• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
• /
• pp.133-141
• /
• 2001

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However is we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set. eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case, set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• 전기학회논문지
• /
• 제61권2호
• /
• pp.276-283
• /
• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.

• 한국IT서비스학회:학술대회논문집
• /
• 한국IT서비스학회 2003년도 추계학술대회
• /
• pp.616-623
• /
• 2003

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However if we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set, eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• 한국전산구조공학회논문집
• /
• 제15권4호
• /
• pp.661-674
• /
• 2002

본 연구의 목적은 Navier-Stokes 유체의 최적 제어 문제의 해를 얻을 수 있는 효과적인 수치해석기법을 개발하고, 이를 물체의 항력(drag)을 최소화하는 문제에 적용하는데 있다. 본 연구는 항력을 줄인다는 산업적인 중요성과 함께 최적 제어를 위한 하나의 효과적인 최적화 기법의 모델을 제공하고 있다. 항력을 줄이기 위한 방법으로써 물체의 경계면에서 유체의 흡입(suction)과 방출(injection)이라는 기법을 사용하여 경계면에서 속도를 제어하였고, 목적함수로써 항력을 표현하기 위하여 에너지 소실의 변화율을 사용하였다. 컴퓨터 용량을 최소화하고 최적화에서의 해의 보장성과 경제성을 위하여, Navier-Stokes의 해석을 위하여 페널티 방법을 사용하였고 최적화 기법을 위해서는 SQP 방법을 사용하였다. 그리고 Navier-Stokes 유체는 대단히 비선형성을 나타내기 때문에 최적화를 수행하기에는 매우 힘들다. 이를 위하여 연속기법(continuation technique)을 사용하였다.