Search results for: triangular fuzzy matrix

Authors: Tingting Lu, Yonghai Wang, Haiyong Wang, Jiaqi Liu

Abstract:

To satisfy the need of outfield tests of star sensors, a method is put forward to construct the reference attitude benchmark. Firstly, its basic principle is introduced; Then, all the separate conversion matrixes are deduced, which include: the conversion matrix responsible for the transformation from the Earth Centered Inertial frame i to the Earth-centered Earth-fixed frame w according to the time of an atomic clock, the conversion matrix from frame w to the geographic frame t, and the matrix from frame t to the platform frame p, so the attitude matrix of the benchmark platform relative to the frame i can be obtained using all the three matrixes as the multiplicative factors; Next, the attitude matrix of the star sensor relative to frame i is got when the mounting matrix from frame p to the star sensor frame s is calibrated, and the reference attitude angles for star sensor outfield tests can be calculated from the transformation from frame i to frame s; Finally, the computer program is finished to solve the reference attitudes, and the error curves are drawn about the three axis attitude angles whose absolute maximum error is just 0.25ÔÇ│. The analysis on each loop and the final simulating results manifest that the method by precise timing to acquire the absolute reference attitude is feasible for star sensor outfield tests.

Keywords: Atomic time, attitude determination, coordinate conversion, inertial coordinate system, star sensor.

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Authors: Vijay Gajanan Neve, Pallavi V. Pullawar, G. M. Dhole

Abstract:

Modern industrial processes are based on a large amount of electronic devices such as programmable logic controllers and adjustable speed drives. Unfortunately, electronic devices are sensitive to disturbances, and thus, industrial loads become less tolerant to power quality problems such as sags, swells, and harmonics. Voltage sags are an important power quality problem. In this paper proposed a new configuration of Static Var Compensator (SVC) considering three different conditions named as topologies and Booster transformer with fuzzy logic based controller, capable of compensating for power quality problems associated with voltage sags and maintaining a prescribed level of voltage profile. Fuzzy logic controller is designed to achieve the firing angles for SVC such that it maintains voltage profile. The online monitoring system for voltage sag mitigation in the laboratory using the hardware is used. The results are presented from the performance of each topology and Booster transformer considered in this paper.

Keywords: Booster Transformer, Fuzzy logic, Static Var Compensator, Voltage sag.

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Authors: A. Perolini

Abstract:

Feature and model selection are in the center of attention of many researches because of their impact on classifiers- performance. Both selections are usually performed separately but recent developments suggest using a combined GA-SVM approach to perform them simultaneously. This approach improves the performance of the classifier identifying the best subset of variables and the optimal parameters- values. Although GA-SVM is an effective method it is computationally expensive, thus a rough method can be considered. The paper investigates a joined approach of Genetic Algorithm and kernel matrix criteria to perform simultaneously feature and model selection for SVM classification problem. The purpose of this research is to improve the classification performance of SVM through an efficient approach, the Kernel Matrix Genetic Algorithm method (KMGA).

Keywords: Feature and model selection, Genetic Algorithms, Support Vector Machines, kernel matrix.

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Authors: Ben Hamed M., Sbita L

Abstract:

This paper presents a new method for the implementation of a direct rotor flux control (DRFOC) of induction motor (IM) drives. It is based on the rotor flux components regulation. The d and q axis rotor flux components feed proportional integral (PI) controllers. The outputs of which are the target stator voltages (vdsref and vqsref). While, the synchronous speed is depicted at the output of rotor speed controller. In order to accomplish variable speed operation, conventional PI like controller is commonly used. These controllers provide limited good performances over a wide range of operations even under ideal field oriented conditions. An alternate approach is to use the so called fuzzy logic controller. The overall investigated system is implemented using dSpace system based on digital signal processor (DSP). Simulation and experimental results have been presented for a one kw IM drives to confirm the validity of the proposed algorithms.

Keywords: DRFOC, fuzzy logic, variable speed drives, control, IM and real time.

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Authors: P. Selvam, S. Senthil Kumar

Abstract:

Maximum Power Point Tracking (MPPT) has played a vital role to enhance the efficiency of solar photovoltaic (PV) power generation under varying atmospheric temperature and solar irradiation. However, it is hard to track the maximum power point using conventional linear controllers due to the natural inheritance of nonlinear I-V and P-V characteristics of solar PV systems. Fuzzy Logic Controller (FLC) is suitable for nonlinear system control applications and eliminating oscillations, circuit complexities present in the conventional perturb and observation and incremental conductance methods respectively. Hence, in this paper, FLC is proposed for tracking exact MPPT of solar PV power generation system under varying solar irradiation conditions. The effectiveness of the proposed FLC-based MPPT controller is validated through simulation and analysis using MATLAB/Simulink.

Keywords: Fuzzy logic controller, maximum power point tracking, photovoltaic.

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Authors: A. Siam, R. Maamri, Z. Sahnoun

Abstract:

The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines, The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques and mechanisms were proposed to develop adaptive UI. In this paper, we propose an approach based on the fuzzy set theory for modeling the concept of the appropriateness of different solutions of UI adaptation with different situations for which interactive systems have to adapt their UIs.

Keywords: Adaptive user interfaces, adaptation solution’s appropriateness, fuzzy sets.

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Authors: M. Mahli, A.I. Che-Ani, M.Z. Abd-Razak. N.M. Tawil, H. Yahaya

Abstract:

Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'.

Keywords: building condition, CSP1 Matrix, assessment, school, Malaysia

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Authors: Ingu Kim, Shangmun Shin, Yongsun Choi, Nguyen Manh Thang, Edwin R. Ramos, Won-Joo Hwang

Abstract:

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.

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Authors: Altab Hossain, Ataur Rahman, Jakir Hossen, A.K.M. P. Iqbal, SK. Hasan

Abstract:

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.

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Authors: M.A. Ahmad

Abstract:

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.

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

Abstract:

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.

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Authors: Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur

Abstract:

In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.

Keywords: Subtractive clustering, fuzzy inference system, fault proneness.

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Authors: Witcha Chimphlee, Abdul Hanan Abdullah, Mohd Noor Md Sap, Siriporn Chimphlee, Surat Srinoy

Abstract:

It is important problems to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). Although preventative techniques such as access control and authentication attempt to prevent intruders, these can fail, and as a second line of defence, intrusion detection has been introduced. Rare events are events that occur very infrequently, detection of rare events is a common problem in many domains. In this paper we propose an intrusion detection method that combines Rough set and Fuzzy Clustering. Rough set has to decrease the amount of data and get rid of redundancy. Fuzzy c-means clustering allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect suspicious activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining-(KDDCup 1999) Dataset show that the method is efficient and practical for intrusion detection systems.

Keywords: Network and security, intrusion detection, fuzzy cmeans, rough set.

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Authors: M. Tarafdar Haque, S. Najafi

Abstract:

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.

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Authors: Murugan Marimuthu, Jeyabharath Rajaih

Abstract:

This paper describes a simple way to control the speed of PMBLDC motor using Fuzzy logic control method. In the conventional PI controller the performance of the motor system is simulated and the speed is regulated by using PI controller. These methods used to improve the performance of PMSM drives, but in some cases at different operating conditions when the dynamics of the system also vary over time and it can change the reference speed, parameter variations and the load disturbance. The simulation is powered with the MATLAB program to get a reliable and flexible simulation. In order to highlight the effectiveness of the speed control method the FLC method is used. The proposed method targeted in achieving the improved dynamic performance and avoids the variations of the motor drive. This drive has high accuracy, robust operation from near zero to high speed. The effectiveness and flexibility of the individual techniques of the speed control method will be thoroughly discussed for merits and demerits and finally verified through simulation and experimental results for comparative analysis.

Keywords: Hall position sensors, permanent magnet brushless DC motor, PI controller, Fuzzy Controller.

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Authors: Vahid Anari, Mina Bakhshi

Abstract:

Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: Positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means.

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Authors: Mohammad Taghi Taghavifard, Danial Mirheydari

Abstract:

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

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Authors: J. P. P. Andrade, V. A. F. Campos

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This work presents an application of Linear Matrix Inequalities (LMI) for the robust control of an F-16 aircraft through an algorithm ensuring the damping factor to the closed loop system. The results show that the zero and gain settings are sufficient to ensure robust performance and stability with respect to various operating points. The technique used is the pole placement, which aims to put the system in closed loop poles in a specific region of the complex plane. Test results using a dynamic model of the F-16 aircraft are presented and discussed.

Keywords: F-16 Aircraft, linear matrix inequalities, pole placement, robust control.

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Authors: P. T. Ahamed Seyd, V. I. Thajudin Ahamed, Jeevamma Jacob, Paul Joseph K

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Diabetes mellitus (DM) is frequently characterized by autonomic nervous dysfunction. Analysis of heart rate variability (HRV) has become a popular noninvasive tool for assessing the activities of autonomic nervous system (ANS). In this paper, changes in ANS activity are quantified by means of frequency and time domain analysis of R-R interval variability. Electrocardiograms (ECG) of 16 patients suffering from DM and of 16 healthy volunteers were recorded. Frequency domain analysis of extracted normal to normal interval (NN interval) data indicates significant difference in very low frequency (VLF) power, low frequency (LF) power and high frequency (HF) power, between the DM patients and control group. Time domain measures, standard deviation of NN interval (SDNN), root mean square of successive NN interval differences (RMSSD), successive NN intervals differing more than 50 ms (NN50 Count), percentage value of NN50 count (pNN50), HRV triangular index and triangular interpolation of NN intervals (TINN) also show significant difference between the DM patients and control group.

Keywords: Autonomic nervous system, diabetes mellitus, frequency domain and time domain analysis, heart rate variability.

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Authors: Yongxin Yuan

Abstract:

Let R ∈ Cm×m and S ∈ Cn×n be nontrivial unitary involutions, i.e., RH = R = R−1 = ±Im and SH = S = S−1 = ±In. A ∈ Cm×n is said to be a generalized reflexive (anti-reflexive) matrix if RAS = A (RAS = −A). Let ρ be the set of m × n generalized reflexive (anti-reflexive) matrices. Given X ∈ Cn×p, Z ∈ Cm×p, Y ∈ Cm×q and W ∈ Cn×q, we characterize the matrices A in ρ that minimize AX−Z2+Y HA−WH2, and, given an arbitrary A˜ ∈ Cm×n, we find a unique matrix among the minimizers of AX − Z2 + Y HA − WH2 in ρ that minimizes A − A˜. We also obtain sufficient and necessary conditions for existence of A ∈ ρ such that AX = Z, Y HA = WH, and characterize the set of all such matrices A if the conditions are satisfied. These results are applied to solve a class of left and right inverse eigenproblems for generalized reflexive (anti-reflexive) matrices.

Keywords: approximation, generalized reflexive matrix, generalized anti-reflexive matrix, inverse eigenvalue problem.

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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 (PFD_avg) 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.

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Authors: Chih-Jer Lin, Chun-Ying Lee, Chiang-Ho Cheng, Geng-Fung Chen

Abstract:

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.

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Authors: Kevin Fong-Rey Liu, Jia-Shen Chen, Han-Hsi Liang, Cheng-Wu Chen, Yung-Shuen Shen

Abstract:

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.

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Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mohammad Fathian

Abstract:

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new method defined to reduce nodes number. This method cluster nodes in FCM based on their cause and effect behaviors.

Keywords: Clustering, Data Mining, Fuzzy Cognitive Map(FCM), Learning.

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Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi

Abstract:

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

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Authors: Erika Martinez Ramirez, Rene V. Mayorga

Abstract:

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.

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Authors: T. Ganesan, M. S. Aris, I. Elamvazuthi, Momen Kamal Tageldeen

Abstract:

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.

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Authors: Do Hyeung Kim, Dae Hee Seo, Byung Doo Kim, Byung Gil Lee

Abstract:

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.

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Authors: Hamed Rafiei, Masoud Rabbani

Abstract:

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.

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Authors: Liping Yang, Curran Crawford, Jr. Ren, Zhengyi Ren

Abstract:

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.

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