• 제목/요약/키워드: stochastic nature

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피로시험 데이터의 산포를 고려한 스프링의 신뢰성 최적설계 (Reliability based optimization of spring fatigue design problems accounting for scatter of fatigue test data)

  • 안다운;원준호;최주호
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.1314-1319
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    • 2008
  • Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

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Ashbery's Aesthetics of Difficulty: Information Theory and Hypertext

  • Ryoo, Gi Taek
    • 영어영문학
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    • 제58권6호
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    • pp.1001-1021
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    • 2012
  • This paper is concerned with John Ashbery's poetics of difficulty, questioning in particular the nature of communication in his difficult poems. Ashbery has an idea of poetry as 'information' to be transmitted to the reader. Meaning, however, is to be created by a series of selections among equally probable choices. Ashbery's poetry has been characterized by resistance to the interpretive system of meaning. But the resistance itself, as I will argue, can be an effective medium of communication as the communicated message is not simply transmitted but 'selected' and thus created by the reader. In Ashbery's poetry, disruptive 'noise' elements can be processed as constructive information. What is normally considered a hindrance or noise can be reversed and added to the information. In Ashbery's poems, random ambiguities or noises can be effectively integrated into the final structure of meaning. Such a stochastic sense of information transfer has been embodied in Ashbery's idea of creating a network of verbal elements in his poetry, analogous to the interconnecting web of hypertext, the most dynamic medium 'information technology' has brought to us. John Ashbery, whose poems are simultaneously incomprehensible and intelligent, employs ambiguities or noise in his poetry, with an attempt to reach through linear language to express nonlinear realities. It is therefore my intention to examine Ashbery's poetics of difficulty, from a perspective of communication transmission, using the theories of information technology and the principles of hypertext theory. Ashbery's poetry raises precisely the problem confronted in the era of communication and information technology. The paper will also show how his aesthetics of difficulty reflects the culture of our uncertain times with overflowing information. With his difficult enigmatic poems, Ashbery was able to move ahead of the technological advances of his time to propose a new way of perceiving the world and life.

Improving SARIMA model for reliable meteorological drought forecasting

  • Jehanzaib, Muhammad;Shah, Sabab Ali;Son, Ho Jun;Kim, Tae-Woong
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.141-141
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    • 2022
  • Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

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Cost Implications of Imperfect Repair in Software Reliability

  • Chuiv, Nora-Ni;Philip J. Boland
    • International Journal of Reliability and Applications
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    • 제2권3호
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    • pp.147-160
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    • 2001
  • The reliability of computer software is of prime importance for all developers of software. The complicated nature of detecting and removing faults from software has led to a plethora of models for reliability growth. One of the most basic of these is the Jelinski Moranda model, where it is assumed that there are N faults in the software, and that in testing, bugs (or faults) are encountered (and removed when defected) according to a stochastic process at a rate which at a given point in time is proportional to the number of bugs remaining in the system. In this research, we consider the possibility that imperfect repair may occur in any attempt to remove a detected bug in the Jelinski Moranda model. We let p represent the probability that a fault which is discovered or detected is actually perfectly repaired. The possibility that the probability p may differ before and after release of the software is also considered. The distribution of both the number of bugs detected and perfectly repaired in a given time period is studied. Cost models for the development and release of software are investigated, and the impact of the parameter p on the optimal release time minimizing expected costs is assessed.

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A Study on the Voltage Stabilization Method of Distribution System Using Battery Energy Storage System and Step Voltage Regulator

  • Kim, Byung-ki;Park, Jae-Beom;Choi, Sung-Sik;Jang, Moon-Seok;Rho, Dae-Seok
    • Journal of Electrical Engineering and Technology
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    • 제12권1호
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    • pp.11-18
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    • 2017
  • In order to maintain customer voltages within the allowable limit($220{\pm}13V$) as much as possible, tap operation strategy of SVR(Step Voltage Regulator) which is located in primary feeder, is widely used for voltage control in the utilities. However, SVR in nature has operation characteristic of the delay time ranging from 30 to 150 sec, and then the compensation of BESS (Battery Energy Storage System) during the delay time is being required because the customer voltages in distribution system may violate the allowable limit during the delay time of SVR. Furthermore, interconnection of PV(Photovoltaic) system could make a difficultly to keep customer voltage within the allowable limit. Therefore, this paper presents an optimal coordination operation algorithm between BESS and SVR based on a conventional LDC (Line Drop Compensation) method which is decided by stochastic approach. Through the modeling of SVR and BESS using the PSCAD/EMTDC, it is confirmed that customer voltages in distribution system can be maintained within the allowable limit.

시장여건의 변화가 시장통합의 검정에 미치는 영향 (Impact of the Change in Market Conditions on a Test for Market Cointegration)

  • 김태호
    • 응용통계연구
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    • 제24권1호
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    • pp.103-114
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    • 2011
  • 시장 간 통합을 검정한 연구들은 시장변수들 자체의 연관성으로만 분석을 한정시키는 경향이 있어 경우에 따라 시장 변동체계의 전반적 현실을 파악하는데 한계가 있다. 주식시장의 경우 위기를 겪은 나라와 그렇지 않은 나라와는 일정 기간 주가변동 성향이 다르므로 이들의 동적 연관성에 대한 연구에 선행연구들과 같이 주가만 고려할 경우 주식시장에 영향을 미친 변수들을 제외함에 따른 통계적 편의가 존재하게 된다. 본 연구에서는 우리나라와 주요 투자국의 주식시장 간 통계적 통합의 검정모형에 각국의 주가 외에 국내 외환 및 금융시장을 동시에 포함시켜 보았다. 분석 결과 위기에 따른 변화의 영향이 계속되는 기간에는 이들이 주식시장의 통합에 유의한 영향을 미치는 것으로 추정되어 주식시장만 고려할 경우 모형의 설정오류 가능성이 존재함을 입증한다.

LonWorks-IP 가상 디바이스 네트워크상에서 예지 및 예방보전을 위한 DC 서보모터의 분산제어 (Distributed Control of DC Servo Motor on LonWorks-IP Virtual Device Network for Predictive and Preventive Maintenance)

  • 송기원
    • 한국안전학회지
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    • 제21권4호
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    • pp.25-32
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    • 2006
  • LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

Multicity Seasonal Air Quality Index Forecasting using Soft Computing Techniques

  • Tikhe, Shruti S.;Khare, K.C.;Londhe, S.N.
    • Advances in environmental research
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    • 제4권2호
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    • pp.83-104
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    • 2015
  • Air Quality Index (AQI) is a pointer to broadcast short term air quality. This paper presents one day ahead AQI forecasting on seasonal basis for three major cities in Maharashtra State, India by using Artificial Neural Networks (ANN) and Genetic Programming (GP). The meteorological observations & previous AQI from 2005-2008 are used to predict next day's AQI. It was observed that GP captures the phenomenon better than ANN and could also follow the peak values better than ANN. The overall performance of GP seems better as compared to ANN. Stochastic nature of the input parameters and the possibility of auto-correlation might have introduced time lag and subsequent errors in predictions. Spectral Analysis (SA) was used for characterization of the error introduced. Correlational dependency (serial dependency) was calculated for all 24 models prepared on seasonal basis. Particular lags (k) in all the models were removed by differencing the series, that is converting each i'th element of the series into its difference from the (i-k)"th element. New time series is generated for all seasonal models in synchronization with the original time line & evaluated using ANN and GP. The statistical analysis and comparison of GP and ANN models has been done. We have proposed a promising approach of use of GP coupled with SA for real time prediction of seasonal multicity AQI.

Seismic reliability assessment of base-isolated structures using artificial neural network: operation failure of sensitive equipment

  • Moeindarbari, Hesamaldin;Taghikhany, Touraj
    • Earthquakes and Structures
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    • 제14권5호
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    • pp.425-436
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    • 2018
  • The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.

실업지속기간의 측정모형 (Measuring Unemployment Durations of Different Types of Workers)

  • 최창곤
    • 한국산학기술학회논문지
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    • 제13권4호
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    • pp.1603-1608
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    • 2012
  • 실업의 규모는 실업상태에 진입하는 진입률의 크기와 실업상태의 지속기간이라는 두가지 요인에 의하여 결정된다. 본 연구는 실업의 지속기간을 측정하는 모형을 개발하여 다양한 형태의 실업자들의 실업지속기간을 측정하고자 한다. 분석결과 신규실업참가자의 실업지속기간과 실직자들의 실업지속기간의 결정요인은 서로 다르다는 것을 보인다. 모형을 이용하여 최근 대학 졸업자들이 노동시장에 신규로 참여하여 장기간 구직활동을 하는데 그 요인을 설명한다.