• Genomics & Informatics
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• 제5권3호
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• pp.95-101
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• 2007

In this paper, we consider the variable selection methods in the Cox model when a large number of gene expression levels are involved with survival time. Deciding which genes are associated with survival time has been a challenging problem because of the large number of genes and relatively small sample size (n<

• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.651-662
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• 2017

We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

• Journal of Advanced Marine Engineering and Technology
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• 제40권2호
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• pp.138-145
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• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• Journal of Positioning, Navigation, and Timing
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• 제12권1호
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• pp.11-22
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• 2023

In this paper, we propose an efficient satellite selection method for multi-constellation GNSS. The number of visible satellites has increased dramatically recently due to multi-constellation GNSS. By the increased availability, the overall GNSS performance can be improved. Whereas, due to the increase of the number of visible satellites, the computational burden in implementing advanced processing such as integer ambiguity resolution and fault detection can be increased considerably. As widely known, the optimal satellite selection method requires very large computational burden and its real-time implementation is practically impossible. To reduce computational burden, several sub-optimal but efficient satellite selection methods have been proposed recently. However, these methods are prone to the local optimum problem and do not fully utilize the information redundancy between different constellation systems. To solve this problem, the proposed method utilizes the inter-system biases and geometric assignments. As a result, the proposed method can be implemented in real-time, avoids the local optimum problem, and does not exclude any single-satellite constellation. The performance of the proposed method is compared with the optimal method and two popular sub-optimal methods by a simulation and an experiment.

• Journal of Power Electronics
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• 제17권5호
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• pp.1203-1210
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• 2017

This paper presents an improved switching selection method for the direct torque control (DTC) of five-phase induction motors (IMs). The proposed method is conducted using optimal switching selection. A five-phase inverter has 32 voltage vectors which are divided into 30 nonzero voltage vectors and two zero voltage vectors. The magnitudes of the voltage vectors consist of large, medium, and small voltage vectors. In addition, these vectors are related to the torque response and torque ripple. When a large voltage vector is selected in a drive system, the torque response time decreases with an increased torque ripple. On the other hand, when a small voltage vector is selected, the torque response time and torque ripple increase. As a result, this paper proposes an optimal voltage vector selection method for improved DTC of a five-phase induction machine depending on the situation. Simulation and experimental results verify the effectiveness of the proposed control algorithm.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 한국지능정보시스템학회
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• pp.351-356
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• 2007

Factory location selection is very important to the success of operation of the whole supply chain, but few effective solutions exist to deliver a good result, motivated by this, this paper tries to introduce a new factory location selection methodology by employing the artificial neural networks technology. First, we reviewed previous research related to factory location selection problems, and then developed a (neural network-based factory selection model) NNFSM which adopted back-propagation neural network theory, next, we developed computer program using C++ to demonstrate our proposed model. then we did case study by choosing a Korean steelmaking company P to show how our proposed model works,. Finnaly, we concluded by highlighting the key contributions of this paper and pointing out the limitations and future research directions of this paper. Compared to other traditional factory location selection methods, our proposed model is time-saving; more efficient.and can produce a much better result.

• Industrial Engineering and Management Systems
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• 제3권2호
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• pp.116-122
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• 2004

This paper presents a process plan selection model with multiple objectives. The process plans for all parts should be selected under multiple objective environment as follows: (1) minimizing the sum of machine processing and material handling time of all the parts considering realistic shop factors such as production volume, processing time, machine capacity, and capacity of transfer device. (2) balancing the load between machines. A multiple objective mathematical model is proposed and an evolutionary algorithm with the adaptive recombination strategy is developed to solve the model. To illustrate the efficiency of proposed approach, numerical examples are presented. The proposed approach is found to be effective in offering a set of satisfactory Pareto solutions within a satisfactory CPU time in a multiple objective environment.

• 충청수학회지
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• 제34권2호
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• pp.169-180
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• 2021

This paper investigates the time-inconsistent agent's optimal consumption and investment problem under inflation risk. The agents' discount factor is governed by hyperbolic discounting, which has a random time to change. We impose the inflation risk which plays a crucial role in long-term financial planning. We derive the semi-analytic solution to the problem of sophisticated agents when the time horizon is finite.

• 대한조선학회 특별논문집
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• 대한조선학회 2017년도 특별논문집
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• pp.88-92
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• 2017

As the considerable request of the fast and accurate way of the selection of circuit breaker is increased, we introduce the development of software of circuit breaker selection for the marine use. Originally, the selection of circuit breaker has been carried out by manual in the marine project. It is not the easy work to select the proper type of circuit breaker to check the time-current characteristic curves of each type of circuit breakers for the various type of loads. In this regards, we developed the software to select the proper type of circuit breaker to confirm fast and accurately. And, we introduce the course of the development of the software for the selection of circuit breaker.

• 지구물리와물리탐사
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• 제14권3호
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• pp.214-219
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• 2011

본 논문에서는 시간영역에서 분리된 잔여 파동장을 이용하여 주파수영역 파형역산을 수행하였다. 시간영역 잔여 파동장들을 절대값의 크기에 따라 정렬하여 분류하고, 이를 여러 개의 그룹으로 분리하였다. 분리된 잔여 파동장들은 각 그룹별로 목적함수의 경사 방향을 정규화한 후 평균하기 때문에 통상적인 잔여 파동장에서 작은 크기를 가지는 파동장들을 상대적으로 강조하는 효과가 있고, 이는 파형역산 시 심부구조의 이미지 향상에 도움을 준다. 파형역산은 시간영역에서 분리된 잔여 파동장을 이용하여 주파수영역에서 수행되며, 목적함수의 경사방향은 구조보정에서 많이 쓰이는 역전파 기법을 적용하여 계산된다. 본 연구에서 제안한 알고리듬의 타당성을 확인하기 위하여 SEG/EAGE 암염 모델과 Marmousi 모델을 이용하여 파형역산을 수행하였다. 역산 결과를 통해 제안된 알고리즘이 일반적인 주파수영역 파형역산에 비해 심부구조에 대하여 향상된 결과를 제시함을 확인하였다.