• Title/Summary/Keyword: stochastic increasing

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On Some New Stochastic Orders of Interest in Reliability Theory

  • Kayid, M.;El-Bassiouny, A.H.;Al-Wasel, I.A.
    • International Journal of Reliability and Applications
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    • v.8 no.1
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    • pp.95-109
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    • 2007
  • The purpose of this paper is to study new notions of stochastic comparisons and ageing classes based on the total time on test transform order. We give relationships to other stochastic orders and aging classes given previously. Several preservation properties under the reliability operations of random minima and series system are given.

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Stochastic Properties of Life Distribution with Increasing Tail Failure Rate and Nonparametric Testing Procedure

  • Lim, Jae-Hak;Park, Dong Ho
    • Journal of Applied Reliability
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    • v.18 no.3
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    • pp.220-228
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    • 2018
  • Purpose: The purpose of this study is to investigate the tail behavior of the life distribution which exhibits an increasing failure rate or other positive aging effects after a certain time point. Methods: We characterize the tail behavior of the life distribution with regard to certain reliability measures such as failure rate, mean residual life and reliability function and derive several stochastic properties regarding such life distributions. Also, utilizing an L-statistic and its asymptotic normality, we propose new nonparametric testing procedures which verify if the life distribution has an increasing tail failure rate. Results: We propose the IFR-Tail (Increasing Failure Rate in Tail), DMRL-Tail (Decreasing Mean Residual Life in Tail) and NBU-Tail (New Better than Used in Tail) classes, all of which represent the tail behavior of the life distribution. And we discuss some stochastic properties of these proposed classes. Also, we develop a new nonparametric test procedure for detecting the IFR-Tail class and discuss its relative efficiency to explore the power of the test. Conclusion: The results of our research could be utilized in the study of wide range of applications including the maintenance and warranty policy of the second-hand system.

Ecohydrologic Analysis on Soil Water and Plant Water Stress : Focus on Derivation and Application of Stochastic Model (토양수분과 식생의 물 압박에 대한 생태수문학적 해석 : 추계학적 모형의 유도와 적용을 중심으로)

  • Han, Suhee;Kim, Sangdan
    • Journal of Korean Society on Water Environment
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    • v.24 no.1
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    • pp.99-106
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    • 2008
  • With globally increasing interests in climate-soil-vegetation system, a new stochastic model of soil water and plant water stress is derived for better understanding of the soil water and plant water stress dynamics and their role in water-controlled ecosystem. The steady-state assumption is used for simplifying the equations. The derived model is simple yet realistic that it can account for the essential features of the system. The model represents the general characteristics of rainfall, soil, and vegetation; i.e. the soil moisture constitutes the decrease form of the steady-state and the plant water stress becomes increasing with the steady state when the rainfall is decreased. With this model, further deep study for the effects of soil water and plant water stress on the system will be accomplished.

A STOCHASTIC VARIANCE REDUCTION METHOD FOR PCA BY AN EXACT PENALTY APPROACH

  • Jung, Yoon Mo;Lee, Jae Hwa;Yun, Sangwoon
    • Bulletin of the Korean Mathematical Society
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    • v.55 no.4
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    • pp.1303-1315
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    • 2018
  • For principal component analysis (PCA) to efficiently analyze large scale matrices, it is crucial to find a few singular vectors in cheaper computational cost and under lower memory requirement. To compute those in a fast and robust way, we propose a new stochastic method. Especially, we adopt the stochastic variance reduced gradient (SVRG) method [11] to avoid asymptotically slow convergence in stochastic gradient descent methods. For that purpose, we reformulate the PCA problem as a unconstrained optimization problem using a quadratic penalty. In general, increasing the penalty parameter to infinity is needed for the equivalence of the two problems. However, in this case, exact penalization is guaranteed by applying the analysis in [24]. We establish the convergence rate of the proposed method to a stationary point and numerical experiments illustrate the validity and efficiency of the proposed method.

Developing the Bullwhip Effect Measure in a Supply Chain Considering Seasonal Demand and Stochastic Lead Time (공급사슬에서 계절적 수요와 추계적 조달기간을 고려한 채찍효과 측도의 개발)

  • Cho, Dong-Won;Lee, Young-Hae
    • Journal of the Korean Operations Research and Management Science Society
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    • v.34 no.4
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    • pp.91-112
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    • 2009
  • The bullwhip effect means the phenomenon of increasing demand variation as moving UP to the upstream in the supply chain. Therefore, it is recognized that the bullwhip effect is problematic for effective supply chain operations. In this paper, we exactly quantifies the bullwhip effect for the case of stochastic lead time and seasonal demand in two-echelon supply chain where retailer employs a base-stock policy considering SARMA demand processes and stochastic lead time. We also investigate the behavior of the proposed measurement for the bullwhip effect with autoregressive and moving average coefficient, stochastic lead time, and seasonal factor.

Application of Hidden Markov Model Using AR Coefficients to Machine Diagnosis (AR계수를 이용한 Hidden Markov Model의 기계상태진단 적용)

  • 이종민;황요하;김승종;송창섭
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.13 no.1
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    • pp.48-55
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    • 2003
  • Hidden Markov Model(HMM) has a doubly embedded stochastic process with an underlying stochastic process that can be observed through another set of stochastic processes. This structure of HMM is useful for modeling vector sequence that doesn't look like a stochastic process but has a hidden stochastic process. So, HMM approach has become popular in various areas in last decade. The increasing popularity of HMM is based on two facts : rich mathematical structure and proven accuracy on critical application. In this paper, we applied continuous HMM (CHMM) approach with AR coefficient to detect and predict the chatter of lathe bite and to diagnose the wear of oil Journal bearing using rotor shaft displacement. Our examples show that CHMM approach is very efficient method for machine health monitoring and prediction.

A STUDY ON DURATION ESTIMATE METHOD USING STOCHASTIC MODEL IN THE BIM ENVIRONMENT

  • Jae H. Park;Seok H. Yun;Joon H. Paek
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.1209-1215
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    • 2009
  • Recently, Construction Projects are being much bigger and more complex. So the importance of Construction Planning and Management is increasing and increasing because of the Construction Projects is involved in a variety of construction-related subjects. Competitive of the Construction Industry decided Cost, Construction Duration and Productivity. But they were just focused on Cost Saving instead of Construction Duration and Productivity. However, they have to finish construction projects using minimum cost and duration with quality and function of required level for successful Construction projects. Thus, current high exchange rate and high period, it is clear to decrease construction cost and to do economic construction in huge Construction Projects and it means more advanced Construction Schedule Management needs for economic construction. But Construction Scheduling Planning, basic of Construction Schedule Management, adjusted contract period without Pre-Planning, just depending on experience and ability of Construction Engineer. Because of that, this study suggests new Duration Estimate Method using Stochastic Model in BIM Environment for advanced Construction Schedule Management. Existing Duration Estimate Methods are just modified wrong points of them or analyzed effective factors of construction schedule. However, New Duration Estimate Method is just consists of Stochastic Model and BIM Environment without existing Duration Estimate Methods. So, new method has creativity and specialty. After this research, it would be a great model in construction industry field.

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Non-statistical Stochastic Finite Element Method Employing Higher Order Stochastic Field Function (고차의 추계장 함수와 이를 이용한 비통계학적 추계론적 유한요소해석)

  • Noh, Hyuk-Chun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.2A
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    • pp.383-390
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    • 2006
  • In this paper, a stochastic field that is compatible with Monte Carlo simulation is suggested for an expansion-based stochastic analysis scheme of weighted integral method. Through investigation on the way of affection of stochastic field function on the displacement vector in the series expansion scheme, it is noticed that the stochastic field adopted in the weighted integral method is not compatible with that appears in the Monte Carlo simulation. As generally recognized in the field of stochastic mechanics, the response variability is not a linear function of the coefficient of variation of stochastic field but a nonlinear function with increasing variability as the intensity of uncertainty is increased. Employing the stochastic field suggested in this study, the response variability evaluated by means of the weighted integral scheme is reproduced with high precision even for uncertain fields with moderately large coefficient of variation. Besides, despite the fact that only the first-order expansion is employed, an outstanding agreement between the results of expansion-based weighted integral method and Monte Carlo simulation is achieved.

A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation

  • Cui, Wei;Yan, Wei;Lee, Wei-Jen;Zhao, Xia;Ren, Zhouyang;Wang, Cong
    • Journal of Electrical Engineering and Technology
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    • v.12 no.1
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    • pp.53-63
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    • 2017
  • The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

Model Following Dual Controller Design for Random Vibrating System Using a Stochastic Controller Technique (확률제어 기법을 이용한 불규칙 진동계의 모델추종 이중제어기 설계)

  • Lee, J.B.;Kim, H.Y.;Ahn, J.Y.;Heo, H.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.525-528
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    • 2005
  • Much of the study has been dong on the design of dual controller that guarantee the stability and improvement of the system performance. A dual controller concept is proposed to consist of first controller estimates the control law and second controller suppresses the combined noises due to numerical error and internal noise as well. These irregular disturbances are not only increasing the fatigue but also destabilize the system because of unwanted output performance. The 'stochastic controller' is used to suppress the irregular random disturbance. Simulation is conducted to reveal that the proposed dual stochastic controller is highly efficient one to control a system hybrid noises.

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