• Title/Summary/Keyword: inherent uncertainty

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Determination Process of Drift Capacity for Seismic Performance Evaluation of Steel Tall Buildings (초고층 철골 건축물의 내진성능평가를 위한 Drift Capacity 산정 프로세스)

  • Min, Ji Youn;Oh, Myoung Ho;Kim, Myeong Han;Kim, Sang Dae
    • Journal of Korean Society of Steel Construction
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    • v.18 no.4
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    • pp.481-490
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    • 2006
  • The actual performance of a building during an earthquake depends on many factors. The prediction of the seismic performance of a new or existing structure is complex, due not only to the large number of factors that need to be considered and the complexity of the seismic response, but also due to the large inherent uncertainties and randomness associated with making these predictions. A central issue of this research is the proper treatment and incorporation of these uncertainties and randomness in the evaluation of structural capacity and response has been adopted in the seismic performance evaluation of steel tall buildings to account for the uncertainties and randomness in seismic demand and capacities in a consistent manner. The basic framework for reliability-based seismic performance evaluation and the key factors for statistical studies were summarized. A total of 36 target structures that represent typical tall steel buildings based on national building code (KBC-2005) were designed for the statistical studies of demand factor s and capacity factors. The incremental dynamic analysis (IDA) approach was examined through the simple steel moment frame building in determination of global drift capacity.

Optimum Design of a Simple Slope considering Multi Failure Mode (다중 파괴모드를 고려한 단순 사면의 최적 설계)

  • Kim, Hyun-Ki;Shin, Min-Ho;Choi, Chan-Yong
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.6
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    • pp.73-80
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    • 2010
  • Conventional slope stability analysis is focused on calculating minimum factor of safety or maximum probability of failure. To minimize inherent uncertainty of soil properties and analytical model and to reflect various analytical models and its failure shape in slope stability analysis, slope stability analysis method considering simultaneous failure probability for multi failure mode was proposed. Linear programming recently introduced in system reliability analysis was used for calculation of simultaneous failure probability. System reliability analysis for various analytical models could be executed by this method. Optimum design to determine angle of a simple slope is executed for multi failure mode using linear programming. Because of complex consideration for various failure shapes and modes, it is possible to secure advanced safety by using simultaneous failure probability.

Research on Location Selection Method Development for Storing Service Parts using Data Analytics (데이터 분석 기법을 활용한 서비스 부품의 저장 위치 선정 방안 수립 연구)

  • Son, Jin-Ho;Shin, KwangSup
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.33-46
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    • 2017
  • Service part has the attribute causing a difficulty of the systematic management like a kind of diversity, uncertainty of demand, high request for quick response against general complete product. Especially, order picking is recognized as the most important work in the warehouse of the parts since inbound cycle of the service part long but outbound cycle is relatively short. But, increasing work efficiency in the warehouse has a limitation that cycle, frequency and quantity for the outbound request depend on the inherent features of the part. Through this research, not only are the types of the parts classified with the various and specified data but also the method is presented that it minimizes (that) the whole distances of the order picking and store location about both inbound and outbound by developing the model of the demand prediction. Based on this study, I expect that all of the work efficiency and the space utilization will be improved without a change of the inbound and outbound quantity in the warehouse.

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A New Robust Continuos VSCS by Saturation Function for Uncertain Nonlinear Plants (불확실 비선형 플랜트를 위한 포화 함수에 의한 새로운 강인한 연속 가변구조제어시스템)

  • Lee, Jung-Hoon
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.3
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    • pp.30-39
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    • 2011
  • In this note, a systematic design of a new robust nonlinear continuous variable structure control system(VSCS) based on the modified state dependent nonlinear form is presented for the control of uncertain affine nonlinear systems with mismatched uncertainties and matched disturbance. After an affine uncertain nonlinear system is represented in the form of state dependent nonlinear system, a systematic design of a new robust nonlinear VSCS is presented. The uncertainty of the nonlinear system function is separated into the tow parts, i.e., state dependent term and state independent term for extension of target plants. To be linear in the closed loop resultant dynamics and in order to easily satisfy the existence condition of the sliding mode, the transformed linear sliding surface is applied. A corresponding control input is proposed to satisfy the closed loop exponential stability and the existence condition of the sliding mode on the linear transformed sliding surface, which will be investigated in Theorem 1. For practical application, the discontinuity of the control input as the inherent property of the VSS is improved dramatically. Through a design example and simulation studies, the usefulness of the proposed controller is verified.

Anomaly Intrusion Detection using Fuzzy Membership Function and Neural Networks (퍼지 멤버쉽 함수와 신경망을 이용한 이상 침입 탐지)

  • Cha, Byung-Rae
    • The KIPS Transactions:PartC
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    • v.11C no.5
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    • pp.595-604
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    • 2004
  • By the help of expansion of computer network and rapid growth of Internet, the information infrastructure is now able to provide a wide range of services. Especially open architecture - the inherent nature of Internet - has not only got in the way of offering QoS service, managing networks, but also made the users vulnerable to both the threat of backing and the issue of information leak. Thus, people recognized the importance of both taking active, prompt and real-time action against intrusion threat, and at the same time, analyzing the similar patterns of in-trusion already known. There are now many researches underway on Intrusion Detection System(IDS). The paper carries research on the in-trusion detection system which hired supervised learning algorithm and Fuzzy membership function especially with Neuro-Fuzzy model in order to improve its performance. It modifies tansigmoid transfer function of Neural Networks into fuzzy membership function, so that it can reduce the uncertainty of anomaly intrusion detection. Finally, the fuzzy logic suggested here has been applied to a network-based anomaly intrusion detection system, tested against intrusion data offered by DARPA 2000 Intrusion Data Sets, and proven that it overcomes the shortcomings that Anomaly Intrusion Detection usually has.

Application of Stepped Isothermal Methods to Lifetime Prediction of Geogrids (SIM을 적용한 성토보강용 지오그리드의 수명예측)

  • Koo, Hyun-Jin;Kim, You-Kyum;Kim, Dong-Whan
    • Journal of the Korean Geosynthetics Society
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    • v.4 no.1
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    • pp.3-6
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    • 2005
  • The failure of geogrids can be defined as an excessive creep strain which causes the collapse of slopes and embankments. In this study, the lifetime of knitted polyester geogrids was predicted by using SIM(Stepped Isothermal Methods using TTS principal) and statistical data analysis techniques. The results indicate that the creep strain was 8.74, 8.79, 8.80% with 2.16~2.20% of CV% at 75, 100, 114 years, respectively and the creep strain reaches 9.3% after 100 years of usage at $27^{\circ}C$ which meets the required lifetime(creep strain less than 10% after 100 years of usage) in the fields. The SIM method is shown to be effective in reduction of uncertainty associated with inherent variability of multi-specimen tests and shorter test times than conventional TTS(Time-Temperature Superposition).

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DIAMETRAL CREEP PREDICTION OF THE PRESSURE TUBES IN CANDU REACTORS USING A BUNDLE POSITION-WISE LINEAR MODEL

  • Lee, Sung-Han;Kim, Dong-Su;Lee, Sim-Won;No, Young-Gyu;Na, Man-Gyun;Lee, Jae-Yong;Kim, Dong-Hoon;Jang, Chang-Heui
    • Nuclear Engineering and Technology
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    • v.43 no.3
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    • pp.301-308
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    • 2011
  • The diametral creep of pressure tubes (PTs) in CANDU (CANada Deuterium Uranium) reactors is one of the principal aging mechanisms governing the heat transfer and hydraulic degradation of the heat transport system (HTS). PT diametral creep leads to diametral expansion, which affects the thermal hydraulic characteristics of the coolant channels and the critical heat flux (CHF). The CHF is a major parameter determining the critical channel power (CCP), which is used in the trip setpoint calculations of regional overpower protection (ROP) systems. Therefore, it is essential to predict PT diametral creep in CANDU reactors. PT diametral creep is caused mainly by fast neutron irradiation, temperature and applied stress. The objective of this study was to develop a bundle position-wise linear model (BPLM) to predict PT diametral creep employing previously measured PT diameters and HTS operating conditions. The linear model was optimized using a genetic algorithm and was devised based on a bundle position because it is expected that each bundle position in a PT channel has inherent characteristics. The proposed BPLM for predicting PT diametral creep was confirmed using the operating data of the Wolsung nuclear power plant in Korea. The linear model was able to predict PT diametral creep accurately.

Forecasting Innovation Performance via Deep Learning Algorithm : A Case of Korean Manufacturing Industry (빅데이터 분석방법을 활용한 제조업 혁신성과예측 방법에 대한 연구 : 딥 러닝 알고리즘을 중심으로)

  • Hwang, Jeong-jae;Kim, Jae Young;Park, Jaemin
    • Journal of Korea Technology Innovation Society
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    • v.21 no.2
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    • pp.818-837
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    • 2018
  • Technological innovation has inherent difficulties, largely due to the uncertainties of technology. Thus, the forecasting methodology to reduce the risk of uncertainty in the innovation process has been presented both in quantitative and qualitative fields. On the other hand, big data and artificial intelligence have attracted great interest recently, and deep learning, which is one of the algorithms of AlphaGo, is showing excellent performance. In this study, deep learning methodology was applied to the prediction of innovation performance. To make the prediction model, we used KIS 2016 data. The input factors were importance of information source and innovation objectives and the output factor was innovation performance index, which was calculated for this study. As a result of the analysis, it can be confirmed that the accuracy of prediction is improved compared with the previous studies. As learning progressed, the degree of freedom of prediction also improved.

Representative Keyword Extraction from Few Documents through Fuzzy Inference (퍼지추론을 이용한 소수 문서의 대표 키워드 추출)

  • 노순억;김병만;허남철
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.9
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    • pp.837-843
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    • 2001
  • In this work, we propose a new method of extracting and weighting representative keywords(RKs) from a few documents that might interest a user. In order to extract RKs, we first extract candidate terms and them choose a number of terms called initial representative keywords (IRKs) from them through fuzzy inference. Then, by expanding and reweighting IRKs using term co-occurrence similarity, the final RKs are obtained. Performance of our approach is heavily influenced by effectiveness of selection method of IRKs so that we choose fuzzy inference because it is more effective in handling the uncertainty inherent in selecting representative keywords of documents. The problem addressed in this paper can be viewed as the one of calculating center of document vectors. So, to show the usefulness of our approach, we compare with two famous methods - Rocchio and Widrow-Hoff - on a number of documents collections. The result show that our approach outperforms the other approaches.

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A Study on the Importance of Risk Factors for Effective Risk Management in the Pre-Project Planning Phase of the Development Projects (국내개발사업 사전기획단계에서의 효율적 리스크 관리를 위한 리스크 인자 중요도에 관한 연구)

  • Shin Kyu-Ho;Kim Jae-Jun
    • Korean Journal of Construction Engineering and Management
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    • v.3 no.2 s.10
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    • pp.75-86
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    • 2002
  • The construction market is diversely changing because social environmental factors are rapidly transforming. Therefore, Construction projects are becoming complex and diverse. Furthermore, the risk being inherent in construction projects are increasing, and now people are considering about the risk management of construction projects in successfully handling the risk factor. The purpose of this study is first to comprehend the preparation of basic references for objective and systematic identification, categorization, and analysis of risk. Secondly it is to find the principle elements within the risk factors identified and categorized around planning process. Finally it is to manage objectively on the planning process, which forms a lot of uncertainty, in order to accentuate the importance about the risk of pre-planning process stage