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

Authors: Nandi, Arup Kumar | Deb, Kalyanmoy | Datta, Shubhabrata | Orkas, Juhani

Article Type: Research Article

Abstract: Evaluation of equivalent thermal conductivity (ETC) of particle reinforced polymer composites (PRPCs) is a complex process since some of the influencing parameters are associated with uncertainties and ambiguities (e.g., dispersion state of filler in the matrix, uniformity of filler particle size and shape, etc). By realizing it, an attempt has been made to model the ETC of 2-phase PRPCs based on a genetic fuzzy approach. The model performance is rigorously tested in three stages to establish its practical applicability: based on experimental data (not used in model development) cited in literature, new measured thermal conductivities of flexible mould composites and …finally by assessing the feasibility of values of missing data in the reported in-complete data set based on the developed model. Estimations of ETC by the proposed model are shown reasonable, even better compare to existing models and suggesting a generic model applicable to a wide range of 2-phase PRPCs. Show more

Keywords: Genetic fuzzy approach, modeling, particle reinforced polymer composites, effective thermal conductivity

DOI: 10.3233/IFS-2012-0633

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 259-270, 2013

Authors: Soleymani, S. | Bastam, M. | Mozafari, B.

Article Type: Research Article

Abstract: One of the most important components of power systems are power transmission lines. Different types of faults in power transmission lines may cause disruption of power transmission or damage power system equipment, as well as it can effect on the power quality of the entire network. Therefore accurate estimation of fault location in power transmission for restoring power transmission at the shortest possible time with the lowest disruption at power transmission is vital. On the other hand accurate estimation of type and location of faults in transmission lines can save time and maintenance cost of power system equipment. In this …paper, EMTP software is used to simulate a real power grid model with 100 km transmission line for different fault locations and fault resistances. Then Discrete Wavelet Transform (DWT), which is anadvance signal processing tool, is applied to acquire fundamental harmonics of three phase voltage and current signals at the end of transmission line. To classify type of faults and their locations, artificial neural network is utilizedat transmission line. The obtained results show that the error percentage in both location and fault typediagnosis is so low. Show more

Keywords: Artificial neural network, Discrete Wavelet Transform, fast fourier transform, faults of power system

DOI: 10.3233/IFS-2012-0634

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 271-277, 2013

Authors: Wang, Weize | Liu, Xinwang

Article Type: Research Article

Abstract: The notion of interval-valued intuitionistic fuzzy set (IVIFS) is a generalization of that of Atanassov's intuitionistic fuzzy set (AIFS). The fundamental characteristic of IVIFS is that the values of its membership function and non-membership function are intervals rather than exact numbers. In this paper, we define some Einstein operations on IVIFS and develop three arithmetic averaging operators, such as the interval-valued intuitionistic fuzzy Einstein weighted averaging (IVIFWAε ) operator, interval-valued intuitionistic fuzzy Einstein ordered weighted averaging (IVIFOWAε ) operator, and interval-valued intuitionistic fuzzy Einstein hybrid weighted averaging (IVIFHWAε ) operator, for aggregating interval-valued intuitionistic fuzzy information. The IVIFHWAε operator …generalizes both the IVIFWAε and IVIFOWAε operators. Moreover, we establish various properties of these operators and derive the relationship between the proposed operators and the exiting aggregation operators. Finally, we apply the IVIFHWAε operator to multiple attribute decision making with interval-valued intuitionistic fuzzy information. Show more

Keywords: Atanassov's intuitionistic fuzzy set (AIFS), interval-valued intuitionistic fuzzy set (IVIFS), Einstein t-norm, arithmetic averaging operator, multi-attribute decision making (MADM)

DOI: 10.3233/IFS-120635

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 279-290, 2013

Authors: Goudarzi, Pejman

Article Type: Research Article

Abstract: Many difficult engineering problems have found natural solutions which have been inspired from biological behaviors of the living kinds. Some important examples include neural networks, Genetic Algorithm (GA), DNA computing, artificial immune systems etc. Fair resource allocation strategies which are developed by many researchers are based on solving a form of constrained optimization problem. However, they are not necessarily lead to high-speed and stable solutions. There are plenty of high-speed fair rate allocation methods in the literature, some of them are based on fuzzy controllers for improving the convergence speed and are not necessarily optimal. Hence, in the current research, …the GA has been adopted for finding the optimum membership functions which must be used in the fuzzy controller. Stability analysis is presented to guarantee the convergence property of the algorithm. After simulating, the results show that using the hybrid fuzzy-genetic approach improves the conventional methods in convergence speed and results in fewer oscillations in allocated rates. Show more

Keywords: Genetic algorithm, evolutionary computation, optimization, penalty function, elastic

DOI: 10.3233/IFS-2012-0636

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 291-302, 2013

Authors: Zhai, Junhai | Zhai, Mengyao | Bai, Chenyan

Article Type: Research Article

Abstract: Fuzzy rough attribute reduct has been widely used to remove redundant real-valued attributes without discretizing. By now, there are two existing fuzzy rough attribute reduct methods, one is based on dependency function and another based on discernibility matrix. The former proposed by Shen in 2002 can deal with fuzzy decision table (FDT) with real-valued condition attributes and fuzzy decision attributes. However, this algorithm is not convergent on many real datasets, and the computational complexity of the algorithm increases exponentially with the number of input variables. The latter proposed by Tsang in 2008 can only deal with fuzzy decision table with …real-valued condition attributes and symbol-valued decision attributes. In this paper, we extend the latter method and propose two algorithms for calculating all fuzzy rough attribute reducts to deal with fuzzy decision table with real-valued condition and decision attributes. The first algorthim is designed for computing all fuzzy attribute reducts, yet the computation complexity of this algorithm increases exponentially with the number of attributes. The second one which can find one near-optimal reduct is a heuristic variant of the first algorithm. The experimental results show the proposed method is feasible and effective. Show more

Keywords: Rough sets, fuzzy rough sets, attribute reduct, fuzzy discernibility matrix, fuzzy decision table

DOI: 10.3233/IFS-2012-0637

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 303-313, 2013

Authors: Yang, Wu-E | Wang, Jian-Qiang

Article Type: Research Article

Abstract: Vague linguistic numbers are especially adaptive to describe the evaluations of alternatives in multi-criteria decision making. Such description reveals the DM's preference and hesitant degree simultaneously. For handling the uncertainty in setting the weights of criteria, a fuzzy matrix game related with the initial decision matrix is established. This fuzzy game model is then transformed to a linear programming. By solving this programming, the weights of criteria are obtained. The weighted arithmetic average operator of vague linguistic numbers yields the aggregated ranking values of alternatives. An example illustrates the procedure of the proposed method.

Keywords: Decision analysis, MCDM, linguistic modeling, vague linguistic number, gaming

DOI: 10.3233/IFS-2012-0638

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 315-324, 2013

Authors: Barin, Alexandre | Canha, Luciane Neves | Abaide, Alzenira da Rosa | Magnago, Karine Faverzani | Matos, Manuel Antônio | Orling, Ricardo Barreira

Article Type: Research Article

Abstract: The aim of this work is to demonstrate a novel fuzzy-based expert system for selecting renewable energy technologies (RET). Fuzzy multi-rules and fuzzy multi-sets are used to evaluate the main operational characteristics of six types of RET fuelled by biogas from municipal solid waste (MSW) landfills. The construction of the fuzzy multi-rules and fuzzy multi-sets is based on the following method: Mamdani controller using the Max-Min (inference process) and Center of Gravity (defuzzification process). Several criteria are used for the investigation: costs, efficiency, cogeneration, life-cycle and environmental impacts. The fuzzy-based expert system considers three different settings with two different constraints: …costs and environmental impacts. One of the most relevant aspects presented by this work is about the previous criteria rank. It was created according to the different relevance observed among the attributes. The purpose of the proposed arrangement is to facilitate the understanding of the methodology and to increase the possibility of incorporating the decision makers' preferences on the decision-aid process. These aspects are essential to strengthen the final decision. Show more

Keywords: Biogas, fuzzy multi-rules and fuzzy multi-sets, municipal solid waste landfills, renewable energy technologies

DOI: 10.3233/IFS-2012-0639

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 325-333, 2013

Authors: Cano-Izquierdo, Jose-Manuel | Pinzolas, Miguel | Gómez-Sánchez, Eduardo | Araúzo-Bravo, Marcos J. | Ibarrola, Julio

Article Type: Research Article

Abstract: Fuzzy ART and Fuzzy ARTMAP models arise from the synergy between the Fuzzy Set Theory and the Adaptive Resonance paradigm (ART). In this work, the performance of these models and the use of Fuzzy ARTMAP for function approximation are studied. In a first analysis, a relationship between the model parameters and the features of the generated categories is established. In the second part, the connection between these categories and the capacity of prediction of the model is analytically described. Joining these two studies, the link between the parameters and the prediction error of the model is found, in the form …of bounds for the prediction error depending on the model parameters and the characteristics of the data used in the learning. These results provide a quantitative description of the parameter influence on the architecture behavior, opening the use of Fuzzy ARTMAP as a model for the unknown dynamic system identification from input/output data. To illustrate the theoretical developments, several experiments have been carried out using different kinds of functions, which show the accuracy of the proposed bounds. Show more

Keywords: Adaptive resonance theory, fuzzy ARTMAP, function identification, neuro-fuzzy

DOI: 10.3233/IFS-2012-0640

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 335-350, 2013

Authors: Islam, S.M. Taohidul | Chik, Zamri | Mustafa, Mohd. Marzuki | Sanusi, Hilmi

Article Type: Research Article

Abstract: This paper presents a technique to obtain the outcomes of soil dry density and optimum moisture contents with artificial neural network (ANN) for compacted soil monitoring through soil resistivity measurement in geotechnical engineering. The compacted soil monitoring through soil electrical resistivity shows the important role in the construction of highway embankments, earth dams and many other engineering structure. Generally, soil compaction is estimated through the determination of maximum dry density at optimum moisture contents in laboratory test. To estimate the soil compaction in conventional soil monitoring technique is time consuming and costly for the laboratory testing with a lot of …samples of compacted soil. In this work, an ANN model is developed for predicting the relationship between dry density of compacted soil and soil electrical resistivity based on experimental data in soil profile. The regression analysis between the output and target values shows that the R2 values are 0.99 and 0.93 for the training and testing sets respectively for the implementation of ANN in soil profile. The significance of our research is to obtain an intelligent model for getting faster, cost-effective and consistent outcomes in soil compaction monitoring through electrical resistivity for a wide range of applications in geotechnical investigation. Show more

Keywords: Soil compaction, ANN modeling, electrical resistivity, dry density

DOI: 10.3233/IFS-2012-0641

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 351-357, 2013

Authors: Aplak, Hakan Soner | Türkbey, Orhan

Article Type: Research Article

Abstract: Decision process can be summarized as a process that helps for choosing the optimal alternatives according to suggested objectives by evaluating all environmental effects in problem solving. Nowadays, since environmental effects are more complex, imprecise and multilateral, fuzzy set theory and game theory are widely preferred instruments in decision making process. The aim of this study is to present a hybrid multi-criteria decision making approach which uses artificial intelligence techniques such as fuzzy logic and game theory. This process is considered in two person non-constant sum game theory perspective. The methods in literature about related topics (such as scenario planning …and fuzzy TOPSIS) are examined and a hybrid decision making methodology that comprises many decision methods is formed. All phases of this approach are executed in game theory perspective by evaluating mutual strategies of players. In the study, the methodology is explained and a fictitious international disagreement case is used as a numerical example to demonstrate the validity and applicability. Show more

Keywords: Game theory, fuzzy sets, multi criteria analysis

DOI: 10.3233/IFS-2012-0642

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 359-371, 2013

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

Authors: Yu, Dejian

Article Type: Research Article

Abstract: An interval-valued intuitionistic fuzzy set (Atanassov and Gargov, 1989) is one of the generalizations of fuzzy set theory. Since it is characterized by a membership range and a non-membership range, it is very useful in modeling real life problems. This study develops an approach to deal with the decision making problems in the context of interval-valued intuitionistic fuzzy sets. First, the generalized interval-valued intuitionistic fuzzy weighted geometric (GIIFWG) and generalized interval-valued intuitionistic fuzzy ordered weighted geometric (GIIFOWG) operators are proposed to aggregate the interval-valued intuitionistic fuzzy values. Then, the properties and special cases of these operators are studied in detail. …Furthermore, an example is provided to illustrate the developed methods. The results reveal that different parameters of the aggregation operators may bring out different ranks of alternatives. Show more

Keywords: Interval-valued intuitionistic fuzzy set, generalized geometric aggregation operator, OWA operator

DOI: 10.3233/IFS-120652

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 471-480, 2013

Authors: da Silva, Wilson Ricardo Leal | Štemberk, Petr

Article Type: Research Article

Abstract: With a goal of reducing the overall production process variability of Ready-mixed concrete (RMC) and decreasing production costs, a fuzzy logic-based expert system was developed. Inspired by shooting sports, the system guides the plant chief technician by recommending the actions to be taken to reduce variability. Such guidance is based on the evaluation of the compressive strength and coefficient of variation results from the samples molded by those responsible for testing concrete. The system was tested in a RMC plant with monthly production of ≈ 3300 m3 . The results indicate that no major interventions are necessary for the investigated …plant; however, training is likely recommended for some of the staff so as to attain a lower overall variability. These conclusions are in agreement with the technician's interpretation, proving that the system is satisfactory for application in the process. Additionally, a cost analysis was performed, and the results show that a potential reduction of 5.6 % in the monthly production cost can be reached. This represents an attractive reduction since the RMC profit margin is about 8.0 %. Show more

Keywords: Expert system, fuzzy logic, Ready-mixed concrete, compressive strength

DOI: 10.3233/IFS-120655

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 481-491, 2013

Authors: Di Nuovo, Alessandro | Ascia, Giuseppe

Article Type: Research Article

Abstract: Following the successful applications of the fuzzy models in various application domains, the issue of automatic generation of Fuzzy Rule Based Systems (FRBSs) from observational data was widely studied in the literature and several approaches have been proposed. Most approaches were designed to search for the best accuracy of the generated model, neglecting the interpretability of FRBSs, which is commonly recognized as one of main reasons of the success of fuzzy linguistic models. To fill this gap, a current hot issue in linguistic fuzzy modelling area is the search for a good accuracy-interpretability trade-off. At present, despite the work done, …the definition of interpretability is rather problematic. In fact there is still not an universal index widely accepted. This is mainly because the understanding of fuzzy systems is a subjective task that strongly depends on the background of the person who makes the assessment. In consequence an effective way consists of proposing a fuzzy system index instead of numerical ones. In this paper, we give our contribution proposing a fuzzy system as index to measure both fuzzy rule and set levels complexity of the system. At best of our knowledge there are not indexes to preserve interpretability of a FRBS when it is deep tuned, to this end a new fuzzy system index is formulated and an implementation is presented. To show how our fuzzy system index could be used for interpretability preservation, it is integrated in a classical Multi-Objective Evolutionary Algorithm (MOEA) and its results are presented through six comparative examples based on well-known data sets in the pattern classification field. Show more

Keywords: Interpretable fuzzy systems, fuzzy rule based classifier systems design, Fuzzy linguistic modifiers, genetic fuzzy systems

DOI: 10.3233/IFS-120660

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 493-504, 2013

Authors: Zhang, Qinghua | Xiao, Yu | Wang, Guoyin

Article Type: Research Article

Abstract: Vague set, as well as intuitionistic fuzzy set, is a further generalization of fuzzy set. Instead of using point-based membership in fuzzy set, interval-based membership is used in vague set. As a result, vague set has more powerful ability to process fuzzy information than fuzzy set in some degree. By exploring the uncertainty of vague set, the disadvantages of existing methods for measuring fuzziness of vague set are analyzed. In order to overcome these disadvantages in existing measuring methods and better characterize uncertainty of vague set, the concept of fuzziness interval of vague set is defined and a new measuring …method, average fuzziness is proposed based on integral calculus method. Accordingly, the proposed method is compared with the existing methods in property, which shows the accuracy of measuring fuzziness of vague set is better than the other methods. Whereas the advantages of the average fuzziness of a vague set, the method of transforming vague set into fuzzy set is proposed and discussed. Show more

Keywords: Vague set, intuitionistic fuzzy set, fuzzy set, fuzziness, uncertainty

DOI: 10.3233/IFS-2012-0571

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 2, pp. 505-515, 2013