Journal of Intelligent & Fuzzy Systems - Volume 36, issue 6

Authors: Wang, Guixiang | Wang, Xiaolian | Qin, Sen | Zhang, Guojing

Article Type: Research Article

Abstract: In this paper, the problem of ranking multi-dimensional uncertain information based on fuzzy order is studied. At first, a specific fuzzy order on the fuzzy ellipsoid number space is defined, with which we can set up a dynamic ranking method which changes with the change of the level r for some objects which can be characterized by some multichannel uncertain digital information. Then its properties are investigated, some related results are obtained. And then, we give a practical example to show how to set up a dynamic ranking method which changes with the change of the level r …for some objects which can be characterized by some multichannel uncertain digital information by using the fuzzy order proposed by us in the paper. Show more

Keywords: Fuzzy number, fuzzy ellipsoid numbers, order, fuzzy order, ranking multi-dimensional uncertain information

DOI: 10.3233/JIFS-18357

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6555-6566, 2019

Authors: Malhotra, Ruchika | Sharma, Anjali

Article Type: Research Article

Abstract:  In order to minimize the over-fitting and related factors that are caused by the high dimensionality of the input data in software defect prediction, the attributes are often optimized using various feature selection techniques. However, the comparative performance of these selection techniques in combination with machine learning algorithms remains largely unexplored using web applications. In this work, we investigate the best possible combination of feature selection technique with machine learning algorithms, with the sample space chosen from open source Apache Click and Rave data sets. Our results are based on 945 defect prediction models derived from parametric, non-parametric and ensemble-based …machine learning algorithms, for which the metrics are derived from the various filter and threshold-based ranking techniques. Friedman and Nemenyi post-hoc statistical tests are adopted to identify the performance difference of these models. We find that filter-based feature selection in combination with ensemble-based machine learning algorithms not only poise as the best strategy but also yields a maximum feature set redundancy by 94%, with little or no comprise on the performance index. Show more

Keywords: Feature selection, feature ranking, machine learning, web application quality

DOI: 10.3233/JIFS-18473

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6567-6578, 2019

Authors: Lu, Ke-Zhong | Liu, Li-Bin | Fang, Honglin | Liu, Lili

Article Type: Research Article

Abstract:  A novel high accuracy numerical method for a singularly perturbed convection-diffusion problem with two small parameters is presented. At first, the given problem is discretized by using a rational spectral collocation method in barycentric form with sinh transformation. By sinh transform, the original Chebyshev points are mapped into the transformed ones clustered near to the boundary layers of the domain. Them, a nonlinear unconstrained optimization problem is designed to determine the widths of boundary layers in sinh transform. Finally, a dual mutation differential evolution (DMDE) algorithm is proposed to solve the nonlinear unconstrained optimization problem, and a comparison of the …DMDE algorithm with other algorithms has been made, which shows that DMDE algorithm can get fast convergence and find better results. Show more

Keywords: Singularly perturbed convection-diffusion problems, rational spectral collocation method, optimization problem, differential evolution algorithm

DOI: 10.3233/JIFS-18573

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6579-6587, 2019

Authors: Zhang, Gangqiang | Li, Zhaowen | Liu, Meng | Xie, Ningxin | Lin, Funing

Article Type: Research Article

Abstract: Attribute reduction is an important issue in knowledge discovery and data mining. Applying rough set theory, information systems based on crisp (or explicit) features can be easily done attribute reductions, but there exists rarely deeper discussion about attribute reduction in fuzzy information systems (i.e. information systems based on vague or undefinable features). A fully fuzzy information system is an information system where each of its attributes determines a fuzzy set on the object set, this paper investigates cc -reduction in this information system. The concept of class-consistent is first introduced. Then, the class-consistent relation cc (P ) induced by the …given attribute subset P in a fully fuzzy information system is proposed. Next, the class-consistent reduction (for short, cc -reduction) in a fully fuzzy information system is proposed and studied along with its corresponding algorithm. Moreover, considering that homomorphism is a kind of tools to study relationships between two fully fuzzy information systems, invariant characterizations of fully fuzzy information systems under homomorphisms are obtained. Finally, a numerical experiment is employed to illustrate the practical significance and possible applications of cc -reduction in a fully fuzzy information system. Show more

Keywords: Rough set theory, fully fuzzy information system, cc-reduction, class-consistent relation, homomorphism, algorithm, characterization

DOI: 10.3233/JIFS-18627

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6589-6604, 2019

Authors: Saeidi, Majid | Niknam, Taher | Aghaei, Jamshid | Zare, Mohsen

Article Type: Research Article

Abstract:  Distribution network operators have been generally engaged over the last few decades toward distribution system automation to enhance reliability and efficiency of power systems. From the viewpoint of reliability, optimal sectionalizing switch placement is an effective strategy since it mitigates both power network asset cost and number of customers not supplied by outages. From efficiency perspective, introducing capacitors and distributed generations (DGs) and DGs optimal sitting in power distribution systems with the goal of volt/var control can reduce system loss and voltage deviation. In this regard, this paper proposes a methodology to determine the optimal location of sectionalizing switches and …DG units while the concept of Volt/Var control problem is also considered. The objective functions are formulated to enhance the network condition during normal and contingency conditions. A new enhanced sine cosine algorithm is proposed for providing the best compromise solution. A self-adaptive probabilistic mutation strategy is appended into the original algorithm to balance exploitation and exploration in order to achieve the promising search space and ultimately converge to the global or near-global optimum. A 33-bus IEEE test system is deployed to assess the superiority of the proposed framework. Show more

Keywords: Distributed generator (DG) placement, multi-objective optimization, sine cosine algorithm, switch placement, volt/var control

DOI: 10.3233/JIFS-18631

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6605-6617, 2019

Authors: Zhong, Yu | Shi, Fu-Gui | Zou, Jie-Tao | Zou, Chu-Yi

Article Type: Research Article

Abstract: In this paper, we introduce the degree to which a mapping C : L X ⟶ M is an (L , M )-fuzzy convexity. When ( X , C X ) and ( Y , C Y ) are (L , M )-fuzzy convex spaces to some extent, the degrees to which a mapping f : X ⟶ Y is convexity-preserving or convex-to-convex are defined. Finally, the degree to which a surjective mapping f : X ⟶ …Y is a quotient mapping is also defined. We not only give their characterizations but also discuss the relationships among them. Show more

Keywords: Convex structure, convexity-preserving mapping, convex-to-convex mapping, (L, M)-fuzzy convex space, (L, M)-fuzzy convexity degree

DOI: 10.3233/JIFS-18659

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6619-6629, 2019

Authors: Liao, Yu-Hsien

Article Type: Research Article

Abstract: By considering supreme-utilities among fuzzy level (decision) vectors, we introduce an index and its efficient extension to investigate power mensuration mechanism in the framework of multicriteria fuzzy transferable-utility (TU) games. We also adopt reduced games and related consistency to analyze the rationality for these two indexes. Further, alternative formulation for the efficient index is also proposed by applying excess function. Based on reduced game and excess function, we introduce different dynamic processes for the efficient index.

Keywords: Multicriteria fuzzy TU games, supreme-utility, reduced game, excess function, dynamic process

DOI: 10.3233/JIFS-18725

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6631-6640, 2019

Authors: Yang, Lanzhen | Mao, Hua

Article Type: Research Article

Abstract: In this study, we provide a generalization of fuzzy threshold graphs, and introduce three notions, which are intuitionistic fuzzy threshold graphs, intuitionistic fuzzy alternating 4-cycle, and threshold dimension of intuitionistic fuzzy graphs. Then we discuss some properties about intuitionistic fuzzy graphs, and obtain two main results. The first one is that under some conditions, an intuitionistic fuzzy graph is equivalent to an intuitionistic fuzzy threshold graph. The second one is that the underlying graph of an intuitionistic fuzzy threshold graph is a split graph, and conversely, a given split graph can be used to construct an intuitionistic fuzzy threshold graph. …Finally, we give two applications of intuitionistic fuzzy threshold graphs, which are used to control water resource and power resources, respectively. Through the two applications, we know that intuitionistic fuzzy threshold graphs are more appropriate than fuzzy threshold graphs in controlling water resource and power resource, because intuitionistic fuzzy sets are more suitable and powerful to deal with uncertainty and vagueness compared to fuzzy sets. Show more

Keywords: Intuitionistic fuzzy graphs, fuzzy threshold graph, intuitionistic fuzzy threshold graphs, intuitionistic fuzzy alternating 4-cycle

DOI: 10.3233/JIFS-18755

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6641-6651, 2019

Authors: Li, Gang | Li, Zhenbo

Article Type: Research Article

Abstract: Uninorms are an important generalization of triangular norms and triangular conorms, having a neutral element lying anywhere in the unit interval. Many different classes of uninorms have been discussed in literature. In this paper, a construction method for a class of left-continuous uninorms is proposed based on the representable uninorm. The idea stems from the rotation method. Some illustrative examples of such uninorms are provided.

Keywords: Uninorm, representable uninorm, additive generator, left continuity

DOI: 10.3233/JIFS-18758

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6653-6661, 2019

Authors: Zhao, Hu | Chen, Gui-Xiu | Zhang, Hong-Ying

Article Type: Research Article

Abstract:  In this paper, using the structures of (L , L )-fuzzy product supratopological spaces which were introduced by Hu Zhao and Gui-xiu Chen, we give a proof of generalized Tychonoff theorem in L -fuzzy supratopological spaces by means of implication operations.

Keywords: (L, M)-fuzzy supratopology, product topological spaces, fuzzy compactness, generalized Tychonoff theorem

DOI: 10.3233/JIFS-18796

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6663-6668, 2019

Authors: Tan, Bo | Guo, Jingbo | Chang, Guang | Xu, Qingfeng

Article Type: Research Article

Abstract: The estimation and detection of a weak magnetic dipole signal is a critical problem in magnetic target detection. The difficulty arises due to a latent variable in the model, which affects the estimation and detection performance, especially at low signal-to-noise ratios (SNRs). A non-probability-distribution expectation maximization (NPD-EM) algorithm is proposed to estimate the magnetic dipole signal with the latent variable at low SNRs. A reasonable value of an intermediate variable instead of the optimal one is determined without any probability information in the iteration of the NPD-EM algorithm, which overcomes an unknown probability distribution appearing in the traditional expectation maximization …(EM) algorithm and reduces the calculated amount by 3 orders of magnitude compared with the traditional EM algorithm. A statistic based on the NPD-EM algorithm representing an unbiased estimator of the target signal energy is constructed to detect the magnetic dipole signal at low SNRs, and an innovative compensation in the detector is introduced so as to reduce the noise influence on the statistic. The experiment results show that, the constructed detector is comparable to the ideal matching filter due to the attractive performance of the NPD-EM algorithm and the outstanding statistic. Show more

Keywords: EM Algorithm, estimation and detection, weak magnetic signal, latent variable, low signal-to-noise ratio

DOI: 10.3233/JIFS-18803

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6669-6684, 2019

Authors: Liu, Qian | Yang, Feng | Li, Ce

Article Type: Research Article

Abstract: Binarized normed gradients (BING) can be utilized as a preprocessing step for generic object proposal generation, and has attracted great attention because of its fast running and appropriate generalization performance. Recently, although some modified schemes were presented to improve the proposal localization quality, the mechanism of enhancing the performance is still an open problem. In this paper, Adaptive weighted binary normed gradients plus (AWBING Plus) algorithm is proposed, based on the BING method, which replaces the support vector machine (SVM) with adaptive weighted extreme learning machine (Adaptive WELM) to reduce the number of proposals, as well as comparable performance, by …using the multi-thresholding straddling expansion (MTSE) as the post-processing stage to enhance the localization quality. We explain the methodology of WELM applied to BING, and analyzed the effect of the improved WELM algorithm, which is named Adaptive WELM. The experimental results from PASCAL VOC2007, Microsoft COCO2014 and ILSVRC2013 show that the proposed approach achieved superior performance compared with other advanced methods on generic object proposal generation, and it runs faster as well. Show more

Keywords: generic object proposal generation, imbalanced data, BING, WELM

DOI: 10.3233/JIFS-18810

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6685-6701, 2019

Authors: Santamaria, Jorge L. | Valentin, Vanessa | Ross, Timothy J.

Article Type: Research Article

Abstract:  Concrete is influenced by affecting conditions during its production and construction processes. The literature reveals that there is limited understanding about the effect of unstructured factors (i.e., construction site factors) on concrete product. Crew experience, compaction method, mixing time, curing humidity, and curing temperature were selected to quantify their impact on concrete compressive strength, fabrication cost, and production rates. Each response was measured and utilized for fuzzy modeling. A Sugeno-type fuzzy inference system (FIS) was obtained for quantifying each response. Model validation was accomplished by plotting predicted versus experimental data while sensitivity analysis used Monte Carlo simulation and Spearman’s correlation …coefficients. Curing temperature was identified as the most influential factor for concrete compressive strength while mixing time was identified to have the largest impact on concrete cost and production rates. All FISs can be used as supporting tools to discern desired concrete operating conditions. Show more

Keywords: Construction site factors, concrete strength

DOI: 10.3233/JIFS-18950

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6703-6715, 2019

Authors: Guler Bayazit, Nilgun | Bayazit, Ulug

Article Type: Research Article

Abstract:  In the conventional fuzzy k-NN classification rule, the vote cast by each nearest neighboring known (labelled) sample on the class membership grades of the unknown (unlabelled) sample is formed by weighting the nearest neighbor’s class membership grades by the inverse of the nearest neighbor’s distance to the unknown sample. This paper proposes a modification of the weight (distance) used for each nearest neighbor by employing the geometrical relation among the nearest neighbor, its most informative known neighbor of the same class and the unknown sample. It is also proposed that this modification be only (conditionally) applied when the feature vector …of the unknown sample lies outside the convex hull of the feature vectors of the known samples of each class. Results on a large number of datasets from the UCI and KEEL repositories and synthetically generated datasets show that, in return for a modest increase in classification complexity over the original fuzzy k-NN rule, the proposed fuzzy k-NN rule offers a better classification accuracy than the accuracies of the original fuzzy kNN rule and most other nearest neighbor type algorithms. Show more

Keywords: k-nearest-neighbor, fuzzy, classification, distance, convex hull

DOI: 10.3233/JIFS-18974

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6717-6729, 2019

Authors: Kuo, R.J. | Cheng, W.C.

Article Type: Research Article

Abstract:  In this study, an intuitionistic fuzzy neural network (IFNN) with Gaussian membership function and Yager-generating function is proposed. Since intuitionistic fuzzy logic (IFL) considers membership, non-membership and hesitation values simultaneously, the incorporation of the concept of IFL into a fuzzy neural network (FNN) can enhance the performance of an FNN. A back-propagation learning algorithm is developed to optimize the IFNN parameters and weights. The proposed IFNN is applied to ten problems, including nonlinear control and prediction problems. The computational results indicate that the proposed IFNN is more efficient than conventional algorithms, such as artificial neural networks (ANN), fuzzy neural networks …(FNN), and a support vector regression (SVR). Show more

Keywords: Fuzzy neural network, intuitionistic fuzzy sets, fuzzy systems

DOI: 10.3233/JIFS-18998

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6731-6741, 2019

Authors: de Campos Souza, Paulo Vitor | Rezende, Thiago Silva | Guimaraes, Augusto Junio | Araujo, Vanessa Souza | Batista, Lucas Oliveira | da Silva, Gabriel Adriano | Silva Araujo, Vinicius Jonathan

Article Type: Research Article

Abstract: The growth of the computerization of processes and services has changed human relations and, as a consequence, have created new forms of attacks and frauds for users of digital equipment. Because many people use computers, smartphones, and e-mail to perform day-to-day tasks, various data traffic is susceptible to attack. This can undermine the competitiveness of a company that may have breached strategic information. Therefore, security and information management are fundamental factors for companies to keep due control and management of their business knowledge. Cyber attacks are represented by a growing worldwide scale of secrecy breach of relevant information and are …characterized as one of the significant challenges of the contemporary world. This article aims to propose a computational system based on intelligent hybrid models, which through fuzzy rules allows the construction of expert systems in attacks on cybernetic data of diverse natures. The tests were carried out with real bases of attacks on the database of governmental computerized devices. The model proposed in this paper uses fuzzy evolving data grouping concepts. The extreme learning machine performs the training and the logical neurons of the unineuron type are responsible for creating fuzzy rules capable of transforming the knowledge acquired by the model into a database for employee training in companies, construction of other computer systems and awareness of elements which may harm the integrity of the data of individuals and companies. The novelty of the intelligent technique presented in the paper is that the nature of cyber attacks defines the structure of the model because the techniques of fuzzification and regularization are based entirely on the complexity of the cybernetic invasions. The binary pattern classification tests confronted with traditional models of the literature prove that the proposal of this paper can maintain the accuracy of detection of cyber attacks and still manages to construct a set of rules that serve as knowledge for the companies that wish to protect their information from attacks devices. Show more

Keywords: Evolving fuzzy neural network, cyber attack, cyber protection, knowledge management

DOI: 10.3233/JIFS-190229

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6743-6763, 2019