• Title/Summary/Keyword: quadratic convergence

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Correlation Between Meteorological Factors and Hospital Power Consumption (기상요인과 병원 전력사용량의 상관관계)

  • Kim, Jang-Mook;Cho, Jung-Hwan;Kim, Byul
    • Journal of Digital Convergence
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    • v.14 no.6
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    • pp.457-466
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    • 2016
  • To achieve eco-friendly hospitals it is necessary to empirically verify the effect of meteorological factors on the power consumption of the hospital. Using daily meteorological big data from 2009 to 2013, we studied the weather conditions impact to power consumption and analyzed the patterns of power consumption of two hospitals. R analysis revealed that temperature among the meteorological factors had the greatest impact on the hospital power consumption, and was a significant factor regardless of hospital size. The pattern of hospital power consumption differed considerably depending on the hospital size. The larger hospital had a linear pattern of power consumption and the smaller hospital had a quadratic nonlinear pattern. A typical pattern of increasing power consumption during a hot summer and a cold winter was evident for both hospitals. The results of this study suggest that a hospital's functional specificity and meteorological factors should be considered to improve energy savings and eco-friendly building.

Genetically Optimized Neurofuzzy Networks: Analysis and Design (진화론적 최적 뉴로퍼지 네트워크: 해석과 설계)

  • 박병준;김현기;오성권
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.8
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    • pp.561-570
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    • 2004
  • In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

Propulsion System Design and Optimization for Ground Based Interceptor using Genetic Algorithm

  • Qasim, Zeeshan;Dong, Yunfeng;Nisar, Khurram
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.330-339
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    • 2008
  • Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

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Semi-active seismic control of a 9-story benchmark building using adaptive neural-fuzzy inference system and fuzzy cooperative coevolution

  • Bozorgvar, Masoud;Zahrai, Seyed Mehdi
    • Smart Structures and Systems
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    • v.23 no.1
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    • pp.1-14
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    • 2019
  • Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.

Design of 10bit gamma line system with small size of gate count and 4bit error(LSB) to implement non-linear gamma curve (비선형 감마 커브 구현을 위한 작은 크기와 4bit(LSB) 오차를 가진 10비트 감마 라인 시스템의 설계)

  • Jang, Won-Woo;Kim, Hyun-Sik;Lee, Sung-Mok;Kim, In-Kyu;Kang, Bong-Soon
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2005.11a
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    • pp.353-356
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    • 2005
  • In this paper, the proposed $gamma({\gamma})$ line system is developed for reducing the error between non-linear gamma curve produced by a formula and result produced by hardware implementation. The proposed algorithm and system is based on the specific gamma value 2.2, namely the formula is represented by {0,1}$^{2.2}$ and the bit width of input and out data is 10bit. In order to reduce the error, the system is using least squares polynomial of the numerical method which is calculating the best fitting polynomial through a set of points. The proposed gamma line is consisting of nine kinds of quadratic equations, each with their own overlap sections to get more precise. Based on the algorithm verified by $MATLAB^{TM}$ 7.0, the proposed system is implemented by using Verilog-HDL. The proposed system has 2 clock latency; 1 result per clock. The error range (LSB) is -4 and +3. Its standard deviation is 1.287956238. The total gate count of system is 2,083 gates and the maximum timing is 15.56[ns].

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A Comparison of the Effects of Optimization Learning Rates using a Modified Learning Process for Generalized Neural Network (일반화 신경망의 개선된 학습 과정을 위한 최적화 신경망 학습률들의 효율성 비교)

  • Yoon, Yeochang;Lee, Sungduck
    • The Korean Journal of Applied Statistics
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    • v.26 no.5
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    • pp.847-856
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    • 2013
  • We propose a modified learning process for generalized neural network using a learning algorithm by Liu et al. (2001). We consider the effect of initial weights, training results and learning errors using a modified learning process. We employ an incremental training procedure where training patterns are learned systematically. Our algorithm starts with a single training pattern and a single hidden layer neuron. During the course of neural network training, we try to escape from the local minimum by using a weight scaling technique. We allow the network to grow by adding a hidden layer neuron only after several consecutive failed attempts to escape from a local minimum. Our optimization procedure tends to make the network reach the error tolerance with no or little training after the addition of a hidden layer neuron. Simulation results with suitable initial weights indicate that the present constructive algorithm can obtain neural networks very close to minimal structures and that convergence to a solution in neural network training can be guaranteed. We tested these algorithms extensively with small training sets.

Three-Dimensional Vibration Analysis of Deep, Nonlinearly Tapered Rods and Beams with Circular Cross-Section (원형단면의 깊은 비선형 테이퍼 봉과 보의 3차원 진동해석)

  • 심현주;강재훈
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.16 no.3
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    • pp.251-260
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    • 2003
  • A three dimensional (3-D) method of analysis is presented for determining the free vibration frequencies and mode shapes of deep, tapered rods and beams with circular cross section. Unlike conventional rod and beam theories, which are mathematically one-dimensional (1-D), the present method is based upon the 3-D dynamic equations of elasticity. Displacement components u/sup r/, u/sub θ/ and u/sub z/, in the radial, circumferential, and axial directions, respectively, are taken to be sinusoidal in time, periodic in , and algebraic polynomials in the r and z directions. Potential (strain) and kinetic energies of the rods and beams are formulated, the Ritz method is used to solve the eigenvalue problem, thus yielding upper bound values of the frequencies by minimizing the frequencies. As the degree of the polynomials is increased, frequencies converge to the exact values. Convergence to four-digit exactitude is demonstrated for the first five frequencies of the rods and beams. Novel numerical results are tabulated for nine different tapered rods and beams with linear, quadratic, and cubic variations of radial thickness in the axial direction using the 3D theory. Comparisons are also made with results for linearly tapered beams from 1-D classical Euler-Bernoulli beam theory.

Three Dimensional Vibration Analysis of Thick, Circular and Annular Plates with Nonlinear Thickness Variation (비선형 두께 변분을 갖는 두꺼운 원형판과 환형판의 3차원적 진동해석)

  • 장승환;심현주;강재훈
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.17 no.2
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    • pp.119-129
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    • 2004
  • A three dimensional (3D) method of analysis is presented for determining the free vibration frequencies and mode shapes of thick, circular and annular plates with nonlinear thickness variation along the radial direction. Unlike conventional plate theories, which are mathematically two dimensional (2D), the present method is based upon the 3D dynamic equations of elasticity. Displacement components u/sub s/, u/sub z/, and u/sub θ/ in the radial, thickness, and circumferential directions, respectively, are taken to be sinusoidal in time, periodic in θ, and algebraic polynomials in the s and z directions. Potential (strain) and kinetic energies of the plates are formulated, and the Ritz method is used to solve the eigenvalue problem thus yielding upper bound values of the frequencies by minimizing the frequencies. As the degree of the polynomials is increased, frequencies converge to the exact values. Convergence to four digit exactitude is demonstrated for the first five frequencies of the plates. Numerical results we presented for completely free, annular and circular plates with uniform linear, and quadratic variations in thickness. Comparisons are also made between results obtained from the present 3D and previously published thin plate (2D) data.

A Study on Teaching the Method of Lagrange Multipliers in the Era of Digital Transformation (라그랑주 승수법의 교수·학습에 대한 소고: 라그랑주 승수법을 활용한 주성분 분석 사례)

  • Lee, Sang-Gu;Nam, Yun;Lee, Jae Hwa
    • Communications of Mathematical Education
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    • v.37 no.1
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    • pp.65-84
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    • 2023
  • The method of Lagrange multipliers, one of the most fundamental algorithms for solving equality constrained optimization problems, has been widely used in basic mathematics for artificial intelligence (AI), linear algebra, optimization theory, and control theory. This method is an important tool that connects calculus and linear algebra. It is actively used in artificial intelligence algorithms including principal component analysis (PCA). Therefore, it is desired that instructors motivate students who first encounter this method in college calculus. In this paper, we provide an integrated perspective for instructors to teach the method of Lagrange multipliers effectively. First, we provide visualization materials and Python-based code, helping to understand the principle of this method. Second, we give a full explanation on the relation between Lagrange multiplier and eigenvalues of a matrix. Third, we give the proof of the first-order optimality condition, which is a fundamental of the method of Lagrange multipliers, and briefly introduce the generalized version of it in optimization. Finally, we give an example of PCA analysis on a real data. These materials can be utilized in class for teaching of the method of Lagrange multipliers.

Grand Circulation Process of Beach Cusp and its Seasonal Variation at the Mang-Bang Beach from the Perspective of Trapped Mode Edge Waves as the Driving Mechanism of Beach Cusp Formation (맹방해안에서 관측되는 Beach Cusp의 일 년에 걸친 대순환 과정과 계절별 특성 - 여러 생성기작 중 포획모드 Edge Waves를 중심으로)

  • Cho, Yong Jun
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.31 no.5
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    • pp.265-277
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    • 2019
  • Using the measured data of waves and shore-line, we reviewed the grand circulation process and seasonal variation of beach cusp at the Mang-Bang beach from the perspective of trapped mode Edge waves known as the driving mechanism of beach cusp. In order to track the temporal and spatial variation trends of beach cusp, we quantify the beach cusp in terms of its wave length and amplitude detected by threshold crossing method. In doing so, we also utilize the spectral analysis method and its associated spectral mean sand wave number. From repeated period of convergence and ensuing splitting of sand waves detected from the yearly time series of spectral mean sand wave number of beach cusp, it is shown that the grand circulation process of beach cusp at Mang-Bang beach are occurring twice from 2017. 4. 26 to 2018. 4. 20. For the case of beach area, it increased by $14,142m^2$ during this period, and the shore-line advanced by 18 m at the northen and southern parts of the Mang-Bang beach whereas the shore-line advanced by 2.4 m at the central parts of Mang-Bang beach. It is also worthy of note that the beach area rapidly increased by $30,345m^2$ from 2017.11.26. to 2017.12.22. which can be attributed to the nature of coming waves. During this period, mild swells of long period were prevailing, and their angle of attack were next to zero. These characteristics of waves imply that the main transport mode of sediment would be the cross-shore. Considering the facts that self-healing capacity of natural beaches is realized via the cross-shore sediment once temporarily eroded. it can be easily deduced that the sediment carried by the boundary layer streaming toward the shore under mild swells which normally incident toward the Mang-Bang beach makes the beach area rapidly increase from 2017.11.26. to 2017.12.22.