• Title/Summary/Keyword: genetic algorithm,

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Application of Levenberg Marquardt Method for Calibration of Unsteady Friction Model for a Pipeline System (관수로 부정류 마찰항 보정을 위한 Levenberg Marquardt 방법의 적용연구)

  • Park, Jo Eun;Kim, Sang Hyun
    • Journal of Korea Water Resources Association
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    • v.46 no.4
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    • pp.389-400
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    • 2013
  • In this study, a conventional pipeline unsteady friction model has been integrated into Levenberg Marquardt method to calibrate friction coefficient in a pipeline system. The method of characteristics has been employed as the modeling platform for the frequency dependant model of unsteady friction. In order to obtain Hessian and Jacobian matrix for optimization, the direct differentiation of pressure to friction factor was calculated and sensitivities to friction for heads and discharges were formulated for implementation to the integration constant in the characteristic method. Using a hypothetical simple pipeline system, time series of pressure, introduced by a sudden valve closure, were obtained for various Reynolds numbers. Convergency in fiction factors were evaluated both in steady and unsteady friction models. The comparison of calibration performance between the proposed method and genetic algorithm indicates that faster and stabler behaviour of Levenberg Marquardt method than those of evolutionary calibration.

Prediction of Local Scour Around Bridge Piers Using GEP Model (GEP 모형을 이용한 교각주위 국부세굴 예측)

  • Kim, Taejoon;Choi, Byungwoong;Choi, Sung-Uk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.6
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    • pp.1779-1786
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    • 2014
  • Artificial Intelligence-based techniques have been applied to problems where mathematical relations can not be presented due to complicatedness of the physical process. A representative example in hydraulics is the local scour around bridge piers. This study presents a GEP model for predicting the local scour around bridge piers. The model is trained by 64 laboratory data to build the regression equation, and the constructed model is verified against 33 laboratory data. Comparisons between the models with dimensional and normalized variables reveals that the GEP model with dimensional variables predicts better. The proposed model is now applied to two field datasets. It is found that the MAPE of the scour depths predicted by the GEP model increases compared with the predictions of local scours in laboratory scale. In addition, the model performance increases significantly when the model is trained by the field dataset rather than the laboratory dataset. The findings suggest that apart from the ANN model, GEP model is a sound and reliable model for predicting local scour depth.

Design of a Double-Faced Window Printed Antenna for Aircraft Applications (항공기용 양면 인쇄형 글래스 안테나 설계)

  • Byun, Gang-Il;Han, Wone-Keun;Choo, Ho-Sung
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.2
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    • pp.131-139
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    • 2011
  • In this paper, we propose a double-faced window printed antenna for aircraft applications. The proposed antenna structure consists of a feeding line and a multi-loop radiator located on different sides of the window to use the limited given-area effectively. The proposed antenna is optimized by the genetic algorithm in conjunction with the FEKO EM simulator. The optimized antenna is built and installed on a 1/10 sized KUH-Surion mock-up and antenna performances such as the reflection coefficient and the radiation patterns are measured. The optimized antenna shows a half power matching bandwidth of about 33 % at 60 MHz and an average bore-sight gain of about -3.49 dBi. To verify the reception capability of the optimized antenna, we simulated the received power according to a flight scenario. The result confirms that the optimized antenna shows a minimum received power level above -60 dBm at a range of 200 km, which is similar to the pole antenna that is currently used as a FM voice antenna for KUH-Surion.

The Correctness Comparison of MCIH Model and WMLF/GI Model for the Individual Haplotyping Reconstruction (일배체형 재조합을 위한 MCIH 모델과 WMLF/GI 모델의 정확도 비교)

  • Jeong, In-Seon;Kang, Seung-Ho;Lim, Hyeong-Seok
    • The KIPS Transactions:PartB
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    • v.16B no.2
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    • pp.157-161
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    • 2009
  • Minimum Letter Flips(MLF) and Weighted Minimum Letter Flips(WMLF) can perform the haplotype reconstruction more accurately from SNP fragments when they have many errors and gaps by introducing the related genotype information. And it is known that WMLF is more accurate in haplotype reconstruction than those based on the MLF. In the paper, we analyze two models under the conditions that the different rates of homozygous site in the genotype information and the different confidence levels according to the sequencing quality. We compare the performance of the two models using neural network and genetic algorithm. If the rate of homozygous site is high and sequencing quality is good, the results of experiments indicate that WMLF/GI has higher accuracy of haplotype reconstruction than that of the MCIH especially when the error rate and gap rate of SNP fragments are high.

A Study on the Development of the Acoustic Absorption Well of the Cruise Yacht (크루즈요트의 기관실 소음 차단용 차음벽 개발에 관한 연구)

  • Yu, Young-Hun;Yi, Jong-Keun
    • Proceedings of KOSOMES biannual meeting
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    • 2007.05a
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    • pp.109-113
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    • 2007
  • Yacht have an high powered main engine relatively light hull, so the noise generated from the engine have a bad influence upon the crew and passenger. Recently, cruise yacht is made an attempt by domestic production skill, however the insulation skill of the noise made by the main engine is not satisfy the real purchasing power of the buyer. Like this, yacht cabin's noise level is becoming the barometer to decide the purchase. the method to insufficient. However, if we use the skill of the monitoring equipment and the genetic algorithm system, the circumference of the main engine can be enclosed by an high quality absorbtion wall and the noise levels of the cabins are improved. In this study, the sound absorbtion barrier is experimentally researched by change the volume and the length of the neck for the Helmholtz resonator as the resonator can absorb the noise effectively.

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Hybrid ANN-based techniques in predicting cohesion of sandy-soil combined with fiber

  • Armaghani, Danial Jahed;Mirzaei, Fatemeh;Shariati, Mahdi;Trung, Nguyen Thoi;Shariati, Morteza;Trnavac, Dragana
    • Geomechanics and Engineering
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    • v.20 no.3
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    • pp.191-205
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    • 2020
  • Soil shear strength parameters play a remarkable role in designing geotechnical structures such as retaining wall and dam. This study puts an effort to propose two accurate and practical predictive models of soil shear strength parameters via hybrid artificial neural network (ANN)-based models namely genetic algorithm (GA)-ANN and particle swarm optimization (PSO)-ANN. To reach the aim of this study, a series of consolidated undrained Triaxial tests were conducted to survey inherent strength increase due to addition of polypropylene fibers to sandy soil. Fiber material with different lengths and percentages were considered to be mixed with sandy soil to evaluate cohesion (as one of shear strength parameter) values. The obtained results from laboratory tests showed that fiber percentage, fiber length, deviator stress and pore water pressure have a significant impact on cohesion values and due to that, these parameters were selected as model inputs. Many GA-ANN and PSO-ANN models were constructed based on the most effective parameters of these models. Based on the simulation results and the computed indices' values, it is observed that the developed GA-ANN model with training and testing coefficient of determination values of 0.957 and 0.950, respectively, performs better than the proposed PSO-ANN model giving coefficient of determination values of 0.938 and 0.943 for training and testing sets, respectively. Therefore, GA-ANN can provide a new applicable model to effectively predict cohesion of fiber-reinforced sandy soil.

Analytical evaluation and experimental validation of energy harvesting using low-frequency band of piezoelectric bimorph actuator

  • Mishra, Kaushik;Panda, Subrata K.;Kumar, Vikash;Dewangan, Hukum Chand
    • Smart Structures and Systems
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    • v.26 no.3
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    • pp.391-401
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    • 2020
  • The present article reports the feasibility of the electrical energy generation from ambient low-frequency vibration using a piezoelectric material mounted on a bimorph cantilever beam actuator. A corresponding higher-order analytical model is developed using MATLAB in conjunction with finite element method under low-frequency with both damped and undamped conditions. An alternate model is also developed to check the material and dimensional viability of both piezoelectric materials (mainly focussed to PVDF and PZT) and the base material. Also, Genetic Algorithm is implemented to find the optimum dimensions which can produce the higher values of voltage at low-frequency frequencies (≤ 100 Hz). The delamination constraints are employed to avoid inter-laminar stresses and to increase the fracture toughness. The delamination has been done using a Teflon sheet sandwiched in between base plates and the piezo material is stuck to the base plate using adhesives. The analytical model is tested for both homogenous and isotropic material characteristics of the base material and extended to investigate the effect of the different geometrical parameters (base plate dimensions, piezo layer dimensions and placement, delamination thickness and placement, excitation frequency) on the model responses of the bimorph cantilever beam. It has been observed that when the base material characteristics are homogenous, the efficiency of the model remains higher when compared to the condition when it is of isotropic material. The necessary convergence behaviour of the current numerical model has been established and checked for the accuracy by comparing with available published results. Finally, using the results obtained from the model, a prototype is fabricated for the experimental validation via a suitable circuit considering Glass fibre and Aluminium as the bimorph material.

Shape Optimization of High Power Centrifugal Compressor Using Multi-Objective Optimal Method (다목적 최적화 기법을 이용한 고출력 원심압축기 형상 최적설계)

  • Kang, Hyun Su;Lee, Jeong Min;Kim, Youn Jea
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.39 no.5
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    • pp.435-441
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    • 2015
  • In this study, a method for optimal design of impeller and diffuser blades in the centrifugal compressor using response surface method (RSM) and multi-objective genetic algorithm (MOGA) was evaluated. A numerical simulation was conducted using ANSYS CFX with various values of impeller and diffuser parameters, which consist of leading edge (LE) angle, trailing edge (TE) angle, and blade thickness. Each of the parameters was divided into three levels. A total of 45 design points were planned using central composite design (CCD), which is one of the design of experiment (DOE) techniques. Response surfaces that were generated on the basis of the results of DOE were used to determine the optimal shape of impeller and diffuser blade. The entire process of optimization was conducted using ANSYS Design Xplorer (DX). Through the optimization, isentropic efficiency and pressure recovery coefficient, which are the main performance parameters of the centrifugal compressor, were increased by 0.3 and 5, respectively.

Learning of Fuzzy Rules Using Fuzzy Classifier System (퍼지 분류자 시스템을 이용한 퍼지 규칙의 학습)

  • Jeong, Chi-Seon;Sim, Gwi-Bo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.5
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    • pp.1-10
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    • 2000
  • In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

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Optimum Design of Radial Gate (회전식 수문의 최적 설계)

  • 권영두;권순범;박창규;윤영중
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.14 no.3
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    • pp.267-276
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    • 2001
  • On the basis of structural analysis of the radial gate(that is, Tainter gate), this paper focuses on the optimization of the moment distribution according to the location of the arm of the radial gate. In spite of its importance from economical view point, we could hardly find the study on the optimum design of radial gate. Accordingly, the present study identifies the optimum section modulus for a radial arm along with the optimum position for 2 of 3 radial arms with a convex cylindrical skin plate relative to a given radius of the skin plate curvature, pivot point, water depth, ice pressure, etc. These optimum measurements are then compared with previously constructed radial gates. The results indicate that the optimum section modulus vague for a radial arm was appreciably smaller than the previously constructed examples.

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