Journal of Intelligent & Fuzzy Systems - Volume 35, issue 2

Authors: Gupta, Ranu | Pachauri, Rahul | Singh, Ashutosh

Article Type: Research Article

Abstract: A linear method based on local statistical parameters of the image to remove the speckles of ultrasound carotid artery medical image is presented in this article. Speckle is the main drawback of medical images and it should be removed before any further processing of images like edge detection and registration. The focus of this article is to filter the speckle efficiently and effectively even at higher density of noise. The filter is designed by keeping in mind that the local statistical parameters are important rather than global statistical parameters. The weighting factor is designed such that it is high for …similar areas and thus results into more smoothing without destroying the useful information, whereas it is low at the edges and thus less smoothing will be done. The filter is applied with the help of 5×5 sliding window. The noise ranging from 0.01–0.09 of variance is unnaturally inserted in the medical images through Matlab. The efficiency calculating parameters like Signal to Noise Ratio (SNR), Quality Index (Q), Mean Square Error (MSE), Similarity Index Measure (SSIM) and Edge Preserved Index (EPI) were used to evaluate the proposed technique. The suggested method is also compared with the existing local statistical mean variance filter for the said parameters in order to analyse the performance of the filter. Show more

Keywords: Medical images, ultrasound, speckle, local statistics

DOI: 10.3233/JIFS-169715

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1807-1816, 2018

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1817-1817, 2018

Authors: Pires, Danúbia | Serra, Ginalber

Article Type: Research Article

Abstract: A methodology to systems identification based on Evolving Fuzzy Kalman Filter, is proposed in this paper. The mathematical formulation using an evolving Takagi-Sugeno (TS) structure, is presented: the offline Gustafson Kessel (GK) algorithm is used for initial parametrization of antecedent of the fuzzy Kalman filter inference system, considering an initial data set; and an evolving version of the GK algorithm is developed for online parametrization of antecedent of the fuzzy Kalman filter inference system. A fuzzy recursive version of OKID (Observer/Kalman Filter Identification) algorithm is proposed for parametrizing the matrices A, B, C, D and K (state matrix, input influence …matrix, output influence matrix, direct transmission matrix, and Kalman gain matrix, respectively), in the consequent of the fuzzy Kalman filter inference system. Computational and experimental results from the estimation of the states and outputs of a dynamic system and a two-degree-of-freedom (2DoF) Helicopter, respectively, show the efficiency and applicability of the proposed methodology. Show more

Keywords: Evolving, fuzzy Kalman filter, Takagi-Sugeno

DOI: 10.3233/JIFS-17087

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1819-1834, 2018

Authors: Zhang, Feng-Xia

Article Type: Research Article

Abstract: Distributivity equation has been widely studied involving different classes of logical connectives or aggregation operators, such as implications, uninorms, t-operators and their generalizations. In this paper, we follow on these works by investigating the distributivity for uninorms and Mayor’s aggregation operators.

Keywords: Aggregation operators, uninorms, Mayor’s aggregation operators, distributivity equation

DOI: 10.3233/JIFS-171286

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1835-1849, 2018

Authors: Erginel, Nihal | Uluskan, Meryem | Küçük, Gamze | Altıntaş, Merve

Article Type: Research Article

Abstract: We propose project evaluation criteria by considering not only the Six Sigma approach, but also European Foundation for Quality Management (EFQM) model features, and introduce an evaluation model for completed Six Sigma projects. The proposed model uses seven main criteria: leadership, policies/strategies, main performance results, social results, employees, cooperation, and resources. These main criteria are enhanced by 18 sub-criteria. Due to the evaluation scale being based on human judgments, fuzzy set theory is an obvious methodology choice to account for uncertainty in the evaluation data. Type-2 fuzzy sets can provide flexibility for uncertainty by considering membership functions and their footprints. …We also propose an evaluation methodology for weighting the main and sub-criteria and for ranking completed Six Sigma projects through a fuzzy analytic network process (ANP) method with interval type-2 fuzzy sets. From our analysis, performance results were found to have the highest weight among the seven main criteria, while achieving project objectives was found to be the most effective criteria. Show more

Keywords: Six Sigma methodology, project evaluations, fuzzy sets, the EFQM model, interval type-2 fuzzy ANP

DOI: 10.3233/JIFS-171306

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1851-1863, 2018

Authors: Ma, Ying | Zhu, Xiatian | Zhu, Shunzhi | Wu, Keshou | Chen, Yuming

Article Type: Research Article

Abstract: Recent studies have shown sparse representation learning is a potentially promising method in pattern classification, but very few focused on class imbalanced problems involved in its applications and practice. This problem is particularly important, since it causes suboptimal classification performances, especially when the cost of misclassifying a minority-class example is substantial. Unlike the prior test sample sparse representation on balanced data sets, which cannot reflect the data distribution in real applications, we proposed a novel sparse representation learning algorithm called Balanced Sparse Representation Classifier (BSRC), considering the contribution from heavily under-represented of minority classes. Our solution first estimates the contribution …of training sample in each class, and then identifies the nearest neighbors with the largest contributions. After that, the test data is expressed based on linear combination of all the nearest samples. Finally, the decision has been made according to sum of contribution for each class. Moreover, we also present the kernel extension of the proposed classifier to deal with complex data. Experimental results also show that with the proposed learning approach, it is possible to design better method to tackle the class imbalance problem in sparse representation learning. Show more

Keywords: Machine learning, sparse representation, class imbalance, classification

DOI: 10.3233/JIFS-171342

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1865-1874, 2018

Authors: Zhou, Lintao | Wang, Yanfeng | Jiang, Yong

Article Type: Research Article

Abstract: Investment project assessment is one of the most critical activities in the investment process, which requires a trade-off between multiple attributes exhibiting vagueness and imprecision with the involvement of a group of experts. The multiple attribute group decision-making (MAGDM) method based on trapezoidal interval type-2 fuzzy sets (IT2FSs) is suitable for the decision makers to deal with this problem. However, some shortcomings in the arithmetic operations of trapezoidal IT2FSs, and some of ranking methods in some cases are invalid. In this paper, the arithmetic operations of trapezoidal IT2FSs are redefined, which can overcome some shortcomings of the ones developed in …existing literature. And then, a new ranking method of trapezoidal IT2FSs based on the incentre point of fuzzy sets is developed. In order to verify the proposed method, thirteen fuzzy sets are used in comparison with some of the existing methods, and the comparison results demonstrate the superiority of the proposed method. Finally, the proposed method is integrated into the technique for order preference by similarity to the ideal solution (TOPSIS) method and an illustrative example in investment project assessment is presented to evaluate the effectiveness of the proposed methods. Show more

Keywords: Investment project assessment, interval type-2 fuzzy sets, multiple attribute group decision-making

DOI: 10.3233/JIFS-171403

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1875-1888, 2018

Authors: Bi, Yunrui | Sun, Zhe | Lu, Xiaobo | Sun, Zhixin | Liu, Di | Liu, Kun

Article Type: Research Article

Abstract: Traffic congestion has become a serious phenomenon in the cities. In order to achieve the effective control of intersections, multi-lane four-phase intersection is studied. The corresponding queue length model and vehicular delay model are established. Aiming at the dynamic uncertainty problem in the intersection, a type-2 fuzzy logic controller is designed. The green time of each phase is dynamically decided according to the real-time traffic information for purpose of achieving the smallest vehicular average delay, so as to enhance the traffic efficiency in the intersection. The excellent performance of the designed controller is confirmed through simulation experiments under different conditions. …Finally, in view of the difficulty of parameter settings in type-2 fuzzy controller, DNA evolutionary algorithm is applied to online optimize and adjust the parameters of membership function. One group of parameters is difficult to fit all traffic situations, so on-line optimization and adjustment is necessary for reflecting the real-time change of traffic flow in time, which is of great significance for the practical application. The experimental results indicate that the online optimized type-2 fuzzy traffic control method has better effect. Show more

Keywords: Type-2 fuzzy logic control, traffic signal control, optimization, DNA evolutionary algorithm

DOI: 10.3233/JIFS-171405

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1889-1904, 2018

Authors: Akram, Muhammad | Sarwar, Musavarah | Borzooei, Rajab Ali

Article Type: Research Article

Abstract: A hypergraph is one of the most developing area for modeling various practical problems in different fields, including computer science, biological sciences, social networks and psychology. Our main discussion in this research paper is to apply the notion of intuitionistic fuzzy sets to extend the theory of hypergraphs. We introduce the concept of isomorphism, dual intuitionistic fuzzy hypergraph, intuitionistic fuzzy line graph and 2-section of an intuitionistic fuzzy hypergraph. We present some applications of intuitionistic fuzzy hypergraphs in planet surface networks, selection of authors of of intersecting communities in a social network and grouping of incompatible chemical substances. We design …certain algorithms to construct dual intuitionistic fuzzy hypergraph, intuitionistic fuzzy line graph and the selection of objects in decision-making problems. Show more

Keywords: Isomorphism, intuitionistic fuzzy hypergraph, planet surface network, social network, incompatible chemicals Mathematics Subject Classification 2010: 05C65, 05C85, 05C90, 03E72

DOI: 10.3233/JIFS-171443

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1905-1922, 2018

Authors: Niroomand, Sadegh

Article Type: Research Article

Abstract: A linear programming with triangular intuitionistic fuzzy parameters is focused in this paper. As a shortcoming, all the solution approaches of the literature for this problem are constructed based on ranking functions, where, use of different ranking functions may result in different solutions. In this study for the first time an approach with no ranking function is developed for the problem. For this aim, the triangular intuitionistic fuzzy objective function is decomposed to a multi-objective function, and the problem is converted to a multi-objective crisp problem. As another contribution, in order to solve the obtained multi-objective problem for its efficient …solutions, a new multi-objective optimization approach was developed and suited to the obtained crisp multi-objective problem. The computational experiments of the study, show the superiority of the proposed multi-objective optimization approach over the existing approaches of the literature. Show more

Keywords: Linear programming, triangular intuitionistic fuzzy number, multi-objective optimization, fuzzy programming approach

DOI: 10.3233/JIFS-171504

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1923-1934, 2018