• Title/Summary/Keyword: optimized genetic algorithm

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Design of Low Frequency Flat Speaker by Piezofilm (Piezofilm 을 이용한 저주파 평면 스피커의 설계)

  • Hwang, Joon-Seok;Lee, Sung;Kim, Seung-Jo
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2000.11a
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    • pp.191-194
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    • 2000
  • In this study, experimental verification of performance of flat speaker has been conducted. The piezofilm (PVDF) actuator has been designed to prevent the distortion of sound and make the frequency response of radiated sound flat. The electrode pattern of piezofilm actuator is optimized to satisfy the design objective. The formulation of design method is based on the coupled finite element and boundary element method and electrode pattern is optimized by genetic algorithm. The flat speaker with optimized piezofilm actuator has been manufactured. The sound pressure level at the distance of 50cm is measured using microphone and compared with the result of numerical simulation.

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An optimized mesh partitioning in FEM based on element search technique

  • Shiralinezhad, V.;Moslemi, H.
    • Computers and Concrete
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    • v.23 no.5
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    • pp.311-320
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    • 2019
  • The substructuring technique is one of the efficient methods for reducing computational effort and memory usage in the finite element method, especially in large-scale structures. Proper mesh partitioning plays a key role in the efficiency of the technique. In this study, new algorithms are proposed for mesh partitioning based on an element search technique. The computational cost function is optimized by aligning each element of the structure to a proper substructure. The genetic algorithm is employed to minimize the boundary nodes of the substructures. Since the boundary nodes have a vital performance on the mesh partitioning, different strategies are proposed for the few number of substructures and higher number ones. The mesh partitioning is optimized considering both computational and memory requirements. The efficiency and robustness of the proposed algorithms is demonstrated in numerous examples for different size of substructures.

Acceleration Optimization of a Dynamic Structure Using a Genetic Algorithm (유전자 알고리즘을 이용한 동적 구조물의 가속도 최적화)

  • 정원지;박창권;홍대선
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.2
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    • pp.25-32
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    • 2004
  • This paper presents a new optimization technique of acceleration curve for dynamic structure's movement in which high speed and low vibration are desirable. This technique is based on a genetic algerian with a penalty function for acceleration optimization under the assumption that an initial profile of acceleration curves constitutes the first generation of the genetic algorithm. Especially the penalty function consists of the violation of constraints and the number of violated constraints. The optimized acceleration of the crane through the genetic algorithm and commercial dynamic analysis software has shown to have accurate movement and low vibration compared to the conventional accelerations with jerk discontinuity.

Tap-length Optimization of Decision Feedback Equalizer Using Genetic Algorithm (유전자 알고리즘을 이용한 결정 궤환 등화기의 탭 길이 최적화)

  • Son, Ji-hong;Kim, Ki-man
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.8
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    • pp.1765-1772
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    • 2015
  • In the underwater acoustic communication channels, multipath reflection become the cause of obstacle. Generally, equalizer has been applied to overcome these problems. In this paper, the method was proposed to optimize tap-length of decision feedback equalizer using genetic algorithm. After inputting feed-forward filter length and feed-back filter length as genetic information of the genetic algorithm, it optimize tap-length using BER(bit error rate) calculation in accordance with object function. The object function consist of decision feedback equalizer and BER calculation. For the purpose of BER calculation in the object function, the method was proposed to optimize the tap-length of decision feedback equalizer with genetic algorithm using preamble signals. As a result of experiments, the optimized BER is 0.0355 for signals which were received through a 25m receiver and which were applied to calculate BER merely using preamble signals in object function. When all data were used to calculate BER in object function, the optimized BER is 0.0215.

Optimization of Heavy-Duty Diesel Engine Operating Parameters Using Micro-Genetic Algorithms (유전알고리즘을 이용한 대형 디젤 엔진 운전 조건 최적화)

  • Kim, Man-Shik;Liechty, Mike P.;Reitz, Rolf D.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.13 no.2
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    • pp.101-107
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    • 2005
  • In this paper, optimized operating parameters were found using multi-dimensional engine simulation software (KIVA-3V) and micro-genetic algorithm for heavy duty diesel engine. The engine operating condition considered was at 1,737 rev/min and 57 % load. Engine simulation model was validated using an engine equipped with a high pressure electronic unit injector (HEUI) system. Three important parameters were used for the optimization - boost pressure, EGR rate and start of injection timing. Numerical optimization identified HCCI-like combustion characteristics showing significant improvements for the soot and $NO_X$ emissions. The optimized soot and $NO_X$ emissions were reduced to 0.005 g/kW-hr and 1.33 g/kW-hr, respectively. Moreover, the optimum results met EPA 2007 mandates at the operating point considered.

Fuzzy Modeling Schemes Using Messy Genetic Algorithms (메시 유전알고리듬을 이용한 퍼지모델링 방법)

  • Kwon, Oh-Kook;Chang, Wook;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.519-521
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    • 1998
  • Fuzzy inference systems have found many applications in recent years. The fuzzy inference system design procedure is related to an expert or a skilled human operator in many fields. Various attempts have been made in optimizing its structure using genetic algorithm automated designs. This paper presents a new approach to structurally optimized designs of FNN models. The messy genetic algorithm is used to obtain structurally optimized fuzzy neural network models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the problem of a time series estimation.

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Parameter Optimization of Controllers for Forward Converters Using Genetic Algorithms (유전자 알고리즘을 이용한 포워드 컨버터 제어기의 파라메터 최적화)

  • Choi, Young-Kiu;Woo, Dong-Young;Park, Jin-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.177-182
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    • 2010
  • The forward convener is one of power supplies used widely. This paper presents parameter tuning methods to obtain optimal circuit element values for the forward converter to minimize the output voltage variation under various load changing environments. The conventional method using the concept of the phase margin is extended to have optimal phase margin that gives slightly improved performance in the output voltage response. For this, the phase margin becomes the tuning parameter and is optimized with the genetic algorithm. Next, the circuit element values are directly chosen as the tuning parameters and also optimized using the genetic algorithm to have very improved performance in the output voltage control of the forward converter.

Indoor Positioning Technique applying new RSSI Correction method optimized by Genetic Algorithm

  • Do, Van An;Hong, Ic-Pyo
    • Journal of IKEEE
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    • v.26 no.2
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    • pp.186-195
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    • 2022
  • In this paper, we propose a new algorithm to improve the accuracy of indoor positioning techniques using Wi-Fi access points as beacon nodes. The proposed algorithm is based on the Weighted Centroid algorithm, a popular method widely used for indoor positioning, however, it improves some disadvantages of the Weighted Centroid method and also for other kinds of indoor positioning methods, by using the received signal strength correction method and genetic algorithm to prevent the signal strength fluctuation phenomenon, which is caused by the complex propagation environment. To validate the performance of the proposed algorithm, we conducted experiments in a complex indoor environment, and collect a list of Wi-Fi signal strength data from several access points around the standing user location. By utilizing this kind of algorithm, we can obtain a high accuracy positioning system, which can be used in any building environment with an available Wi-Fi access point setup as a beacon node.

Estimation of fundamental period of reinforced concrete shear wall buildings using self organization feature map

  • Nikoo, Mehdi;Hadzima-Nyarko, Marijana;Khademi, Faezehossadat;Mohasseb, Sassan
    • Structural Engineering and Mechanics
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    • v.63 no.2
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    • pp.237-249
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    • 2017
  • The Self-Organization Feature Map as an unsupervised network is very widely used these days in engineering science. The applied network in this paper is the Self Organization Feature Map with constant weights which includes Kohonen Network. In this research, Reinforced Concrete Shear Wall buildings with different stories and heights are analyzed and a database consisting of measured fundamental periods and characteristics of 78 RC SW buildings is created. The input parameters of these buildings include number of stories, height, length, width, whereas the output parameter is the fundamental period. In addition, using Genetic Algorithm, the structure of the Self-Organization Feature Map algorithm is optimized with respect to the numbers of layers, numbers of nodes in hidden layers, type of transfer function and learning. Evaluation of the SOFM model was performed by comparing the obtained values to the measured values and values calculated by expressions given in building codes. Results show that the Self-Organization Feature Map, which is optimized by using Genetic Algorithm, has a higher capacity, flexibility and accuracy in predicting the fundamental period.

Optimization of Satellite Structures by Simulated Annealing (시뮬레이티드 어닐링에 의한 인공위성 구조체 최적화)

  • Im Jongbin;Ji Sang-Hyun;Park Jungsun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.2 s.233
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    • pp.262-269
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    • 2005
  • Optimization of a satellite structure under severe space launching environments is performed considering various design constraints. Simulate annealing, one of combinatorial optimization techniques, is used to optimize the satellite. The optimization results by the simulated annealing are compared to those by the method of modified feasible direction and genetic algorithm. Ten bar truss structure is optimized for feasibility study of the simulated annealing. Finally, the satellite structure is optimized by the simulated annealing algorithm under space environment. Weights of the satellite upper platform and propulsion module are minimized with consideration of several static and dynamic constraints. MSC/NASTRAN is used to find the static and dynamic responses. Simulated annealing has been programmed and integrated with the finite element analysis program for optimization. It is shown that the simulated annealing algorithm can be extended to the optimization of space structures.