• Title/Summary/Keyword: Multiplicative model

검색결과 155건 처리시간 0.027초

Effect of Plastic Gradient from GND on the Behavior of Polycrystalline Solids (GND 효과에 의한 소성 구배의 다결정 고체 거동에 대한 영향)

  • Chung, Sang-Yeop;Han, Tong-Seok
    • Journal of the Computational Structural Engineering Institute of Korea
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    • 제24권2호
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    • pp.185-191
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    • 2011
  • Plastic gradient from geometrically necessary dislocation(GND) can affect material behavior significantly. In this research, mechanical behavior of polycrystalline solid is investigated using the finite element method incorporating plastic gradient from long range dislocation or GND effect. Plastic gradient effect is implemented in the analysis model by considering a long range strain term as well as elastic and plastic terms in the multiplicative decomposition. In the model, gradient hardness coefficient and length parameter are used to evaluate the effect of the long range strains and sensitive study is conducted for the parameters. It is confirmed that the GND amplifies hardening response of polycrystals compared with the single crystal.

Forecasting the Port Trading Volumes for Improvement of Port Competitive Power (항만경쟁력 제고를 위한 항만교역량 예측)

  • Son, Yong-Jung
    • Journal of Korea Port Economic Association
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    • 제25권1호
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    • pp.1-14
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    • 2009
  • This study predicted Port trade volume by considering Korea's export to China and import Com China separately using ARIMA model (Multiplicative Seasonal ARIMA Model). We predicted monthly Port trade volumes for 27 months from October 2008 to December 2010 using monthly data from September 2008 to January 2001 using monthly data. As a result of prediction, we found that the export volume decreased in January, February, August and September while the import volume decreased in February, March, August and September. As the decrease period was clearly differentiated, it was possible to predict export and import volumes. Therefore, it is believed that the results of this study will generate useful basic data for policy makers or those working for export and import enterprises when they set up policies and management plans. And to improve competitive power of Port trade, this study suggests privatization of Port, improvement of information capability, improvement of competitive power of Port management companies, support for Port distribution companies, plans for active encouragement of transshipment, and management of added value creation policy.

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An Efficient and Stable Congestion Control Scheme with Neighbor Feedback for Cluster Wireless Sensor Networks

  • Hu, Xi;Guo, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4342-4366
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    • 2016
  • Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur'e type system. In the context of delayed Lur'e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

Forecasting of Yeongdeok Tourist by Seasonal ARIMA Model (계절 아리마 모형을 이용한 관광객 예측 -경북 영덕지역을 대상으로-)

  • Son, Eun-Ho;Park, Duk-Byeong
    • Journal of Agricultural Extension & Community Development
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    • 제19권2호
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    • pp.301-320
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    • 2012
  • The study uses a seasonal ARIMA model to forecast the number of tourists of Yeongdeok in an uni-variable time series. The monthly data for time series were collected ranging from 2006 to 2011 with some variation between on-season and off-season tourists in Yeongdeok county. A total of 72 observations were used for data analysis. The forecast multiplicative seasonal ARIMA(1,0,0)$(0,1,1)_{12}$ model was found the most appropriate one. Results showed that the number of tourists was 10,974 thousands in 2012 and 13,465 thousands in 2013, It was suggested that the grasping forecast model is very important in respect of how experts in tourism development in Yeongdeok county, policy makers or planners would establish strategies to allocate service in Yeongdeok tourist destination and provide tourism facilities efficiently.

Semiparametric and Nonparametric Modeling for Matched Studies

  • Kim, In-Young;Cohen, Noah
    • Proceedings of the Korean Statistical Society Conference
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    • 한국통계학회 2003년도 추계 학술발표회 논문집
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    • pp.179-182
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    • 2003
  • This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

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On a Detection Scheme for Weak Deterministic Signals in Non-Additive Noise (비가산성 잡음에서의 약한 화정적 신호의 검파방식에 관하여)

  • Song, Iick-Ho
    • Journal of the Korean Institute of Telematics and Electronics
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    • 제25권9호
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    • pp.1019-1026
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    • 1988
  • A parametric detection scheme for determenistic signals is obtained in a generalized observation model which contains non-additive noise. The model employed in this paper includes several special cases such as those describing purely-additive noise, multiplicative noise, and signal dependent noise and allows the consideration of deterministic and random signals. Locally optimum detectors for known deterministic signals in the model are derived and analyzed for performance. It is shown that the locally optimum detectors are interesting generalizations of those for the purely-additive noise model. Performance of the locally optimum detectors designed for the generalized observation model is compared to that of other common detectors.

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Phase Transitions and Phase Diagram of the Island Model with Migration

  • Park, Jeong-Man
    • Journal of the Korean Physical Society
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    • 제73권9호
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    • pp.1219-1224
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    • 2018
  • We investigate the evolutionary dynamics and the phase transitions of the island model which consists of subdivided populations of individuals confined to two islands. In the island model, the population is subdivided so that migration acts to determine the evolutionary dynamics along with selection and genetic drift. The individuals are assumed to be haploid and to be one of two species, X or Y. They reproduce according to their fitness values, die at random, and migrate between the islands. The evolutionary dynamics of an individual based model is formulated in terms of a master equation and is approximated by using the diffusion method as the multidimensional Fokker-Planck equation (FPE) and the coupled non-linear stochastic differential equations (SDEs) with multiplicative noise. We analyze the infinite population limit to find the phase transitions from the monomorphic state of one type to the polymorphic state to the monomorphic state of the other type as we vary the ratio of the fitness values in two islands and complete the phase diagram of our island model.

HIERARCHICAL SWITCHING CONTROL OF LONGITUDINAL ACCELERATION WITH LARGE UNCERTAINTIES

  • Gao, F.;Li, K.Q.
    • International Journal of Automotive Technology
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    • 제8권3호
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    • pp.351-359
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    • 2007
  • In this study, a hierarchical switching control scheme based on robust control theory is proposed for tracking control of vehicle longitudinal acceleration in the presence of large uncertainties. A model set consisting of four multiplicative-uncertainty models is set up, and its corresponding controller set is designed by the LMI approach, which can ensures the robust performance of the closed loop system under arbitray switching. Based on the model set and the controller set, a switching index function by estimating the system gain of the uncertainties between the plant and the nominal model is designed to determine when and which controller should be switched into the closed loop. After theoretical analyses, experiments have also been carried out to validate the proposed control algorithm. The results show that the control system has good performance of robust stability and tracking ability in the presence of large uncertainties. The response time is smaller than 1.5s and the max tracking error is about $0.05\;m/S^2$ with the step input.

Prediction of Electricity Sales by Time Series Modelling (시계열모형에 의한 전력판매량 예측)

  • Son, Young Sook
    • The Korean Journal of Applied Statistics
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    • 제27권3호
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    • pp.419-430
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    • 2014
  • An accurate prediction of electricity supply and demand is important for daily life, industrial activities, and national management. In this paper electricity sales is predicted by time series modelling. Real data analysis shows the transfer function model with cooling and heating days as an input time series and a pulse function as an intervention variable outperforms other time series models for the root mean square error and the mean absolute percentage error.

Additive Main Effects and Multiplicative Interaction Analysis of Host-Pathogen Relationship in Rice-Bacterial Blight Pathosystem

  • Nayak, D.;Bose, L.K.;Singh, S.;Nayak, P.
    • The Plant Pathology Journal
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    • 제24권3호
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    • pp.337-351
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    • 2008
  • Host-pathogen interaction in rice bacterial blight pathosystem was analyzed for a better understanding of their relationship and recognition of stable pathogenicity among the populations of Xanthomonas oryzae pv. oryzae. A total number of 52 bacterial strains isolated from diseased leaf samples collected from 12 rice growing states and one Union Territory of India, were inoculated on 16 rice varieties, each possessing known genes for resistance. Analysis of variance revealed that the host genotypes(G) accounted for largest(78.4%) proportion of the total sum of squares(SS), followed by 16.5% due to the pathogen isolates(I) and 5.1% due to the $I{\times}G$ interactions. Application of the Additive Main effects and Multiplicative Interaction(AMMI) model revealed that the first two interaction principal component axes(IPCA) accounted for 66.8% and 21.5% of the interaction SS, respectively. The biplot generated using the isolate and genotypic scores of the first two IPCAs revealed groups of host genotypes and pathogen isolates falling into four sectors. A group of five isolates with high virulence, high absolute IPCA-1 scores, moderate IPCA-2 scores, low AMMI stability index '$D_i$' values and minimal deviations from additive main effects displayed in AMMI biplot as well as response plot, were identified as possessing stable pathogenicity across 16 host genotypes. The largest group of 27 isolates with low virulence, small IPCA-1 as well as IPCA-2 scores, low $D_i$ values and minimal deviations from additive main effect predictions, possessed stable pathogenicity for low virulence. The AMMI analysis and biplot display facilitated in a better understanding of the host-pathogen interaction, adaptability of pathogen isolates to specific host genotypes, identification of isolates showing stable pathogenicity and most discriminating host genotypes, which could be useful in location specific breeding programs aiming at deployment of resistant host genotypes in bacterial blight disease control strategies.