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In this study, a new index is defined to measure a degree of node of the multi central complex network. The proposed index measures the belonging degree to the networks based on general type-2 fuzzy membership values. The proposed general type-2 fuzzy degree (GT2FD) consists of the primary degree, which indicates the similarity between nodes and central nodes; and the secondary degree, which indicated...
In this paper a new method is proposed for ranking members of the set with uncertainty in the center of set. It means that the set's center is considered as multi objects rather that single object. The degree of belonging to the set is defined based on general type-2 fuzzy membership values which the primary variable indicates the closeness to the each center; and the secondary variable indicates...
In this paper, a new prototype for fuzzy type-2 clustering is proposed. The proposed model considers ellipsoid shape for clusters and ellipsoid focal vectors are basis for measuring the distance from clusters, instead of cluster centers. Therefore, the degrees of belonging to clusters are defined as interval fuzzy type-2 sets indicated by the upper and lower membership values. The results of proposed...
This paper presents a new prototype of fuzzy type-2 clustering entitle Dual Center Fuzzy Type-2 Clustering based on possibilistic c-means(PCM). We mainly focus on uncertainty associated with the cluster centers and define a pair of points as center for each cluster. This model can recognize clusters with asymmetric shape. The results of proposed model on the sample data sets are compared with fuzzy...
The aim of this paper is developing the optimization model for global market analysis. The type-2 fuzzy model is developed based on the variables which indicate the export trade trend during the specified period. The proposed model is implemented for forecasting export value of international market segment of Parisian carpet. This model can be used for selecting proper segment of international market...
In this paper, a type-2 fuzzy TSK expert system is developed for optimizing the global market prediction. Interval type-2 fuzzy logic system permits us to model rule uncertainties and every membership value of an element is interval itself. The proposed type-2 fuzzy model applies the variables which indicate the export trade trend during the specified period. The PCM algorithm is employed to partitions...
Fuzzy functions are used to identify the structure of system models and reasoning with them. Fuzzy functions can be determined by any function identification method such as Least Square Estimates (LSE), Maximum Likelihood Estimates (MLE) or Support Vector Machine Estimates (SVM). However, estimating fuzzy functions using LSE method is structurally a new and unique approach for determining fuzzy functions...
Location Set Covering Problem (LSCP) is a traditional problem in the location literature. LSCP is used in locating fire stations, computer networks, and many other service facilities. This paper proposes a covering problem with variable radii. In this problem, the cost to establish a facility is a monotonically increasing function of distance to the farthest covered node by the facility. The problem...
This paper presents a new index for measuring interval distances and its related metric. The proposed index and metric are both based on the Hausdorff distance which can be used for clustering uncertain interval data. Then using the new metric, a clustering method is introduced for clustering of intervals. Finally, some experiments are provided to validate the method. Results show that the method...
A Hub Location Problem (HLP) deals with finding the locations of hub facilities and assignment of demand nodes to established facilities. Due to special characteristics of HLP, the overall performance of the network highly depends on proper performance of hubs. Therefore, the design of reliable networks is a critical issue to be considered. In this paper, we design a single-allocation hub-and-spoke...
Determining interval length in fuzzy time series has been one of the main concerns of many researchers in this area. Since an interval length has a continuous nature, in this paper, a novel metaheuristic algorithm (ICA), Imperialist Competitive Algorithm, is implemented. ICA can determine accurate interval length and it directly leads to results of fuzzy time series. For checking the validity of proposed...
In this paper a new intelligent multi-agent system is proposed for finding the best ordering policy. The best ordering policy is the policy which minimizes the total cost of the supply chain that is the sum of all echelons' costs over all periods. The best ordering policy is obtained by a new window-base genetic algorithm. One limitation of the previous presented GA-based algorithms is the constraint...
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