• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.511-518
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• 2009

A lot of methods are proposed to provide services for object informations in distributed domain to satisfy the recent increase of user-centered services. This paper proposed a method called fuzzy drop manager for the service of reliable distribution application domain objects. The proposed system accesses the domain using replica parameter ci,j and access matrix Z, and evaluates the reference relatedness inside the domain using the relatedness, given by the mapping of intra-domain fuzzy relevance, between fuzzy sets. Objects in the domain generated an $\alpha$-level set according to the reference relatedness obtained by applying $\alpha$-level to extend queries. Simulation results showed that the proposed method has better performance than the other methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.1-5
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• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.281-286
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• 2010

We propose a space and time based sensor fusion method and a robust landmark detecting algorithm based on sensor fusion for mobile robot navigation. To fully utilize the information from the sensors, first, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to landmark recognition for mobile robot navigation in an unstructured environment as well as structured environment, and the experimental results demonstrate the performances of the landmark recognition.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.108-113
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• 2005

This paper suggests a control method for an efficient topology/parameter evolution in a bond graph-based GP design framework that automatically synthesizes designs for multi-domain, lumped parameter dynamic systems. We adopt a hierarchical breeding control mechanism with fitness-level-dependent differences to obtain better balancing of topology/parameter search - biased toward topological changes at low fitness levels, and toward parameter changes at high fitness levels. As a testbed for this approach in bond graph synthesis, an eigenvalue assignment problem, which is to find bond graph models exhibiting minimal distance errors from target sets of eigenvalues, was tested and showed improved performance for various sets of eigenvalues.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.157-163
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• 2005

In this paper, we present the multimodal system based on the fusion of two user-friendly biometric modalities: Iris and Face. In order to reach robust identification and verification we are going to combine two different biometric features. we specifically apply 2-D discrete wavelet transform to extract the feature sets of low dimensionality from iris and face. And then to obtain Reduced Joint Feature Vector(RJFV) from these feature sets, Direct Linear Discriminant Analysis (DLDA) is used in our multimodal system. In addition, the Synergetic Neural Network(SNN) is used to obtain matching score of the preprocessed data. This system can operate in two modes: to identify a particular person or to verify a person's claimed identity. Our results for both cases show that the proposed method leads to a reliable person authentication system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.272-277
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• 1998

If we want to compare the form of two objects, the human vision takes into account the parameter's width/length/height at the same time. however, the machine needs to compare width then lengths and finally height. In each comparison the machine considers only one character. The goal of this paper is to imitate the human manner of comparison and recognition by using two or three characters instead of one during the comparison. The ellipse is a first approach of comparison because it provides us a general and a simple relation that can link two parameters that are the half axis of the ellipse. Indeed, we assimilate each character to a half axis of the ellipse and the result is a geometrical figure that varies according to values of the two characters.

• Journal of applied mathematics & informatics
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• v.33 no.5_6
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• pp.671-686
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• 2015

The notion of soft α-ideals and α-idealistic soft BCI-algebras is introduced and their basic properties are discussed. Relations between soft ideals and soft α-ideals of soft BCI-algebras are provided. Also idealistic soft BCI-algebras and α-idealistic soft BCI-algebras are being related. The restricted intersection, union, restricted union, restricted difference and "AND" operation of soft α-ideals and α-idealistic soft BCI-algebras are established. The characterizations of (fuzzy) α-ideals in BCI-algebras are given by using the concept of soft sets. Relations between fuzzy α-ideals and α-idealistic soft BCI-algebras are discussed.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.71-75
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• 1992

This paper proposes algorithm in order to classify Korean consonant phonemes same as polosives, fricatives affricates into la sounds, glottalized sounds, aspirated sounds. This three kinds of sounds are one of distinctive characters of the Korean language which don't eist in language same as English. This is thesis on classfication of 14 Korean consonants(k, t, p, s, c, k', t', p', s', c', kh, ph, ch) as a previous stage for Korean phone recognition. As feature sets for classification, LPC cepstral analysis. The eperiments are two stages. First, using short-time speech signal analysis and Mahalanobis distance, consonant segments are detected from original speech signal, then the consonants are classified by fuzzy inference. As the results of computer simulations, the classification rate of the speech data was come to 93.75%.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.3
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• pp.189-194
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• 2014

Due to the increasing of power consumption, it is difficult to construct accurate prediction model for daily peak power demand. It is very important work to know power demand in next day for manager and control power system. In this research, we develop a daily peak power demand prediction method based on hybrid type composed of AR and Neuro-Fuzzy model. Using data sets between 2006 and 2010 in Korea, the proposed method has been intensively tested. As the prediction results, we confirm that the proposed method makes it possible to effective estimate daily peak power demand than conventional methods.

• Communications of the Korean Mathematical Society
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• v.19 no.1
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• pp.143-153
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• 2004

In [3] and [6] the concepts of smooth closure, smooth interior, smooth ${\alpha}-closure$ and smooth ${\alpha}-interior$ of a fuzzy set were introduced and some of their properties were obtained. In this paper, we introduce the concepts of several types of weak smooth compactness and weak smooth ${\alpha}-compactness$ in terms of these concepts introduced in [3] and [61 and investigate some of their properties.