• 제목/요약/키워드: Growth Algorithm

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Placement 확률 진화 알고리즘의 설계와 구현 (Design and Implementation of a Stochastic Evolution Algorithm for Placement)

  • 송호정;송기용
    • 융합신호처리학회논문지
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    • 제3권1호
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    • pp.87-92
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    • 2002
  • 배치(Placement)는 VLSI 회로의 physical design에서 중요한 단계로서 회로의 성능을 최대로 하기 위하여 회로 모듈의 집합을 배치시키는 문제이며, 배치 문제에서 최적의 해를 얻기 위해 클러스터 성장(cluster growth), 시뮬레이티드 어닐링(simulated annealing; SA), ILP(integer linear programming)등의 방식이 이용된다. 본 논문에서는 배치 문제에 대하여 확률 진화 알고리즘(stochastic evolution algorithm; StocE)을 이용한 해 공간 탐색(solution space search) 방식을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링 방식과 비교, 분석하였다.

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현대 건축 디자인에서의 생물학적 형태의 적용에 관한 연구 (A Study on the Application of Biomorphism on Contemporary Architectural Design)

  • 김원갑
    • 한국실내디자인학회논문집
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    • 제15권1호
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    • pp.30-38
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    • 2006
  • The new aspect of contemporary architectural design is the computer simulation of morphogenesis and evolution of the organic body. Morphogenesis and evolution is the kind of emergence that is the process of complex pattern formation from simpler rules in complex system. The development comprises the sequence of pattern formation, differentiation, morphogenesis, growth. This study analyzes the application methodology of various biomorphism in contemporary architecture. The methods of generative application by computation in architecture are self-organization, differentiation, growth algorithm via MoSS. And the methods of evolution by computation are genetic algorithm, multi-parameter in environments, phylogenetic cross-over, competing as natural selection, mutation+external constraints, generative algorithm+genetic algorithm via Genr8.

A Data Mining Algorithm to Gaining Customer Loyalty to Ports Based on OD Data for Improving Port Competitiveness

  • Lin, Qianfeng;Son, Jooyoung
    • 한국항해항만학회지
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    • 제44권5호
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    • pp.391-399
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    • 2020
  • Every port is competing for attracting loyal customers from other ports to achieve more profits stably. This paper proposes a data-mining scheme to facilitate this process. For resolving the problem, the OD (Origination-Destination) data are gathered from the AIS (Automatic Identification System) data. The OD data are clustered according to the arrival dates and ports. The FP-growth algorithm is applied to mine the frequent patterns of ships arriving at ports. Maintaining a loyal customer list for port updates and accuracy is critical in establishing its usefulness. These lists are critical as they can be used to provide suggestions for new products and services to loyal customers. Finally, based on the frequent patterns of the ships and the mode of arrival times, a formula proposed in this paper to derive shipping companies' loyalty to ports was applied. The case of Kaohsiung port was shown as an example of our algorithm, and the OD data of ships in 2017-2018 were processed. Using the results of our algorithm, other rival ports, such as Shanghai or Busan, may attract customers no longer loyal to Kaohsiung ports in the last two years and attract them as new loyal customers.

An Observation Supporting System for Predicting Citrus Fruit Production

  • Kang, Hee Joo;Yoo, Seung Tae;Yang, Young Jin
    • Agribusiness and Information Management
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    • 제7권1호
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    • pp.1-9
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    • 2015
  • The purpose of this study is to develop a growth prediction model that can predict growth and development information influencing the production of citrus fruits: the growth model algorithm that can predict floral leaf ratio, number of fruit sets, fruit width, and overweight depending on the main period of growth and development with consideration of the applied weather factors. Every year, large scale of manpower was mobilized to investigate the production of outdoor-grown citrus fruits, but it was limited to recycling the data without an observation supporting system to systemize the database. This study intends to create a systematical database based on the basic data obtained through the observation supporting system in application of an algorithm according to the accumulated long term data and prepare a base for its continuous improvement and development. The importance of the observed data is increasingly recognized every year, and the citrus fruit observation supporting system is important for utilizing an effective policy and decision making according to various applications and analysis results through an interconnection and an integration of the investigated statistical data. The citrus fruit is a representative crop having a great ripple effect in Jeju agriculture. An early prediction of the growth and development information influencing the production of citrus fruits may be helpful for decision making in supply and demand control of agricultural products.

인공씨감자 생육상태 모니터링을 위한 화상처리 알고리즘 개발에 관한 연구 (A Study of Vision Algorithm Development for Growth Monitoring of Potato Microtubers)

  • 최재완;정광조;임선종;최성락;정혁;남호원
    • Journal of Biosystems Engineering
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    • 제23권4호
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    • pp.373-380
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    • 1998
  • The contribution of this paper is to provide the methods for the production automation of potato microtuber using the vision process in growth monitoring. The first method deals with computation for the growth density in the primary growth process. The second method addresses cognition process to identify the number and the volume of potato microtuber in secondary growth process. The third is to decide whether potato microtubers are infected by a virus or bacteria in growth process. The computation for the growth density in the primary growth process uses the method of Labeling. The second and third methods use template matching based on color patterns. With the developed method using vision process, this experiment is capable of discriminating weekly growth-rate in primary growth process, 85% cognition rate in secondary process and identifying whether there are infections. Therefore, we conclude that our experimental results are capable of growth monitoring for mass production of potato microtubers.

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Crystallization of High Purity Ammonium Meta-Tungstate for production of Ultrapure Tungsten Metal

  • Choi, Cheong-Song
    • 한국결정성장학회:학술대회논문집
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    • 한국결정성장학회 1997년도 Proceedings of the 13th KACG Technical Meeting `97 Industrial Crystallization Symposium(ICS)-Doosan Resort, Chunchon, October 30-31, 1997
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    • pp.1-5
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    • 1997
  • The growth mechanism of AMT(Ammonium Meta-Tungstate) crystal was interpreted as two-step model. The contribution of the diffusion step increased with the increase of temperature, crystal size, and supersaturation. The crystal size distribution from a batch cooling crystallizer was predicted by the numerical solution of a mathematical model which uses the kinetics of nucleation and crystal growth. Temperature control of a batch crystallizer was studied using Learning control algorithm. The purity of AMT crystal producted in this investigation was above 99.99%.

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퍼지 전문가 제어 기법을 이용한 시설재배 자동화 소프트웨어의 구현 (Implementation of an Automation System Using Fuzzy Expertized Control Algorithm for the Cultivation in a Greenhouse)

  • 김승우
    • 컴퓨터교육학회논문지
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    • 제7권1호
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    • pp.67-77
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    • 2004
  • 본 논문에서는 시설내 작물재배 시스템의 완전자동화를 구현함에 동시에 자동 제어 방식 설계상에 존재하는 많은 문제들 때문에 실현하지 못했던 작물의 직접제어자동화를 구현하였다. 시설내 작물재배 자동제어 시스템은 제어대상에 따라서 세 가지로 구분될 수 있다. 시설외부로부터 기상 환경 등을 계측하여서 시설내 재배 제어에 응용하는 외부 환경 제어, 시설 내부 환경을 직접 계측하고 제어하는 내부 환경 제어, 작물의 성장에 직접 공급되는 배양액의 적절한 조성에 관련된 배양액 제어로 나눌 수 있다. 본 논문에서는 이 세 가지의 자동 제어시스템을 완전 실현하며, 배양액의 급액량을 제어함으로서 작물의 우량 성장을 자동적으로 조절할 수 있는 고난도 제어시스템을 설계하였다.

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최적 배치를 위한 유전자 알고리즘의 설계와 구현 (Design and Implementation of a Genetic Algorithm for Optimal Placement)

  • 송호정;이범근
    • 한국컴퓨터정보학회논문지
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    • 제7권3호
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    • pp.42-48
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    • 2002
  • 배치(Placement)는 VLSI 회로의 physical design에서 중요한 단계로서 회로의 성능을 최대로 하기 위하여 회로 모듈의 집합을 배치시키는 문제이며, 배치 문제에서 최적의 해를 얻기 위해 클러스터 성장(cluster growth), 시뮬레이티드 어닐링(simulated annealing; SA), ILP(integer linear programming)등의 방식이 이용된다. 본 논문에서는 배치 문제에 대하여 유전자 알고리즘(genetic algorithm; GA)을 이용한 해 공간 탐색(solution space search) 방식을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링 방식과 비교, 분석하였다.

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Optimization of Finite Element Retina by GA for Plant Growth Neuro Modeling

  • Murase, H.
    • Agricultural and Biosystems Engineering
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    • 제1권1호
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    • pp.22-29
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    • 2000
  • The development of bio-response feedback control system known as the speaking plant approach has been a challenging task for plant production engineers and scientists. In order to achieve the aim of developing such a bio-response feedback control system, the primary concern should be to develop a practical non-invasive technique for monitoring plant growth. Those who are skilled in raising plants can sense whether their plants are under adequate water conditions or not, for example, by merely observing minor color and tone changes before the plants wilt. Consequently, using machine vision, it may be possible to recognize changes in indices that describe plant conditions based on the appearance of growing plants. The interpretation of image information of plants may be based on image features extracted from the original pictorial image. In this study, the performance of a finite element retina was optimized by a genetic algorithm. The optimized finite element retina was evaluated based on the performance of neural plant growth monitor that requires input data given by the finite element retina.

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Odoo Data Mining Module Using Market Basket Analysis

  • Yulia, Yulia;Budhi, Gregorius Satia;Hendratha, Stefani Natalia
    • Journal of information and communication convergence engineering
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    • 제16권1호
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    • pp.52-59
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    • 2018
  • Odoo is an enterprise resource planning information system providing modules to support the basic business function in companies. This research will look into the development of an additional module at Odoo. This module is a data mining module using Market Basket Analysis (MBA) using FP-Growth algorithm in managing OLTP of sales transaction to be useful information for users to improve the analysis of company business strategy. The FP-Growth algorithm used in the application was able to produce multidimensional association rules. The company will know more about their sales and customers' buying habits. Performing sales trend analysis will give a valuable insight into the inner-workings of the business. The testing of the module is using the data from X Supermarket. The final result of this module is generated from a data mining process in the form of association rule. The rule is presented in narrative and graphical form to be understood easier.