• Title/Summary/Keyword: gradient model

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Comparison of tropical cyclone wind field models and their influence on estimated wind hazard

  • Gu, J.Y.;Sheng, C.;Hong, H.P.
    • Wind and Structures
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    • v.31 no.4
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    • pp.321-334
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    • 2020
  • Engineering type tropical cyclone (TC) wind field models are used to estimate TC wind hazard. Some of the models are well-calibrated using observation data, while others are not extensively compared and verified. They are all proxies to the real TC wind fields. The computational effort for their use differs. In the present study, a comparison of the predicted wind fields is presented by considering three commonly used models: the gradient wind field model, slab-resolving model, and a linear height-resolving model. These models essentially predict the horizontal wind speed at a different height. The gradient wind field model and linear height-resolving model are simple to use while the nonlinear slab-resolving model is more compute-intensive. A set of factors is estimated and recommended such that the estimated TC wind hazard by using these models becomes more consistent. The use of the models, including the developed set of factors, for estimating TC wind hazard over-water and over-land is presented by considering the historical tracks for a few sites. It is shown that the annual maximum TC wind speed can be adequately modelled by the generalized extreme value distribution.

Fuzzy Model Identification using a mGA Hybrid Schemes (mGA의 혼합된 구조를 사용한 퍼지 모델 동정)

  • Ju, Yeong-Hun;Lee, Yeon-U;Park, Jin-Bae
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.8
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    • pp.423-431
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    • 2000
  • This paper presents a systematic approach to the input-output data-based fuzzy modeling for the complex and uncertain nonlinear systems, in which the conventional mathematical models may fail to give the satisfying results. To do this, we propose a new method that can yield a successful fuzzy model using a mGA hybrid schemes with a fine-tuning method. We also propose a new coding method fo chromosome for applying the mGA to the structure and parameter identifications of fuzzy model simultaneously. During mGA search, multi-purpose fitness function with a penalty process is proposed and adapted to guarantee the accurate and valid fuzzy modes. This coding scheme can effectively represent the zero-order Takagi-Sugeno fuzzy model. The proposed mGA hybrid schemes can coarsely optimize the structure and the parameters of the fuzzy inference system, and then fine tune the identified fuzzy model by using the gradient descent method. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its applications to two nonlinear systems.

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Mean fragmentation size prediction in an open-pit mine using machine learning techniques and the Kuz-Ram model

  • Seung-Joong Lee;Sung-Oong Choi
    • Geomechanics and Engineering
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    • v.34 no.5
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    • pp.547-559
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    • 2023
  • We evaluated the applicability of machine learning techniques and the Kuz-Ram model for predicting the mean fragmentation size in open-pit mines. The characteristics of the in-situ rock considered here were uniaxial compressive strength, tensile strength, rock factor, and mean in-situ block size. Seventy field datasets that included these characteristics were collected to predict the mean fragmentation size. Deep neural network, support vector machine, and extreme gradient boosting (XGBoost) models were trained using the data. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of determination (r2). The XGBoost model had the smallest RMSE and the highest r2 value compared with the other models. Additionally, when analyzing the error rate between the measured and predicted values, XGBoost had the lowest error rate. When the Kuz-Ram model was applied, low accuracy was observed owing to the differences in the characteristics of data used for model development. Consequently, the proposed XGBoost model predicted the mean fragmentation size more accurately than other models. If its performance is improved by securing sufficient data in the future, it will be useful for improving the blasting efficiency at the target site.

Object Model ing from Depth Information Using Z-gradient (3차원 정보로 부터 Z축의 기울기를 이용한 물체의 조형.)

  • Kim, T.Y.;Cho, D.U.;Choi, B.U.
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1069-1072
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    • 1987
  • In this paper, we drive useful data from 3-D depth information as input using discontinuity boundary or clustering. And using magnitude and direction of z-gradient we classify the data into adaptable primitive types through intrinsic and stochastical processing. After these processing information is reconstructed for forming data base. And make relationship and standard view position for matching.

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An optimal control in cement kiln heat-up (시멘트 소성로 가열 단계에서의 최적 제어)

  • 김송호;이광순;이원규
    • 제어로봇시스템학회:학술대회논문집
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    • 1986.10a
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    • pp.468-470
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    • 1986
  • An optimal control in heat-up operation was formulated for minimizing the quadratic performance criterion which is a function of temperature, temperature gradient in the wall and fuel flow rate. For optimal control law computations mathematical model was simplified with assumptions and then linearized by use of orthogonal collocation in radial direction. Effects of weighting function assigned to temperature and temperature gradient and final time were compared with industrial data.

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Extraction of Human Body Using Hybrid Silhouette Extraction Method in Intelligent Robot System (지능형 로봇 시스템에서 하이브리드 실루엣 추출 방법을 이용한 인간의 몸 추출)

  • Kim Moon Hwan;Joo Young Hoon;Park Jin Bae;Cho Young Jo;Chi Su Young;Kim hye Jin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.7
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    • pp.852-857
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    • 2005
  • This paper discusses a human body extraction method for intelligent robot system. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. The new hybrid silhouette extraction method is proposed to overcome this constrained environment. The temporal and gradient information is combined as hybrid silhouette. The motion region model is used to adjust combining parameters in hybrid silhouette. Finally, the experimental results show the superiority of the proposed method.

An improved plasma model by optimizing neuron activation gradient (뉴런 활성화 경사 최적화를 이용한 개선된 플라즈마 모델)

  • 김병환;박성진
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.20-20
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    • 2000
  • Back-propagation neural network (BPNN) is the most prevalently used paradigm in modeling semiconductor manufacturing processes, which as a neuron activation function typically employs a bipolar or unipolar sigmoid function in either hidden and output layers. In this study, applicability of another linear function as a neuron activation function is investigated. The linear function was operated in combination with other sigmoid functions. Comparison revealed that a particular combination, the bipolar sigmoid function in hidden layer and the linear function in output layer, is found to be the best combination that yields the highest prediction accuracy. For BPNN with this combination, predictive performance once again optimized by incrementally adjusting the gradients respective to each function. A total of 121 combinations of gradients were examined and out of them one optimal set was determined. Predictive performance of the corresponding model were compared to non-optimized, revealing that optimized models are more accurate over non-optimized counterparts by an improvement of more than 30%. This demonstrates that the proposed gradient-optimized teaming for BPNN with a linear function in output layer is an effective means to construct plasma models. The plasma modeled is a hemispherical inductively coupled plasma, which was characterized by a 24 full factorial design. To validate models, another eight experiments were conducted. process variables that were varied in the design include source polver, pressure, position of chuck holder and chroline flow rate. Plasma attributes measured using Langmuir probe are electron density, electron temperature, and plasma potential.

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Harmonic analysis and field quality improvement of an HTS quadrupole magnet for a heavy ion accelerator

  • Zhang, Zhan;Wei, Shaoqing;Lee, Sangjin;Jo, Hyun Chul;Kim, Do Gyun;Kim, Jongwon
    • Progress in Superconductivity and Cryogenics
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    • v.18 no.2
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    • pp.21-24
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    • 2016
  • In recent years, the iron-dominated high-temperature superconductor (HTS) quadrupole magnets are being developed for heavy ion accelerators. Field analyses for iron-dominated quadrupole magnets were based on the normal-conducting (NC) quadrupole magnet early in the development for accelerators. Some conclusions are still in use today. However, the magnetic field of iron-dominated HTS quadrupole magnets cannot fully follow these conclusions. This study established an HTS quadrupole magnet model and an NC quadrupole magnet model, respectively. The harmonic characteristics of two magnets were analyzed and compared. According to the comparison, the conventional iron-dominated quadrupole magnets can be designed for maximum field gradient; the HTS quadrupole magnet, however, should be considered with varying field gradient. Finally, the HTS quadrupole magnet was designed for the changing field gradient. The field quality of the design was improved comparing with the result of the previous study. The new design for the HTS quadrupole magnet has been suggested.

Development of Railway Vibration Evaluation System Using Actual Railway Vibration Database (실측 철도 진동 데이터베이스를 이용한 철도진동 평가 시스템 개발)

  • Lee, Hyunjun;Seo, Eun Seong;Hwang, Young Sup
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.4
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    • pp.153-162
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    • 2019
  • Recently, it is necessary to develop a technology for quantitatively evaluating railway vibration to prevent civil complaints about orbital structures caused by railway noise and normal operation of ultra-precise equipment of orbital industrial complexes. The existing analytical method requires a very complicated dynamic response model, and it is difficult to secure the reliability of the result due to the inaccuracy of the demand model. Therefore, in this paper, we propose a railway vibration evaluation algorithm and system that deduce the vibration value generated from railway operation by using Linear Regression and Gradient Descent technique based on actual measurement railway vibration database that classifies factors affecting railway vibration. The prediction results obtained by the proposed algorithm show higher efficiency and accuracy than the existing analytical methods.

FINITE SPEED OF PROPAGATION IN DEGENERATE EINSTEIN BROWNIAN MOTION MODEL

  • HEVAGE, ISANKA GARLI;IBRAGIMOV, AKIF
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.26 no.2
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    • pp.108-120
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    • 2022
  • We considered qualitative behaviour of the generalization of Einstein's model of Brownian motion when the key parameter of the time interval of free jump degenerates. Fluids will be characterised by number of particles per unit volume (density of fluid) at point of observation. Degeneration of the phenomenon manifests in two scenarios: a) flow of the fluid, which is highly dispersing like a non-dense gas and b) flow of fluid far away from the source of flow, when the velocity of the flow is incomparably smaller than the gradient of the density. First, we will show that both types of flows can be modeled using the Einstein paradigm. We will investigate the question: What features will particle flow exhibit if the time interval of the free jump is inverse proportional to the density and its gradient ? We will show that in this scenario, the flow exhibits localization property, namely: if at some moment of time t0 in the region, the gradient of the density or density itself is equal to zero, then for some T during time interval [t0, t0 + T] there is no flow in the region. This directly links to Barenblatt's finite speed of propagation property for the degenerate equation. The method of the proof is very different from Barenblatt's method and based on the application of Ladyzhenskaya - De Giorgi iterative scheme and Vespri - Tedeev technique. From PDE point of view it assumed that solution exists in appropriate Sobolev type of space.