Top 10 Downloaded Articles - International Journal of Fuzzy Logic Systems (IJFLS)

Top 10 Downloaded Articles in Fuzzy Logic Systems International Journal of Fuzzy Logic Systems (IJFLS) ISSN: 1839 – 6283 https://wireilla.com/ijfls/index.html

A NEW RANKING ON HEXAGONAL FUZZY NUMBERS Dr. Mrs. A.Sahaya Sudha1 and Mrs.M.Revathy2 1Department of Mathematics, Nirmala College for women, Coimbatore 2Department of Mathematics, Dr.N.G.P.Arts and Science College, Coimbatore

ABSTRACT The objective of this paper is to introduce a fuzzy linear programming problem with hexagonal fuzzy numbers. Here the parameters are hexagonal fuzzy numbers and Simplex method is used to arrive an optimal solution by a new method compared to the earlier existing method. This procedure is illustrated with numerical example. This will further help the decision makers to come out with a feasible alternatives with better economical viability.

KEY WORDS Fuzzy Number, Hexagonal Fuzzy Number, Fuzzy Linear Programming Problem

Full Text: https://wireilla.com/papers/ijfls/V6N4/6416ijfls01.pdf Volume Link: https://wireilla.com/ijfls/vol6.html

REFERENCES [1] A.Thamaraiselvi and R.Santhi, (2015) “Optimal solution of Fuzzy Transportation Problem Using Hexagonal Fuzzy Numbers”, International Journal of Scientific & Engineering Research, 6, pp. 40- 45.

[2] Dr.G.Nirmala and R. Anju, (2014) “An application of fuzzy quantifier in fuzzy Transportation problem”, International Journal of Scientific Research, 3, pp.175-177.

[3] H.J. Zimmermann, ( 1991) “Fuzzy Set Theory and Its Applications”, Boston: Kulwer.

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[9] P.Rajarajeswari and A. Sahaya Sudha, (2014) “Ranking of Hexagonal Fuzzy Numbers using Centroid”, AARJMD, 1, pp. 265-277.

[10] P. Senthilkumar and G. Rajendran, (2010) “On the solution of Fuzzy linear programming Problem”, International journal of computational Cognition, 8(3) pp 45-47.

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ADAPTIVE FUZZY KERNEL CLUSTERING ALGORITHM

Weijun Xu1 1The Department of Electrical and Information Engineering, Northeast Petroleum University at Qinhuangdao, Qinhuangdao, P.R. China

ABSTRACT Fuzzy clustering algorithm can not obtain good clustering effect when the sample characteristic is not obvious and need to determine the number of clusters firstly. For thi0s reason, this paper proposes an adaptive fuzzy kernel clustering algorithm. The algorithm firstly use the adaptive function of clustering number to calculate the optimal clustering number, then the samples of input space is mapped to highdimensional feature space using gaussian kernel and clustering in the feature space. The Matlab simulation results confirmed that the algorithm's performance has greatly improvement than classical clustering algorithm and has faster convergence speed and more accurate clustering results.

KEYWORDS Fuzzy clustering; Gaussian kernel; Adaptive clustering number; fuzzy kernel clustering

Full Text: https://wireilla.com/papers/ijfls/V5N4/5415ijfls05.pdf Volume Link: https://wireilla.com/ijfls/vol5.html

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

Imianvan Anthony Agboizebeta.1 and Obi Jonathan Chukwuyeni2 .1Department of Computer Science, Faculty of Physical Sciences, University of Benin, Benin City, Edo State, Nigeria.

2Department of Computer Science, Faculty of Physical Sciences, University of Benin, Benin City, Edo State, Nigeria.

ABSTRACT Thyroid disorders are common disorders of the thyroid gland. Thyroid disorders include such diseases and conditions as graves disease, thyroid nodules, Hashimoto's thyroiditis, trauma to the thyroid, thyroid cancer and birth defects. These include being born with a defective thyroid gland or without a thyroid gland. Thyroid disorder can be caused by hyperthyroidism, thyroid cancer, goiter, hyperparathyroidism and postpartum thyroiditis. Thyroid disorder are usually characterized by life threatening symptoms such as 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 explores approximation techniques from neural networks to finds the parameter of a fuzzy system.

This paper which demonstrates the practical application of Information Technology (IT) in the health sector, has presented a hybrid neuro-fuzzy Expert System to help in diagnosis of thyroid disorder using a set of symptoms. The system designed is an interactive system that tells the patient his current condition as regards thyroid disorder.

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

Full Text: https://wireilla.com/papers/ijfls/V2N2/2212ijfls01.pdf Volume Link: https://wireilla.com/ijfls/vol2.html

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A COMBINATION OF PALMER ALGORITHM AND GUPTA ALGORITHM FOR SCHEDULING PROBLEM IN APPAREL INDUSTRY

Cecilia E. Nugraheni1, Luciana Abednego1 and Maria Widyarini2 1Dept. of Computer Science, Parahyangan Catholic University, Bandung, Indonesia 2Dept. of Business Adm., Parahyangan Catholic University, Bandung, Indonesia

ABSTRACT The apparel industry is a class of textile industry. Generally, the production scheduling problem in the apparel industry belongs to Flow Shop Scheduling Problems (FSSP). There are many algorithms/techniques/heuristics for solving FSSP. Two of them are the Palmer Algorithm and the Gupta Algorithm. Hyper-heuristic is a class of heuristics that enables to combine of some heuristics to produce a new heuristic. GPHH is a hyper-heuristic that is based on genetic programming that is proposed to solve FSSP [1]. This paper presents the development of a computer program that implements the GPHH. Some experiments have been conducted for measuring the performance of GPHH. From the experimental results, GPHH has shown a better performance than the Palmer Algorithm and Gupta Algorithm.

KEYWORDS Hyper-heuristic, Genetic Programming, Palmer Algorithm, Gupta Algorithm, Flow Shop Scheduling Problem, Apparel Industry

Full Text: https://wireilla.com/papers/ijfls/V11N1/11121ijfls01.pdf Volume Link: https://wireilla.com/ijfls/vol11.html

REFERENCES [1] Cecilia E. Nugraheni and Luciana Abednego. On the Development of Hyper Heuristics Based Framework for Scheduling Problems in Textile Industry. International Journal of Modeling and Optimization, Vol. 6, No. 5, October 2016.

[2] Robert, N. Tomastik, Peter, B. Luh, and Guandong, Liu. Scheduling Flexible Manufacturing System for Apparel Production. IEEE Transaction on Robotics and Automation. 12(5): 789-799.

[3] Scholz-Retter Bernd et al. 2015. Applying Autonomous Control in Apparel Manufacturing. Proc. Of 9th WSEAS Int. Conference on Robotics, Control and Manufacturing Technology. 73-78.

[4] C. E. Nugraheni and L. Abednego, “A survey on heuristics for scheduling problem in textile industry,” in Proc. ICEAI 2015.

[5] C. E. Nugraheni and L. Abednego, “A comparison of heuristics for scheduling problems in textile industry,” Jurnal Teknologi, vol. 78, no. 6-6. 2016.

[6] Said Aqil and Karam Allali. Three metaheuristics for solving the flow shop problem with permutation and sequence dependent setup time. Proc. Of Conference: 2018 4th International Conference on Optimization and Applications (ICOA). 2019.

[7] Peter Bamidele Shola and Asaju La’aro Bolaji. A metaheuristic for solving flowshop problem. International Journal of Advanced Computer Research, Vol 8(37).

[8] Le Zhang and Jinnan Wu. A PSO-Based Hybrid Metaheuristic for Permutation Flowshop Scheduling Problems. The Scientific World Journal. Vol. 2014.

[9] Ochoa G., Rodriguez J.A.V, Petrovic S., and Burke E. K. 2009. Dispatching Rules for Production Scheduling: a Hyper-heuristic Landscape Analysis. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2009), Montreal, Norway.

[10] C. E. Nugraheni and L. Abednego, “Collaboration of multi-agent and hyper-heuristics systems for production scheduling problem,”International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 7, no. 8, pp. 1136-1141, 2013.

[11] C. E. Nugraheni and L. Abednego, “A combined meta-heuristic with hyper-heuristic approach to single machine production scheduling,” International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 8, no. 8, pp. 1322-1326, 2014.

[12] C.E. Nugraheni, L. Abednego, and M. Widyarini. A Genetic Programming based HyperHeuristic for Production Scheduling in Apparel Industry. International Conference on Machine Learning Techniques and NLP (MLNLP 2020), October 24-25, 2020, Sydney, Australia Volume Editors : David C. Wyld, Dhinaharan Nagamalai (Eds) ISBN : 978-1925953-26-8.

[13] E. Taillard. Some efficient heuristic methods for the flow shop sequencing problem.

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A NEW APPROACH FOR RANKING OF OCTAGONAL INTUITIONISTIC FUZZY NUMBERS

Dr.P.Rajarajeswari1 and G.Menaka2 1Department of Mathematics, Chikkanna Govt Arts College, Tirupur.

2Department of Mathematics, Park College of Technology, Coimbator.

ABSTRACT In this paper we introduce Octagonal Intuitionistic fuzzy numbers with its membership and nonmembership functions. A new method is proposed for finding an optimal solution for intuitionistic fuzzy transportation problem, in which the costs are octagonal intuitionistic fuzzy numbers. The procedure is illustrated with a numerical example.

KEYWORDS Intuitionistic fuzzy transportation problems, Octagonal Intuitionistic fuzzy numbers, Ranking method, Modi method, Initial Basic Feasible Solution, Optimal Solution.

Full Text: https://wireilla.com/papers/ijfls/V7N2/7217ijfls01.pdf Volume Link: https://wireilla.com/ijfls/vol7.html

REFERENCES [1] Fuzzy sets and K.Atanassov.1989. More on Intuitionistic Fuzzy sets, Fuzzy sets and systems, 33, pp.37-46.

[2] Atanassov .K.T. “Intuitionistic Fuzzy Sets”, Fuzzy sets and systems, Vol.20 (1), pp: 8796,(1986) [3] A.Thamaraiselvi and R. Santhi,“On Intuitionistic Fuzzy Transportation Problem Using Hexagonal Intuitionistic Fuzzy Numbers”, International Journal of Fuzzy Logic systems (IJFLS) Vol.5, No.1, January 2015.

[4] Thangaraj Beaula – M. Priyadharshini, “ A New Algorithm for Finding a Fuzzy Optimal Solution for Intuitionistic Fuzzy Transportation Problems, International Journalof Applications of Fuzzy Sets and Artificial Intelligence ( ISSN 2241-1240), Vol.5(2015),183192.

[5] Dr.S.Ismail Mohideen, K.Prasanna Devi, M. Devi Durga, “Fuzzy Transportation Problem of Octagon Fuzzy Numbers with α-Cut and Ranking Technique”, Dr.Ismail Mohideen et al, Journal of Computer – JoC, Vol.1 Issue.2, July-2016, pg-60-67.

[6] Dr.Chandrasekaran,G.Gokila, Juno Saju, “ Ranking of Octagonal Fuzzy Numbers for Solving Multi Objective Fuzzy Linear Programming Problem with Simplex Method and Graphical Method, International Journal of Scientific Engineering and Applied Science (IJSEAS) – Volume -1, Issue-5, August-2015.

[7] Dr.M.S.Annie Christi Int. “Transportation Problem with Pentagonal Intuitionistic Fuzzy Numbers Solved Using Ranking Technique and Russell’s Method, Journal of Engineering Research and Applications, ISSN: 2248 – 9622, Vol.6.Issue 2, (part-4), Feb 2016, pp.82-86.

[8] Nagoor Gani.A, Abbas. S,(2013) “A New method for solving in Fuzzy Transportation Problem”, Applied Mathematics Sciences, vol.7,No.28, pp.1357 – 1365.

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PROPERTIES OF FUZZY INNER PRODUCT SPACES

Asit Dey1and Madhumangal Pal2 1Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore-721102, India 2Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore-721102, India

ABSTRACT In this paper, natural inner product structure for the space of fuzzy n−tuples is introduced.

Also we have introduced the ortho vector, stochastic fuzzy vectors, ortho- stochastic fuzzy vectors, ortho-stochastic fuzzy matrices and the concept of orthogonal complement of fuzzy vector subspace of a fuzzy vector space.

KEYWORDS Ortho vector, Stochastic vector, Ortho-Stochastic vector, Orthogonal Complement, Orthostochastic matrix, Reflection.

Full Text: https://wireilla.com/papers/ijfls/V4N2/4214ijfls03.pdf Volume Link: https://wireilla.com/ijfls/vol4.html

REFERENCES [1] A.M.El-Ahmed and H.M.El-Hamouly, Fuzzy inner-product spaces, Fuzzy Sets and Systems, 44, 309- 326, 1991.

[2] S.Gudder and F. Latremoliere, Boolean inner-product spaces and Boolean matrices, Linear Algebra Appl., 431, 274-296, 2009.

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α -ANTI FUZZY NEW IDEAL OF PUALGEBRA

Samy M. Mostafa , Mokhtar A. Abdel Naby, Alaa Eldin I. Elkabany 1,2,3 Department of mathematics ,Ain Shams University, Roxy, Cairo

ABSTRACT In this paper, the notion α -anti fuzzy new-ideal of a PU-algebra are defined and discussed.

The homomorphic images (pre images) ofα -anti fuzzy new-ideal under homomorphism of a PU-algebras has been obtained. Some related result have been derived.

KEYWORDS PU-algebra, α -anti fuzzy new-ideal, the homomorphic images (pre images) ofα -anti fuzzy new-ideal. Mathematics Subject Classification: 03F55, 08A72

Full Text: https://wireilla.com/papers/ijfls/V5N3/5315ijfls01.pdf Volume Link: https://wireilla.com/ijfls/vol5.html

REFERENCES [1] K. Is´eki, “On BCI-algebras,” Mathematics Seminar Notes, vol. 8, no. 1, pp. 125–130, 1980.

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[6] S. M. Mostafa , M. A. Abdel Naby, A. I. Elkabany ,New View Of Ideals On PU-Algebra.

International Journal of Computer Applications (0975 – 8887) Volume 111 – No 4, February 2015.

[7] S. M. Mostafa , M. A. Abdel Naby, A. I. Elkabany, -Fuzzy new ideal of PU-algebra , Accepted 03 April 2015 in Annals of Fuzzy Mathematics and Informatics. [ 8] J. Neggers, Y.B. Jun and H.S. Kim, On d-ideals in d-algebras , Math. Slovaca , vol.49 (1999) , 243- 251.

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THINK FUZZY SYSTEM: DEVELOPING NEW PRICING STRATEGY METHODS FOR CONSUMER GOODS USING FUZZY LOGIC

Antonio Morim, Eduardo Sá Fortes, Paulo Reis, Carlos Cosenza, Francisco Doria, Armando Gonçalves Production Engineering Master’s Program, Federal University of Rio de Janeiro, Instituto Alberto Luiz Coimbra de Pós–Graduação e Pesquisa de Engenharia ,COPPE, Bloco G, Ilha do Fundão, 21945-970, Rio de Janeiro - Brasil

ABSTRACT The main purpose of this article is to present and explore potential applications in marketing administration related to pricingstrategyusingfuzzylogic. Considering the new trends in consumer behaviour in Brazil’s economy and the consistent growth of C and D social classes an application was developed by the authors to better understand and adjust pricing strategies: The Think Fuzzy System that combines fuzzy logic (COPPE Cosenza Model), and some other related strategic concepts, supported by mathematical microeconomic modeling, utility factor, indifference curves and an experiential hierarchic clustering model.

KEYWORDS Consumer behavior, think fuzzy system, fuzzy logic, pricing methods, microeconomic mathematical models

Full Text: https://wireilla.com/papers/ijfls/V7N1/7117ijfls01.pdf Volume Link: https://wireilla.com/ijfls/vol7.html

REFERENCES [1] ALAMGIR, M., et al.Influence of brand name on consumer decision making process - an empirical study on car buyers (2010). Ann. “Ştefancel Mare” Univ. Suceava. Fascicle Fac. Econ. Public Admin., 10 (2) (2010), pp. 142–153; [2] BAGOOZI, et al. (1999). The role of emotions in marketing. Journal of Academic Marketing Science, 27 (2) (1999), pp. 184–206 [3] BIDIN, NUZARARHIA et al (2016);7th. International Economics & Business Management Conference; [4] AAKER, David A.(2009), Marketing Research; Wiley & Sons, New York; [5] CHANG .C.,(2015). A hybrid decision-making model for factors influencing the purchase intentions of technology products: the moderating effect of lifestyle. Behaviour & Information Technology. Volume 34, Issue 12; [6] COSENZA, Carlos A. (2011), Notas de aula disciplina - Introdução à Lógica Fuzzy – COPPE – UFRJ; Rio de Janeiro; [7] COSENZA, Carlos A. (1981), - "A Industrial Location Model"- Working paper, Martin Centre for Architectural and Urban Studies, Cambridge University [8] DORIA, Francisco, A. (2011) – Notas de aula disciplina- Limites Computacionais e Modelagem Matemática – COPPE – UFRJ; Rio de Janeiro; [9] DORIA, Francisco A. & COSENZA, Carlos A. (2009), Crise na Economia. Editora Revan, Rio de janeiro; [10] GANIDEH, S. et al, 2011. Can Fuzzy Logic Predict Consumer Ethnocentric Tendencies? An Empirical Analysis in Jordan. Journal of Physical Science and Application, 100-106; [11] HENDERSON, James M. & QUANDT, Richard E. (1968), Teoria Microeconomica – Uma Abordagem Matemática. Biblioteca Pioneira de Ciências Sociais, São Paulo; [12] KOTLER P. (2012), Marketing Management, New Jersey, Simon & Schuster Co. [13] LAISoon, W., et al, (2013). Hybrid vehicle adoption - a conceptual study. J. Educ.

Vocat. Res. 4 (6), 165e168.

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OPTIMAL ALTERNATIVE SELECTION USING MOORA IN INDUSTRIAL SECTOR - A REVIEW

Karuppanna Prasad N1 and Sekar K2 1 Technical Training Centre, TVS Training and Services Ltd, Chennai, India 2 Department of Mechanical Engineering, National Institute of Technology, Calicut, India

ABSTRACT Modern manufacturing organizations tend to face versatile challenges due to globalization, modern lifestyle trends and rapid market requirements from both locally and globally placed competitors. The organizations faces high stress from dual perspective namely enhancement in science and technology and development of modern strategies. In such an instance, organizations were in a need of using an effective decision making tool that chooses out optimal alternative that reduces time, complexity and highly simplified. This paper explores a usage of new multi criteria decision making tool known as MOORA for selecting the best alternatives by examining various case study. The study was covered up in two fold manner by comparing MOORA with other MCDM and MADM approaches to identify its advantage for selecting optimal alternative, followed by extending MOORA with interval grey numbers, crisp and interval grey number and whitening coefficient and future scope of the present work concentrate on highlighting the scope and gap between MOORA, Multiplicative form of MOORA(MULTIMOORA) and Multi objective optimization on the basis of simple ratio analysis (MOOSRA) for numerous manufacturing and service applications.

KEYWORDS MADM, MCDM, MOORA, optimization, manufacturing sector, service sector

Full Text: https://wireilla.com/papers/ijfls/V6N2/6216ijfls01.pdf Volume Link: https://wireilla.com/ijfls/vol6.html

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FOREX DATA ANALYSIS USING WEKA

Luciana Abednego and Cecilia Esti Nugraheni Department of Informatics, Parahyangan Catholic University, Indonesia

ABSTRACT This paper conducts some experiments with forex trading data. The data being used is from kaggle.com, a website that provides datasets for machine learning and data scientists. The goal of the experiments is to know how to design many parameters in a forex trading robot.

Some questions that want to be investigated are: How far the robot must set the stop loss or target profit level from the open position? When is the best time to apply for a forex robot that works only in a trending market? Which one is better: a forex trading robot that waits for a trending market or a robot that works during a sideways market? To answer these questions, some data visualizations are plotted in many types of graphs. The data representations are built using Weka, an open-source machine learning software. The data visualization helps the trader to design the strategy to trade the forex market.

KEYWORDS Forex trading data, forex data experiments, forex data analysis, forex data visualization.

Full Text: https://wireilla.com/papers/ijfls/V11N1/11121ijfls03.pdf Volume Link: https://wireilla.com/ijfls/vol11.html

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Prosiding International Congress on Engineering and Information.

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[6] J. Norris, T. Bell, A. Gaskill (2010). Mastering the Currency Market: Forex Strategies for High- and Low-Volatility Markets.McGraw-Hill.