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October 2020 :Top 10 Cited Article in Fuzzy Logic Systems

COMPARATIVE ANALYSIS OF AHP AND FUZZY AHP MODELS FOR MULTICRITERIA INVENTORY CLASSIFICATION

    Golam Kabir1 and Dr. M. AhsanAkhtar Hasin2 1,2 Bangladesh University of Science and Technology (BUET),Bangladesh

    ABSTRACT

    A systematic approach to the inventory control and classification may have a significant influence on company competitiveness. In practice, all inventories cannot be controlled with equal attention. In order toefficiently control the inventory items and to determine the suitable ordering policies for them, multicriteria inventory classification is used. Analytical Hierarchy Process (AHP) is one of the best ways fordeciding among the complex criteria structure in different levels. Fuzzy Analytical Hierarchy Process (FAHP) is a synthetic extension of classical AHP method when the fuzziness of the decision makers is considered. In this paper, a comparative analysis of AHP and FAHP for multi-criteria inventoryclassification model has been presented. To accredit the proposed models, those were implemented for the351 raw materials of switch gear section of Energypac Engineering Limited (EEL), a large power engineering company of Bangladesh.

    KEYWORDS

    Analytic Hierarchy Process, Chang’s Extent Analysis, Inventory Classification


    For More Details :
    https://wireilla.com/papers/ijfls/V1N1/1011ijfls01.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol1.html




Bipolar Fuzzy Hypergraphs

A NEW OPERATION ON HEXAGONAL FUZZY NUMBER

    P. Rajarajeswari1, A.Sahaya Sudha2 and R.Karthika3 1Chikkanna Government Arts College, Tirupur 2Nirmala College for women, Coimbatore 3Hindustan Institute of Technology, Coimbatore

    ABSTRACT

    The Fuzzy set Theory has been applied in many fields such as Management, Engineering etc. In this paper a new operation on Hexagonal Fuzzy number is defined where the methods of addition,subtraction, and multiplication has been modified with some conditions. The main aim of this paper is to introduce a new operation for addition, subtraction and multiplication of Hexagonal Fuzzy number on the basis of alpha cut sets of fuzzy numbers.

    KEYWORDS

    Fuzzy arithmetic, Hexagonal fuzzy numbers, Function principles .


    For More Details :
    https://wireilla.com/papers/ijfls/V3N3/3313ijfls02.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol3.html




A FUZZY MODEL FOR ANALOGICAL PROBLEM SOLVING

    Michael Gr. Voskoglou School of Technological Applications Graduate Technological Educational Institute, Patras, Greece

    ABSTRACT

    In this paper we develop a fuzzy model for the description of the process of Analogical Reasoning by representing its main steps as fuzzy subsets of a set of linguistic labels characterizing the individuals’performance in each step and we use the Shannon- Wiener diversity index as a measure of the individuals’abilities in analogical problem solving. This model is compared with a stochastic model presented inauthor’s earlier papers by introducing a finite Markov chain on the steps of the process of AnalogicalReasoning. A classroom experiment is also presented to illustrate the use of our results in practice.

    KEYWORDS

    Fuzzy Sets, Analogical Reasoning, Problem Solving


    For More Details :
    https://wireilla.com/papers/ijfls/V2N1/2112ijfls01.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol2.html




Brain Tumor Segmentation using hybrid Genetic Algorithm and Artificial Neural Network Fuzzy Inference System (ANFIS)

    Minakshi Sharma1, Dr. Sourabh Mukharjee2 1GIMT kanipla, India 2Banasthali university, Rajasthan

    ABSTRACT

    Medical image segmentation plays an important role in treatment planning, identifying tumors, tumor volume, patient follow up and computer guided surgery. There are various techniques for medical image segmentation. This paper presents a image segmentation technique for locating brain tumor(AstrocytomaA type of brain tumor).Proposed work has been divided in two phases-In the first phase MRI imagedatabase(Astrocytoma grade I to IV) is collected and then preprocessing is done to improve quality ofimage. Second-phase includes three steps-Feature extraction, Feature selection and Image segmentation.For feature extraction proposed work uses GLCM (Grey Level co-occurrence matrix).To improve accuracyonly a subset of feature is selected using hybrid Genetic algorithm(Genetic Algorithm+fuzzy rough set) andbased on these features fuzzy rules and membership functions are defined for segmenting brain tumor fromMRI images of .ANFIS is a adaptive network which combines benefits of both fuzzy and neural network.Finally, a comparative analysis is performed between ANFIS, neural network, Fuzzy ,FCM,K-NN,DWT+SOM,DWT+PCA+KN, Texture combined +ANN, Texture Combined+ SVM in terms of sensitivity,specificity ,accuracy.

    KEYWORDS

    ANFIS, Brain tumor(Astrocytoma), sensitivity, specificity, accuracy, MR images, Neural network, Fuzzy,ANFIS,FCM,K-NN, GLCM, Genetic algorithm.


    For More Details :
    https://wireilla.com/papers/ijfls/V2N4/2412ijfls03.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol2.html




Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter

    Hana Boudjedir1, Omar Bouhali1and Nassim Rizoug2 1LAJ Lab, Automatic department, Jijel University, Algeria 2Mecatronic Lab, ESTACA School, Laval, Franc

    ABSTRACT

    A neural network control scheme with an adaptive observer is proposed in this paper to Quadrotorhelicopter stabilization. The unknown part in Quadrotor dynamical model was estimated on line by aSingle Hidden Layer network. To solve the non measurable states problem a new adaptive observer wasproposed. The main purpose here is to reduce the measurement noise amplification caused by conventionalhigh gain observer by introducing some changes in observer’s original structure that can minimize the variance and the amplitude of the noisy signal without increasing tracking error. The stability analysis ofthe overall closed-loop system/ observer is performed using the Lyapunov direct method. Simulation resultsare given to highlight the performances of the proposed scheme.

    KEYWORDS

    Adaptive observer; high gain observer; Neural Network control; Quadrotor; Lyapunov stability.


    For More Details :
    https://wireilla.com/papers/ijitca/V2N3/2312ijitca04.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol2.html




INTERVAL-VALUED INTUITIONISTIC FUZZY CLOSED IDEALS OF BG-ALGEBRA AND THEIR PRODUCTS

    Tapan Senapati1, MonoranjanBhowmik2, Madhumangal Pal3 1Vidyasagar University,India 2V. T. T. College, India

    ABSTRACT

    In this paper, we apply the concept of an interval-valued intuitionistic fuzzy set to ideals and closed idealsin BG-algebras. The notion of an interval-valued intuitionistic fuzzy closed ideal of a BG-algebra isintroduced, and some related properties are investigated. Also, the product of interval-valuedinntuitionistic fuzzy BG-algebra is investgated.

    KEYWORDS

    BG-algebras, interval-valued intuitionistic fuzzy sets (IVIFSs), IVIF-ideals, IVIFC-ideals, homomorphism,equivalence relation, upper(lower)-level cuts, product of BG-algebra. .


    For More Details :
    https://wireilla.com/papers/ijfls/V2N2/2212ijfls03.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol2.html




Application of Neuro-Fuzzy Expert System for the Probe and Prognosis of Thyroid Disorder

    Imianvan Anthony Agboizebeta1 and Obi Jonathan Chukwuyeni2 1University of Benin,Nigeria 2University of Benin, Nigeria

    ABSTRACT

    Thyroid disorders are common disorders of the thyroid gland. Thyroid disorders include such diseases andconditions as graves disease, thyroid nodules, Hashimoto's thyroiditis, trauma to the thyroid, thyroidcancer and birth defects. These include being born with a defective thyroid gland or without a thyroidgland. Thyroid disorder can be caused by hyperthyroidism, thyroid cancer, goiter, hyperparathyroidismand postpartum thyroiditis. Thyroid disorder are usually characterized by life threatening symptoms suchas insomnia, irritability, nervousness, unexplained weight loss, heat sensitivity, increased perspiration,thinning of skin, warm skin, fine hair, brittle hair and thinning hair. Neuro-Fuzzy Logic exploresapproximation techniques from neural networks to finds the parameter of a fuzzy system. This paper whichdemonstrates the practical application of Information Technology (IT) in the health sector, has presented ahybrid neuro-fuzzy Expert System to help in diagnosis of thyroid disorder using a set of symptoms. Thesystem designed is an interactive system that tells the patient his current condition as regards thyroiddisorder.

    KEYWORDS

    Neural network, Fuzzy logic, Diagnosis, Prognosis, Thyroid Disorder


    For More Details :
    https://wireilla.com/papers/ijfls/V2N2/2212ijfls01.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol2.html




COMPARISON OF DIFFERENT T-NORM OPERATORS IN CLASSIFICATION PROBLEMS

    Fahimeh Farahbod1 and Mahdi Eftekhari2 1,2ShahidBahonar University, Iran

    ABSTRACT

    Fuzzy rule based classification systems are one of the most popular fuzzy modeling systems used in patternclassification problems. This paper investigates the effect of applying nine different T-norms in fuzzy rulebased classification systems. In the recent researches, fuzzy versions of confidence and support merits fromthe field of data mining have been widely used for both rules selecting and weighting in the construction offuzzy rule based classification systems. For calculating these merits the product has been usually used as aT-norm. In this paper different T-norms have been used for calculating the confidence and supportmeasures. Therefore, the calculations in rule selection and rule weighting steps (in the process ofconstructing the fuzzy rule based classification systems) are modified by employing these T-norms.Consequently, these changes in calculation results in altering the overall accuracy of rule based classification systems. Experimental results obtained on some well-known data sets show that the best performance is produced by employing the Aczel-Alsina operator in terms of the classification accuracy, the second best operator is Dubois-Prade and the third best operator is Dombi. In experiments, we have used 12 data sets with numerical attributes from the University of California, Irvine machine learning repository (UCI).

    KEYWORDS

    Pattern classification, Fuzzy systems, T-norm operators.


    For More Details :
    https://wireilla.com/papers/ijfls/V2N3/2312ijfls03.pdf


    International Journal of Fuzzy Logic Systems (IJFLS)

    Volume Link :
    https://wireilla.com/ijfls/vol2.html




A NEW METHOD FOR RANKING IN AREAS OF TWO GENERALIZED TRAPEZOIDAL FUZZY NUMBERS





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