal to Noise Ratio (PSNR) and Normalized Cross-Correlation (NCC). Experimental results reveal that the introduced algorithm is robust against different attacks and has good results compared to the contourlet-based algorithm.
Keywords: image watermarking; discrete wavelet transform, discrete contourlet transform, multiple description coding, quantization index modulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20661032 Application of Neuro-Fuzzy Dynamic Programming to Improve the Reactive Power and Voltage Profile of a Distribution Substation
Authors: M. Tarafdar Haque, S. Najafi
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Improving the reactive power and voltage profile of a distribution substation is investigated in this paper. The purpose is to properly determination of the shunt capacitors on/off status and suitable tap changer (TC) position of a substation transformer. In addition, the limitation of secondary bus voltage, the maximum allowable number of switching operation in a day for on load tap changer and on/off status of capacitors are taken into account. To achieve these goals, an artificial neural network (ANN) is designed to provide preliminary scheduling. Input of ANN is active and reactive powers of transformer and its primary and secondary bus voltages. The output of ANN is capacitors on/off status and TC position. The preliminary schedule is further refined by fuzzy dynamic programming in order to reach the final schedule. The operation of proposed method in Q/V improving is compared with the results obtained by operator operation in a distribution substation.Keywords: Neuro-fuzzy, Dynamic programming, Reactive power, Voltage profile.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16271031 Development of Predictive Model for Surface Roughness in End Milling of Al-SiCp Metal Matrix Composites using Fuzzy Logic
Authors: M. Chandrasekaran, D. Devarasiddappa
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Metal matrix composites have been increasingly used as materials for components in automotive and aerospace industries because of their improved properties compared with non-reinforced alloys. During machining the selection of appropriate machining parameters to produce job for desired surface roughness is of great concern considering the economy of manufacturing process. In this study, a surface roughness prediction model using fuzzy logic is developed for end milling of Al-SiCp metal matrix composite component using carbide end mill cutter. The surface roughness is modeled as a function of spindle speed (N), feed rate (f), depth of cut (d) and the SiCp percentage (S). The predicted values surface roughness is compared with experimental result. The model predicts average percentage error as 4.56% and mean square error as 0.0729. It is observed that surface roughness is most influenced by feed rate, spindle speed and SiC percentage. Depth of cut has least influence.Keywords: End milling, fuzzy logic, metal matrix composites, surface roughness
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21691030 A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm
Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim
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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.
Keywords: Currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8631029 Anomaly Detection and Characterization to Classify Traffic Anomalies Case Study: TOT Public Company Limited Network
Authors: O. Siriporn, S. Benjawan
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This paper represents four unsupervised clustering algorithms namely sIB, RandomFlatClustering, FarthestFirst, and FilteredClusterer that previously works have not been used for network traffic classification. The methodology, the result, the products of the cluster and evaluation of these algorithms with efficiency of each algorithm from accuracy are shown. Otherwise, the efficiency of these algorithms considering form the time that it use to generate the cluster quickly and correctly. Our work study and test the best algorithm by using classify traffic anomaly in network traffic with different attribute that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and compare it to the previously used (K-Means). Our research will be use to develop anomaly detection system to more efficiency and more require in the future.
Keywords: Unsupervised, clustering, anomaly, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21111028 Robust Parameter and Scale Factor Estimation in Nonstationary and Impulsive Noise Environment
Authors: Zoran D. Banjac, Branko D. Kovacevic
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The problem of FIR system parameter estimation has been considered in the paper. A new robust recursive algorithm for simultaneously estimation of parameters and scale factor of prediction residuals in non-stationary environment corrupted by impulsive noise has been proposed. The performance of derived algorithm has been tested by simulations.
Keywords: Adaptive filtering, Non-Gaussian filtering, Robustestimation, Scale factor estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17051027 A New Framework for Evaluation and Prioritization of Suppliers using a Hierarchical Fuzzy TOPSIS
Authors: Mohammad Taghi Taghavifard, Danial Mirheydari
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This paper suggests an algorithm for the evaluation and selection of suppliers. At the beginning, all the needed materials and services used by the organization were identified and categorized with regard to their nature by ABC method. Afterwards, in order to reduce risk factors and maximize the organization's profit, purchase strategies were determined. Then, appropriate criteria were identified for primary evaluation of suppliers applying to the organization. The output of this stage was a list of suppliers qualified by the organization to participate in its tenders. Subsequently, considering a material in particular, appropriate criteria on the ordering of the mentioned material were determined, taking into account the particular materials' specifications as well as the organization's needs. Finally, for the purpose of validation and verification of the proposed model, it was applied to Mobarakeh Steel Company (MSC), the qualified suppliers of this Company are ranked by the means of a Hierarchical Fuzzy TOPSIS method. The obtained results show that the proposed algorithm is quite effective, efficient and easy to apply.Keywords: ABC analysis, Hierarchical Fuzzy TOPSIS, Primary supplier evaluation, Purchasing strategy, supplier selection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14031026 Design of Nonlinear Robust Control in a Class of Structurally Stable Functions
Authors: V. Ten
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An approach of design of stable of control systems with ultimately wide ranges of uncertainly disturbed parameters is offered. The method relies on using of nonlinear structurally stable functions from catastrophe theory as controllers. Theoretical part presents an analysis of designed nonlinear second-order control systems. As more important the integrators in series, canonical controllable form and Jordan forms are considered. The analysis resumes that due to added controllers systems become stable and insensitive to any disturbance of parameters. Experimental part presents MATLAB simulation of design of control systems of epidemic spread, aircrafts angular motion and submarine depth. The results of simulation confirm the efficiency of offered method of design. KeywordsCatastrophes, robust control, simulation, uncertain parameters.
Keywords: Catastrophes, robust control, simulation, uncertain parameters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12911025 Unit Root Tests Based On the Robust Estimator
Authors: Wararit Panichkitkosolkul
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The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.
Keywords: Autoregressive, Ordinary least squares, Type I error, Power of the test, Monte Carlo simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17871024 Performance Evaluation of Clustered Routing Protocols for Heterogeneous Wireless Sensor Networks
Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith
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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.Keywords: Clustering, heterogeneous, stability, scalability, throughput, IoT, WSN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4191023 Monte Carlo Analysis and Fuzzy Sets for Uncertainty Propagation in SIS Performance Assessment
Authors: Fares Innal, Yves Dutuit, Mourad Chebila
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The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.
Keywords: Fuzzy sets, Monte Carlo simulation, Safety instrumented system, Safety integrity level.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27781022 Vibration Control of a Cantilever Beam Using a Tunable Vibration Absorber Embedded with ER Fluids
Authors: Chih-Jer Lin, Chun-Ying Lee, Chiang-Ho Cheng, Geng-Fung Chen
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This paper investigates experimental studies on vibration suppression for a cantilever beam using an Electro-Rheological (ER) sandwich shock absorber. ER fluid (ERF) is a class of smart materials that can undergo significant reversible changes immediately in its rheological and mechanical properties under the influence of an applied electric field. Firstly, an ER sandwich beam is fabricated by inserting a starch-based ERF into a hollow composite beam. At the same time, experimental investigations are focused on the frequency response of the ERF sandwich beam. Second, the ERF sandwich beam is attached to a cantilever beam to become as a shock absorber. Finally, a fuzzy semi-active vibration control is designed to suppress the vibration of the cantilever beam via the ERF sandwich shock absorber. To check the consistency of the proposed fuzzy controller, the real-time implementation validated the performance of the controller.
Keywords: Electro-Rheological Fluid, Semi-active vibration control, shock absorber, fuzzy control, Real-time control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32271021 Combining Fuzzy Logic and Data Miningto Predict the Result of an EIA Review
Authors: Kevin Fong-Rey Liu, Jia-Shen Chen, Han-Hsi Liang, Cheng-Wu Chen, Yung-Shuen Shen
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The purpose of determining impact significance is to place value on impacts. Environmental impact assessment review is a process that judges whether impact significance is acceptable or not in accordance with the scientific facts regarding environmental, ecological and socio-economical impacts described in environmental impact statements (EIS) or environmental impact assessment reports (EIAR). The first aim of this paper is to summarize the criteria of significance evaluation from the past review results and accordingly utilize fuzzy logic to incorporate these criteria into scientific facts. The second aim is to employ data mining technique to construct an EIS or EIAR prediction model for reviewing results which can assist developers to prepare and revise better environmental management plans in advance. The validity of the previous prediction model proposed by authors in 2009 is 92.7%. The enhanced validity in this study can attain 100.0%.Keywords: Environmental impact assessment review, impactsignificance, fuzzy logic, data mining, classification tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19431020 Heavy Metals Estimation in Coastal Areas Using Remote Sensing, Field Sampling and Classical and Robust Statistic
Authors: Elena Castillo-López, Raúl Pereda, Julio Manuel de Luis, Rubén Pérez, Felipe Piña
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Sediments are an important source of accumulation of toxic contaminants within the aquatic environment. Bioassays are a powerful tool for the study of sediments in relation to their toxicity, but they can be expensive. This article presents a methodology to estimate the main physical property of intertidal sediments in coastal zones: heavy metals concentration. This study, which was developed in the Bay of Santander (Spain), applies classical and robust statistic to CASI-2 hyperspectral images to estimate heavy metals presence and ecotoxicity (TOC). Simultaneous fieldwork (radiometric and chemical sampling) allowed an appropriate atmospheric correction to CASI-2 images.
Keywords: Remote sensing, intertidal sediment, airborne sensors, heavy metals, ecotoxicity, robust statistic, estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12521019 Fuzzy Group Decision Making for the Assessment of Health-Care Waste Disposal Alternatives in Istanbul
Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi
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Disposal of health-care waste (HCW) is considered as an important environmental problem especially in large cities. Multiple criteria decision making (MCDM) techniques are apt to deal with quantitative and qualitative considerations of the health-care waste management (HCWM) problems. This research proposes a fuzzy multi-criteria group decision making approach with a multilevel hierarchical structure including qualitative as well as quantitative performance attributes for evaluating HCW disposal alternatives for Istanbul. Using the entropy weighting method, objective weights as well as subjective weights are taken into account to determine the importance weighting of quantitative performance attributes. The results obtained using the proposed methodology are thoroughly analyzed.Keywords: Entropy weighting method, group decision making, health-care waste management, hierarchical fuzzy multi-criteriadecision making
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16861018 A Cascaded Fuzzy Inference System for Dynamic Online Portals Customization
Authors: Erika Martinez Ramirez, Rene V. Mayorga
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In our modern world, more physical transactions are being substituted by electronic transactions (i.e. banking, shopping, and payments), many businesses and companies are performing most of their operations through the internet. Instead of having a physical commerce, internet visitors are now adapting to electronic commerce (e-Commerce). The ability of web users to reach products worldwide can be greatly benefited by creating friendly and personalized online business portals. Internet visitors will return to a particular website when they can find the information they need or want easily. Dealing with this human conceptualization brings the incorporation of Artificial/Computational Intelligence techniques in the creation of customized portals. From these techniques, Fuzzy-Set technologies can make many useful contributions to the development of such a human-centered endeavor as e-Commerce. The main objective of this paper is the implementation of a Paradigm for the Intelligent Design and Operation of Human-Computer interfaces. In particular, the paradigm is quite appropriate for the intelligent design and operation of software modules that display information (such Web Pages, graphic user interfaces GUIs, Multimedia modules) on a computer screen. The human conceptualization of the user personal information is analyzed throughout a Cascaded Fuzzy Inference (decision-making) System to generate the User Ascribe Qualities, which identify the user and that can be used to customize portals with proper Web links.
Keywords: Fuzzy Logic, Internet, Electronic Commerce, Intelligent Portals, Electronic Shopping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17861017 Type–2 Fuzzy Programming for Optimizing the Heat Rate of an Industrial Gas Turbine via Absorption Chiller Technology
Authors: T. Ganesan, M. S. Aris, I. Elamvazuthi, Momen Kamal Tageldeen
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Terms set in power purchase agreements (PPA) challenge power utility companies in balancing between the returns (from maximizing power production) and securing long term supply contracts at capped production. The production limitation set in the PPA has driven efforts to maximize profits through efficient and economic power production. In this paper, a combined industrial-scale gas turbine (GT) - absorption chiller (AC) system is considered to cool the GT air intake for reducing the plant’s heat rate (HR). This GT-AC system is optimized while considering power output limitations imposed by the PPA. In addition, the proposed formulation accounts for uncertainties in the ambient temperature using Type-2 fuzzy programming. Using the enhanced chaotic differential evolution (CEDE), the Pareto frontier was constructed and the optimization results are analyzed in detail.Keywords: Absorption chillers, turbine inlet air cooling, power purchase agreement, multiobjective optimization, type-2 fuzzy programming, chaotic differential evolution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9331016 An Intelligent Controller Augmented with Variable Zero Lag Compensation for Antilock Braking System
Authors: Benjamin C. Agwah, Paulinus C. Eze
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Antilock braking system (ABS) is one of the important contributions by the automobile industry, designed to ensure road safety in such way that vehicles are kept steerable and stable when during emergency braking. This paper presents a wheel slip-based intelligent controller with variable zero lag compensation for ABS. It is required to achieve a very fast perfect wheel slip tracking during hard braking condition and eliminate chattering with improved transient and steady state performance, while shortening the stopping distance using effective braking torque less than maximum allowable torque to bring a braking vehicle to a stop. The dynamic of a vehicle braking with a braking velocity of 30 ms⁻¹ on a straight line was determined and modelled in MATLAB/Simulink environment to represent a conventional ABS system without a controller. Simulation results indicated that system without a controller was not able to track desired wheel slip and the stopping distance was 135.2 m. Hence, an intelligent control based on fuzzy logic controller (FLC) was designed with a variable zero lag compensator (VZLC) added to enhance the performance of FLC control variable by eliminating steady state error, provide improve bandwidth to eliminate the effect of high frequency noise such as chattering during braking. The simulation results showed that FLC-VZLC provided fast tracking of desired wheel slip, eliminated chattering, and reduced stopping distance by 70.5% (39.92 m), 63.3% (49.59 m), 57.6% (57.35 m) and 50% (69.13 m) on dry, wet, cobblestone and snow road surface conditions respectively. Generally, the proposed system used effective braking torque that is less than the maximum allowable braking torque to achieve efficient wheel slip tracking and overall robust control performance on different road surfaces.
Keywords: ABS, Fuzzy Logic Controller, Variable Zero Lag Compensator, Wheel Slip Tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3411015 A New Criterion Pose and Shape of Objects for Collision Risk Estimation
Authors: Do Hyeung Kim, Dae Hee Seo, Byung Doo Kim, Byung Gil Lee
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As many recent researches being implemented in aviation and maritime aspects, strong doubts have been raised concerning the reliability of the estimation of collision risk. It is shown that using position and velocity of objects can lead to imprecise results. In this paper, therefore, a new approach to the estimation of collision risks using pose and shape of objects is proposed. Simulation results are presented validating the accuracy of the new criterion to adapt to collision risk algorithm based on fuzzy logic.
Keywords: Collision risk, Pose and shape, Fuzzy logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19081014 An Advanced Nelder Mead Simplex Method for Clustering of Gene Expression Data
Authors: M. Pandi, K. Premalatha
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The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures and identify interesting patterns in the underlying data. In the proposed work clustering gene expression data is done through an Advanced Nelder Mead (ANM) algorithm. Nelder Mead (NM) method is a method designed for optimization process. In Nelder Mead method, the vertices of a triangle are considered as the solutions. Many operations are performed on this triangle to obtain a better result. In the proposed work, the operations like reflection and expansion is eliminated and a new operation called spread-out is introduced. The spread-out operation will increase the global search area and thus provides a better result on optimization. The spread-out operation will give three points and the best among these three points will be used to replace the worst point. The experiment results are analyzed with optimization benchmark test functions and gene expression benchmark datasets. The results show that ANM outperforms NM in both benchmarks.
Keywords: Spread out, simplex, multi-minima, fitness function, optimization, search area, monocyte, solution, genomes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25571013 Project Selection Using Fuzzy Group Analytic Network Process
Authors: Hamed Rafiei, Masoud Rabbani
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This paper deals with the project selection problem. Project selection problem is one of the problems arose firstly in the field of operations research following some production concepts from primary product mix problem. Afterward, introduction of managerial considerations into the project selection problem have emerged qualitative factors and criteria to be regarded as well as quantitative ones. To overcome both kinds of criteria, an analytic network process is developed in this paper enhanced with fuzzy sets theory to tackle the vagueness of experts- comments to evaluate the alternatives. Additionally, a modified version of Least-Square method through a non-linear programming model is augmented to the developed group decision making structure in order to elicit the final weights from comparison matrices. Finally, a case study is considered by which developed structure in this paper is validated. Moreover, a sensitivity analysis is performed to validate the response of the model with respect to the condition alteration.
Keywords: Analytic network process, Fuzzy sets theory, Nonlinear programming, Project selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17671012 A Fuzzy Satisfactory Optimization Method Based on Stress Analysis for a Hybrid Composite Flywheel
Authors: Liping Yang, Curran Crawford, Jr. Ren, Zhengyi Ren
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Considering the cost evaluation and the stress analysis, a fuzzy satisfactory optimization (FSO) method has been developed for a hybrid composite flywheel. To evaluate the cost, the cost coefficients of the flywheel components are obtained through calculating the weighted sum of the scores of the material manufacturability, the structure character, and the material price. To express the satisfactory degree of the energy, the cost, and the mass, the satisfactory functions are proposed by using the decline function and introducing a satisfactory coefficient. To imply the different significance of the objectives, the object weight coefficients are defined. Based on the stress analysis of composite material, the circumferential and radial stresses are considered into the optimization formulation. The simulations of the FSO method with different weight coefficients and storage energy density optimization (SEDO) method of a flywheel are contrasted. The analysis results show that the FSO method can satisfy different requirements of the designer and the FSO method with suitable weight coefficients can replace the SEDO method.
Keywords: Flywheel energy storage, fuzzy, optimization, stress analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9621011 Effect of Clustering on Energy Efficiency and Network Lifetime in Wireless Sensor Networks
Authors: Prakash G L, Chaitra K Meti, Poojitha K, Divya R.K.
Abstract:
Wireless Sensor Network is Multi hop Self-configuring Wireless Network consisting of sensor nodes. The deployment of wireless sensor networks in many application areas, e.g., aggregation services, requires self-organization of the network nodes into clusters. Efficient way to enhance the lifetime of the system is to partition the network into distinct clusters with a high energy node as cluster head. The different methods of node clustering techniques have appeared in the literature, and roughly fall into two families; those based on the construction of a dominating set and those which are based solely on energy considerations. Energy optimized cluster formation for a set of randomly scattered wireless sensors is presented. Sensors within a cluster are expected to be communicating with cluster head only. The energy constraint and limited computing resources of the sensor nodes present the major challenges in gathering the data. In this paper we propose a framework to study how partially correlated data affect the performance of clustering algorithms. The total energy consumption and network lifetime can be analyzed by combining random geometry techniques and rate distortion theory. We also present the relation between compression distortion and data correlation.Keywords: Clusters, multi hop, random geometry, rate distortion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16361010 Digital Watermarking Based on Visual Cryptography and Histogram
Authors: R. Rama Kishore, Sunesh
Abstract:
Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.
Keywords: Butterworth filter, digital watermarking, histogram, visual cryptography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1675