• Geomechanics and Engineering
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• 제36권2호
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.427-436
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• 2000

The prediction of stock price index is a very difficult problem because of the complexity of the stock market data it data. It has been studied by a number of researchers since they strong1y affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain Intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network (BPN). Fina1ly, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.246-259
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• 2021

IMO stability regulations include various stability parameters such as GM values. To assess the stability of the ships, we should check all stability parameters of the IMO requirements. However, since this process is complex, a more convenient way to evaluate stability performance is required. In this research, the index for marine ship intact stability assessment (IMSISA) model was developed to solve these problems. The IMSISA model consists of a stability index calculation module and a stability assessment module. In the stability index calculation module, ten stability parameters, including GM, were used to develop the stability index, which has the advantage of being able to quantify the ship stability. The stability assessment module uses the stability index value to determine the stability status of the ship and provides the captain with stability management guidelines. To verify the proposed model, the basic stability calculations were performed for two model ships in 32 loading situations. The proposed model was found to provide better performance in the stability assessment than the previous study. By applying the IMSISA model to the ships, the captain can assess the ship stability more quantitatively and efficiently.

• 품질경영학회지
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• 제44권2호
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• pp.297-308
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• 2016

Purpose: This paper treats a defense-supply chain quality management model for analyzing the Korea defense industry. Methods: Various literature, the quality collaboration index for supply chain management model proposed by Korean Standards Association and shared growth index presented by Korea Commission for Corporate Partnership are reviewed to develop the defense supply chain quality management index and model based on the method presented by Hafeez et al.(2006). In addition, based on the proposed model, we survey the supply chain quality management efficiency including focused group interviews in the defense industry. Results: We propose a defense-supply chain quality management index and model for analyzing the quality level between the parent companies and its partners. In addition, the results of applying the model are proposed to improve the quality of military items. Conclusion: A model is developed for improving the quality of military items. This proposed model will be adopted to enhance the quality of military items.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.305-312
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• 2015

We extend a generalized partially linear single-index model and newly define a generalized partially double-index model (GPDIM). The philosophy of sufficient dimension reduction is adopted in GPDIM to estimate unknown coefficient vectors in the model. Subsequently, various combinations of popular sufficient dimension reduction methods are constructed with the best combination among many candidates determined through a bootstrapping procedure that measures distances between subspaces. Distinguishing values are newly defined to match the estimates to the corresponding population coefficient vectors. One of the strengths of the proposed model is that it can investigate the appropriateness of GPDIM over a single-index model. Various numerical studies confirm the proposed approach, and real data application are presented for illustration purposes.

• 한국안전학회지
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• 제22권6호
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• pp.63-68
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• 2007

The purpose of this study is to verify the relation between the risk index using AHP(Analytic Hierarchy Process) and the risk index using Computing Model. For doing the objective, this research classified 22 work types in architectural construction work from the analysis Korean architectural standard specification and Korea occupational safety & health agency code. Based on the classified 22 work types in architectural construction work, the risk index of each work type was calculated by AHP and Computing Model. For verifying the correlation of risk index between AHP and Computing Model methods, SAS version 8.0 System, which is one of the statistics programs, was used.

• ETRI Journal
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• 제27권4호
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• pp.377-384
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• 2005

We investigate near-infrared light (NIR) propagation in a model of an adult head using an extensive Monte Carlo (MC) simulation. The adult head model is a four-layered slab which consists of a surface layer, a cerebrospinal fluid layer, a gray-matter layer, and a white-matter layer. We study the effects of a refractive index mismatch on the model, calculating the intensity of detected light, mean flight time, and partial mean flight time of each layer for various refractive indices of the cerebrospinal fluid layer as functions of source-detector spacing. The Monte Carlo simulation shows that the refractive index mismatch presents very rich results including rapidly decaying intensity of detected light and a peak and cross-over in the partial mean flight time with source-detector spacing. We also investigate spatial sensitivity profiles at various source-detector spacings, discussing the index mismatch effect on the model.

• 문화기술의 융합
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• 제10권1호
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• pp.489-493
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• 2024

행복 지수는 집단적인 행복 정도를 직관적으로 파악하는데 효과적인 측정 시스템이다. 가치관의 변화에 따라행복 지수에 행동의 가치를 추가한 연구들이 제안되고 있으나, 개인이 느끼는 감정을 활용하여 관계성을 분석한 연구는 부족한 실정이다. 따라서 본 연구는 행동의 가치를 나타내는 사회적 변수와 개개인의 감정지수를 함께 고려해 행복 지수를 예측하는 딥러닝 모델을 설계한다. 첫째, 2005년 1월 ~ 2020년 12월의 사회적, 감정적 변수를 수집한다. 둘째, 데이터 전처리 및 유의변수 탐색을 수행한다. 셋째, 딥러닝 기반의 회귀 모델로 학습하고, 5-Fold 교차 검증(Cross Validation)으로 학습 모델을 평가한다. 본 연구의 제안 모델은 테스트 데이터에서 90.65%의 높은 예측 정확도를 보인다. 향후 이 연구는 국가별 데이터로 확대 적용하여 행복 지수 주요 요인 분석 등의 연구에 활용될 수 있을 것으로 기대된다.

• 경영과학
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• 제30권3호
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• pp.1-16
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• 2013

In this paper, we deal with an enhanced index fund strategy by implementing the exchange trade funds (ETFs) within the context of the Black-Litterman approach. The KOSPI200 index ETF is used to build risk-controlled portfolio that tracks the benchmark index, while the proposed Black-Litterman model mitigates estimation errors in incorporating both active investment views and equilibrium views. First, we construct a Black-Litterman model portfolio with the active market perspective based on the momentum strategy. Then, we update the portfolio with the KOSPI200 index ETF by using the equilibrium return ratio and weighted averages, while devising optimization modeling for improving the information ratio (IR) of the portfolio. Finally, we demonstrate the empirical viability of the proposed enhanced index strategies with KOSPI 200 data.

• 한국도서관정보학회지
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• 제37권4호
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• pp.247-270
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• 2006

본 연구의 목적은 국가과학기술전자도서관(NDSL)의 고객만족지수를 측정하는데 있다. NDSL 정보시스템에 맞는 이용자만족지수 모형을 제안하고 개발된 모형의 검증을 위해 구조방정식모형 분석도구인 LISREL을 통해 인과적 경로분석을 실시하였다. 또한 차원별로 서로 다른 이용자 만족지수 산출 방법을 수립하고 수립된 산출 방법에 따라 다양한 이용자만족지수를 측정하고 분석하였다.