• Journal of the Korean Data and Information Science Society
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• 제14권4호
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• pp.889-901
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• 2003

In this paper, we consider the optimal replacement policies following the expiration of the combination warranty. The combination warranty can be divided into the renewing combination warranty and the non-renewing combination warranty. The criterion used to determine the optimal replacement period is the overall value function based on the expected cost and the expected downtime. Thus, we obtain the expected cost rate per unit time and the expected downtime per unit time for our model. And then the overall value function suggested by Jiagn and Ji(2002) is applied to obtain the optimal replacement period. The numerical examples are presented for illustrative purpose.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• 정보보호학회논문지
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• 제33권1호
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• pp.99-116
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• 2023

데이터, AI 등 정보기술 기반의 초연결 사회인 4차 산업혁명 시대의 데이터 중요성이 증가하고 있으며 이에 발맞추어 정부도 데이터경제 활성화를 위한 법률 제정 및 개정이 활발히 진행되고 있으나 규제 법률인 개인정보보법과 데이터 활성화 법률(데이터기반행정 활성화에 관한 법률, 데이터 산업진흥 및 이용촉진에 관한 기본법, 산업디지털 전환 촉진법) 간 충돌 가능성, 결합전문기관 유형별 입장차, 데이터전문기관과 결합전문기관의 수행 범위 등 데이터산업 활성화의 발목을 잡거나 잘못된 방향 설정 등의 문제를 예방하고 개선할 필요가 있다. 이에 결합전문기관의 역할 및 현황, 활용 사례를 분석하고 현장의견을 청취하여 데이터경제 활성화를 위한 결합전문기관 역할 확대 방안과 개선방안을 도출하여 소개하고자 합니다.

• Journal of information and communication convergence engineering
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• 제2권3호
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• pp.193-197
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• 2004

In this paper, a combination problem of controllers which are the same type of $H_{\infty}$ controllers designed with different weighting functions. This approach can remove the difficulty in the selection of the weighting functions. As a sub-controller, the Youla type of $H_{\infty}$ controller is used. In the $H_{\infty}$ controller, Youla parameterization is used to minimize $H_{\infty}$ norm of mixed sensitivity function by using polynomial approach. Computer simulation results show the robustness improvement and the performance improvement.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2001년도 춘계학술발표논문집 (상)
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• pp.337-340
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• 2001

A major impediment in using the Dempster-Shafer evidence combination scheme is its computational complexity, which in general is exponential since DS scheme allows any subsets over the frame of discernment as focal elements. To avoid this problem, we propose a method called approximate evidence combination scheme. This scheme is applied to a few sample applications and the experiment results are compared with those of VBS. The results show that the approximation scheme achieves a great amount of computational speedup and produces belief values within the range of deviation that the expert allows.

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.185-193
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• 2002

The purpose of this paper is to suggest a method for detecting the linear regression change-points or variance change-points in regression model by the combination of Schwarz information criteria. The advantage of the suggested method is to detect change-points more detailed when one compares the suggest method with Chen (1998)'s method.

• 대한전자공학회논문지TE
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• 제42권2호
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• pp.15-22
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• 2005

본 논문에서는 이동 로봇 주행의 경로 탐색에 장해가 되는 환경 인식의 불확실성을 감소시키기 위한 센서 결합 방식을 제시하였다. 광학식엔코더, 초음파센서(SRF04)및, 적외선센서(GP2YA02YK)에서 수집된 데이터를 운동제어기(TMS320LF2407A)에서 처리하여 장애물을 감지하고, 안정적인 경로탐색을 계산할 수 있는 이동로봇 제어방식을 실험을 통하여 구현하였다.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.285-295
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• 2024

Driven by the vague assessment big data, a product service system (PSS) evaluation method is developed based on a hybrid model of multi-weight combination and improved TOPSIS by relative entropy. The index values of PSS alternatives are solved by the integration of the stakeholders' vague assessment comments presented in the form of trapezoidal fuzzy numbers. Multi-weight combination method is proposed for index weight solving of PSS evaluation decision-making. An improved TOPSIS by relative entropy (RE) is presented to overcome the shortcomings of traditional TOPSIS and related modified TOPSIS and then PSS alternatives are evaluated. A PSS evaluation case in a printer company is given to test and verify the proposed model. The RE closeness of seven PSS alternatives are 0.3940, 0.5147, 0.7913, 0.3719, 0.2403, 0.4959, and 0.6332 and the one with the highest RE closeness is selected as the best alternative. The results of comparison examples show that the presented model can compensate for the shortcomings of existing traditional methods.

• ETRI Journal
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• 제31권3호
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• pp.263-270
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• 2009

This paper investigates linear soft combination schemes for cooperative spectrum sensing in cognitive radio networks. We propose two weight-setting strategies under different basic optimality criteria to improve the overall sensing performance in the network. The corresponding optimal weights are derived, which are determined by the noise power levels and the received primary user signal energies of multiple cooperative secondary users in the network. However, to obtain the instantaneous measurement of these noise power levels and primary user signal energies with high accuracy is extremely challenging. It can even be infeasible in practical implementations under a low signal-to-noise ratio regime. We therefore propose reference data matrices to scavenge the indispensable information of primary user signal energies and noise power levels for setting the proposed combining weights adaptively by keeping records of the most recent spectrum observations. Analyses and simulation results demonstrate that the proposed linear soft combination schemes outperform the conventional maximal ratio combination and equal gain combination schemes and yield significant performance improvements in spectrum sensing.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1037-1040
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• 2000

We introduce the forecasting method for a next day electric peak load that uses the optimal combination of two types of neural networks. First network uses learning data that are past 10days of the target day. We name the neural network Short Term Neural Network (STNN). Second network uses those of last year. We name the neural network Long Term Neural Network (LTNN). Then we get the forecasting results that are the linear combination of the forecasting results by STNN and the forecasting results by LTNN. We name the method Combination Forecasting Method (CFM). Then we discuss the optimal combination of STNN and LTNN. Using CFM of the optimal combination of STNN and LTNN, we can reduce the forecasting error.