Journal of Intelligent & Fuzzy Systems - Volume 25, issue 2

Authors: Eslamipoor, R. | Haji, M. Janizade | Sepehriar, A.

Article Type: Research Article

Abstract: Due to the vague nature of fuzzy numbers, ranking them according to their magnitude is an interesting area of fuzzy numbers. For this reason, several techniques have been proposed for ranking them. Each of these techniques has shown non-intuitive results in specific cases. Cheng employed “distance method” for ranking fuzzy numbers in Ref [3]. Then Chu and Tsao in [5] found another method. In this article, some problems of Cheng distance method is indicated and then a new revised method for ranking fuzzy numbers has been proposed which can avoid problem for ranking fuzzy numbers. The considerable priority of the …proposed method is its simplicity and easiness in calculation with distance method. For showing the superiority of this method some numerical examples is illustrated, recognizing its dominance over the deficiencies existing in other resembled ranking approaches. Show more

Keywords: Fuzzy ranking, fuzzy set, centroid point, generalized fuzzy numbers

DOI: 10.3233/IFS-120643

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 373-378, 2013

Authors: Özek, Cebeli | Çelik, Yahya Hışman | Özek, Müzeyyen Bulut

Article Type: Research Article

Abstract: Deep drawing process is one of the widely used methods in sheet-metal forming. With the deep drawing method, products of various geometrical shapes such as saucepans, tubes, perfume and soft drink cans can be obtained easily. Therefore, the optimization of the deep drawing process is very important for the industry. In conventional deep drawing method, no angle is given to the surfaces of die and pressure plate. Both die and pressure plate and the geometrical shape of die and punch have a significant effect on drawing ratio. In this study, the effect of angles and radii on the drawing ratio …of blank holder and punch forces were theoretically calculated and experimentally investigated in order to deep drawing the DIN EN 10130-91 sheet by giving angles on the die/blank holder surfaces and radii on the punch edge surfaces. In addition, the data obtained from the experimental study were calculated with the Fuzzy Logic Model and the optimum and the lowest drawing ratios for the die and punch radius as well as the die/blank holder were determined. The optimum drawing ratio in the experimental study was obtained as β = 2.3, when the die and punch radius was R = 10 mm and the die/blank holder angle was θ = 12.5°, and as β = 2.2 in the Fuzzy Logic model. The lowest drawing ratio was obtained as β = 1.8 when the blank holder angle was θ = 0° in the experimental study and as β = 1.82 in the Fuzzy Logic model. Show more

Keywords: Deep drawing dies, The Fuzzy Logic, drawing ratio

DOI: 10.3233/IFS-2012-0644

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 379-388, 2013

Authors: de Castro, Thiago N. | Souza, Francisco | , José M.B. | Alves, | Pontes, Ricardo S.T. | dos Reis, Laurinda L.N. | Daher, Sérgio

Article Type: Research Article

Abstract: The knowledge about the seasonal rainfall in some Brazilian regions is essential for agriculture and the adequate management of water resources. For this purpose, linear and nonlinear models are commonly used for seasonal rainfall prediction, while some of them are based on Artificial Neural Networks, demonstrating great potential as shown in literature. According to this tendency, this work presents a rainfall seasonal forecast model based on a neuro-fuzzy technique called Neo-Fuzzy Neuron Model. Improved performance by using this approach has been obtained in terms of reduced root mean square error (RMSE) and increased correlation between predicted and real output when …compared with dynamic downscaling model using the Regional Spectral Model. Experimental results show the effectiveness of the proposed method in predictions regarding the first four trimesters from year 2002 up to the current one. Show more

Keywords: Seasonal rainfall prediction, ANN, neo-fuzzy neuron, dynamic model

DOI: 10.3233/IFS-2012-0645

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 389-394, 2013

Authors: Rahmany, Sajjad | Basiri, Abdolali | Farahani, Hamed | Borzabadi, Akbar Hashemi

Article Type: Research Article

Abstract: This paper presents a novel approach for finding positive solution of fully fuzzy polynomial equations systems employing Gröbner bases benefits. First, the system of fully fuzzy polynomial equations is converted to an equivalent crisp polynomial equations system. Then, using Gröbner basis properties a criteria for determining existence and finding positive fuzzy solutions of original system is introduced. The big advantage of the proposed method lies in the fact that it attains all positive fuzzy solutions of problem at a time. Finally, some applied numerical examples are illustrated to demonstrate the proficiency of the given approach.

Keywords: Fuzzy numbers, fully fuzzy polynomial equations systems, Gröbner bases, affine varieties

DOI: 10.3233/IFS-2012-0646

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 395-402, 2013

Authors: Allam, Fayrouz | Nossair, Zaki | Gomma, Hesham | Ibrahim, Ibrahim | Abdelsalam, Mona

Article Type: Research Article

Abstract: Current insulin therapy for patients with type 1 diabetes often results in high variability in blood glucose concentration and may cause hyper-and hypoglycemic episodes. Closing the glucose control loop with a fully automated control system improves the quality of life for insulin-dependent patients. This paper presents a nonlinear model predictive control technique for glucose regulation in type 1 diabetic patients. The proposed technique uses a neural network as a nonlinear model for prediction of future glucose values and a fuzzy logic controller (FLC) to determine the insulin dose required to regulate the blood glucose level, especially after unmeasured meals. In …the proposed technique, to avoid errors of meal estimation, the patient is not required to enter any data such as the meal time and size which was, in previous systems, necessary to determine the insulin bolus. The use of neural networks in predicting future glucose levels helps the proposed control strategy to handle delays associated with insulin absorption and time-lag between subcutaneous glucose readings and the plasma glucose level. The FLC uses the predicted glucose values to determine the required insulin bolus. A feed forward neural network (FFNN) and a recurrent neural network (RNN) are tested and evaluated as nonlinear glucose prediction models. Simulation results for three meal challenges are demonstrated. our results indicate that, the use of a neural network as a predictor along with a FL controller can decrease the postprandial glucose concentration, avoids hyper glycemia, and dynamically responds to glycemic challenges. The simulation results also indicate that, the use of a RNN in glucose prediction gives better results than the use of a FFNN. The RNN provides much better prediction performance than the FFNN especially at longer prediction horizons. Show more

Keywords: Prediction, type-1 diabetes, RNN, FFNN, FLC

DOI: 10.3233/IFS-120648

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 403-413, 2013

Authors: Hashemi, M.S. | Malekinagad, J.

Article Type: Research Article

Abstract: In this paper, the homotopy analysis method (HAM) is proposed to obtain a semi-analytical solution of the fuzzy wave-like equations with variable coefficients. This method contains the auxiliary parameter $\hbar$, which provides us a simple way to adjust and control the convergence region of solution series. Convergency of HAM for the fuzzy wave-like equations with variable coefficients has been considered and some examples are given to illustrate its power and efficiency.

Keywords: Homotopy analysis method, fuzzy wave-like equations, auxiliary parameter, variable coefficient

DOI: 10.3233/IFS-120649

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 415-428, 2013

Authors: Kalaichelvi, V. | Karthikeyan, R. | Sivakumar, D.

Article Type: Research Article

Abstract: The weld quality is generally controlled by the welding parameters. In gas metal arc welding process, the welding parameters are inter related and the adjustment of one parameter may affect another parameter and hence it is considered as a non-linear process. The non-linear nature of the welding system makes it difficult to implement a conventional control method. Fuzzy logic control is an attractive alternative approach. The performance of fuzzy controller will be very much dependent on the knowledge provided to the system. Therefore in recent years, more research has been devoted to augment the approximate reasoning method of fuzzy systems …with genetic algorithms. In the present work, genetic algorithm tuned conventional controller is implemented for gas metal arc welding system. Its performance is compared with that of genetic algorithm based fuzzy logic controller. Show more

Keywords: Gas metal arc welding system, welding current, arc voltage, conventional controller, fuzzy logic controller, genetic algorithm

DOI: 10.3233/IFS-120650

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 429-440, 2013

Authors: Jiménez, F. | Sánchez, G. | Vasant, P.

Article Type: Research Article

Abstract: In this paper we propose a multi-objective optimization approach to solve nonlinear fuzzy optimization problems. Solutions in the Pareto front correspond with the fuzzy solution of the former fuzzy problem expressed in terms of the group of three parameters (x* , μ, α), i.e., optimal solution - degree of satisfaction - vagueness factor. The decision maker could choose, in a posteriori decision environment, the most convenient optimal solution according to his degree of satisfaction and vagueness factor. Additionally, an ad-hoc Pareto-based multi-objective evolutionary algorithm, ENORA-II, is proposed and validated in a production planning optimization environment. A real-world industrial problem for …product-mix selection involving 8 decision variables and 21 constraints with fuzzy coefficients is considered as case study. ENORA-II has been evaluated with the existing methodologies in the field and results have been compared with the well-known multi-objective evolutionary algorithm NSGA-II. Show more

Keywords: Fuzzy optimization, production planning, pareto-based multi-objective evolutionary algorithms, NSGA-II

DOI: 10.3233/IFS-130651

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 441-455, 2013

Authors: Mahmoudzadeh, Morteza | Bafandeh, Ali. R.

Article Type: Research Article

Abstract: This paper presents that the consistency test with consideration of a tolerance deviation in fuzzy AHP proposed by L. C. Leung and D. Cao (2000) is not efficient and has some errors, hence a new method of fuzzy consistency test by direct fuzzification of (Quick Response) QR algorithm - which is one of numerical methods for calculating eigenvalues of an arbitrary matrix - has been proposed.

Keywords: Fuzzy AHP, consistency test, QR algorithm, genetic algorithm

DOI: 10.3233/IFS-120653

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 457-461, 2013

Authors: Ersoy, Bayram Ali | Davvaz, B.

Article Type: Research Article

Abstract: The notion of intuitionistic fuzzy sets was introduced by Atanassov as a generalization of the notion of fuzzy sets. In this paper, we apply this concept to Γ – semihypergroups and we introduce the notion of an intuitionistic fuzzy Γ – hyperideal of a Γ – semihypergroup. Then, we investigate some properties connected with intuitionistic fuzzy Γ – hyperideals in a Γ – semihypergroup.

Keywords: Hyperstructure, semihypergroup, Γ – semihypergroup, intuitionistic fuzzy set, Γ – hyperideal, intuitionistic fuzzy Γ – hyperideal

DOI: 10.3233/IFS-120654

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 463-470, 2013