• Annual Conference of KIPS
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• 2008.11a
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• pp.27-29
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• 2008

시스템 분석에 주로 사용하는 자료 중에는 비선형 자료와 시계열 등이 있다. 이들 자료는 그 함축적인 관계가 매우 복잡하여 전통적인 통계분석 도구로 분석하는데 어려움이 많다. 본 연구에서는 현실 세계에서 다양하게 나타나는 복잡성을 다루기 위하여 하이브리드 진화 신경망 모델링 접근 방법으로 자료를 모형화 하고 이를 통한 학습의 적합도를 살펴본다. 비선형 자료 등을 모형화하기 위한 학습은 역전파 신경망 기법을 이용한다. 학습의 효율을 높이기 의해서 격자감소 학습 알고리즘과 함께 이용하는 유전자 알고리즘은 네트워크 구조를 최적화 시킬 수 있는 초기가중값을 이용한 전역 최소값을 찾는데 이용한다. 학습 결과를 통해 제안된 하이브리드형 접근방법의 학습이 보다 효율적임을 살펴보기 위하여 유전자 알고리즘으로 최적화된 신경망 학습 알고리즘을 비선형 모의자료의 학습에 적용하여 보았다.

• Korean Journal of Social Welfare
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• v.64 no.2
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• pp.159-183
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• 2012

This study intends to explore structural characteristics of social networks for female immigrants married to Korean men, and to analyze the relationship between the characteristics and types of social supports provided by their social networks and the differences between support-giving and support-receiving networks. Ego-centered network analysis is used for collecting network data on fifty-three migrant wives selected by a snowball sampling method. Results show that social support receiving and giving networks of female immigrants have similarities rather than differences, which implied that they play roles not only as support receivers, but also as support givers in their social networks. Also the study suggests that there are correlations between networks' characteristics, such as density and effective size of ego network, and types of supports. The result indicates that the less cohesive and less redundant ties female immigrants had, the more diverse and more informational and emotional supports they obtained from their social networks. Due to the sampling method and size, this study has a limitation to generalize the results for the whole population of female immigrants in Korea. However, it provides a basic understanding of female immigrants' social networks.

• The Journal of Bigdata
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• v.3 no.2
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• pp.101-112
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• 2018

The purpose of the study is to predict the number of police calls using neural network which is one of the machine learning and negative binomial regression, by using the data of 112 police calls received from Chungnam Provincial Police Agency from June 2016 to May 2017. The variables which may affect the police calls have been selected for developing the prediction model : time, holiday, the day before holiday, season, temperature, precipitation, wind speed, jurisdictional area, population, the number of foreigners, single house rate and other house rate. Some variables show positive correlation, and others negative one. The comparison of the methods can be summarized as follows. Neural network has correlation coefficient of 0.7702 between predicted and actual values with RMSE 2.557. Negative binomial regression on the other hand shows correlation coefficient of 0.7158 with RMSE 2.831. Neural network has low interpretability, but an excellent predictability compared with the negative binomial regression. Based on the prediction model, the police agency can do the optimal manpower allocation for given values in the selected variables.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.7-11
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• 1998

ATM 망을 효율적으로 구축하고 여러 가지 형태의 제어를 통하여 망 자원을 안정적으로 관리하기 위해서는 망의 성능에 대한 다양한 관점에서의 분석이 필수적이며, 그 기본이 되는 것이 ATM 다중화기에 대한 성능 분석이다. ATM 다중화기에 입력되는 트래픽을 분석하는데 있어서 MRP(Markov Renewal Processes) 또는 SMP(Semi-Markov Processes)는 자동 상관계수를 계산하기가 비교적 용이해서 높은 양의 상관관계를 가지는 버스티한 트래픽을 표현하기에 적절한 구조를 가지고 있으며, 입력 트래픽의 머무는 시간이 어떠한 분포이든 표현 가능한 장점이 있다. 본 연구에서는 ATM 트래픽을 분석하는데 있어서 입력되는 on/off 소스를 MRP로 모형화하고, 이를 도착과정으로 하는 이산시간 MR/D/1B 대기시스템으로 구성하여 ATM 다중화기의 셀 손실확률 등의 성능분석을 제시한다. 또한 본 연구에서 제시한 방법에 대한 타당성 검증을 위하여 시뮬레이션과 비교 검토한다.

• 한국노년학
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• v.41 no.3
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• pp.353-371
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• 2021

The purpose of this study is to provide clues to social welfare policy making by revealing discourse on social intervention and response based on big data on elderly living alone in the COVID-19 situation. Keyword analysis, network analysis, and topic analysis were utilized to explore the ways in which news media have portrayed challenges facing older individuals and the ways in which the central and local government as well as private organization have responded to them. Results are as follows. First, networks(degree, closeness, betweenness) were formed around region, delivery, society, support, and vulnerability, suggesting an increased demand for economic assistance and social support as well as stronger service delivery systems. Second, key topics derived included "establishing public delivery systems", "establishing local networks", "Managing care gap", "Establishing a private economic support system", and "Establishing service organization system". Based on the research results, discourse on the organic role of government, communities and the private sector has been presented, suggesting policy and practical implications by proposing a discussion on how to intervene for elderly living alone in disaster situations such as COVID-19.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.393-403
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• 2012

This study is to investigate social network of sports for all's instructor and occupational achievement. To accomplish this goal, this study sampled 240 instructors of sports facilities of Seoul utilizing purposive sampling method in 2011. But this study finally used 203 samples in data analysis. Validity and reliability of instruments tested by expert meetings and reliability analysis. Chronbach's ${\alpha}$ is over .674. Data analysis is logistic regression analysis and multiple regression analysis using SPSSWIN 18.0. Conclusions are the followings. First, gender, number of employment influence on employment throughout individual network. Second, social network influences on occupational achievement. Namely, individual network influences on wage satisfaction, social network influences fitness of academic career.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.178-188
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• 2009

A blog is a personal website where its owner publishes his/her articles for others. A blog can have relationships with other blogs. In this paper, we define a network that is composed of blogs connected together with such relationships as a blog network. Blog networks can have two different propensities characterized by the articles published in the blogs: information-valued propensity and friendship-valued propensity. The degree of each propensity of a blog network plays an important role in deciding business policies for blog networks. In this paper, we address the problem of determining the degrees of two propensities of a given blog network. First, we determine the degree of the propensity of every relationship, a basic unit of a blog network, by using classification that is one of data mining functionalities. Then, by utilizing the result thus obtained, we compute the degrees of two propensities of the whole blog network. Also, we propose a method to solve the problem that the degree of propensities depends on the size of blog networks. To verify the superiority of the proposed approach, we perform extensive experiments using a huge volume of real-world blog data. The results show that our approach provides high accuracy of around 93% in determining the degrees of both propensities of relationships between arbitrary two blogs. We also verify the applicability of the proposed approach by showing that if determines the degrees of the information-valued and friendship-valued propensities correctly in real-world blog networks.

• The Journal of Engineering Geology
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• v.25 no.3
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• pp.369-376
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• 2015

Numerical models simulating groundwater flow are often used to estimate groundwater discharge into a tunnel. In designing numerical models, the grid size should be carefully considered to ensure that groundwater discharge is accurately predicted. However, several recent studies have employed various grid sizes without providing an adequate explanation for their choice. This paper suggests the optimal grid size based on a comparison of numerical models with analytical solutions. Discrepancies between numerical and analytical solutions result from the effect of model boundaries as well as the grid size. By nullifying boundary effects, the errors solely associated with the grid size could be analyzed. The optimal grid size yielding accurate numerical solutions was thus derived. The suggested relationship between tunnel radius and optimal grid size is analogous to the relationship between the equivalent well block radius and grid size.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.713-720
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• 2004

In this paper we suggest error control scheme to improve CLR performance degradation on wireless ATM access networks which consist of access node and wireless channel. Based on the cell scale and hurst scale, traffic model of wireless ATM access network is analyzed. The CLR equation due to buffer overflow for wireless access node is derived for VBR traffic. the CLR equation due to random bit errors and burst errors for wireless channel is derived. Using the CLR equation for both access node and wireless channel, the CLR equation of wireless ATM access network is derived, and we evaluate the CLR performance on the wireless ATM access networks with conventional SR ARQ scheme and recommended error control scheme, that is, Type I Hybrid ARQ scheme. It is confirmed that CLR performance of the access networks with recommended error control schemes is superior to that of access networks with conventional error control scheme.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.75-86
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• 2020

Hotel review data can extract various information that includes purchasing factors that lead to consumption, advantages, and disadvantages for hotels. In particular, the sentiment keyword of the review data helps consumers understand the pros and cons of hotels. However, it is not efficient for consumers to read a large number of reviews. Therefore, it is necessary to offer a summary review to customers. In this study, we suggest providing summary information on sentiment keywords association as well as a network of hotels based on sentiment keywords. Based on a sentiment keyword dictionary, the extracted sentiment keywords associations construct the hotel network through topological data analysis based mapper. This hotel network allows a consumer to find some hotels associated with specific sentiment keywords as well as recommends the same related hotels. This summary information provides users with a summarized emotional assessment of hotels and helps hotel marketing teams understand consumers' perceptions of their hotel.