• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.378-388
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• 2016

International societies are currently working together to achieve the Climate-Smart Agriculture (CSA) initiative which aims the triple wins: (1) sustainably increasing agricultural productivity and incomes; (2) adapting and building resilience to climate change; and (3) mitigating greenhouse gases emissions. In terms of its scope and context, CSA follows the '3Nong (三農)' vision cast about 200 years ago by Dasan Jeong Yak-Yong who emphasized the triad of governance, management and monitoring towards comfortable, profitable and noble agriculture. Yet, the CSA provides the practical aims that facilitate the development of holistic indicators for quantitative evaluation and monitoring, on which decision-making support system is based. In this study, we introduce an agent-based model, i.e. Mathematical Programming Multi-Agent Systems (MP-MAS), as a tool for supporting the decision-making toward CSA. We have established the initial version of MP-MAS adapted for domestic use and present the preliminary results from an application to the rice farming case in Haenam, Korea. MP-MAS can support both farmers and policy-makers to consider diverse management options from multiple perspectives. When the modules for system resilience and carbon footprint are added, MP-MAS will serve as a robust tool that fulfills not only CSA but also Dasan's '3Nong' vision of sustainable agricultural-societal systems.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.39-39
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• 2017

한반도 기후변화 경향은 이미 기상 생태 환경 수자원 등 광범위한 부분에서 감지되고 있다(기상청, 2011a, 2011b). 현재까지의 연구에 따르면 한반도 기후변화에 따른 영향으로 강우패턴은 첨두강우가 7월에서 점차 8월로 이동 변화하는 것으로 전망되고, 양적으로 연강수량은 점차 감소가 전망되면서도 극한 값은 발생빈도와 크기가 점증할 것으로 전망되고 있다. 그래서 그간 기존댐에 대한 재평가(1998, 2010, 2012)와 발생 가능한 최대강우량 설계기준으로 기존 댐의 여수로 배제 능력을 증대시키는 비상여수로 설치 등 기존 댐 시설위주의 효율적인 기후변화 대응 또는 적응 방안을 시행해 왔다. 그러나, 기후변화로 인한 기상 상황은 전에 발생한 적이 없었던 새로운 기상이변과 재난을 가져오고 있다. 이에 기상 변화에 하나의 시설로서 대응 하던 방식에서 한 번의 기상이변이 유역 전반에 걸쳐 재난을 발생하는 최근의 상황에 맞추어 수자원 시설을 계획하는 방식에 대한 변화의 필요성 있다고 생각하였다. 이에 장래 전망되는 기후변화를 감안하여 이수와 치수 시설의 가뭄과 홍수에 대한 대처 능력을 유역 차원에서 평가하는 방법을 찾아보고자 한다. Robust 하다는 것은 어떤 상황에서도 작동이 되는 것을 말하는 강건한 계획으로, 이와 같은 시설 계획을 위해서는 먼저 현재의 시설물에 대한 회복력을 판단하는 평가가 있어야 할 것이다. 따라서, 용수공급이든 홍수 재난이든 회복력(복원력)에 대한 평가를 하고, 대안에 대한 로버스트 의사 결정 방법(RDM: Robust Decision Making)을 적용하여 우수한 대안을 찾으면 강건한 시설계획 수립이라는 절차가 될 수 있다고 판단하였다. 본 연구는 회복력(복원력)을 갖는 로버스트 의사결정방법에 대한 과거 연구 조사를 기초로 하여 연구 수행 절차를 마련한 후에 장래 한반도 기후변화 시나리오를 시범 유역에 적용하여 수자원 시설의 복원 또는 회복력을 분석하고, robust 의사결정방법을 적용함으로써, 향후 로버스트 수자원 시설 계획이 어떻게 이루어져야 하는지와 함께 이수와 치수 시설의 종합적인 계획 등에 대한 개념적인 절차와 방법의 제시를 도모하였다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.462-468
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• 2019

Offshore oil production faces several difficulties caused by oil price decline and unexpected changes in the global petroleum logistics. This paper suggests a stochastic model for optimizing the offshore oil production under uncertainty. The proposed model incorporates robust optimization and restricted recourse framework, and uses the lower partial mean as the measure of variability of the recourse profit. Some computational experiments and results based on the proposed model using scenario-based data on the crude oil price and demand under uncertainty are examined and presented. This study would be meaningful in decision-making for the offshore oil production problem considering risks under uncertainty.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.81-98
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• 2009

Collaborative filtering, one of the most successful technologies among recommender systems, is a system assisting users in easily finding the useful information and supporting the decision making. However, despite of its success and popularity, one notable issue is incredibility of recommendations by unreliable users called shilling attacks. To deal with this problem, in this paper, we analyze the type of shilling attacks and propose a unique method of building a model for protecting the recommender system against manipulated ratings. In addition, we present a method of applying the model to collaborative filtering which is highly robust and stable to shilling attacks.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.362-379
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• 2015

In this study, Nuclear Power Plant (NPP) construction schedule delay risk assessment methodology is developed and the construction delay risk is assessed for turnkey international NPP projects. Three levels of delay factors were selected through literature review and discussions with nuclear industry experts. A questionnaire survey was conducted on the basis of an analytic hierarchy process (AHP) and Relative Importance Index (RII) methods and the schedule delay risk is assessed qualitatively and quantitatively by severity and frequency of occurrence of delay factors. This study assigns four main delay factors to the first level: main contractor, utility, regulatory authority, and financial and country factor. The second and the third levels are designed with 12 sub-factors and 32 sub-sub-factors, respectively. This study finds the top five most important sub-sub-factors, which are as follows: policy changes, political instability and public intervention; uncompromising regulatory criteria and licensing documents conflicting with existing regulations; robust design document review procedures; redesign due to errors in design and design changes; and worldwide shortage of qualified and experienced nuclear specific equipment manufacturers. The proposed combined AHP-RII methodology is capable of assessing delay risk effectively and efficiently. Decision makers can apply risk informed decision making to avoid unexpected construction delays of NPPs.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.123-140
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• 2023

In recent times, the global economy has been subject to increasing volatility, which has made it considerably more difficult to accurately predict economic indicators compared to previous periods. In response to this challenge, the present study conducts an exploratory investigation that aims to predict the Business Survey Index (BSI) by leveraging data mining techniques on both structured and unstructured data sources. For the structured data, we have collected information regarding foreign, domestic, and industrial conditions, while the unstructured data consists of content extracted from newspaper articles. By employing an extensive set of 44 distinct data mining techniques, our research strives to enhance the BSI prediction accuracy and provide valuable insights. The results of our analysis demonstrate that the highest predictive power was attained when using data exclusively from the t-1 period. Interestingly, this suggests that previous timeframes play a vital role in forecasting the BSI effectively. The findings of this study hold significant implications for economic decision-makers, as they will not only facilitate better-informed decisions but also serve as a robust foundation for predicting a wide range of other economic indicators. By improving the prediction of crucial economic metrics, this study ultimately aims to contribute to the overall efficacy of economic policy-making and decision processes.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.17-17
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• 1996

An experimental research is a useful approach for realizing autonomous mobile robots to work in real environment. We are developing an autonomous mobile robot platform named "Yamabico" as a tool for experimental real world robotics research. The architecture of Yamabico is based on the concept of centralized decision making and functionally modularization. Yamabico robot has two level structure with behavior and function levels, and its hardware and software are functionally distributed for providing incremental development and good maintenancibility. We are using many Yamabico robots in our laboratory to realize the robust navigation technology for autonomous robots. The methodology for experimental and task-oriented approach of mobile robotics will be presented. And some experimental results of real world navigation in indoor and outdoor environment will be shown. be shown.

• Smart Structures and Systems
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• v.4 no.5
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• pp.517-530
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• 2008

This paper deals with civil infrastructures in general, sensor and smart structure technology, and smart steel structures in particular. Smart structures technology, an integrated engineering field comprising sensor technology, structural control, smart materials and structural health monitoring, could dramatically transform and revolutionize the design, construction and maintenance of civil engineering structures. The central core of this technology is sensor and sensor networks that provide the essential data input in real time for condition assessment and decision making. Sensors and robust monitoring algorithms that can reliably detect the occurrence, location, and severity of damages such as crack and corrosion in steel structures will lead to increased levels of safety for civil infrastructure, and may significantly cut maintenance or repair cost through early detection. The emphasis of this paper is on sensor technology with a potential use in steel structures.

• 한국디지털정책학회:학술대회논문집
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• 2003.12a
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• pp.11-24
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• 2003

It is far more expensive for companies to acquire new customers than it is to retain customers. As a result, companies are turning to Customer Relationship Management (CRM) in order to make decisions about managing the relationship and the profitability of those customer relationships. CRM is a strategy that integrates the concepts of Knowledge Management, Data Mining and Data Warehousing in order to support the organization's decision -making process to retain long-term and profitable relationships with its customers. This paper examines the design implications that CRM poses to data warehousing. We then present a robust data warehouse schema to support CRM analyses and decisions. For example, the proposed schema could be used to calculate customer profitability and to identify social networks of influence between customers. The paper also discusses future areas for research pertaining to CRM data warehousing and data mining.