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In this paper we present two modified and improved versions of the formerly published Fuzzy-Based Single-Stroke Character Recognizer (FUBAR) algorithm. After introducing the original method, the study investigates the effects of two different improvements of the designed algorithm. The first extension is the use of symbol-dependent fuzzy grids to extract symbol features; the second one is the use...
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...
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 to introduce a set of procedures capable of produce a text summary from a causal graph. In previous works we have presented several algorithms to extract causal information from text documents by means of a semi-automatic process. As result we obtained a causal graph connecting concepts related to a given topic. In this paper we present a procedure capable of generating an...
Retrieving representative information from large-scale data becomes an important research issue nowadays. This paper focuses on certain aspects of representativeness in database queries and web search, and proposes an approach to extracting a subset of results from original search results in light of high coverage and low redundancy. In the paper, the notion of λ-Represent is introduced based on similarities...
Creating high quality products/services in terms of consumer preference has become a critical issue for tourism managers. To fulfil these needs, this paper proposes a route recommendation algorithm that supplies movement routes with the locations they want visit. The analysis of visiting locations and corresponding timestamps are based on a Radio-Frequency Identification (RFID) data and stored in...
This paper proposes a novel way of matching general type-2 fuzzy sets using a sequence-based approach. General sequences are defined as an ordered list of objects, which are called events. In our contribution, an event of the sequenced type-2 fuzzy set is defined as the footprint of uncertainty of a specific α-plane. Suited matching algorithms for generalized sequences can be applied to this new interpretation,...
In this paper, we propose a procedure for computing the dissimilarity measure of finite general type-2 fuzzy sets, represented as sequences of vertical slices. Through representing general type-2 fuzzy sets as a sequence of objects, we compute their overall dissimilarity value using suited matching algorithms for generalized sequences. The evaluation of the proposed matching algorithm is performed...
Finding the location of a fault in code is an important research and practical problem, which often requires much time and manual effort. To automate this time consuming task, a class of predicate-based statistical fault localization techniques have been proposed, which test the similarity of dynamic predicate spectra between non-failed runs and failed runs and suggest suspicious predicates to the...
In this paper, an interval type-2 neural fuzzy system (IT2NFIS) with compensatory operator is proposed for system modeling. The IT2NFIS uses type-2 fuzzy sets in the premise clause in order to effectively handle the uncertainties in terms of data and information. The premise part of each compensatory fuzzy rule is an interval type-2 fuzzy set in the IT2NFIS, where compensatory operation is able to...
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...
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,...
This paper presents a Fuzzy Consensus Qualitative Risk Analysis Framework to identify and prioritize risks encountered in Building Construction Projects, which is applied to developing countries. The framework utilizes and compares three fuzzy consensus aggregation algorithms to select the most appropriate one in aggregating experts' opinions in prioritizing risks: (1) Fuzzy Similarity Aggregation...
Let L be a fuzzy propositional logic based on triangular norm min(x,y) (Zadeh's logic). A fact in L is an expression of the form r ≤ ϕ ≤ s where ϕ ∈ L and 0 ≤ r ≤ s ≤ 1. In fuzzy interpretation I of L every fact is true or false, and I(r ≤ ϕ ≤ s) = 1 if and only if the two-side inequality r ≤ I(ϕ) ≤ s is satisfied. Thus, the set FL of all facts defines a crisp logic with fuzzy interpretations. Logical...
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,...
In this paper, we present a flocking control algorithm for a group of autonomous underwater vehicles (AUVs) using the leader-follower concept. Leader vehicle have global knowledge of desired trajectory and other AUVs are chosen as followers which are mounted with sensors to estimate the positions of neighbor AUVs. The follower vehicles have no knowledge of desired path. There is a flocking center...
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