• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.521-524
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• 2002

This paper deals with the rule generation from data for control system and data mining using rough set. If the cores and reducts are searched for without consideration of the frequency of data belonging to the same equivalent class, the unnecessary attributes may not be discarded, and the resultant rules don't represent well the characteristics of the data. To improve this, we handle the inconsistent data with a probability measure defined by support, As a result the effect of uncertainty in knowledge reduction can be reduced to some extent. Also we construct the rule base in a hierarchical structure by applying core as the classification criteria at each level. If more than one core exist, the coverage degree is used to select an appropriate one among then to increase the classification rate. The proposed method gives more proper and effective rule base in compatibility and size. For some data mining example the simulations are performed to show the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.583-590
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• 1999

We propose the reusability decision model of the object-oriented components, which can decide the potentiality of reusability of the object-oriented components actively. Fisrt, we select attributes for the reusability decision of the object-oriented components. Then, we acquire information from the reused components based on the quality measures and criteria proposed by many researches. Lastly, we generate algorithm for the reusability decision of the object-oriented components from the acquired information employing rough set.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• Journal of the Korean housing association
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• v.20 no.2
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• pp.27-35
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• 2009

With the change of construction environment, the main body of construction industry was moved from project suppliers to consumers. Accordingly in order to strengthen competitiveness, project suppliers have to concentrate on marketing for diversification. Thus, it is required to utilize real estate marketing from the beginning of development project to introduce 'consumer-centered marketing strategies' instead of 'supplier-centered marketing'. This study aims to find out what consumers consider the most important factors when selecting apartment. According to the study, when residents select their apartment in residential area, they valued those attributes with investment, location, dwelling attribute, apartment complex attribute, unit price per square meter, in order. This result will contribute to qualitative improvement of housing development project.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.231-236
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• 2008

The purpose of this study is to develop assessment model for selection of new DSM investment programs. In this research, MAUT method which find assessment value by each attributes related to selecting new DSM investment programs using utility function and integrate with structural frame was used to develop assessment model. In order to validate the usefulness of the model, assessment model was applied for actual candidate group of new DSM investment programs in natural gas domain. By utilize this assessment model to select new DSM investment programs, it is expected to minimize risk of new program launching and to maximize efficiency of DSM investment programs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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• pp.72-81
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• 2003

The purpose of this paper is to propose an interactive method, which is designed to select the optimal preferred alter-native for the MLDM(Multiple-the Larger-the better type Decision-Making) problems with the-larger-the-better quality characteristics. The basic idea of the paper is essentially to eliminate inefficient alternative based on the concept of Taguchi Signal-to-Noise ratios and the cutting range instead of using UVF(Utility/value Function) on the group of attributes that can be considered importantly by the decision makers. As a result, the method proposed in the paper for MLDM problems can be significant in that the change of characteristics is transformed into the size of Signal-to-Noise ratio, which can be relatively easy to understand by decision makers.

• ETRI Journal
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• v.24 no.3
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• pp.226-238
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• 2002

A spatial object changes its states over time. However, existing spatial and temporal database systems cannot fully manage time-varying data with both spatial and non-spatial attributes. To overcome this limitation, we present a framework for spatio-temporal databases that can manage all time-varying historical information and integrate spatial and temporal relationship operators into the select statement in SQL3. For the purpose of our framework, we define three referencing macros and a history aggregate operator and classify the existing spatial and temporal relationship operators into three groups: exclusively spatial relationship operators, exclusively temporal relationship operators, and spatio-temporal common relationship operators. Finally, we believe the integration of spatial and temporal relationship operators into SQL3 will provide a useful framework for the history management of time-varying spatial objects in a uniform manner.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.493-502
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• 1998

The purpose of this paper is to propose an interactive method, which is designed to select the optimal preferred alternatives for the MNDM(Multi-N type Decision- Making) problems with the-Nominal-the-best characteristics. The basic idea of the paper is essentially to eliminate inefficient alternatives based on the concept of the lass function and the cutting range instead of using the utility/value function on the group of attributes that can be considered as important by the decision-maker. As a result, the method proposed in the paper for MNDM problems can be significant in that the change of characteristics is transformed into the size of loss, which can be relatively easy to understand by decision-makers.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.35-43
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• 1993

The principal objective of a sampling plan is to make efficient use of the budget allocated and to obtain as precise an estimate of a population parameter as possible. In order to estimate the proportion of defectives produced or to determine some measure of product Quality, it is necessary to select random samples which represent a population parameter of the process. In this case, the two stage sampling is more efficient and convenient than simple random sampling. Therefore this paper aims to propose the design procedures of two stage sampling plan to obtain a representative samples in considering the sampling precision under the restricted sampling unspection cost.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.38-43
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• 2022

In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.