Journal of Intelligent & Fuzzy Systems - Volume 30, issue 2

Authors: Firouz, Mansour Hosseini | Ghadimi, Noradin

Article Type: Research Article

Abstract: In this paper, a new controller based on combination of Fuzzy Power System Stabilizer (FPSS) and Flexible Ac Transmission Systems (FACTS) proposed in multi machine power system environment. In this model, the power system oscillation damping has been analyzed by considering the wide area control method. A fuzzy controller is a nonlinear controller and it is not so sensitive to system topology, parameter and operating condition changes as the conventional ones. According to wide area power system complexity and variation of the loads and network conditions, FPSS has been considered in this paper. Where, this structure is based on fewer …fuzzy rules and less computational burden. Furthermore, the proposed FACTS controller has been improved by Vector Evaluated Honey Bee Mating Optimization (VEHBMO) as an optimization problem. Effectiveness of the proposed method has been applied over two case studies of single-machine infinite-bus (SMIB) and ten machine 39 bus New England power system. Obtained results demonstrate the superiority of proposed strategy. Show more

Keywords: FACTS, FPSS, VEHBMO, wide area control, multi machine power system

DOI: 10.3233/IFS-151807

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 845-859, 2016

Authors: Tosun, Umut

Article Type: Research Article

Abstract: M-Tree, Slim-Tree, DF-Tree, and Omni-Tree are some of the popular dynamic structures which can grow incrementally by splitting overflowed nodes, and adding new levels to the tree very much like the B-tree variants. Unfortunately, they have been shown to perform very poorly compared to flat structures such as AESA, LAESA, Spaghettis, and Kvp that use a fixed set of global pivots. HKvp index structure is an extension of Kvp allowing the elimination of pivots as well as the database objects. The number of pivots can be easily increased to provide more selectivity and query performance. However, there is an optimum …number of pivots for a given query radius, and using too many pivots increases the costs of queries and index initialization. In this paper, a new set of pivot elimination mechanisms is proposed to determine the right number of pivots for different query radii. The suggested pivot elimination schemes perform significant cost reduction in terms of number of distance computations, and they estimate the drop rate value for HKvp on query time. Show more

Keywords: Kvp, Hkvp, pivot elimination, distance computation

DOI: 10.3233/IFS-151808

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 861-868, 2016

Authors: Guo, Jian

Article Type: Research Article

Abstract: Failure mode and effects analysis (FMEA) is an extensively used engineering technique for defining, identifying and prioritizing the potential failure modes. Traditionally the Risk Priority Number (RPN) is used to rank the potential failure modes. In this paper, a new risk assessment methodology which combines intuitionistic fuzzy sets (IFSs) with evidence theory is proposed to analyze the potential failure modes. The risk factors S, O, and D are evaluated by using linguistic variables and intuitionistic fuzzy numbers, which can be transformed into the basic probability assignment functions. The Jousselme distance is used to compute the weights of decision makers in …order to efficiently combine highly conflicting evidence. The weighted average of evidence is obtained and the classical Dempster’s combination rule is used to combine the mass functions modified. The proposed approach is applied thereafter to the prioritization of failure modes. A numerical example for risk assessment is given to illustrate the effectiveness and rationality of the proposed method finally. Show more

Keywords: Failure mode and effects analysis, intuitionistic fuzzy set, evidence theory, Jousselme distance of evidence, group decision making

DOI: 10.3233/IFS-151809

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 869-881, 2016

Authors: Keshavarz, Esmail

Article Type: Research Article

Abstract: In this paper, a new vertex-coloring problem of a fuzzy graph with crisp vertices and fuzzy edges is studied. Membership degree of a fuzzy edge is interpreted as incompatibility degree of its associated incident vertices. This interpretation can be used to define the concept of total incompatibility . Here, unlike the traditional graph coloring problems, two adjacent vertices can receive same colors; these type of vertices and their associated edge are named incompatible vertices and incompatible edge, respectively. In proposed coloring methodology, the total incompatibility of a vertex-coloring is defined as the sum of incompatibility degrees of all incompatible …edges. Then, based on the minimum possible degree of total incompatibilities, fuzzy chromatic number of a fuzzy graph is introduced. In order to find an optimal k-coloring, with minimum degree of total incompatibly, firstly a binary programming problem is formulated. Then, a hybrid local search genetic algorithm is designed to solve the large-size problems. Practical uses of the proposed algorithm are illustrated and analyzed by different-size problems. Finally, a cell site assignment problem, as a real world application of the presented fuzzy graph vertex-coloring, is formulated and solved. Show more

Keywords: Fuzzy graph, incompatibility degree, fuzzy chromatic number, binary programming, genetic algorithm

DOI: 10.3233/IFS-151810

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 883-893, 2016

Authors: Abadpour, Arash

Article Type: Research Article

Abstract: Data clustering is the generic process of splitting a set of datums into a number of homogenous sets. Nevertheless, although a clustering process inputs datums as a set of separate mathematical objects, these entities are in fact correlated within a spatial context specific to the problem class in hand. For example, when the data acquisition process yields a 2D matrix of regularly sampled measurements, as it is the case with image sensors which utilize different modalities, adjacent datums are highly correlated. Hence, the clustering process must take into consideration the spatial context of the datums. A review of the literature, …however, reveals that a significant majority of the well-established clustering techniques in the literature ignore spatial context. Other approaches, which do consider spatial context, however, either utilize pre- or post-processing operations or engineer into the cost function one or more regularization terms which reward spatial contiguity. We argue that employing cost functions and constraints based on heuristics and intuition is a hazardous approach from an epistemological perspective. This is in addition to the other shortcomings of those approaches. Instead, in this paper, we apply Bayesian inference on the clustering problem and construct a mathematical model for data clustering which is aware of the spatial context of the datums. This model utilizes a robust loss function and is independent of the notion of homogeneity relevant to any particular problem class. We then provide a solution strategy and assess experimental results generated by the proposed method in comparison with the literature and from the perspective of computational complexity and spatial contiguity. Show more

Keywords: Fuzzy clustering, Bayesian modeling, robust clustering, correlated clustering, spatial context, bilateral clustering

DOI: 10.3233/IFS-151811

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 895-919, 2016

Authors: Kocken, Hale Gonce | Ahlatcioglu, Mehmet | Albayrak, Inci

Article Type: Research Article

Abstract: In this paper, a new algorithm is proposed to find the solutions of a general (square or nonsquare) Fully Fuzzy Linear Equation System (FFLS) with arbitrary trapezoidal fuzzy numbers, i.e. there are no sign restrictions on the variables or the parameters of the system. We introduce the “feasible (strong) fuzzy solution” and “approximate fuzzy solution” concepts, then accordingly “no solution” case of a general FFLS is defined. And a model is proposed by means of a mixed integer programming modelling of “min” and “max” concepts in the multiplication of two arbitrary trapezoidal fuzzy numbers. With the logic of goal programming, …the objective function of this model is constructed within the deviation variables. Based on the proposed model, also an algorithm is presented to determine the nature of solutions of a general FFLS. The method is illustrated with some numerical examples. Our numerical results for the examples from the literature are analyzed within some distance functions. Show more

Keywords: General fully fuzzy linear equation system, trapezoidal fuzzy number, fuzzy decision making, mixed integer programming problem, feasible and approximate fuzzy solution

DOI: 10.3233/IFS-151813

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 921-933, 2016

Authors: Al Ghour, Samer | Fora, Ali

Article Type: Research Article

Abstract: We extend the concept of being countable dense homogeneous to include fuzzy topological spaces. Our extension is proved to be a good extension in the sense of Lowen. We study the relation between fuzzy CDH spaces and some ordinary topological spaces generated by these fuzzy spaces.

Keywords: Homogeneity, countable dense homogeneity, fuzzy topological spaces, good extension

DOI: 10.3233/IFS-151815

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 935-941, 2016

Authors: Adam, Fatma | Hassan, Nasruddin

Article Type: Research Article

Abstract: Molodtsov introduced the concept of soft set as a general mathematical tool for dealing with uncertainty. In this work,we first defined a multi Q-fuzzy soft expert set and its basic operations, namely complement, union, intersection, OR and AND. We then construct a decision-making method on multi Q-fuzzy soft expert set. We finally provide an example to show that the method can be successfully applied to problems which contain uncertainties.

Keywords: Multi Q-fuzzy set, soft set, soft expert set

DOI: 10.3233/IFS-151816

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 943-950, 2016

Authors: Akram, Muhammad | Kavikumar, Jacob | Khamis, Azme Bin

Article Type: Research Article

Abstract: This paper aims at introducing the notion of intuitionistic N-fuzzy set (INFS) and its application along with its examples. As the application of this set, its idea has been applied to a newly defined algebraic structure “BiΓ-Ternary Semigroup”. The notions of intuitionistic N-fuzzy biΓ-ternary subsemigroup and intuitionistic N-fuzzy biΓ-left (right, lateral and bi) ideals have been defined and related properties have been investigated here. The characterization of biΓ-ternary semigroup under these ideals has been established.

Keywords: BiΓ-ternary smigroup, intuitionistic N-fuzzy set, intuitionistic N-fuzzy biΓ-ternary subsmigroup, intuitionistic N-fuzzy biΓ-ideal

DOI: 10.3233/IFS-151817

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 951-960, 2016

Authors: Guan, Lihe | Hu, Feng | Han, Fengqing

Article Type: Research Article

Abstract: In data mining, many real-life data sets are not only incomplete, but also encompass various kinds of knowledge and are shared by many users. Different users may prefer different kinds of knowledge. Nowadays how to mine rules meeting users’ requirements from incomplete data sets has become one of the important research issues of data mining. In this paper, we investigate decision rules induction methods in incomplete decision tables by considering attribute order. The users’ requirements are described by an attribute order. Then a hierarchical algorithm of decision rules mining based on the attribute order is proposed, and its properties and …complexity are examined. An example is given to illustrate the algorithm. Simulation experimental results show that compared with the algorithm MLEM2, the proposed algorithm is valid and effective. Show more

Keywords: Data mining, rough set, incomplete decision table, knowledge discovery

DOI: 10.3233/IFS-151818

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 2, pp. 961-969, 2016