Journal of Intelligent & Fuzzy Systems - Volume 28, issue 6

Authors: Su, Pan | Shang, Changjing | Shen, Qiang

Article Type: Research Article

Abstract: Cluster ensembles organically integrate individual component methods which may utilise different parameter settings and features, and which may themselves be generated on the basis of different representations and learning mechanisms. Such a technique offers an effective means for aggregating multiple clustering results in order to improve the overall clustering accuracy and robustness. Many topics regarding cluster ensembles have been proposed and promising results are gained in the literature. To reinforce such development, this paper presents another cluster ensemble approach for fuzzy clustering, with an aim to be applied for clustering of big data. The proposed algorithm first generates fuzzy base …clusters with respect to each data feature and then, employs a fuzzy hierarchical graph to represent the relationships between the resulting base clusters. Whilst the work employs fuzzy c -means and hierarchical clustering in generating base cluster and implementing consensus function respectively, when applied to large datasets it has lower time complexity than the original fuzzy c -means and hierarchical clustering. The resultant ensemble clustering mechanism is tested against traditional clustering methods on various benchmark datasets. Experimental results demonstrate that it generally outperforms crisp cluster ensembles and single linkage agglomerative clustering, in terms of accuracy in conjunction with time efficiency, thereby showing that it has the potential for application in clustering big data. Show more

Keywords: Fuzzy cluster ensemble, big data clustering, fuzzy c-means, hierarchical clustering, data mining

DOI: 10.3233/IFS-141518

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2409-2421, 2015

Authors: Li, Lingqiang | Li, Qingguo

Article Type: Research Article

Abstract: By making use of fuzzy inclusion order, the notions of bases (subbases) for three enriched L -topologies including stratified L -topologies, strong L -topologies and Alexandrov L -topologies, are presented. Some characterizations for these notions are given. The results exhibit many different features from the base (subbase) in L -topologies. Some non-trivial examples including a base for the topologically generated (stratified, strong) L -topologies and a base for the Alexandrov L -topologies derived from L -fuzzy rough sets, are constructed. At last, an application in open and continuous functions is offered.

Keywords: Base, subbase, enriched L-topologies, L-fuzzy rough set, residuated lattice

DOI: 10.3233/IFS-141522

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2423-2432, 2015

Authors: Yang, Xiangfeng | Gao, Jinwu

Article Type: Research Article

Abstract: Uncertain set theory is a generalization of uncertainty theory that has become a new branch of mathematics for modeling human belief degrees. Uncertain set is a fundamental concept to describe unsharp concepts in uncertain set theory. The moments are important characteristics of an uncertain set. This paper studies the moments and central moments of uncertain set and gives some formulas to calculate the moments and central moments by membership function. In addition, some examples are provided to calculate the moments and central moments of uncertain set.

Keywords: Uncertainty theory, uncertain set, membership function, moments

DOI: 10.3233/IFS-141523

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2433-2442, 2015

Authors: Sun, Hong-Xia | Yang, Hao-Xiong | Wu, Jian-Zhang | Ouyang, Yao

Article Type: Research Article

Abstract: In this paper, the Choquet integral and the interval neutrosophic set theory are combined to make multi-criteria decision for problems under neutrosophic fuzzy environment. Firstly, a ranking index is proposed according to its geometrical structure, and an approach for comparing two interval neutrosophic numbers is given. Then, a ≤L implied operation-invariant total order which satisfies order-preserving condition is proposed. Secondly, an interval neutrosophic number Choquet integral (INNCI) operator is established and a detailed discussion on its aggregation properties is presented. In addition, the procedure of multi-criteria decision making based on INNCI operator is given. Finally, a practical example …for selecting the third party logistics providers is provided to illustrate the feasibility of the developed approach. Show more

Keywords: Neutrosophic set (NS), order relation, fuzzy measure, Choquet integral, multi-criteria decision making (MCDM)

DOI: 10.3233/IFS-141524

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2443-2455, 2015

Authors: Ghodratnama, Ali | Tavakkoli-Moghaddam, Reza | Kalami-Heris, S. Mostapha | Nagy, Gábor

Article Type: Research Article

Abstract: This paper deals with three characteristics of transportation costs, crowding and traffic costs, and the costs of hub installation. The main aim of this paper is to define the independent cost function in order to connect to the crowding rate and incurred cost in an exponential way not considered in the literature directly. In this function, the independent variable is the crowding and traffic rate input, and the output is the cost incurred. However, involving three separate objective functions namely total cost, congestion and hub installation costs are not considered up to now. Also, considering the contrast among three foregoing …costs, each function is considered independently. Due to the NP-hardness of this kind of problem to solve this multi-objective mathematical model, at first we devised an efficient approach to navigate through the feasible solution space iteratively without using penalty function. To solve our developed multi-objective mathematical model we propose five multi-objective meta-heuristic algorithms, namely 1) NSGA-II with an elitism solution, 2) NSGA-II without an elitism solution, 3) NRGA with an elitism solution, 4) NRGA without an elitism solution, and 5) MOPSO. Finally, three criteria are used to compare the related results obtained by these five algorithms. Show more

Keywords: Hub location-allocation problem, crowding and traffic costs, transportation cost, meta-heuristic algorithms

DOI: 10.3233/IFS-141525

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2457-2469, 2015

Authors: Xu, Weihua | Li, Wentao | Luo, Shuqun

Article Type: Research Article

Abstract: Knowledge reduction is one of the most important issues in rough set theory. According to various requirements and factors, information processing is based on two or more than two universes, other than single universe in many real-life cases. In this paper, we mainly investigate the knowledge reductions in generalized approximation space over two universes based on evidence theory. By defining the concepts of object belief and plausibility consistent sets over two universes, the object belief and plausibility consistent reductions are introduced in generalized approximation space over two universes. At the same time, the belief and plausibility significance reductions are also …presented carefully in this space. Relationships among these proposed reductions are further studied, and it is proved that the object belief consistent reduction must be belief significance reduction and the object plausibility consistent reduction must be plausibility significance reduction. Show more

Keywords: Approximation space, evidence theory, knowledge reduction, two universes

DOI: 10.3233/IFS-141526

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2471-2480, 2015

Authors: Rostami, Mohammad-Ali | Raoofat, Mahdi | Abunasri, Alireza | Kavousi-Fard, Abdollah

Article Type: Research Article

Abstract: By rapid growth in the technology of the electric vehicles (EVs), the new smart power grids will include millions of these devices in the near future. The high penetration of EVs especially in the form of plug-in hybrid EVs (PHEV) can result in new challenges in the optimal operation and management of the systems. The charging behavior of PHEVs in a typical system is affected by a number of uncertain parameters which makes the overall charging behavior of PHEVs uncertain. Therefore, this paper makes use of a newly introduced smart model for charging demand of PHEVs to assess their effect …on the reconfiguration issue as a precious and significant strategy in the smart automated distribution systems (ADS). In this regard, two different charging modes including charging at the public station and in a local residential community are investigated. Also, a sufficient scenario-based stochastic framework is proposed to model the uncertainties associated with the PHEVs on the reconfiguration problem. The proposed stochastic framework employs the roulette wheel mechanism in conjunction with a modified evolutionary-based optimization technique to deal with the targets. The feasibility and effectiveness of the proposed method is investigated on the 69 bus IEEE distribution system. Show more

Keywords: Plug-in Hybrid Electric Vehicles (PHEVs), reconfiguration, uncertainty, stochastic framework, smart automated distribution systems, θ modified cuckoo search algorithm

DOI: 10.3233/IFS-141527

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2481-2492, 2015

Authors: Chakraborty, Debjani

Article Type: Research Article

Abstract: Geometric programming problem is a special class of nonlinear programming problem which deals with posynomial type functions. However, the parameters of the problem are sometimes uncertain in nature. Two kinds of uncertainty, fuzziness and randomness, do exist simultaneously in real decision situation. One of the way to model such situation with fuzzy random variable. In this paper, posynomial geometric programming problem with fuzzy random variable coefficients is studied. A fuzzy two stage stochastic programming technique has been developed to handle fuzzy random variable. A numerical example is solved to illustrate the methodology.

Keywords: Fuzzy random variable, fuzzy geometric programming problem, two stage stochastic programming, fuzzy inequality

DOI: 10.3233/IFS-141528

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2493-2499, 2015

Authors: Abiri, Ebrahim | Dastanian, Rezvan | Salehi, Mohammad Reza | Taherinia, Khadije

Article Type: Research Article

Abstract: In this paper a backscatter modulator of passive tags used for RFID applications is proposed. For designing this backscatter modulator, QPSK modulation is utilized for transferring data from the tag to the reader. This modulator working in UHF frequency has high data rate and low power consumption. This circuit is simulated in 0.18μm CMOS technology with 1.8 V supply voltage with the help of Cadence software. TLBO algorithm is applied in order to evaluate the optimized transistors sizes for maximizing the difference between various values of varactor in modulation states. The DC power dissipation and the chip area of the proposed …modulator equal to 15.57nW and 5767μm2 , respectively. Show more

Keywords: QPSK backscatter modulation, UHF RFID, low power dissipation, TLBO algorithm

DOI: 10.3233/IFS-141529

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2501-2507, 2015

Authors: Hussain, Sajid

Article Type: Research Article

Abstract: Gearbox is an inseparable part of any rotating machinery today. Gearbox transfers speed and torque from one shaft to another. Hence, correct diagnosis of gearbox faults is an important and critical task for maintenance operators. But, due to nonlinear, time-varying behavior and imprecise measurement information of the systems it is difficult to deal with gearbox failures with precise mathematical equations. Human operators with the aid of their practical experience can handle these complex situations, with only a set of imprecise linguistic if-then rules and imprecise system state. The purpose of this study is to provide a correct and timely diagnosis …of gearbox failures in the context of condition based maintenance. The diagnosis is performed by knowledge acquisition through a fuzzy rule-based inference system which could approximate human reasoning. The proposed approach is tested and applied to an experimental data emanating from a gearbox system. Show more

Keywords: Fuzzy logic, vibration analysis, features extraction, clustering, gearbox fault diagnosis

DOI: 10.3233/IFS-141530

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2509-2518, 2015