• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.145-145
• /
• 2000

In this paper, we propose a hybrid d-step predictor which is composed of an adaptive predictor and a Kalman predictor. We prove the performance limit of the proposed predictor. Simulation is conducted to examine the performance of the proposed predictor. Simulation results show that the proposed combined predictor is superior to the adaptive predictor and the Kalman predictor. Proposed predictor is used for prediction of gun tip vibration of k1 tank. The result is compared with that of conventional adaptive predictor.

• 대한가정학회지
• /
• 제36권2호
• /
• pp.47-60
• /
• 1998

The effects of personal(gender, physical growth) and environmental(communication with parent, intimacy of friendship, school performance, and satisfaction of school-life) factors on adolescent's self-esteem were examined in a samlpe of 525 first and second grades in middle school. The subdomains of the self-esteem were peer-related self, home self, teacher-related self, academic self, physical appearance self, physical competence self, personality self, and general self. T-test, Pearson's correlation, and regression were used as statistical analysis. Results were as follows. First, there was evidence of a gender difference in the level of the subsdomains of self-esteem: teacher-related, physical-appearance, physical-competence, and personality. Second, the factor which was the most powerful predictor of each subdomain of the self-esteem was as follows 1) the most powerful predictor of the peer-related self was the intimacy of friendship, 2) the most powerful predictor of the home self was the communication with parent, 3) the most powerful predictor of the teacher-related self was the satisfaction of school-life, 4) the most powerful predictor of the academic self was the school performance, 5)the most powerful predictor of the physical-appearance self, the physical competence self, and the personality self was the satisfaction of school-life, 6) the most powerful predictor of the general self was the school performance.

• 전기학회논문지
• /
• 제63권12호
• /
• pp.1704-1709
• /
• 2014

In order to increase the performance of multi-core system processor architectures, the multi-thread branch predictor which speculatively fetches and allocates threads to each core should be highly accurate. In this paper, the perceptron based multi-thread branch predictor is proposed for the multi-core processor architectures. Using SPEC 2000 benchmarks as input, the trace-driven simulation has been performed for the 2 to 16-core architectures employing perceptron multi-thread branch predictor extensively. Its performance is compared with the architecture which utilizes the two-level adaptive multi-thread branch predictor.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제52권11호
• /
• pp.619-625
• /
• 2003

We proposed an optimum PID controller design method of the Smith Predictor It can be applied to various processes. The real process is approximated via the second order plus time delay model (SOPTD) whose parameters are specified through a model reduction algorithm. We already proposed a new model reduction method that considered four point in the Nyquist curve to reduced the steady state error between the real process model and the reduced model using the gradient decent method and the genetic algorithms. In addition, the Smith predictor is used to compensate time delay of the real process model. In this paper, the new optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
• /
• pp.235-238
• /
• 2003

Conventional stride predictor is useful for predicting data values which vary by a constant value. However, when the data values of shift, multiplication, and division instructions are predicted, the stride predictor can't show the best performance. Thus, we propose predictor using stride and shift to improve predictability. The predictor using stride and shift takes advantage of shift values as well as stride values, so that the overall coverage of prediction increases.

• 산업기술연구
• /
• 제29권B호
• /
• pp.9-15
• /
• 2009

In the case of traditional binary encoding technique, it takes long time to converge the optimal solutions and brings about complexity of the systems due to encoding and decoding procedures. However, the ROGAs (real-coded genetic algorithms) do not require these procedures, and the k-means clustering algorithm can avoid global searching space. Thus, this paper proposes a new approach by using their advantages. The proposed method constructs the multiple predictors using the optimal differences that can reveal the patterns better and properties concealed in non-stationary time series where the k-means clustering algorithm is used for data classification to each predictor, then selects the best predictor. After selecting the best predictor, the cluster centers of the predictor are tuned finely via RCGKA in secondary tuning procedure. Therefore, performance of the predictor can be more enhanced. Finally, we verifies the prediction performance of the proposed system via simulating typical time series examples.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
• /
• pp.117-121
• /
• 1990

The control process involving pure time delays presents a continuing challenge to the control system engineer. The nonlinear nature of the delay which can be introduced into the system make the use of conventional control algorithms a poor prospect. The Smith Predictor was developed to alleviate this problem. Unfortunately the quality of control achieved with the Smith Predictor is known to be sensitive to modelling errors. Only recently have researchers attempted to quantify the Smith Predictor controller's robustness to modelling errors. In several studies stability boundaries were plotted as functions of errors in parameters. But the research results address the question of performance of Smith Predictor controllers, In this paper, the Rule based Expert Systems for performance improvement of the Smith Predictor controller are developed.

• Genomics & Informatics
• /
• 제19권1호
• /
• pp.10.1-10.7
• /
• 2021

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC₅₀ and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC₅₀ and 0.81 for AUC. We identify common predictor genes for IC₅₀ and AUC, with which the performance was similar to those with genes separately found for IC₅₀ and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC₅₀, 0.7945 for AUC) with 321 predictor genes.

• 전기학회논문지
• /
• 제57권8호
• /
• pp.1447-1453
• /
• 2008

In this paper, we proposed to improve performance of the design of a cascade controller with the smith-predictor structure. The parameters of controller in the inner loop are determined to minimize the integral of time multiplied by the absolute value of error (ITAE) value of performance Index. The controller of outer loop and parameters of Smith-Predictor can be obtain using reduction model. The model reduction is considered that it is the transient response and the steady-state response through the use of nyquist curve. Simulation examples are given to show the better performance of the proposed method than conventional methods.

• 정보처리학회논문지A
• /
• 제19A권2호
• /
• pp.77-84
• /
• 2012

프로세서의 성능을 효율적으로 증가시키기 위한 기법 중 하나로 명령어 수준의 병렬성을 높이는 추론적 수행(Speculative execution)이 사용되고 있다. 추론적 수행 기법의 효율성을 결정하는 가장 중요한 핵심 요소는 분기 예측기의 정확도이다. 하지만, 높은 예측율을 보장하는 복잡한 구조의 분기 예측기를 최근 주목 받고 있는 3차원 구조 멀티코어 프로세서에 적용하는데 있어서는 발열 현상이 큰 장애요소가 될 것으로 예측된다. 본 논문에서는 3차원 구조 멀티코어 프로세서에서 발생할 수 있는 분기 예측기의 높은 발열 문제를 해결하기 위해 두 가지 기법을 제시하고, 이에 대한 효율성을 상세하게 분석하고자 한다. 첫번째 기법은 분기 예측기의 온도가 임계 온도 이상으로 올라가는 경우 분기 예측기의 동작을 일시적으로 정지시키는 동적 온도 관리 기법이고, 두번째 기법은 3차원 구조 멀티코어 프로세서의 각 층 별로 온도를 고려하여 서로 다른 복잡도를 지닌 분기 예측기를 차등 배치하는 기법이다. 두 가지 기법 중에서 복잡도를 고려한 차등 배치 기법은 평균 $87.69^{\circ}C$의 온도를 나타내는 반면, 동적 온도 관리 기법은 평균 $89.64^{\circ}C$의 온도를 나타내었다. 그리고, 각 층에서 발생하는 온도 변화율을 각 기법에 대하여 비교한 결과, 동적 온도 관리 기법의 온도 변화율은 평균 $17.62^{\circ}C$을 나타내었고 복잡도 차등 배치 기법의 온도 변화율은 평균 $11.17^{\circ}C$을 나타내었다. 이러한 온도 분석을 통하여 3차원 멀티코어 프로세서에서 분기 예측기의 온도를 제어하였을 경우, 복잡도 차등 배치 기법을 적용하는 것이 더 효율적임을 알 수 있다. 성능적인 측면을 분석한 결과, 동적 온도 관리 기법은 해당 기법을 적용하지 않았을 경우보다 평균 27.66%의 성능하락을 나타내었지만, 복잡도 차등 배치 기법은 평균 3.61%의 성능 하락만을 나타내었다.