Journal of Intelligent & Fuzzy Systems - Volume 38, issue 3

Authors: Najib, Fatma M. | Ismail, Rasha M. | Badr, Nagwa L. | Gharib, Tarek F.

Article Type: Research Article

Abstract: Recent applications such as sensor networks generate continuous and dynamic data streams. Data streams are often gathered from multiple data sources with some incompleteness. Clustering such data is constrained by incompleteness of data, data distribution, and continuous nature of data streams. Ignoring missing values in incomplete data clustering, especially in high missing rates decreases the clustering performance. Traditional clustering is applied on the whole data without dealing with data distribution. This paper presents an efficient framework called Fuzzy c-means clustering for Incomplete Data streams (FID) that works adaptively with incomplete data streams even with high missing rates. The proposed FID …estimates missing values based on the corresponding nearest-neighbors’ intervals. To overcome the previously mentioned data streams clustering problems, the continuous clustering mechanism is adopted and extended to accurately handle the incomplete data streams. Experimental results using two different data sets prove the efficiency of the proposed FID comparing to the alternative approaches. Show more

Keywords: Data streams, incomplete data clustering, fuzzy clustering, nearest neighbor rule

DOI: 10.3233/JIFS-191184

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3213-3227, 2020

Authors: Sánchez, Daniela | Melin, Patricia | Castillo, Oscar

Article Type: Research Article

Abstract: In this paper dynamic parameter adjustment in particle swarm optimization (PSO) for modular neural network (MNN) design using granular computing and fuzzy logic (FL) is proposed. Nowadays, there are a plethora of optimization techniques, but their implementations require having knowledge about these techniques in order to establish their parameters, because the performance and final results of a particular technique depend on the optimal parameter values. For this reason, in this paper the fuzzy adjustment of parameters during the execution is proposed, and this proposal allows to adjust the parameters depending on current PSO behavior in each iteration. The proposed method …performs modular neural network optimization applied to human recognition using benchmark ear, iris and face databases. Two fuzzy inference systems are proposed to perform this dynamic adjustment, comparisons against a PSO without this dynamic adjustment (simple PSO) are performed to verify if the proposed adjustment using a fuzzy system is better improving recognition rate and execution time. The PSO variants presented in this paper are aimed at performing MNNs optimization. This optimization consists on finding optimal parameters, such as: the number of modules (or sub granules), percentage of data for the training phase, learning algorithm, goal error, number of hidden layers and their number of neurons. Show more

Keywords: Modular neural networks, granular computing, particle swarm optimization, fuzzy adaptation, human recognition, ear recognition, iris recognition, face recognition, pattern recognition

DOI: 10.3233/JIFS-191198

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3229-3252, 2020

Authors: Ko, Jung Mi | Kim, Yong Chan

Article Type: Research Article

Abstract:  We introduce the concepts of fuzzy join complete lattices and Alexandrov L -pretopologies in complete residuated lattices. We show that fuzzy join complete lattices, Alexandrov L -pretopologies, fuzzy meet complete lattices and Alexandrov L -precotopologies are equivalent. Moreover, we define L -preinterior operators (resp. L -preclosure operators) as a viewpoint of fuzzy joins (resp. fuzzy meet) and fuzzy rough sets. Furthermore their properties and examples are investigated.

Keywords: Complete residuated lattices, fuzzy join(meet)-complete lattices Alexandrov L-pre(co)topologies, fuzzy rough sets

DOI: 10.3233/JIFS-191344

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3253-3266, 2020

Authors: Gu, Jinheng | Liu, Changqing | Fu, Shenghui | Mao, Enrong | Pang, Changle

Article Type: Research Article

Abstract: Service-oriented design is used in product development to accommodate diverse customer requirements and provide a profit-making strategy. Existing designs encounter difficulties in assessing design alternatives systematically during conceptual design involving customer heterogeneity and cognition vagueness. To evaluate these alternatives, a new systematic service-oriented design is proposed. The fuzzy analytic hierarchy process is used to handle the subjectivity and uncertainty of expert judgments and customer desires. In addition, the structure of service-oriented design within a mapping information flow is illustrated and then associated with technical characteristics via the results of the House of Quality. A consideration of influential design factors is …developed to identify optimal alternative on the basis of the PageRank algorithm. Based on the integrated methods, a priority index is proposed to evaluate these alternatives, which can flexibly handle customer heterogeneity under limited technical conditions. At the same time, a design calculation program of a front axle suspension system was developed based on MATLAB GUI, which shows the design extensibility and robustness of the proposed approach. Overall, the results of the priority index-based method clearly demonstrate the superiority and appropriateness of the technique in selecting the optimal alternative. It also standardizes the design process from the case study of the front axle suspension system, provides rapid reasonable selection of the design scheme, and thereby improving intelligent design capacity from the perspective of product and its services. Show more

Keywords: Service-oriented design, fuzzy analytic hierarchy process, PageRank, MATLAB GUI, influential design factors

DOI: 10.3233/JIFS-191499

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3267-3284, 2020

Authors: Hashemi, S. Ahmad | Farrokhi, Hamid

Article Type: Research Article

Abstract: Self-Organization networking (SON) consists of function sets which are responsible for automatically reliable configuring, planning and optimizing next generation mobile networks. Effective self-organization functions improve the level of network key performance indicators by determining optimal network setting and continuously finding efficient solutions that will be very hard for experts to distinguish. Most current self-organization networking functions apply rule-based recommended systems to control network resources in which performance metrics are evaluated and the effective actions are performed in accordance with a set of command sequences which such algorithms are too complicated to design, because rules and command sequences should be derived …for each target index during each possible scenario. This research has proposed cognitive wireless networks as a fully intelligent approach to self-organization networking. We generalize the concept of network automation considering fuzzy-based self-organization networking functions as Q-learning problems in which, a framework is described to find the fuzzy optimal solution of linear programming optimization problem. The achieved results prove that the proposed cognitive approach, provides a prominent cellular framework for developing self-organization solutions, particularly where the relevance of metrics to the control indices is not clearly known. Also, assessment of the scheme in multiple-speed scenarios revealed that Q-learning load balancing obtains more accurate results compared to rule-based adaptive load balancing methods. This is particularly correct in dynamic networks, with high-speed users. Show more

Keywords: Next-generation mobile networks, reinforcement learning, handover optimization, load balancing, network automation

DOI: 10.3233/JIFS-191558

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3285-3300, 2020

Authors: Nilofer, Ms. | Rizwanullah, Mohd.

Article Type: Research Article

Abstract: In this paper a simplification of the CPP is measured, a set of important nodes is given in a linear order and the work is to path all edges at least once in such a technique that the advanced priority nodes are stayed as soon as possible. All roads in the networks are covered by postman tour.postman tour covering all the roads in the network. The solutions found here are valid for the case, where the cost of additional edges traversed is much bigger that the cost of delays and delay for the first priority node is much bigger than …the cost of delay for the second node, and so on. More detailed study of various cost functions may be an interesting topic for future research. Show more

Keywords: Graph, Eulerian tour, road network, higher priority node

DOI: 10.3233/JIFS-190035

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3301-3305, 2020

Authors: Peng, Xindong | Ma, Xueling

Article Type: Research Article

Abstract: Pythagorean fuzzy set (PFS), as a generalization of intuitionistic fuzzy set (IFS), is more suitable to capture the indeterminacy of the experts’ decision making information. This paper is designed to build new algorithm for managing multi-criteria decision making (MCDM) issue under Pythagorean fuzzy environment. First, we initiate a novel score function based Pythagorean fuzzy number (PFN). Later, we explore an algorithm for solving MCDM problem based on CODAS (COmbinative Distance-based ASsessment). Ultimately, the availability of method is stated by some numerical examples. The dominating traits of the developed algorithm, compared to some existing Pythagorean fuzzy decision making algorithms, are (1) …derive a ranking without the complex process; (2) achieve the optimal alternative without counterintuitive phenomena; (3) strong ability to differentiate the optimal alternative. Show more

Keywords: Pythagorean fuzzy number, CODAS, score function, MCDM

DOI: 10.3233/JIFS-190043

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3307-3318, 2020

Authors: Jin, Liying | Zhao, Shengdun | Zhang, Congcong | Gao, Wei | Dou, Yao | Lu, Mengkang

Article Type: Research Article

Abstract: For the uncertain problem that between-cluster distance influences clustering in the soft subspace clustering (SSC) process, a novel clustering technique called adaptive soft subspace clustering (ASSC) is proposed by employing both within-cluster and between-cluster information. First, a new objective function is constructed by minimizing the within-cluster compactness and maximizing the between-cluster distance based on the framework of SSC algorithm. Based on this objective function, a new way of computing clusters’ feature weights, centers and membership is then derived by using Lagrange multiplier method. The uniqueness of ASSC is that the objective function does not increase any control parameters, which can …avoid the sensitivity of clustering results to the initial points of the control parameters. The properties of this algorithm are investigated and the performance is evaluated experimentally using UCI datasets. The contrastive experiment results demonstrate that the accuracy and the stability of the proposed algorithm outperform the four existing clustering algorithms, i.e., ESSC, EWKM, FWKM and CIM_QPSO_SSC. Show more

Keywords: Soft subspace clustering, within-cluster compactness, between-cluster distance, not increase any control parameters

DOI: 10.3233/JIFS-190146

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3319-3330, 2020

Authors: Ke, Su | Lele, Ren | Xiaohui, Ren

Article Type: Research Article

Abstract: In this paper, a modified nonmonotone QP-free method without penalty function or filter is proposed for inequality constrained optimization. There is only two or three systems of linear equations with the same coefficients are solved at each iteration. We obtain a fundamental direction and the corresponding multiplier by the first equation, and then make full use of Lagrangian function information and multiplier to bend the search direction appropriately and obtain the search direction by the second linear equation. Moreover, the acceptable criterion of trial points is relaxed by the modified nonmonotone linear search technique. Under mild conditions, the global convergence …of the algorithm is proved. Numerical results are given at the end of the paper. Show more

Keywords: Inequality constrained optimization, QP-free method, nonmonotone, working set, global convergence

DOI: 10.3233/JIFS-190475

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3331-3342, 2020

Authors: Shao, Songtao | Zhang, Xiaohong

Article Type: Research Article

Abstract:  The probabilistic neutrosophic hesitant fuzzy numbers are considered to be effective tools for dealing with such decision problems when both subjective and objective uncertainties exist simultaneously. However, the existing methods for dealing with real-life decision-making in the context is based on the assumption that the relationships between all criteria are independent and irrelevant. It is worth noting that this assumption is not sufficient. In fact, there may be interrelationships between attributes. In order to consider the correlation between factors from a more global perspective, the generalized Shapley probabilistic neutrosophic hesitant fuzzy Choquet averaging (GS-PNHFCA) operator and the generalized Shapley probabilistic …hesitant fuzzy Choquet geometric (GS-PNHFCG) operator are investigated. Next, in order to find the optimal weight vector about DMs and criteria, a model is constructed by the maximizing score deviation (MSD) method. In addition, based on the integrated operators and built models, an algorithm for solving the MCGDM problem of PNHFN is designed. The effectiveness and practicability of the algorithm is proved by comparison with existingresults. Show more

Keywords: Probabilistic neutrosophic hesitant fuzzy set, multi-criteria group decision-making (MCGDM), Choquet integral, shapley function, aggregation operator

DOI: 10.3233/JIFS-190493

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 3, pp. 3343-3357, 2020