• 한국전자거래학회지
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• 제6권2호
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• pp.143-157
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• 2001

There has been a need for predicting development efforts and costs of the system during the early stage of the software process and hundreds of metrics have been proposed for computer software, but not all provide practical support to the software engineer. Some demand measurement that is too complex, others are so esoteric that few real-world professionals have any hope of understanding them, and others violate the basic intuitive notions of what high-quality software really is. It is worthwhile that metrics should be tailored to best accommodate specific products and processes after grasping their good and no good point. This paper describes two size estimation techniques, the Karner technique and the Marchesi technique, and compares and analyzes them with proposed evaluation criteria. Both techniques are to estimate software size analyzed by use case that is mainly described during the object-oriented analysis phase. We also present an empirical comparison of them, both are applied in the Internet Medicine Prescription System. We also propose some guidance for experiments based on our analysis. We believe that it should be facilitating project management more effective by adjusting software metrics properly.

• 한국자동차공학회논문집
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• 제5권1호
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• pp.59-68
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• 1997

The modelling techniques of a center pillar-to-roof rail joint for low frequency vibration analysis are examined and some fundamental problems are addressed. To develop a simplified beam-spring model of the joint, the present work is focused on 1) practical shell modelling techniques and 2) joint spring stiffness estimation methods a practical model-updating method to match the calculated natural frequencies to the experimentally determine ones is proposed, particularly focusing on spot welding modelling. In joint spring modelling, the results from the model with one joint spring are compared with those from the model with three coupled springs. Finally, some fundamental problems in beam-spring modelling are addressed.

• Journal of Ship and Ocean Technology
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• 제9권1호
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• pp.64-71
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• 2005

In probabilistic design, the challenge is to estimate the uncertainty propagation, since outputs of subsystems at lower levels could constitute inputs of other systems or at higher levels of the multilevel systems. Three uncertainty propagation estimation techniques are compared in this paper in terms of numerical efficiency and accuracy: root sum square (linearization), distribution-based moment approximation, and Taguchi-based integration. When applied to reliability-based design optimization (RBDO) under uncertainty, it is investigated which type of applications each method is best suitable for. Two nonlinear analytical examples and one vehicle crashworthiness for side-impact simulation example are employed to investigate the unique features of the presented techniques for uncertainty propagation. This study aims at helping potential users to identify appropriate techniques for their applications in the multilevel design.

• Journal of Hydrospace Technology
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• 제2권2호
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• pp.24-35
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• 1996

This paper describes parameter identification techniques formulated for the estimation of maneuvering coefficients of a submerged body. The first part of this paper is concerned with the identifiability of the system parameters. The relationship between a stochastic linear time-invariant system and the equivalent dynamic system is investigated. The second is concerned with the development of the numerically stable identification technique. Two identification techniques are tested; one is the ma7mum likelihood (ML) methods using the Holder & Mead simplex search method and using the modified Newton-Raphson method, and the other is the modified extended Kalman filter (MEKF) method with a square-root algorithm, which can improve the numerical accuracy of the extended Kalman filter. As a results, it is said that the equations of motion for a submerged body have higher probability to generate simultaneous drift phenomenon compared to general state equations and only the ML method using the Holder & Mead simplex search method and the MEKF method with a square-root algorithm gives acceptable results.

• International Journal of Computer Science & Network Security
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• 제24권6호
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• pp.17-22
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• 2024

Software cost and schedule estimation is usually based on the estimated size of the software. Advanced estimation techniques also make use of the diverse factors viz, nature of the project, staff skills available, time constraints, performance constraints, technology required and so on. Usually, estimation is based on an estimation model prepared with the help of experienced project managers. Estimation of software cost is predominantly a crucial activity as it incurs huge economic and strategic investment. However accurate estimation still remains a challenge as the algorithmic models used for Software Project planning and Estimation doesn't address the true dynamic nature of Software Development. This paper presents an efficient approach using the contemporary Constructive Cost Model (COCOMO) augmented with the desirable feature of fuzzy logic to address the uncertainty and flexibility associated with the cost drivers (Effort Multiplier Factor). The approach has been validated and interpreted by project experts and shows convincing results as compared to simple algorithmic models.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2012년도 춘계학술발표대회 논문집
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

• 대한전자공학회논문지TC
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• 제37권9호
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• pp.1-10
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• 2000

본 논문에서는 페이딩 채널환경에서 COFDM 시스템에 대한 채널 추정과 결합된 심볼 검출 방법에 대해 제안하였다. 제안된 방법은 1) 심볼의 길이에 채널 부호화기의 코드워드 길이를 배합하는 기법과, 2) 세가지 채널 추정 기법과의 조합으로 나타내었다. 첫째 방법은 훈련 신호를 이용한 채널추정 기법과 제안한 심볼 검출 기법을 결합시킨 것이며, 둘째 방법은 첫째 방법에 결정지향 채널추정(Decision-Directed Channel Estimation) 기법을 결합시킨 방법이다. 마지막으로, 근접 부채널간의 AWGN(Additive White Gaussian Noise)의 영향을 줄이기 위해 디인터리브된 평균 채널추정(Averaged Channel Estimation) 기법을 둘째 방법에 결합시켰다. 제안한 3가지 방법들은 영 강압 등화(Zero Forcing Equalizing)방법과 비교하여 커다란 성능 개선 효과가 있음을 컴퓨터 시뮬레이션을 통하여 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1356-1376
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• 2023

Software effort estimation is one of the most difficult tasks in software development whereas predictability is also of equal importance for strategic management. Accurate prediction of the actual cost that will be incurred in software development can be very beneficial for the strategic management. This study discusses the latest trends in software estimation focusing on analogy-based techniques to show how they have improved the accuracy for software effort estimation. It applies the standard deviation technique to the expected value of analogy-based estimates to improve accuracy. In more than 60 percent cases the applied technique of this study helped in improving the accuracy of software estimation by reducing the Magnitude of Relative Error (MRE). The technique is simple and it calculates the expected value of cost or time and then uses different confidence levels which help in making more accurate commitments to the customers.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.47-54
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• 2000

This article is concerned with the algorithm for the Chebyshev estimation with/without linear equality and/or inequality constraints. The algorithm employs a linear scaling transformation scheme to reduce the computational burden which is induced when the data set is quite large. The convergence of the proposed algorithm is proved. And the updating and orthogonal decomposition techniques are considered to improve the computational efficiency and numerical stability.

• 대한환경공학회지
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• 제38권2호
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• pp.87-95
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• 2016

탁도는 송 배수 관로의 부식 등에 의해 발생되는 것으로 알려진 'Discolored Water'현상을 수용가의 물 사용자가 인지할 수 있는 주요 지표로서 활용되고 있다. 즉, 'Discolored Water'는 수돗물 사용자가 육안으로 인지할 수 있는 정도의 탁도를 가진 상태로 정의할 수 있으며, 사용자는 수돗물에 존재하는 불특정의 용존 물질보다는 미세한 입자들에 대한 시각적인 인지인 탁도를 통해서 'Discolored Water'를 인식하게 된다. 이에 본 연구에서는 실제 국내 상수도 시스템 내에서 관측된 다항목의 수질데이터(탁도, pH 및 잔류염소)를 대상으로 하여 탁도 이외의 수질데이터들을 예측모형의 설명변수로 설정한 후 데이터 마이닝 기법(data mining)을 통해 기계학습(machine learning)을 수행하여, 상수도 시스템 내에서의 탁도 변화를 예측하는 모형을 수립하고자 하였다. 수집된 수질 데이터를 대상으로 데이터 마이닝 기법인 Decision Tree를 이용해 탁도 예측모형을 구축한 결과 pH 및 잔류염소를 설명변수로 적용한 모형이 가장 높은 예측결과를 나타내었다. 하지만 예측모형들은 peak 관측치에 대해서는 예측오차가 다소 증가하였는데 이를 보완하기 위해 고주파통과필터를 이용한 전처리 과정을 적용하였다. 그 결과 탁도 데이터의 시계열변화 및 peak 관측치에 대한 예측오차가 감소하는 것으로 나타났다.