Earticle

본 연구는 프로젝트 경영 분야 중 Al-Harbi (2001)의 논문을 Pyrczak (2008)이 제시한 평가절차에 의하여 분석하였다. 분석 대상으로 선정된 Al-Harbi (2001)의 논문은 프로젝트 경영에서 의사결정방법론으로서의 AHP (Analytical Hierarchy Process) 적용 가능성을 제시하였다. 이러한 논문의 평가를 위해서 여러 절로 구분하여 Pyrczak (2008)에서 제시하는 분석표에 의해 논문을 세부적으로 평가하였다. 본 연구는 연구 논문의 평가 방법을 정량화된 수치에 의해 보여줄 수 있음을 제안했다는 점에의 의미를 갖고 있다.

This study focuses on the evaluation of an article about the AHP methodology in project area at 2001 edition. It is titled, “Application of AHP in project management,” by K.M.A.S-S. Al-Harbi. This paper presents the Analytical Hierarchy Process (AHP) as a decision making method in project management. The evaluation by each section is based on the model by Fred Pyrczak (2008) in Evaluating Research in Academic Journals. This paper has an implication that evaluation method can be shown by quantitative numerical value.

A comprehensive understanding of functions and performances enables a selection of appropriate alternatives to the existing design and can prevent defective design. A performance-based design quality management can ensure successful project completion. This study proposes a new model for design quality management in order to prevent defective design and to minimize design change. The new quality management model defines the requirement about function and performance based on technical characteristic, and assesses suitability for design alternatives. This study attempts to propose a quality matrix assessment method that can compare the alternative design and requirements defined with the new quality management model. This method can judge conformity and suitability of design quality in accordance with the requirements configured.

Interval-valued neutrosophic hesitant fuzzy set (IVNHFS) is an extension of neutrosophic set (NS) and hesitant fuzzy set (HFS), each element of which has truth membership hesitant function, indeterminacy membership hesitant function and falsity membership hesitant function and the values of these functions lie in several possible closed intervals in the real unit interval [0,1]. In contrast with NS and HFS, IVNHFS can be more flexibly used to deal with uncertain, incomplete, indeterminate, inconsistent and hesitant information. In this study, I propose the novel correlation coefficient of IVNHFSs and my paper discusses its properties. Then, based on the novel correlation coefficient, I develop an approach to deal with multi-attribute decision-making problems within the framework of IVNHFS. In the end, a practical example is used to show that the approach is reasonable and effective in dealing with decision-making problems.

Emergency incident makes a high request for timeliness of emergency rescue. How to make scientific and reasonable schemes and reduce the influence of subjectivity is the key to rescue in order. According to situations in disaster, three issues of environmental limits, objective attributes and subjective judgments need to consider in decision-making. A method combing cloud model and interval number was put forward. An optimal scheme was obtained by comparing the rescue scheme evaluation cloud with the standard cloud. The results showed that the cloud model decision-making method can overcome the subjectivity of decision and the conclusion was clear and easy to sort. With this method the decision scheme can be more direct and vivid.

In order to respond to coastal disasters, it is necessary to prepare a system that can comprehensively judge opinions by collecting experts' opinions, and to establish optimal policy alternatives based on this. This study attempted to select detailed priorities and weights for policy establishment to establish a coastal disaster response system using a fuzzy multi-criteria decision-making method. In particular, this study was intended to identify the importance and priority of detailed stages of the coastal disaster response system, and to identify the importance and priority of each detailed technology for related technology development research. As a result of analyzing expert answers on the importance of detailed stages of the coastal disaster response system, it was found that the weight of prediction and preparation was higher than recovery and evaluation with a large gap. In the case of technical items for strengthening the coastal disaster response system, the importance of technology related to the forecasting stage was found to be great. appeared to be important.

본 연구는 R&D정책기획시 개발기술의 사업화관점에 서 의사결정방안을 제시하는 것이다. 이를 위해 예산배 분의 효율성 관점에서 특정 기술분야에 지원된 정부 지 원예산 수준과 사업화성과를 비교하고자 하였다. 주요 방법론으로는 연구개발과제와 관련된 기술과 제품 간의 연계 형태를 네트워크 분석방법을 이용하였다.

Nowadays, many countries have strived to promote prospective industries and occupations at the national level under the global circumstances such as green growth, job creation and so on. For this reason, the decision making method for qualifications foresight which will be available for the mentioned category-prospective industry and occupation- is required for it's feasibility. Pilot surveys on future workforce demand and promotion policies on service industries which are selected as a prospective industry or occupation by government parties were conducted through this research. Based on them, available qualifications-including not only national(skill) qualification but also private qualification- which can be created for prospective industries and occupations related to green growth and job creation were predicted. On the other hand, observing the change of service industry, occupation and qualification abroad, this research attempts to present the decision making method for verifying the decision' validity on qualification in Korean service industry and related occupation. Applying multicriteria decision making, a preference was examined for checking the validity of the created qualifications by prospective service industries and occupations in both sides-experts and laypeople. Based on it's result, the research was conducted regarding a validity of new qualifications in prospective industries and occupations.

본 연구는 강건성 지수와 불확실성 분석기법을 활용하여 기후변화 취약성 평가과정에서 발생하는 불확실성을 정량화하였다. 본 연구는 우리나라의 6개 광역시(부산, 대구, 인천, 광주, 대전, 울산)를 대상으로 다기준 의사결정기법 중 하나인 TOPSIS 기법을 이용하여 용수공급 취약성 순위를 산정하였다. 강건성 지수는 두 대상 도시의 순위가 가중치의 변화로 인해 순위역전현상이 발생할 수 있는 가능성을 정량화하고 불확실성 분석 기법은 두 도시 사이에 순위역전이 발생할 수 있는 가중치의 최소 변화량을 산정한다. 그 결과 인천과 대구는 용수공급 측면에서 취약한 것으로 나타났으며, 대구와 부산은 용수공급 취약성에 민감한 것으로 나타났다. 따라서 대구는 다른 대안에 비해 상대적으로 용수공급이 취약한 지역으로 나타났으나, 취약성에 민감하기 때문에 기후변화 적응대책 수립 및 시행을 통해 취약성이 크게 향상될 수 있을 것으로 판단된다. 본 연구는 기후변화와 용수공급 측면에서의 적응전략을 계획하고 수립하는데 있어서 우선적으로 고려해야하는 방향을 제안하는 데 사용될 수 있다.

In this study, robustness index and uncertainty analysis were proposed to quantify the risk inherent in the process of climate change vulnerability assessment. The water supply vulnerability for six metropolitan cities (Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan), except for Seoul, were prioritized using TOPSIS, a kind of multi-criteria decision making method. The robustness index was used to analyze the possibility of rank reversal and the uncertainty analysis was introduced to derive the minimum changed weights of the criteria that determine the rank reversal between any paired cities. As a result, Incheon and Daegu were found to be very vulnerable and Daegu and Busan were derived to be very sensitive. Although Daegu was relatively vulnerable against the other cities, it can be largely improved by developing and performing various climate change adaptation measures because it is more sensitive. This study can be used as a preliminary assessment for establishing and planning climate change adaptation measure.

최근 기후변화에 의한 집중호우의 발생빈도 및 강도가 증가하고 있으며, 이로 인한 지자체의 저수지 붕괴 피해가 지 속적으로 발생하고 있다. 지자체 저수지는 대부분 건설된 지 50년 이상된 노후 저수지로, 최근 발생하는 집중호우에 대한 붕괴 위험성이 높다. 집중호우에 의한 저수지 붕괴 또는 월류를 예방하기 위해서는 저수용량 변화에 따른 위험 을 판단할 수 있는 의사결정지원체계가 필요하다. 본 연구에서는 다양한 변수 간의 인과관계를 동적으로 나타낼 수 있는 시스템 다이내믹스 기법을 활용한 저수지 방류 시뮬레이션 모델을 구축하였다. 방류 시뮬레이션을 통해 강우에 의한 저수용량 변화를 분석하고, 저수지 월류 예방을 위한 방류시설의 운영시점 및 종료 시점을 분석하였다. 본 연구 결과를 활용하여 집중호우에 의한 저수지 월류 발생시점을 파악할 수 있으며, 또한 월류 예방을 위한 방류시설의 용 량 및 투입시기를 알 수 있다. 이를 통해 지자체에서는 저수지 피해에 대한 위험을 판단하고, 피해예방을 위한 사전 대응계획을 수립할 수 있을 것으로 기대된다.

Recently, the frequency and intensity of torential rains caused by climate change are increasing, and the damage to reservoir collapse in local governments continues to occur. Most local government reservoirs are aged reservoirs that have been built for more than 50 years, and there is a high risk of collapse due to recent heavy rainfall. In order to prevent reservoir collapse or overflow caused by heavy rainfall, a decision-making support system that can judge risks due to changes in storage capacity is needed. In this study, a reservoir discharge simulation model was constructed using a system dynamics technique that can dynamically represent causal relationships between various variables. Through discharge simulation, the change in storage capacity due to rainfall was analyzed, and the operation time and termination time of the discharge facility to prevent overflow of the reservoir were analyzed. Using the results of this study, it is possible to determine the timing of the overflow of the reservoir due to torrential rain, and also the capacity and operation timing of the discharge facility to prevent overflow can be known. hrough this, it is expected that local governments will be able to judge the risk of damage to reservoirs and establish a preliminary response plan to prevent damage.

As buildings which had been constructed passing through the rapid growth period since 1960s became older, interests in the remodeling market have heightened owing to merits such as comparatively high profitability, short business period, and so on compared with reconstruction. In remodeling, the way of inhabited-condition remodeling of the entire floor focused on big apartment buildings with great unit quantities has been displayed in order to use buildings consistently and maintain the worth of the facilities. Recently, as competition of the housing rent market came to be strong, remodeling advantageous in aspect of profitability is coming to the fore even in non-residential constructions. Especially, since the inhabited-condition remodeling has advantages like guarantee of stable rent profits, reduction of risks in attracting new tenants, and so forth, it is suggested as a new way of remodeling. This inhabited-condition remodeling has diverse considerations in decision making of business due to difficulty that the business should be conducted under more restricted condition like inhabited situation than the remodeling with empty rooms of the entire floor.

기후변화에 따른 집중호우, 태풍 등의 발생빈도의 증가로 인하여 댐 운영의 고도화가 요구되고 있다. 일반적으로 댐 운영의 경우 강우예측, 강우-유출, 홍수추적 등 다양한 수리수문학적 요소들을 반영하여 수행되나 기 계획된 특정 규칙에 기반한 댐 운영 모형의 경우, 때때로 개별 모듈들의 불확실성과 복합적인 인자들로 인하여 댐의 방류량을 능동적으로 제어하는데 제약이 있을 수 있다. 본 연구는 남강댐 직하류 홍수피해 예방을 위하여 댐의 방류량 결정 등 효율적인 댐 운영을 지원하기 위해 딥러닝 기반 LSTM (Long Short-Term Memory) 모형을 구축하고, 선행시간별 댐직하류 수위예측 정확도를 분석하는 것을 목적으로 한다. LSTM 모형의 입력자료는 댐 운영에 사용되는 기초자료 및 하류 장대동 수위관측소의 수위 자료를 시 단위로 2009년부터 2021년 7월까지 수집하였다. 2009년부터 2018년 자료는 모형의 학습과 검증 및 2019년부터 2021년 7월 자료는 선행시간을 7개(1 h, 3 h, 6 h, 9 h, 12 h, 18 h, 24 h)로 구분하여 관측 수위와 예측 수위를 비교·분석하였다. 그 결과, 선행시간 1시간의 예측결과는 평균적으로 MAE가 0.01 m, RMSE가 0.015 m, NSE가 0.99 로 관측 수위에 매우 근접한 예측 결과를 나타내었다. 또한, 선행시간이 길어질수록 예측 정확도는 근소하게 감소하였지만, 관측 수위의 시간적 패턴을 유사하게 안정적으로 예측하는 것으로 분석되었다. 따라서 수리수문학적 비선형의 복잡한 자료간의 특징을 자동으로 추출하여 예측 자료를 생산하는 LSTM 모형은 댐 방류량 의사결정에 있어 활용이 가능할 것으로 판단된다.

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.

공조시스템의 경우 건축물에서 소비되는 에너지량 중 약 절반정도를 차지하고 있을 뿐만 아니라 재실자들의 열적, 음적, 공기적 쾌적성 및 시스템의 경제성, 편리성, 시공성, 사회성 등을 만족시켜야 하는 특성을 지니고 있다. 따라서 공조시스템의 리모델링 시 최적의 계획안을 도출하기 위해서는 CWM 또는 AHP 기법을 사용하여 경제성 외에 다양한 요소들을 바탕으로 이를 종합적으로 평가하여야 하며, 이의 평가를 위해서는 우선적으로 전문가 집단을 대상으로 한 중요도가 산출되어야 한다. 이에 본 연구에서는 비교적 단순하면서도 다양한 평가요소를 통해 공조시스템 리모델링 계획안을 평가할 수 있는 CWM을 중심으로 사무소, 호텔 건축물의 공조시스템 리모델링 시 계획안을 평가하기 위한 평가기준의 중요도 및 평가척도를 산출하고 이를 검정해 봄으로써 의사결정 분석기법의 기초자료로 제공하고자 한다.

The most important purpose on remodeling is decision-making process which establishes a plan that correspond with objects and how draws a optimal alternative. Especially, alternatives of air-conditioning systems are evaluated with various factors to select an alternative using multi criteria decision analysis methodology such as criteria weighting method and analytic hierarchy process because air-conditioning system has a characteristic to satisfy agreeability, economic efficiency, convenience and construction after weights based on data invested from experts are calculated. This paper tries to product weights of criteria and scales based on the questionnaire data of professionals and implement consistency test and model suitability to suggest a basic data for alternative evaluation of air-conditioning system remodeling focused on criteria weighting method that research data is insufficient relatively than analytic hierarchy process in office and hotel building. Producted weights and scales were suitable as consistency ratios of each alternatives were involved within 0.1 and p-valves of scales for analysis matrix were more than 0.05.

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

한국 정부는 공공부문에 클라우드를 도입하기 위한 다양한 정책들을 시행하고 있다. 이 연구의 목적은 공공무문의 클라우드 도입을 위한 의사결정 모델을 개발하고 공공부문의 클라우드 도입 로드맵을 제안하는 것이다. 이를 위하여 공공 서비스의 특성과 공공부문의 클라우드 서비스의 유형을 분석하였다. 이를 통해 공공부문의 클라우드 도입을 위한 요구사항 을 파악하여, 퍼지 AHP기반의 융합의사결정 모델을 이용한 공공부문의 클라우드 도입방법을 개발하였다. 연구결과 클라 우드 도입 후보군의 우선순위를 결정하였고, 이를 기반으로 단계별 클라우드 도입 로드맵을 제안하였다. 이 연구의 결과는 공공부문의 클라우드 도입과 전환 및 클라우드 정책 수립에 도움이 될 것으로 기대한다. 향후에는 클라우드 도입을 위한 추가적인 의사결정요인뿐만 아니라 예산계획을 개발하는 것이 필요하다.

The Korean government has implemented various policies to introduce the cloud to the public sector. The objectives of the paper are to develop a decision-making model and to propose the roadmap for cloud introduction in the public sector. To achieve these objectives, we analyze the characteristics of public services and types of cloud service. Then we develope a cloud introduction method using fuzzy AHP based convergence decision-making model. As a result of this study, we decided to prioritize the cloud service candidates and proposed a three-step roadmap. The results are expected to contribute to cloud introduction and transition in the public sector and establishment of the cloud policy. In the future, it will be necessary to develop budget plans as well as additional decision-making factors for cloud adoption.

This study suggests new approach to identify core technologies through patent analysis. Specially, the approach applied data mining technique and multi-criteria decision making method to the co-classification information of registered patents. First, technological interrelationship matrices of intensity, relatedness, and cross-impact perspectives are constructed with support, lift and confidence values calculated by conducting an association rule mining on the co-classification information of patent data. Second, the analytic network process is applied to the constructed technological interrelationship matrices in order to produce the importance values of technologies from each perspective. Finally, data envelopment analysis is employed to the derived importance values in order to identify priorities of technologies, putting three perspectives together. It is expected that suggested approach could help technology planners to formulate strategy and policy for technological innovation.

The green products in manufacture industry still differ from each other in terms of economics, technology, environmental friendliness, though they all reach the criteria of limitation. This paper expounds the necessity for product choice optimization and provides a model based on information entropy to judge different advantages of product groups. According to Entropy Weight Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the basic theory of green product evaluation model is established. The index system includes selected evaluation indicators of green products, considering about the evaluation index of the critical values to construct a hierarchy criterion, which uses entropy to objectively determine the weight vector of each evaluation index. Then, combined with TOPSIS analysis approach and calculates the pros and cons of green products. It is concluded that the evaluation results based on the Entropy-TOPSIS evaluation model are consistent with the actual results, and the results are consistent with the evaluation results of fuzzy mathematics. The method comprehensively considered many influential factors of the green products, to avoid the limitation of single criterion, and the importance of various factors are analyzed and compared, the prediction result is more scientific, as the theoretical basis of green products, and provide a reliable guidance method for product improvement. This is objective to empower the law, which also fully embodies the idea of variable weights and overcome the past green products that exist in the evaluation process homogeneity empowering. That means fixed weights lead to the limitation of a lack of flexible evaluation.

Group decision-making is a situation faced when individuals collectively make a choice from the alternatives before them. Aiming to the drawback that not all plans can be evaluated by a single expert during group decision-making process, a group decision-making method for dynamic cloud distribution is proposed in this paper based on cumulative prospect theory. First, experts and plans were divided into groups according to the classification rule, and plans were described with the cloud model. The expectation, the entropy and the super entropy decision matrix were structured respectively. Then, the maximum and minimum values in decision matrix were set as positive and negative reference points. The parameter values of cumulative cloud prospect were calculated and the synthesis prospect values of every group were obtained. Finally, the plans were sorted based on the mean of synthesis prospect values for every group, and illustrated by specific examples. The ranking results show that the proposed method is rationality and practicability. So the proposed method can be widely used in group decision-making of grouping scheme or grouping expert.