• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.188-193
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• 2000

This paper presents an approach to obtain a reduced neuro-fuzzy model for a plant. The Neuro-Fuzzy Network are compose of the Radial Basis Function Networks with Gausis membership and learned by using temporal back propagation. The dependency in rough set theory is used to eliminate rules. Dependency between the condition membership value of each rule in a model and the output of the plant can allow us to see how much contribution the rule is to identify the plant. While the reduced model maintains the same performance as the original one, the selection algorithm can minimize its complexity and redundancy of the structure.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.333-337
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• 1998

의학분야에서 컴퓨터 활용은 단순히 처리할 데이터의 자동화뿐만 아니라 각종 의학영상들을 자동으로 처리함으로서 의사의 진단을 도와주는 형태로 발전되어 가고 있다. 본 논문에서는 병원의 임상병리과에서 번번히 수행하는 혈액검사를 자동화하기 위한 것으로 혈액을 자동 분석하는 웹 기반 분석시스템을 구축하였다. 이를 위해 본 논문에서는 혈액 영상으로부터 특징을 추출하기 위한 단계를 서술하고 세포분류를 위한 다층 신경망을 이용해 구현한 내용을 보인다. 또한 본 연구의 결과로 신경망의 학습 효율을 높이기 위한 전처리로서 학습 데이터에 대해 러프 집합 이론을 적용하여 학습 데이터의 차원을 효과적으로 줄일 수 있었다.

• Journal of the Korean housing association
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• v.24 no.6
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• pp.199-208
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• 2013

Developing a modern Han-style design and providing support for the commercialization development model in recent years has been propelled by the Han-style Support Strategies of the central government in conjunction with Han-style revitalization related projects that reflect the efforts of local governments. Han-style revitalization, the rekindling and revaluing of human behavior and interest in local governments following the social and cultural changes of the past decades, has emerged as an increasingly traditional area of concern in Han-style design. The purpose of the study was to provide a method which clarifies the design rules of the Han-style bathroom based on an evaluation of sensibilities and a rough set theory, and to give the components meaning and to systematize the method. Essentially, the Han-style bathroom design evaluation is a complex multi-criteria decision making process that seeks to improve the effectiveness and objectively of the Han-style bathroom design. Han-style bathroom design can be displayed in a graphical representation in response to input from the evaluation concerning sensibilities. Because the graphical representation is composed of 3D data, it is possible to display the Han-style bathroom design form in any desired perspective and also to perform shading and other operations. With the proposed method, it is possible to obtain a combination of several contributory components which can be referred to as Reducts, Covering Index and Column Score. Han-Style/Non Han-Style Bathroom Designs were identified by the combination of several components.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.183-188
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• 2013

A variety of cluster analysis techniques prerequisite to cluster objects having similar characteristics in data mining. But the clustering of those algorithms have lots of difficulties in dealing with categorical data within the databases. The imprecise handling of uncertainty within categorical data in the clustering process stems from the only algebraic logic of rough set, resulting in the degradation of stability and effectiveness. This paper proposes a information-theoretic rough entropy(RE) by taking into account the dependency of attributes and proposes a technique called min-mean-mean roughness(MMMR) for selecting clustering attribute. We analyze and compare the performance of the proposed technique with K-means, fuzzy techniques and other standard deviation roughness methods based on ZOO dataset. The results verify the better performance of the proposed approach.

• Journal of Digital Contents Society
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• v.2 no.2
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• pp.103-115
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• 2001

This paper proposes the two algorithms which generate a minimal decision rule and approximate inference operation, adapted the rough set and the factor space theory in fuzzy knowledge base. The generation of the minimal decision rule is executed by the data classification technique and reduct applying the correlation analysis and the Bayesian theorem related attribute factors. To retrieve the specific object, this paper proposes the approximate inference method defining the membership function and the combination operation of t-norm in the minimal knowledge base composed of decision rule. We compare the suggested algorithms with the other retrieval theories such as possibility theory, factor space theory, Max-Min, Max-product and Max-average composition operations through the simulation generating the object numbers and the attribute values randomly as the memory size grows. With the result of the comparison, we prove that the suggested algorithm technique is faster than the previous ones to retrieve the object in access time.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2222-2224
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• 1998

This paper presents a 3D feature extraction method using rough set theory. Using the stereo cameras, we obtain the raw images and then perform several processes including gradient computation and image matching process. Decision rule constructed via rough set theory determines whether a ceratin point in the image is 3D edge or not. We propose a method finding rules for 3D edge extraction using rough set.

• The KIPS Transactions:PartC
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• v.15C no.6
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• pp.493-506
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• 2008

In this paper we suggest dynamic access control model based on context satisfied with requirement of u-healthcare environment through researching the role based access control model. For the dynamic security domain management, we used a distributed object group framework and context information for dynamic access control used the constructed database. We defined decision rule by knowledge reduction in decision making table, and applied this rule in our model as a rough set theory. We showed the executed results of context based dynamic security service through u-healthcare application which is based on distributed object group framework. As a result, our dynamic access control model provides an appropriate security service according to security domain, more flexible access control in u-healthcare environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.97-102
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• 2008

In this paper we propose an object-based image retrieval method using spatial color model and feature points registration method for an effective color query detection. The proposed method in other to overcome disadvantages of existing color histogram methods and then this method is use the HMMD model and rough set in order to segment and detect the wanted image parts as a real time without the user's manufacturing in the database image and query image. Here, we select candidate regions in the similarity between the query image and database image. And we use SIFT registration methods in the selected region for object retrieving. The experimental results show that the proposed method is more satisfactory detection radio than conventional method.

• The Journal of Information Systems
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• v.14 no.1
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• pp.41-65
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• 2005

The credit ration is a significant area of financial management which is of major interest to practitioners, financial and credit analysts. The components of credit rating are identified decision models are developed to assess credit rating an the corresponding creditworthiness of firms an accurately ad possble. Although many early studies demonstrate a priori which of these techniques will be most effective to solve a specific classification problem. Recently, a number of studies have demonstrate that a hybrid model integration artificial intelligence approaches with other feature selection algorthms can be alternative methodologies for business classification problems. In this article, we propose a hybrid approach using rough set theory as an alternative methodology to select appropriate attributes for case-based reasoning. This model uses rough specific interest lies in lthe stable combining of both rough set theory to extract knowledge that can guide dffective retrevals of useful cases. Our specific interest lies in the stable combining of both rough set theory and case-based reasoning in the problem of corporate credit rating. In addition, we summarize backgrounds of applying integrated model in the field of corporate credit rating with a brief description of various credit rating methodologies.

• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.631-637
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• 2010

The aim of affective engineering is to develop a new product by translating customer affections into design factors. Affective data have so far been analyzed using a multivariate statistical analysis, but the affective data do not always have linear features assumed under normal distribution. Rough sets model is an effective method for knowledge discovery under uncertainty, imprecision and fuzziness. Rough sets model is to deal with any type of data regardless of their linearity characteristics. Therefore, this study utilizes rough sets model to extract affective knowledge from affective data. Four types of scent alternatives and four types of sounds were designed and the experiment was performed to look into affective differences in subject's preference on air conditioner. Finally, the purpose of this study also is to extract knowledge from affective data using rough sets model and to figure out the relationships between rough sets based affective engineering method and statistical one. The result of a case study shows that the proposed approach can effectively extract affective knowledge from affective data and is able to discover the relationships between customer affections and design factors. This study also shows similar results between rough sets model and statistical method, but it can be made more valuable by comparing fuzzy theory, neural network and multivariate statistical methods.