• Journal of Information Processing Systems
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• 제8권4호
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• Smart Structures and Systems
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• 제23권3호
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• 한국초등과학교육학회지:초등과학교육
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• 제38권1호
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• pp.73-86
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• 2019

The purpose of this study is to investigate the characteristics of problem solving strategies that gifted students use in science inquiry problem. The subjects of the study are the notes and presentation materials that the 15 team of elementary and junior high school students have solved the problem. They are a team consisting of 27 elementary gifted and 29 middle gifted children who voluntarily selected topics related to dimple among the various inquiry themes. The analysis data are the observations of the subjects' inquiry process, the notes recorded in the inquiry process, and the results of the presentations. In this process, the knowledge related to dimple is classified into the declarative knowledge level and the process knowledge level, and the strategies used by the gifted students are divided into general strategy and supplementary strategy. The results of this study are as follows. First, as a result of categorizing gifted students into knowledge level, six types of AA, AB, BA, BB, BC, and CB were found among the 9 types of knowledge level. Therefore, gifted students did not have a high declarative knowledge level (AC type) or very low level of procedural knowledge level (CA type). Second, the general strategy that gifted students used to solve the dimple problem was using deductive reasoning, inductive reasoning, finding the rule, solving the problem in reverse, building similar problems, and guessing & reviewing strategies. The supplementary strategies used to solve the dimple problem was finding clues, recording important information, using tables and graphs, making tools, using pictures, and thinking experiment strategies. Third, the higher the knowledge level of gifted students, the more common type of strategies they use. In the case of supplementary strategy, it was not related to each type according to knowledge level. Knowledge-based learning related to problem situations can be helpful in understanding, interpreting, and representing problems. In a new problem situation, more problem solving strategies can be used to solve problems in various ways.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.2945-2965
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• 2023

The laser inertial measurement unit is a precision device widely used in rocket navigation system and other equipment, and its quality is directly related to navigation accuracy. In the quality evaluation of laser inertial measurement unit, there is inevitably uncertainty in the index input information. First, the input numerical information is in interval form. Second, the index input grade and the quality evaluation result grade are given according to different national standards. So, it is a key step to transform the interval information input by the index into the data form consistent with the evaluation result grade. In the case of uncertain input, this paper puts forward a method based on probability distribution to solve the problem of asymmetry between the reference grade given by the index and the evaluation result grade when evaluating the quality of laser inertial measurement unit. By mapping the numerical relationship between the designated reference level and the evaluation reference level of the index information under different distributions, the index evidence symmetrical with the evaluation reference level is given. After the uncertain input information is transformed into evidence of interval degree distribution by this method, the information fusion of interval degree distribution evidence is carried out by interval evidential reasoning algorithm, and the evaluation result is obtained by projection covariance matrix adaptive evolution strategy optimization. Taking a five-meter redundant laser inertial measurement unit as an example, the applicability and effectiveness of this method are verified.

• 한국건설관리학회논문집
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• 제16권4호
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• pp.50-59
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• 2015

한국 건설 기업들의 해외 진출이 기하급수적으로 늘어나고 있지만 프로젝트를 수행함에 있어 사업의 수익률은 대기업과 경험이 부족한 중소기업을 비교하였을 때 큰 차이가 나타난다(대기업 5건 중 1건 적자, 중소기업 3건 중 1건 적자 공사). 또한 경험이 부족한 중소, 중견 기업들, 특히 하도급 업체에게는 프로젝트 참여시 사업의 적절성을 판단하기란 어려우며 그에 따른 수익률 또한 예측하기 어렵다. 이에 본 연구는 중소/중견 업체, 특히 하도급 업체 관점에서 해외 건설공사 진출 시 수익률에 영향을 미치는 영향인자를 도출하기 위해 1965년부터 시행된 8,637건의 해외건설 준공데이터 및 문헌고찰 기반으로 수익률에 영향을 미치는 10개 인자를 도출 후 다중회귀분석을 통해 영향인자 간 가중치를 도출하였다. 이를 기반으로 사례기반 추론 기법을 이용하여 수익률 예측 모델을 개발하였으며, Type1 &Type2 error 분석을 통해 검증 결과 11%의 오차율을 보였다. 이러한 수익성 예측 모델을 활용하여 국내 건설 하도급업체들은 해외건설공사 진출 시 해당 프로젝트의 수익성 분포를 사전에 확인하여 양질의 프로젝트를 선별하고, 사업 참여의 의사결정에 중요한 참고자료가 될 것을 기대한다.

• ETRI Journal
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• 제39권4호
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• pp.592-604
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• 2017

Intrusion detection is very important for network situation awareness. While a few methods have been proposed to detect network intrusion, they cannot directly and effectively utilize semi-quantitative information consisting of expert knowledge and quantitative data. Hence, this paper proposes a new detection model based on a directed acyclic graph (DAG) and a belief rule base (BRB). In the proposed model, called DAG-BRB, the DAG is employed to construct a multi-layered BRB model that can avoid explosion of combinations of rule number because of a large number of types of intrusion. To obtain the optimal parameters of the DAG-BRB model, an improved constraint covariance matrix adaption evolution strategy (CMA-ES) is developed that can effectively solve the constraint problem in the BRB. A case study was used to test the efficiency of the proposed DAG-BRB. The results showed that compared with other detection models, the DAG-BRB model has a higher detection rate and can be used in real networks.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
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• pp.235-241
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• 2000

This article suggests integrated neural network models for the interest rate forecasting using change point detection. The basic concept of proposed model is to obtain intervals divided by change point, to identify them as change-point groups, and to involve them in interest rate forecasting. the proposed models consist of three stages. The first stage is to detect successive change points in interest rate dataset. The second stage is to forecast change-point group with data mining classifiers. The final stage is to forecast the desired output with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. This article is then to examine the predictability of integrated neural network models for interest rate forecasting using change-point detection.

• 한국정보통신학회논문지
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• 제11권4호
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• pp.678-686
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• 2007

유비쿼터스 서비스는 사용자 및 주변의 상황(context) 정보를 능동적으로 인식하여 사용자에게 제공되는 차별화된 고품질의 서비스로서, 이를 구현하기 위한 핵심 기술 중의 하나가 상황인지 미들웨어 기술이다. 본 논문에서는 일정 한 사용자 공간에서 유비쿼터스 서비스를 효과적으로 제공할 수 있는 방법에 대하여 제안한다. 즉, 다양한 센서로부터 상황 정보를 입력받아 현재의 상황에 적절한 서비스를 추론하여 결정하고 이를 사용자에게 제공하는 상황인식기반 지능형 홈서비스 미들웨어를 설계하고 구현한다.

• 한국시뮬레이션학회논문지
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• 제17권2호
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• pp.49-61
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• 2008

대부분의 함정 전투체계의 교전 시뮬레이션은 필수적으로 운용자(통제관 및 대항군)가 포함될 수밖에 없음으로 인해 시뮬레이션은 실시간 정도의 저속이며, 시뮬레이션 결과도 객관적인 평가가 어렵다. 이러한 문제를 다루기 위해 본 논문에서는 인간 대신 다중 에이전트 시스템을 이용하는 에이전트 기반의 함정전투 M&S 시스템을 제안한다. 에이전트기반 M&S 시스템은 인간의 개입을 배제하고 자율적 추론기능을 제공함으로써 전투체계의 효과도 분석 및 운용전술개발 등께 대한 효과적인 지원을 가능하게 해준다. 본 논문에서는 이를 위하여 첨단 M&S 프레임워크와 자율 에이전트 설계 원칙을 도입함으로써 인간 미개입형 M&S 시스템 설계 개념과 방법론을 제시하였고, 서해교전상의 함정전투 사례연구를 통해 그 타당성을 검증하였다.

• 한국과학교육학회지
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• 제19권2호
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• pp.256-265
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• 1999

본 연구의 목적은 실험 평가를 이용하여 탐구과정 기능을 측정하고, 인지 수준과 탐구과정 기능의 성취도와의 관계를 알아보는 것이다. 연구 대상은 인지 수준과 지역을 유층으로 하여 중학교 2학년 162명을 표집하였다. 실험 평가는 SISS에서 사용한 실험 과정기능검사 문항을 수정 보완한 산 염기, 밀도, 염화코발트의 성질에 관한 3가지 과제를 이용하여 순환 실험 형식으로 수행하였다. 탐구과정 기능은 D(계획), P(수행), R(추론) 등의 하위 기능을 포함한다. 실험 평가의 채점은 학생용 보고서를 이용하였으며, 5명의 평가자가 채점한 결과의 평균값으로 분석을 하였다. 연구의 결과 인지 수준이 발달함에 따라 탐구과정 기능의 전체 점수와 하위 기능인 D(계획), P(수행), R(추론)의 성취도가 모두 통계적으로 유의미하게 높아지는 것으로 나타났다. 그리고 인지 수준을 통제하고 탐구과정 기능의 성취도를 비교한 결과 지역간에 탐구과정 기능의 성취도 차이와 남녀간에 탐구과정 기능의 성취도 차이는 나타나지 않았다. 이러한 결과를 통해, 실험 평가를 통한 탐구과정 기능의 성취도는 인지 수준에 크게 영향을 받으므로 탐구과정 기능을 향상시키기 위해서는 학습자의 인지 수준을 고려하는 것이 매우 중요한 일임을 알 수 있다.