• Title/Summary/Keyword: stochastic models

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Modeling of Hydrologic Time Series using Stochastic Neural Networks Approach (추계학적 신경망 접근법을 이용한 수문학적 시계열의 모형화)

  • Kim, Seong-Won;Kim, Jeong-Heon;Park, Gi-Beom
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.1346-1349
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    • 2010
  • The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

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Stochastic response of suspension bridges for various spatial variability models

  • Adanur, Suleyman;Altunisik, Ahmet C.;Soyluk, Kurtulus;Dumanoglu, A. Aydin
    • Steel and Composite Structures
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    • v.22 no.5
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    • pp.1001-1018
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    • 2016
  • The purpose of this paper is to compare the structural responses obtained from the stochastic analysis of a suspension bridge subjected to uniform and partially correlated seismic ground motions, using different spatial correlation functions commonly used in the earthquake engineering. The spatial correlation function employed in this study consists of a term that characterizes the loss of coherency. To account for the spatial variability of ground motions, the widely used four loss of coherency models in the literature has been taken into account in this study. Because each of these models has its own characteristics, it is intended to determine the sensitivity of a suspension bridge due to these losses of coherency models which represent the spatial variability of ground motions. Bosporus Suspension Bridge connects Europe to Asia in Istanbul is selected as a numerical example. The bridge has steel towers that are flexible, inclined hangers and a steel box-deck of 1074 m main span, with side spans of 231 and 255 m on the European and Asian sides, respectively. For the ground motion the filtered white noise model is considered and applied in the vertical direction, the intensity parameter of this model is obtained by using the S16E component of Pacoima Dam record of 1971 San Fernando earthquake. An analytically simple model called as filtered white noise ground motion model is chosen to represent the earthquake ground motion. When compared with the uniform ground motion case, the results obtained from the spatial variability models with partial correlation outline the necessity to include the spatial variability of ground motions in the stochastic dynamic analysis of suspension bridges. It is observed that while the largest response values are obtained for the model proposed by Harichandran and Vanmarcke, the model proposed by Uscinski produces the smallest responses among the considered partially correlated ground motion models. The response values obtained from the uniform ground motion case are usually smaller than those of the responses obtained from the partially correlated ground motion cases. While the response values at the flexible parts of the bridge are totally dominated by the dynamic component, the pseudo-static component also has significant contributions for the response values at the rigid parts of the bridge. The results also show the consistency of the spatial variability models, which have different characteristics, considered in this study.

THE VALUATION OF VARIANCE SWAPS UNDER STOCHASTIC VOLATILITY, STOCHASTIC INTEREST RATE AND FULL CORRELATION STRUCTURE

  • Cao, Jiling;Roslan, Teh Raihana Nazirah;Zhang, Wenjun
    • Journal of the Korean Mathematical Society
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    • v.57 no.5
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    • pp.1167-1186
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    • 2020
  • This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.

Determination of flutter derivatives by stochastic subspace identification technique

  • Qin, Xian-Rong;Gu, Ming
    • Wind and Structures
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    • v.7 no.3
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    • pp.173-186
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    • 2004
  • Flutter derivatives provide the basis of predicting the critical wind speed in flutter and buffeting analysis of long-span cable-supported bridges. In this paper, one popular stochastic system identification technique, covariance-driven Stochastic Subspace Identification(SSI in short), is firstly presented for estimation of the flutter derivatives of bridge decks from their random responses in turbulent flow. Secondly, wind tunnel tests of a streamlined thin plate model and a ${\Pi}$ type blunt bridge section model are conducted in turbulent flow and the flutter derivatives are determined by SSI. The flutter derivatives of the thin plate model identified by SSI are very comparable to those identified by the unifying least-square method and Theodorson's theoretical values. As to the ${\Pi}$ type section model, the effect of turbulence on aerodynamic damping seems to be somewhat notable, therefore perhaps the wind tunnel tests for flutter derivative estimation of those models with similar blunt sections should be conducted in turbulent flow.

Stochastic finite element analysis considering the uncertainty of shape (형상의 불확실성을 고려한 확률유한요소 해석)

  • Kim, Young-Kyoun;Hong, Jung-Pyo;Kim, Gyu-Tak;Hur, Jin
    • Proceedings of the KIEE Conference
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    • 1999.07a
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    • pp.200-202
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    • 1999
  • A method of stochastic finite element analysis is developed for yield a uncertainty of engineering problems. Where, a stochastic finite-element method for shapes modeling is proposed a6 a means to solve the models with the uncertainty and variety. This method is based on the probability and illustrated by a first-Order Second-Moment Method and considering the covariance of random variables. The validity and accuracy of the stochastic finite element method is verified through comparing with those solved by the conventional 2-D finite element method.

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Modeling of Stochastic Properties of Internal Heat Generation of an Office Building for Slab Cooling Storage (사무소건물의 슬래브축냉을 위한 내부발열부하의 확률적 성상 모델화)

  • Jung, Jae-Hoon
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.23 no.12
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    • pp.836-842
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    • 2011
  • It has been shown that the air-conditioning system with slab cooling storage is effective in cutting peak load and utilizing nighttime electric power. The stochastic properties of internal heat generation which has great influence on the cooling load are examined in this paper. Based on the measured cooling load and electric power consumption in an office building with slab cooling storage, stochastic time series models to simulate these random processes are investigated. Furthermore, a calculated result by an optimal control method of thermal analysis taking into account the internal heat is compared with the measured cooling load.

Design of the Fuzzy-based Mobile Model for Energy Efficiency within a Wireless Sensor Network

  • Yun, Dai Yeol;Lee, Daesung
    • Journal of information and communication convergence engineering
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    • v.19 no.3
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    • pp.136-141
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    • 2021
  • Research on wireless sensor networks has focused on the monitoring and characterization of large-scale physical environments and the tracking of various environmental or physical conditions, such as temperature, pressure, and wind speed. We propose a stochastic mobility model that can be applied to a MANET (Mobile Ad-hoc NETwork). environment, and apply this mobility model to a newly proposed clustering-based routing protocol. To verify its stability and durability, we compared the proposed stochastic mobility model with a random model in terms of energy efficiency. The FND (First Node Dead) was measured and compared to verify the performance of the newly designed protocol. In this paper, we describe the proposed mobility model, quantify the changes to the mobile environment, and detail the selection of cluster heads and clusters formed using a fuzzy inference system. After the clusters are configured, the collected data are sent to a base station. Studies on clustering-based routing protocols and stochastic mobility models for MANET applications have shown that these strategies improve the energy efficiency of a network.