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Selection of contractors is the process of hiring the most appropriate contractor to deliver the project within specific time, with good quality, and at low cost. Selection based on a set of qualification criteria has become essential to the success of construction projects and it outperforms the traditional lowest cost selection method. A common problem however is the compatibility of the selected...
In this paper, a new hybrid method for forming interval type 2 fuzzy inference systems (IT2 FIS) is shown. This methodology builds upon an existing type 1 fuzzy inference system (T1 FIS) or from the output centers from any clustering algorithm, calculating the footprint of uncertainty (FOU) based on the implementation of the principle of justifiable granularity, and finally a particle swarm optimization...
Defining a proper measure of proximity (or remoteness) between two groups of objects is of crucial importance in applied research. Much attention has been paid to consideration of continuous-valued attributes while nominal-valued attributes seems to be more difficult to handle. In this paper we defined non empty groups of objects, and each group is described as K-tuple sets of attributes values. Next,...
Principal curves, as a nonlinear generalization of principal components, are a common tool used in multivariate analysis for ends like dimensionality reduction and feature extraction. However, one of the difficulties that arise when utilizing this technique is that efficiency of existing principal curves algorithms is often low when dealing with large data set owing to high computational complexity...
Most researches of time series forecasting mainly focus on the aspect of pursuing the numerical forecasting precision by constructing the quantitative model. But in the real world, precision is sometimes not necessary for perceiving and reasoning of human, and the qualitative forecasting of time series is able to satisfy requirement of some decision problems. In this paper, a new qualitative forecasting...
Global Corporations have to manage distributed production over the whole world. Therefore global supply chains are needed. This paper discusses the problem how global production plants and their supply chains can be classified. The classification focuses on demand and supply of production and supply chain. The problem of forecasting the demand of a global supply chain is introduced. The difficulty...
Fuzzy clustering has been one of the commonly used vehicles to construct information granules (whose description is provided in terms of prototypes and partition matrices). The quality of resulting information granules can be assessed by quantifying how well the original numeric data from which information granules have been constructed can be represented (granulated) by information granules and subsequently...
The clustering of web search has become a very interesting research area among academic and scientific communities involved in information retrieval. Clustering of web search result systems, also called Web Clustering Engines, seek to increase the coverage of documents presented for the user to review, while reducing the time spent reviewing them. Several algorithms for web document clustering already...
The aim of this paper is designing a new approach for objective function- based fuzzy clustering. A new algorithm will be proposed for possibilistic c-means (PCM)-based models. This PCM-based algorithm uses fuzzy relations. In order to consider both separation between clusters and compactness within clusters, fuzzy relations will be applied. For verifying the efficiency of the proposed algorithm,...
Images and visual understandings are basis in everyday life and are very important tool for decision making. However, for improving the image appearance to a human viewer, or to convert an image to a format better suited to machine processing, enhancing methods should be used. There are wide varieties of techniques for this purpose including, contrast and histogram modification, de-noising, statistical...
This paper introduces a new semisupervised fuzzy algorithm that makes use of must-link and cannot-link constraints. These constraints are applied to the process of finding the optimum α-cut of a dendrogram. We have applied this method to identity identification in digital libraries.
Nowadays the bag-of-visual-words is a very popular approach to perform the task of Visual Object Classification (VOC). Two key phases of VOC are the vocabulary building step, i.e. the construction of a ‘visual dictionary’ including common codewords in the image corpus, and the assignment step, i.e. the encoding of the images by means of these codewords. Hard assignment of image descriptors to visual...
The Fuzzy Joint Points (FJP) method which comprehends fuzziness in a level-based point of view is handled. At each iteration of the clustering process, unlike the classical fuzzy clustering in which the membership degrees of the points to the clusters are determined, the points which constitute the α-level sets are determined in FJP algorithm. In this study, some theoretical results are given for...
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 is concerned with a new architecture of an optimized FCM-based interval type-2 fuzzy neural network classifier developed with aid of Fuzzy C-Means (FCM) clustering and Particle Swarm Optimization (PSO). The premise part of the rules of this architecture is realized by two FCM clustering algorithms. These FCM clustering algorithms run for several values of the fuzzification coefficient subsequently...
This paper uses the concepts of fuzzy membership and granularity proposed by Zadeh to propose a fuzzy meta-clustering algorithm for creating associated profiles of networked granules. The proposed algorithm uses repeated applications of fuzzy c-means algorithm to create soft clustering. Representation of a granule is recursively updated using the fuzzy cluster memberships of other connected granules...
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