• East Asian mathematical journal
• /
• 제40권1호
• /
• pp.119-125
• /
• 2024

Predicting the number of ICU patients holds significant importance, serving as a critical aspect in efficiently allocating resources, ensuring high-quality care for critically ill individuals, and implementing effective public health strategies to mitigate the impact of diseases. This research focuses on estimating ICU patient numbers through the development of a simple mathematical model. Utilizing data on confirmed COVID-19 cases and deaths, this model becomes a valuable tool for predicting and managing ICU resource requirements during the ongoing pandemic. By incorporating historical data on infected individuals and fatalities from previous weeks, we establish a straightforward equation. We found the substantial impact of the delay in infected individuals, particularly those occurring more than five weeks earlier, on the accuracy of ICU predictions. Proactively preparing for potential surges in severe cases becomes feasible by forecasting the demand for intensive care beds, ultimately improving patient outcomes and preventing excessive strain on medical facilities.

• 문화기술의 융합
• /
• 제8권6호
• /
• pp.861-866
• /
• 2022

서울시에서는 공유 자전거 시스템, "따릉이"를 2015년부터 도입, 운영하여, 교통량 감축과 대기오염 해소를 위해 노력하고 있다. 하지만 공유 자전거 시스템, "따릉이"의 운영전략 미훕으로 인해 많은 문제가 발생하고 있어 이를 해결하고자 다양한 연구들이 제시되고 있다. 이들 연구의 대다수는 수요와 공급의 불균형을 해결하고자 하는 전략적 "자전거 배치"에 집중되어 있으며 또한 이들 중 다수가 날씨나 계절과 같은 특징을 그룹화함으로써 수요를 예측하고 있다. 그리고 이전에는 이들 예측방법이 주로 시계열 분석을 기반으로 하고 있었으나 최근에는 딥러닝/머신러닝으로 수요를 예측하는 연구들이 속속 등장하고 있다. 본 논문에서는 기존에 제시된 다양한 특징들을 기반으로 하면서, 새로운 특징을 발견하고 선택된 특징들의 중요도를 비교, 이를 순서화함으로써, 보다 정확한 수요 예측이 가능함을 보인다. 그리하여, 우리는 기존의 딥러닝/머신러닝 및 시계열 분석을 그대로 사용하면서 비교적 정확한 결정계수를 획득하고 이를 이용해 개선된 수요예측이 가능하도록 한다.

• 한국방재안전학회논문집
• /
• 제14권2호
• /
• pp.35-42
• /
• 2021

본 논문은 전기자동차 충전시설 확충계획에 중요한 요소인 전기자동차 전력 수요량 예측정보를 생산하기 위하여 Exponential Smoothing를 이용하여 전력 수요량 예측 모형을 제안하였다. 모형의 입력자료 구축을 위하여 종속변수로 월별 시군구 전력수요량을 독립변수로 월별 시군구 충전소 보급대수, 월별 시군구 전기자동차 충전소 충전 횟수, 월별 전기자동차 등록대수 자료를 월 단위로 수집하고 수집된 7년간 자료 중 4년간 자료를 학습기간으로 3년간 자료를 검증 기간으로 적용하였다. 전기자동차 전력 수요량 예측 모형의 정확성을 검증하기위하여 통계적 방법인 Exponential Smoothing(ETS), ARIMA모형의 결과와 비교한 결과 ETS, ARIMA 각각의 오차율은 12%, 21%로 본 논문에서 제시한 ETS가 9% 더 정확하게 분석되었으며, 전기자동차 전력 수요량 예측 모형으로써 적합함을 확인하였다. 향후 이 모형을 이용한 전기자동차 충전소 설치 계획부터 운영관리 측면에서 활용될 것으로 기대한다.

• 한국인터넷방송통신학회논문지
• /
• 제19권1호
• /
• pp.171-178
• /
• 2019

한국의 조선 산업은 대내외 환경 변화로 인해 심각한 위기 상황에 처해 있다. 이 위기를 극복하기 위해서, 선박 신수요 예측을 통한 제품 및 기술의 선제적 개발이 필요하다. 본 연구의 목표는 선박 신수요 예측을 위해 선박 빅데이터에 기반한 인공지능 알고리즘의 개발이다. 본 연구에서는 선박 수요 예측에 특화된 빅데이터 분석 플랫폼을 개발하고 데이터 분석을 통한 선박 신수요 예측 결과를 신제품 기획/개발에 활용하고자 한다. 이를 통해 장비 및 기자재 제조업체를 위한 지속 가능한 신사업 모델 개발로 조선소 및 선박 기자재 업체에 대한 신성장동력을 창출할 수 있을 것이다. 또한 조선 업체들은 측정 가능한 성과를 기반으로 비즈니스 사례를 창출하고 시장 지향적 인 제품과 서비스를 계획하며 높은 시장 파괴력을 가진 혁신을 지속적으로 달성 할 수 있을 것으로 기대된다.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
• /
• pp.207-210
• /
• 1997

The drastic structural changes in telecommunications industry are imposing new strains on operators, regulators and customers. Many researchers have offered diverse frameworks for the changes from the perspectives of sociology, technology, and/or economics. However, there have been few attempts to document the competitive phenomena from management perspectives because of the technological complexities and dynamism in the fundamental transition of competition. In this study, we examine competitive environment in telecommunications industry, and identified five structural elements; telecom operator, competitors, regulation, suppliers, and customer demand. The suggested framework is used to provide a basis for explaining the changes in the characteristics of individual elements and the interactions among them. The dynamic industry-specific changes will be explained through an evolutionary model. We specify the characteristics of progressive stages and the determinants of the evolution. Changes are reviewed in terms of five criteria; regulations and competitions, value chain, technology, customers demand, and internal operations. The result of this study will be useful in analyzing and predicting industry structure and major participants' strategic behaviors and decision patterns. This study can alse be extended to other industries facing dynamic structural changes.

• 산업경영시스템학회지
• /
• 제34권4호
• /
• pp.169-178
• /
• 2011

In this study, a forecasting engine from the user perspective is studied and developed. Characteristics of forecasting engine can be divided into a few categories, an algorithms for predicting variety of situations and the depth of algorithms based on the number and the types of data. Then applying a variety of algorithms that most closely match the predicted values for the actual value that deduce criteria for selecting an appropriate forecasting algorithm is to organize. Through the forecast quality assessment, the suggested distribution algorithm compared to the existing demand forecast algorithms is good indicators for its accuracy.

• 한국정보시스템학회지:정보시스템연구
• /
• 제26권3호
• /
• pp.171-185
• /
• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• 한국해양공학회:학술대회논문집
• /
• 한국해양공학회 2003년도 추계학술대회 논문집
• /
• pp.163-166
• /
• 2003

Hull form designers have to design a ship with satisfying an economical, technical and environmental demand. When it is concerned by a technical and environmental demand, there will be a economical demand left to criticize optimization. In this case, there were used to be requirements which needs to meet only a best performance not concerning about input of Human resource. Life cycle's cost contains building cost and operation cost so that now we need to check Man Hour cost in building a ship. This research shows a correlation between hull form information, i.e. curvature, length, breadth and thickness of surface and Man Hour of the Shell plating manufacture with using Artificial Neural Network and Gentic Programming. This study will support to classify initial work, to have a high assumption possible through predicting a Man Hour and to provide a guide book to infer a building cost and a economical optimization hull form.

• 한국태양에너지학회:학술대회논문집
• /
• 한국태양에너지학회 2008년도 춘계학술발표대회 논문집
• /
• pp.111-116
• /
• 2008

The objective of this paper was to show the possibility of demand-controlled ventilation (DCV) using the current Korean ventilation standard for multi-purposed facilites. Two attractive DCV approaches; $CO_2$-DCV and RFID-DCV were applied to DCV simulations for a theoretical public assembly space served by a dedicated outdoor air system (DOAS) with enthalpy recovery device. A numerical model for predicting realtime occupant number, ventilation rate, and $CO_2$ concentration under given conditions was developed using a commercial equation solver program. It was found that the current ventilation standard causes unstable ventilation system control in DCV applications, especially under $CO_2$-DCV. It is because the ventilation rate (per person) used in Korea is the sum of the outdoor air required to remove or dilute air contaminants generated by both occupant and building itself, and not a pure function of occupant numbers. Finally, it makes DCV control unstable when ventilation flow is regulated only by the number of occupants. In order for solving this problem, current Korean ventilation standard was modified as a form of ASHRAE Standard 62.1-2007 showing good applicability to various DCV approaches. It was found that this modification enhances applicability of the current ventilation standard to DCV significantly.

• Child Health Nursing Research
• /
• 제16권1호
• /
• pp.84-92
• /
• 2010

Purpose: One of the main reasons why mothers quit breast feeding is that the volume of breast milk is inadequate due to insufficiency in suckling. We believe suckling experience may be a factor affecting nipple confusion. So an alternative feeding method, namely cup, spoon, finger, or nasogastric tube feeding may be needed to prevent nipple confusion. The purpose of this study was to construct a predictive model for demand for alternative feeding education by nurses. Methods: A descriptive design with structured self-report questionnaires was used for this study. Data from 175 nurses working in hospitals in Busan were collected between April 1 and 15, 2009. Data were analyzed by decision tree method, one of the data mining techniques using SAS 9.1 and Enterprise Miner 4.3 program. Results: Of the nurses, 81.1% demanded alternative feeding education and 5 factors showed that most of them expressed intention to pay, desire to know about alternative feeding, age, and learning experience. From these results, the derived model is considered appropriative for explaining and predicting demand for alternative feeding education. Conclusion: This confirms that knowledge and compliance in alternative breast feeding for newborn babies should be correct and any inaccuracies or insufficient information should be supplemented.