• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.61-68
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• 2020

E-sports has grown steadily in recent years and has become a popular sport in the world. In this paper, we propose a win-loss prediction model of League of Legends at the start of the game. In League of Legends, the combination of a champion statistics of the team that is made through each player's selection affects the win-loss of the game. The proposed model is a deep learning model based on Bidirectional LSTM embedding which considers a combination of champion statistics for each team without any domain knowledge. Compared with other prediction models, the highest prediction accuracy of 58.07% was evaluated in the proposed model considering a combination of champion statistics for each team.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.27-43
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• 2024

The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.339-342
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• 2007

The power control system of Smart UAV is similar to the propeller pitch governing concept of turboprop aircraft. The pilot inputs the engine power directly and the pitch governor controls the propeller pitch to maintain the propeller RPM. The manual back-up system of PW206C engine is used for the engine power control of Smart UAV. Engine performance estimation program is used to predict the control range of power lever arm(PLA) angle according to the variation of flight altitude and speed. These data provide a guide for the engine control in manual mode operation.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.4
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• pp.42-47
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• 2008

The power control system of Smart UAV is similar to the propeller pitch governing concept of turboprop aircraft. The pilot adjusts the engine power directly and the pitch governor controls the propeller pitch to maintain the propeller rotational speed. The electronic engine controller(EEC) of PW206C engine developed for helicopter is not fit for the power control concept of Smart UAV, and therefore the manual back-up system of PW206C engine is used for the engine power control of Smart UAV. Engine performance estimation program is used to predict the control range of power lever angle(PLA) according to the variation of engine output shaft speed, flight altitude and flight speed. These data provide a guide for the PLA control in manual mode operation.

• 한국벤처창업학회:학술대회논문집
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• 2017.04a
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• pp.17-17
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• 2017

구조방정식모델(Structural Equation Modeling: SEM)은 변수들 간의 인관관계 및 상관관계를 검증하기 위한 통계기법으로 사회학 및 심리학 분야에서 개발되었지만 현재는 경영학, 광고학, 교육학, 생물학, 체육학, 의학, 정치학 등 여러 학문분야에서 광범위하게 사용되고 있다. Amos는 기본적으로 그래픽(Amos graphics)과 베이직(Amos basic)을 제공하기 때문에 정확한 프로그램의 작성이나 행렬에 대한 지식이 없는 초보자들도 아이콘을 이용하여 복잡한 연구모델이나 다중집단분석모델을 분석할 수 있다. PLS(Partial Least Square)는 모형 추정과정에서 발생하는 잔차 또는 예측오차를 최소화하여 예측력을 극대화하기 위한 프로그램이며, 즉, PLS-SEM는 표본 수가 적고 자료가 정규분포를 보이지 않거나 조형지표 모델이거나 복잡한 연구모델 분석에 유용하다. 최근 빅데이터의 열풍으로 자료들을 분석을 위한 도구로 R이 실무 현장에서 인기를 끌고 있다. R은 통계 프로그래밍 언어이자 오픈 소프트웨어 환경으로 통계, 그래픽, 데이터마이닝 등의 다양하고 방대한 양의 패키지들을 지원한다. R에서 제공되는 패키지들이 오픈 소스이고 선형 및 비선형 모델링, 고전적인 통계분석, 시 계열 분석, 분류 및 군집분석 등의 다양한 통계 패키지들을 제공한다는 측면에서 R은 실무는 물론 학문적인 측면에서도, 특히 통계를 기반으로 실증분석을 수행하는 사회과학연구들에서 중요한 역할을 할 수 있을 것으로 기대된다.

• Information and Communications Magazine
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• v.30 no.12
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• pp.17-24
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• 2013

본고에서는 세계전파통신회의(WRC: World Radio Conference)에서 IMT로 지정된 주파수 현황과 국내 이동통신 주파수 현황 및 계획을 알아본다. 또한 현재 시점에서 데이터 트래픽 증가 추세에 비추어 2020년 Beyond4G(5G)시대를 대비한 ITU(국제전기통신연합) 해당 표준화그룹의 소요량 예측 및 통신방식별 분담 율을 분석하였다. 주파수 수요예측에 따라 WRC-15에서 IMT 추가 주파수 지정 목적으로 진행하고 있는 위성, 방송, 과학 및 고정 등 기존업무와의 공유 연구 진행현황을 주파수 대역별로 살펴본다. 또한 도시 밀집 지역에서 대용량 데이터 전송을 위한 서비스 기술이 중요해진 시점에서 Beyond4G(5G) 시대를 위해 우리나라가 주도하고 있는 6GHz 이상 대역을 IMT로 활용하기 위한 활동을 소개한다. 마지막으로 WRC가 주파수를 분배 할당하는 방식인 '주파수 대역에 서비스 방식 지정'과 달리 '서비스 방식에 의한 주파수 대역 점유(예: LTE 기술표준(PS-LTE)을 PPDR대역에서 활용) 가능성'등 LTE 기술표준의 확산 추세에 대응하기 위해 5G시대에 준비할 사항에 대한 시사점을 언급하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.66-68
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• 2015

최적항로 지원 시스템은 실해역 속도 성능 예측방법에서의 선택 근거확보와 정확도 평가를 위한 효과 검증이 반드시 필요하다. 하지만 이 같은 성능검증에 있어서 동일한 선박에 대한 다양한 대안 항로에서의 동시성능계측이 불가능하기 때문에 효과를 직접 비교하기는 상당히 어렵다. 따라서 본 논문에서는 최적항로 지원 시스템의 효과 검증을 위한 간접적인 절차를 제안하였고, 시스템의 내부 분석코드를 이용하여 효과를 비교 검증하였다. 그 절차는 1) 계산의 근거 인기상 정보의 정확성 검증, 2) 실제 항로에서의 성능예측계산의 신뢰성 확인, 3) 신뢰성이 확보된 계산방법을 이용한 최적항로선택, 4) 실제 항로와 최적항로의 연료 효율성 비교의 4단계로 이루어진다. 대상 선박은 폴라리스쉬핑의 솔라돌핀호(208k BC)이며 실선 운항 데이터는 최적항로 지원 시스템을 통하여 직접 계측하였다. 그 결과 호주-한국 항차에서 최적항로를 항해할 경우 약 6.0%의 연료 절감 효과를 기대할 수 있음을 확인하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.5
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• pp.275-285
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• 2006

This paper proposes an efficient market mechanism-based resource transaction model for grid computing. This model predicts the next resource demand of users and suggests reasonable resource price for both of customers and resource providers. This model increases resource transactions between customers and resource providers and reduces the average of transaction response times from resource providers. For prediction accuracy improvement of resource demands and suggestion of reasonable resource price, this model introduces a statistics-based prediction model and a price decision model of microeconomics. For performance evaluating, this paper measures resource demand prediction accuracy rate of users, response time of resource transaction, the number of resource transactions, and resource utilization. With 87.45% of reliable prediction accuracy, this model works on the less 72.39% of response time than existing resource transaction models in a grid computing environment. The number of transactions and the resource utilization increase up to 162.56% and up to 230%, respectively.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.237-250
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• 2017

A new field of e-sports gains the great popularity in Korea as well as abroad. AOS (aeon of strife) genre games are quickly gaining popularity with gamers from all over the world and the game companies hold game competitions. The e-sports broadcasting teams and webzines use a variety of statistical indicators. In this paper, as an AOS genre game, League of Legends game data is used for statistical analysis using the indicators to predict the outcome. We develop new indicators with the factor analysis to improve existing indicators. Also we consider discriminant function, neural network model, and SVM (support vector machine) for make winning forecasting models. As a result, the new position indicators reflect the nature of the role in the game and winning forecasting models show more than 95 percent accuracy.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.81-94
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• 2022

Real estate and artworks were considered challenging investment targets for individual investors because of their relatively high average transaction price despite their long investment history. Recently, the so-called fractional investment, generally known as investing in a share of the ownership right for real-life assets, etc., and most investors perceive that they actually own a piece (fraction) of the ownership right through their investments, is gaining popularity. Founded in 2016, Musicow started the first service that allows users to invest in copyright fees related to music distribution. Using the LSTM algorithm, one of the deep learning algorithms, this research predict the price of right to participate in copyright fees traded in Musicow. In addition to variables related to claims such as transfer price, transaction volume of claims, and copyright fees, comprehensive indicators indicating the market conditions for music copyright fees participation, exchange rates reflecting economic conditions, KTB interest rates, and Korea Composite Stock Index were also used as variables. As a result, it was confirmed that the LSTM algorithm accurately predicts the transaction price even in the case of fractional investment which has a relatively low transaction volume.