• Title/Summary/Keyword: genetic process

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Hierarchical Height Reconstruction of Object from Shading Using Genetic Algorithm (유전자 알고리즘을 이용한 영상으로부터의 물체높이의 계층적 재구성)

  • Ahn, Eun-Young;Cho, Hyung-Je
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.12
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    • pp.3703-3709
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    • 1999
  • We propose a new approach to reconstruct the surface shape of an object from a shaded image. We use genetic algorithm instead of gradient descent algorithm which is apt to take to local minima and also proposes genetic representation and suitable genetic operators for manipulating 2-D image. And for more effective execution, we suggest hierarchical process to reconstruct minutely the surface of an object after coarse and global reconstruction. A modified Lambertian illumination model including the distance factor was herein adopted to get more reasonable result and an experiment was performed with synthesized and real images to demonstrate the devised method, of which results show the usefulness of our method.

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Optimization of Engine Mount Using an Enhanced Genetic Algorithm (향상된 유전알고리듬을 이용한 유체마운트의 최적화)

  • Ahn, Young-Kong;Kim, Young-Chan;Yang, Bo-Suk
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.12
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    • pp.935-942
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    • 2002
  • When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth. Therefore. an automatic optimal technique is needed to optimize the performance of the fluid mount. In this study. the enhanced genetic algorithm (EGA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The EGA is modified genetic algorithm to search global and local optimal solutions of multi-modal function optimization. Furthermore. to reduce the searching time as compare to conventional genetic algorithm and Increase the precision of the solutions, the modified simplex method is combined with the algorithm. The results show that the performance of the optimized mount by using the hybrid algorithm is better than that of the conventional fluid mount.

Efficient alternative route path-search techniques to the damaged path using genetic algorithm processing (유전알고리즘의 연산처리를 통한 손상된 경로의 효율적인 대체경로 탐색기법)

  • Ji, Hong-il;Moon, Seok-hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.729-731
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    • 2016
  • The efficiency of genetic algorithm may be improved, as genetic generation increases. However, a number of algorithms are needed until desired results are obtained. In addition, if Hoc unit increases when linked to a network, there may be a need to compare with all the cases, which would result in many algorithms at a time, and if a single process deals with such algorithms, the efficiency will decrease. Therefore, efficiency of overall network will be decreased in the end. Proposal algorithm in this thesis introduced cells, units of router group, for distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm.

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Genetic Diagnosis of Inherited Metabolic Disorders using Next-Generation Sequencing (차세대 염기서열분석을 이용한 유전성 대사질환의 유전진단)

  • Chang-Seok Ki
    • Journal of The Korean Society of Inherited Metabolic disease
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    • v.23 no.2
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    • pp.1-7
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    • 2023
  • Inherited metabolic disorders (IMD) are a group of disorders involving various metabolic pathways. Genetic diagnosis of IMD has been challenging because of extremely heterogeneous nature and extensive laboratory and/or phenotype overlap. Conventional genetic diagnosis was a gene-by-gene approach that needs a priori information on the causative genes that might underlie the IMD. Recent implementation of next-generation sequencing (NGS) technologies has changed the process of genetic diagnosis from a gene-by-gene approach to simultaneous analysis of targeted genes possibly associated with the IMD using gene panels or using whole exome/genome sequencing (WES/WGS) covering entire human genes. Clinical NGS tests can be a cost-effective approach for the rapid diagnosis of IMD with genetic heterogeneity and are becoming standard diagnostic procedures.

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Analysis of Dynamic Model and Design of Optimized Fuzzy PID Controller for Constant Pressure Control (정압제어를 위한 동적모델 해석 및 최적 퍼지 PID 제어기설계)

  • Oh, Sung-Kwun;Cho, Se-Hee;Lee, Seung-Joo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.2
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    • pp.303-311
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    • 2012
  • In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

Supply Chain Planning in Multiplant Network (다중플랜트 네트워크에서의 공급사슬계획)

  • Jeong Jae-Hyeok;Mun Chi-Ung;Kim Jong-Su
    • Proceedings of the Society of Korea Industrial and System Engineering Conference
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    • 2002.05a
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    • pp.203-208
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    • 2002
  • In case of the problems with multiple plants, alternative operation sequence, alternative machine, setup time, and transportation time between plants, we need a robust methodology for the integration of process planning and scheduling in supply chain. The objective of this model is to minimize the tardiness and to maximize the resource utilization. So, we propose a multi-objective model with limited-capacity constraint. To solve this model, we develope an efficient and flexible model using adaptive genetic algorithm(AGA), compared to traditional genetic algorithm(TGA)

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A Rapid Packing Algorithm for SLS Rapid Prototyping System (SLS 쾌속조형장치를 위한 고속 패킹 알고리즘 개발)

  • 김부영;김호찬;최홍태;이석희
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.05a
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    • pp.561-564
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    • 2002
  • With Rapid Prototyping system, the efficient packing in a fixed work volume reduces build time when multiple parts are built in a process. In this paper, an efficient and rapid packing algorithm is developed for SLS system that has cylindrical workspace. A genetic algorithm is implemented to place as many part as possible in a vat. For fast computation, a collision detection algorithm "k-DOPs Tree" is implemented.

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A Study on the Optimal Signal Timing for Area Traffic Control (지역 교통망 관리를 위한 최적 신호순서에 관한 연구)

    • Journal of the Korean Operations Research and Management Science Society
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    • v.24 no.2
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    • pp.69-80
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    • 1999
  • A genetic algorithm to determine the optimal signal sequence and double cycle pattern is described. The signal sequence and double cycle pattern are used as the input for TRANSYT to find optimal signal timing at each junction in the area traffic networks, In the genetic process, the partially matched crossover and simple crossover operators are used for evolution of signal sequence and double cycle pattern respectively. A special conversion algorithm is devised to convert the signal sequence into the link-stage assignment for TRANSYT. Results from tests using data from an area traffic network in Leicester region R are given.

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A Genetic Algorithm for the Ship Scheduling Problem (선박운항일정계획 문제의 유전해법)

  • 이희용;김시화
    • Journal of the Korean Institute of Navigation
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    • v.24 no.5
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    • pp.361-371
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    • 2000
  • This paper treats a genetic algorithm for ship scheduling problem in set packing formulation. We newly devised a partition based representation of solution and compose initial population using a domain knowledge of problem which results in saving calculation cost. We established replacement strategy which makes each individual not to degenerate during evolutionary process and applied adaptive mutate operator to improve feasibility of individual. If offspring is feasible then an improve operator is applied to increase objective value without loss of feasibility. A computational experiment was carried out with real data and showed a useful result for a large size real world problem.

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