• 제목/요약/키워드: END random variables

검색결과 33건 처리시간 0.026초

COMPLETE CONVERGENCE AND COMPLETE MOMENT CONVERGENCE THEOREMS FOR WEIGHTED SUMS OF ARRAYS OF ROWWISE EXTENDED NEGATIVELY DEPENDENT RANDOM VARIABLES

  • Huang, Haiwu;Zhang, Qingxia
    • 대한수학회보
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    • 제56권4호
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    • pp.1007-1025
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    • 2019
  • In the present work, the complete convergence and complete moment convergence properties for arrays of rowwise extended negatively dependent (END) random variables are investigated. Some sharp theorems on these strong convergence for weighted sums of END cases are established. These main results not only generalize the known corresponding ones of Cai [2], Wang et al. [17] and Shen [14], but also improve them, respectively.

COMPLETE f-MOMENT CONVERGENCE FOR EXTENDED NEGATIVELY DEPENDENT RANDOM VARIABLES UNDER SUB-LINEAR EXPECTATIONS

  • Lu, Chao;Wang, Rui;Wang, Xuejun;Wu, Yi
    • 대한수학회지
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    • 제57권6호
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    • pp.1485-1508
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    • 2020
  • In this paper, we investigate the complete f-moment convergence for extended negatively dependent (END, for short) random variables under sub-linear expectations. We extend some results on complete f-moment convergence from the classical probability space to the sub-linear expectation space. As applications, we present some corollaries on complete moment convergence for END random variables under sub-linear expectations.

STRONG STABILITY OF A TYPE OF JAMISON WEIGHTED SUMS FOR END RANDOM VARIABLES

  • Yan, Jigao
    • 대한수학회지
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    • 제54권3호
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    • pp.897-907
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    • 2017
  • In this paper, we consider the strong stability of a type of Jamison weighted sums, which not only extend the corresponding result of Jamison etc. [13] from i.i.d. case to END random variables, but also obtain the necessary and sufficient results. As an important consequence, we present the result of SLLN as that of i.i.d. case.

Parametric study on probabilistic local seismic demand of IBBC connection using finite element reliability method

  • Taherinasab, Mohammad;Aghakouchak, Ali A.
    • Steel and Composite Structures
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    • 제37권2호
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    • pp.151-173
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    • 2020
  • This paper aims to probabilistically evaluate performance of two types of I beam to box column (IBBC) connection. With the objective of considering the variability of seismic loading demand, statistical features of the inter-story drift ratio corresponding to the second, fifth and eleventh story of a 12-story steel special moment resisting frames are extracted through incremental dynamic analysis at global collapse state. Variability of geometrical variables and material strength are also taken into account. All of these random variables are exported as inputs to a probabilistic finite element model which simulates the connection. At the end, cumulative distribution functions of local seismic demand for each component of each connection are provided using histogram sampling. Through a parametric study on probabilistic local seismic demand, the influence of some geometrical random variables on the performance of IBBC connections is demonstrated. Furthermore, the probabilistic study revealed that IBBC connection with widened flange has a better performance than the un-widened flange. Also, a design procedure is proposed for WF connections to achieve a same connection performance in different stories.

Study on the Dynamic Model and Simulation of a Flexible Mechanical Arm Considering its Random Parameters

  • He Bai-Yan;Wang Shu-Xin
    • Journal of Mechanical Science and Technology
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    • 제19권spc1호
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    • pp.265-271
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    • 2005
  • Randomness exists in engineering. Tolerance, assemble-error, environment temperature and wear make the parameters of a mechanical system uncertain. So the behavior or response of the mechanical system is uncertain. In this paper, the uncertain parameters are treated as random variables. So if the probability distribution of a random parameter is known, the simulation of mechanical multibody dynamics can be made by Monte-Carlo method. Thus multibody dynamics simulation results can be obtained in statistics. A new concept called functional reliability is put forward in this paper, which can be defined as the probability of the dynamic parameters(such as position, orientation, velocity, acceleration etc.) of the key parts of a mechanical multibody system belong to their tolerance values. A flexible mechanical arm with random parameters is studied in this paper. The length, width, thickness and density of the flexible arm are treated as random variables and Gaussian distribution is used with given mean and variance. Computer code is developed based on the dynamic model and Monte-Carlo method to simulate the dynamic behavior of the flexible arm. At the same time the end effector's locating reliability is calculated with circular tolerance area. The theory and method presented in this paper are applicable on the dynamics modeling of general multibody systems.

CONVERGENCE PROPERTIES OF THE PARTIAL SUMS FOR SEQUENCES OF END RANDOM VARIABLES

  • Wu, Yongfeng;Guan, Mei
    • 대한수학회지
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    • 제49권6호
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    • pp.1097-1110
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    • 2012
  • The convergence properties of extended negatively dependent sequences under some conditions of uniform integrability are studied. Some sufficient conditions of the weak law of large numbers, the $p$-mean convergence and the complete convergence for extended negatively dependent sequences are obtained, which extend and enrich the known results in the literature.

확률적인 사용시간하의 이산적 일제교체정책 (Discrete Block Replacement Policies under Random Use Durations)

  • 유영관
    • 품질경영학회지
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    • 제32권3호
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    • pp.62-67
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    • 2004
  • This paper presents and compares two block replacement policies under random use durations. The units are put in service altogether and then idle for some time. The time durations during which units are put in service are random variables. Two block replacement policies, called N-policy and T-policy, are presented. Under N-policy, units are replaced altogether after the Nth use. Under T-policy, units are replaced altogether at the end of the use after cumulative use time T elapses. The failures during use durations are replaced by new ones individually. The cost rate expressions under the policies are derived for exponential use durations. Numerical examples are presented to compare the performances of the two policies.

머신러닝 기법을 활용한 대졸 구직자 취업 예측모델에 관한 연구 (Study on the Prediction Model for Employment of University Graduates Using Machine Learning Classification)

  • 이동훈;김태형
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권2호
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    • pp.287-306
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    • 2020
  • Purpose Youth unemployment is a social problem that continues to emerge in Korea. In this study, we create a model that predicts the employment of college graduates using decision tree, random forest and artificial neural network among machine learning techniques and compare the performance between each model through prediction results. Design/methodology/approach In this study, the data processing was performed, including the acquisition of the college graduates' vocational path survey data first, then the selection of independent variables and setting up dependent variables. We use R to create decision tree, random forest, and artificial neural network models and predicted whether college graduates were employed through each model. And at the end, the performance of each model was compared and evaluated. Findings The results showed that the random forest model had the highest performance, and the artificial neural network model had a narrow difference in performance than the decision tree model. In the decision-making tree model, key nodes were selected as to whether they receive economic support from their families, major affiliates, the route of obtaining information for jobs at universities, the importance of working income when choosing jobs and the location of graduation universities. Identifying the importance of variables in the random forest model, whether they receive economic support from their families as important variables, majors, the route to obtaining job information, the degree of irritating feelings for a month, and the location of the graduating university were selected.

Higher-Order Conditional Random Field established with CNNs for Video Object Segmentation

  • Hao, Chuanyan;Wang, Yuqi;Jiang, Bo;Liu, Sijiang;Yang, Zhi-Xin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권9호
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    • pp.3204-3220
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    • 2021
  • We perform the task of video object segmentation by incorporating a conditional random field (CRF) and convolutional neural networks (CNNs). Most methods employ a CRF to refine a coarse output from fully convolutional networks. Others treat the inference process of the CRF as a recurrent neural network and then combine CNNs and the CRF into an end-to-end model for video object segmentation. In contrast to these methods, we propose a novel higher-order CRF model to solve the problem of video object segmentation. Specifically, we use CNNs to establish a higher-order dependence among pixels, and this dependence can provide critical global information for a segmentation model to enhance the global consistency of segmentation. In general, the optimization of the higher-order energy is extremely difficult. To make the problem tractable, we decompose the higher-order energy into two parts by utilizing auxiliary variables and then solve it by using an iterative process. We conduct quantitative and qualitative analyses on multiple datasets, and the proposed method achieves competitive results.

Analysis of Unfinished Work and Queue Waiting Time for the M/G/1 Queue with D-policy

  • Park, Yon-Il;Chae, Kyung-Chul
    • Journal of the Korean Statistical Society
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    • 제28권4호
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    • pp.523-533
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    • 1999
  • We consider the M/G/1 queueing model with D-policy. The server is turned off at the end of each busy period and is activated again only when the sum of the service times of all waiting customers exceeds a fixed value D. We obtain the distribution of unfinished work and show that the unfinished work decomposes into two random variables, one of which is the unfinished work of ordinary M/G/1 queue. We also derive the distribution of queue waiting time.

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