Search results for: fuzzy c-means algorithm (FCM)

Authors: Sophia Fry, Mahir Irtiza, Alexa Hoffman, Yousef Sardahi

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This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude.

Keywords: fuzzy logic control, model-free control, flexible joint manipulators, nonlinear control

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Authors: R. Rama Kishore, Sunesh

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Recent development in the usage of internet for different purposes creates a great threat for the copyright protection of the digital images. Digital watermarking can be used to address the problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field of secured, robust and imperceptible watermarking. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (2, 2) share visual cryptography and Bezier curve based algorithm to improve the security of the watermark. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method. The algorithm is optimized using fuzzy entropy for better results.

Keywords: digital watermarking, fractional transform, visual cryptography, Bezier curve, fuzzy entropy

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani

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As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.

Keywords: computational grid, job scheduling, learning automata, dynamic scheduling

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Authors: U.V. Suryawanshi, S.S. Chowhan, U.V Kulkarni

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Accuracy of segmentation methods is of great importance in brain image analysis. Tissue classification in Magnetic Resonance brain images (MRI) is an important issue in the analysis of several brain dementias. This paper portraits performance of segmentation techniques that are used on Brain MRI. A large variety of algorithms for segmentation of Brain MRI has been developed. The objective of this paper is to perform a segmentation process on MR images of the human brain, using Fuzzy c-means (FCM), Kernel based Fuzzy c-means clustering (KFCM), Spatial Fuzzy c-means (SFCM) and Improved Fuzzy c-means (IFCM). The review covers imaging modalities, MRI and methods for noise reduction and segmentation approaches. All methods are applied on MRI brain images which are degraded by salt-pepper noise demonstrate that the IFCM algorithm performs more robust to noise than the standard FCM algorithm. We conclude with a discussion on the trend of future research in brain segmentation and changing norms in IFCM for better results.

Keywords: image segmentation, preprocessing, MRI, FCM, KFCM, SFCM, IFCM

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Authors: B. G. Sampath, K. C. R. Perera, W. A. S. I. Wijesuriya, V. P. C. Dassanayake

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In this paper the design, development and testing of a stabilizer control system for a Quad-rotor is presented which is focused on the maneuverability. The mechanical design is performed along with the design of the controlling algorithm which is devised using fuzzy logic controller. The inputs for the system are the angular positions and angular rates of the Quad-Rotor relative to three axes. Then the output data is filtered from an accelerometer and a gyroscope through a Kalman filter. In the development of the stability controlling system Mandani Fuzzy Model is incorporated. The results prove that the fuzzy based stabilizer control system is superior in high dynamic disturbances compared to the traditional systems which use PID integrated stabilizer control systems.

Keywords: fuzzy stabilizer, maneuverability, PID, quad-rotor

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Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

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This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

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Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Talal H. Alzanki

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This paper presents a hybrid fuzzy logic control strategy for a unicycle trajectory following robot on irregular terrains. In literature, researchers have presented the design of path tracking controllers of mobile robots on non-frictional surface. In this work, the robot is simulated to drive on irregular terrains with contrasting frictional profiles of peat and rough gravel. A hybrid fuzzy logic controller is utilised to stabilise and drive the robot precisely with the predefined trajectory and overcome the frictional impact. The controller gains and scaling factors were optimised using spiral dynamics optimisation algorithm to minimise the mean square error of the linear and angular velocities of the unicycle robot. The robot was simulated on various frictional surfaces and terrains and the controller was able to stabilise the robot with a superior performance that is shown via simulation results.

Keywords: fuzzy logic control, mobile robot, trajectory tracking, spiral dynamic algorithm

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Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: Kouzi Katia

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This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

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Authors: Xiong Xie, Yuhang Chen

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Vulnerability discovery technology is a significant field of the current. In this paper, a fuzzy framework based on concolic execution has been proposed. Fuzzy test and symbolic execution are widely used in the field of vulnerability discovery technology. But each of them has its own advantages and disadvantages. During the path generation stage, path traversal algorithm based on generation is used to get more accurate path. During the constraint solving stage, dynamic concolic execution is used to avoid the path explosion. If there is external call, the concolic based on function summary is used. Experiments show that the framework can effectively improve the ability of triggering vulnerabilities and code coverage.

Keywords: concolic execution, constraint solving, fuzzy test, vulnerability discovery

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Authors: Sachin Kumar

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Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy.

Keywords: fractional PDE, fuzzy valued function, diffusion equation, Legendre polynomial, spectral method

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Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

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Authors: Shih-Pin Chen, Shih-Syuan You

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Fuzzy regression models are useful for investigating the relationship between explanatory variables and responses in fuzzy environments. To overcome the deficiencies of previous models and increase the explanatory power of fuzzy data, the graded mean integration (GMI) representation is applied to determine representative crisp regression coefficients. A fuzzy regression model is constructed based on the modified dissemblance index (MDI), which can precisely measure the actual total error. Compared with previous studies based on the proposed MDI and distance criterion, the results from commonly used test examples show that the proposed fuzzy linear regression model has higher explanatory power and forecasting accuracy.

Keywords: dissemblance index, fuzzy linear regression, graded mean integration, mathematical programming

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Authors: Salman Hameed

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In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

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Authors: Jalel Khelil

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In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification.

Keywords: fault diagnosis, fuzzy classification k-nearest neighbor, vibration

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Authors: Sardar Ameer Akram Khan, Shahzad Amin Sheikh

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Blind equalization is an important technique amongst equalization family. Multimodulus algorithms based on blind equalization removes the undesirable effects of ISI and cater ups the phase issues, saving the cost of rotator at the receiver end. In this paper a new algorithm combination of recursive least square and Multimodulus algorithm named as RLSMMA is proposed by providing few assumption, fast convergence and minimum Mean Square Error (MSE) is achieved. The excellence of this technique is shown in the simulations presenting MSE plots and the resulting filter results.

Keywords: blind equalizations, constant modulus algorithm, multi-modulus algorithm, recursive least square algorithm, quadrature amplitude modulation (QAM)

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

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Authors: Indrajit Ghosh, Jaydip Roy

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Literacy rate is an important indicator for measurement of human development. But this is not a good one to capture the qualitative dimension of educational attainment of an individual or a society. The overall educational level of an area is an important issue beyond the literacy rate. The overall educational level can be thought of as an outcome of the educational levels of individuals. But there is no well-defined algorithm and mathematical model available to measure the overall educational level of an area. A heuristic approach based on accumulated experience of experts is effective one. It is evident that fuzzy logic offers a natural and convenient framework in modeling various concepts in social science domain. This work suggests the implementation of fuzzy logic to develop a mathematical model for measurement of educational attainment of an area in terms of Education Index. The contribution of the study is two folds: conceptualization of “Education Profile” and proposing a new mathematical model to measure educational attainment in terms of “Education Index”.

Keywords: education index, education profile, fuzzy logic, literacy

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Authors: Sultan Noman Qasem

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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

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Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng

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The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.

Keywords: electro-rheological fluid, semi-active vibration control, shock absorber, type 2 fuzzy control

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Authors: Yi-Cheng Tian, Miin-Shen Yang

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The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.

Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization

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Authors: Cesar Hernández, Diego Giral, Ingrid Páez

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This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.

Keywords: cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks

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Authors: Liang-Hsuan Chen, Chia-Jung Chang

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Fuzzy random variables have been introduced as an imprecise concept of numeric values for characterizing the imprecise knowledge. The descriptive parameters can be used to describe the primary features of a set of fuzzy random observations. In fuzzy environments, the expected values are usually represented as fuzzy-valued, interval-valued or numeric-valued descriptive parameters using various metrics. Instead of the concept of area metric that is usually adopted in the relevant studies, the numeric expected value is proposed by the concept of distance metric in this study based on two characters (fuzziness and randomness) of FRVs. Comparing with the existing measures, although the results show that the proposed numeric expected value is same with those using the different metric, if only triangular membership functions are used. However, the proposed approach has the advantages of intuitiveness and computational efficiency, when the membership functions are not triangular types. An example with three datasets is provided for verifying the proposed approach.

Keywords: fuzzy random variables, distance measure, expected value, descriptive parameters

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Authors: T. Wanyama, B. Far

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Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

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Authors: Tai Nguyen, Minh Bui, Huong Ninh, Tu Nguyen, Hai Tran

Abstract:

GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research.

Keywords: CUDA, graph cut, image stitching, texture synthesis, maxflow/mincut algorithm

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Authors: Rosy Joseph

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From an algebraic point of view, Semirings provide the most natural generalization of group theory and ring theory. In the absence of additive inverse in a semiring, one had to impose a weaker condition on the semiring, i.e., the additive cancellative law to study interesting structural properties. In many practical situations, fuzzy numbers are used to model imprecise observations derived from uncertain measurements or linguistic assessments. In this connection, a special class of fuzzy numbers whose shape is symmetric with respect to a vertical line called the symmetric fuzzy numbers i.e., for α ∈ (0, 1] the α − cuts will have a constant mid-point and the upper end of the interval will be a non-increasing function of α, the lower end will be the image of this function, is suitable. Based on this description, arithmetic operations and a ranking technique to order the symmetric fuzzy numbers were dealt with in detail. Wherein it was observed that the structure of the class of symmetric fuzzy numbers forms a commutative semigroup with cancellative property. Also, it forms a multiplicative monoid satisfying sub-distributive property.In this paper, we introduce the algebraic structure, sub-distributive semiring and discuss its various properties viz., ideals and prime ideals of sub-distributive semiring, sub-distributive ring of difference etc. in detail. Symmetric fuzzy numbers are visualized as an illustration.

Keywords: semirings, subdistributive ring of difference, subdistributive semiring, symmetric fuzzy numbers

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Authors: J. Kaabi, Y. Harrath

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This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.

Keywords: flow shop scheduling, genetic algorithm, maintenance, priority rules

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Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

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The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

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