• Title/Summary/Keyword: best-fit algorithm

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AN ALGORITHM FOR FITTING OF SPHERES

  • Kim, Ik-Sung
    • The Pure and Applied Mathematics
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    • v.11 no.1
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    • pp.37-49
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    • 2004
  • We are interested in the problem of fitting a sphere to a set of data points in the three dimensional Euclidean space. In Spath [6] a descent algorithm already have been given to find the sphere of best fit in least squares sense of minimizing the orthogonal distances to the given data points. In this paper we present another new algorithm which computes a parametric represented sphere in order to minimize the sum of the squares of the distances to the given points. For any choice of initial approximations our algorithm has the advantage of ensuring convergence to a local minimum. Numerical examples are given.

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Prediction-based Dynamic Thread Pool System for Massively Multi-player Online Game Server

  • Ju, Woo-Suk;Im, Choong-Jae
    • Journal of Korea Multimedia Society
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    • v.12 no.6
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    • pp.876-881
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    • 2009
  • Online game servers usually has been using the static thread pool system. But this system is not fit for huge online game server because the overhead is always up-and-down. Therefore, in this paper, we suggest the new algorithm for huge online game server. This algorithm is based on the prediction-based dynamic thread pool system. But it was developed for web servers and every 0.1 seconds the system prediction the needed numbers of threads and determine the thread pool size. Some experimental results show that the check time of 0.4 seconds is the best one for online game server and if the number of worker threads do not excess or lack to the given threshold then we do not predict and keep the current state. Otherwise we apply the prediction algorithm and change the number of threads. Some experimental results shows that this proposed algorithm reduce the overhead massively and make the performance of huge online game server improved in comparison to the static thread pool system.

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A Study on the Facial Feature Matching using Genetic Algorithm (유전자 알고리즘을 이용한 얼굴특징 정합에 관한 연구)

  • 김윤수;류정식;김준식
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2001.06a
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    • pp.269-272
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    • 2001
  • In this paper, we proposed the face recognition algorithm which can use a security system. The distance and angle of the face features are used in the conventional method, but the proposed method used the genetic algorithm which selects image to best fit the input image in the database images. The performance of proposed algorithm is verified through the simulation. The proposed one has good performance.

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A Study on the Feature Extraction and Matching Algorithm for a Face Recognition (얼굴인식을 위한 특징 추출 및 정합 알고리즘에 관한 연구)

  • 김윤수;류정식;김준식
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.2
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    • pp.15-22
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    • 2002
  • In this paper, we proposed the face recognition algorithm which can be used for a security system. The distance and angle of the face features are used in the conventional method, but the proposed method used the genetic algorithm which selects image to best fit the input image in the database images. The performance of proposed algorithm is verified through the simulation. The results of proposed method show good performance.

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A Machine Learning Univariate Time series Model for Forecasting COVID-19 Confirmed Cases: A Pilot Study in Botswana

  • Mphale, Ofaletse;Okike, Ezekiel U;Rafifing, Neo
    • International Journal of Computer Science & Network Security
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    • v.22 no.1
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    • pp.225-233
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    • 2022
  • The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

Shape Recognition of Parts and Software Development by using Border Tracking and Cross Correlatioin Method (경계선추적과 상관계수법을 이용한 부품의 형상인식과 소프트웨어개발)

  • 유성민
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1998.03a
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    • pp.100-105
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    • 1998
  • Image processing was used to recognize parts at various disposition. Non-transpatent tachometer panel for automobile and semi-transparent panel have been used as test specimen. Laplacian filter and various threshold values have been applied for preprocessing and edge following algorithm has been applied. Series of length data between edges have been generated from each image and compared using cross correlation coefficient. The result using cross correlation coefficient. The result using both edge following and cross correlation coefficient was proven to be the best fit for the proposed parts.

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Application of genetic Algorithm to the Back Analysis of the Underground Excavation System (지하굴착의 역해석에 대한 유전알고리즘의 적용)

  • 장찬수;김수삼
    • Proceedings of the Korean Geotechical Society Conference
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    • 2002.10a
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    • pp.65-84
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    • 2002
  • The Observational Method proposed by Terzaghi can be applied for the safe and economic construction projects where the exact prediction of the behavior of the structures is difficult as in the underground excavation. The method consists of measuring lateral displacement, ground settlement and axial force of supports in the earlier stage of the construction and back analysis technique to find the best fit design parameters such as earth pressure coefficient, subgrade reaction etc, which will minimize the gap between calculated displacement and measured displacement. With the results, more reliable prediction of the later stage can be obtained. In this study, back analysis programs using the Direct Method, based on the Hill Climbing Method were made and evaluated, and to overcome the limits of the method, Genetic Algorithm(GA) was applied and tested for the actual construction cases.

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A Design of New Digital Adaptive Predistortion Linearizer Algorithm Based on DFP(Davidon-Fletcher-Powell) Method (DFP Method 기반의 새로운 적응형 디지털 전치 왜곡 선형화기 알고리즘 개발)

  • Jang, Jeong-Seok;Choi, Yong-Gyu;Suh, Kyoung-Whoan;Hong, Ui-Seok
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.3
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    • pp.312-319
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    • 2011
  • In this paper, a new linearization algorithm for DPD(Digital PreDistorter) is suggested. This new algorithm uses DFP(Davidon-Fletcher-Powell) method. This algorithm is more accurate than that of the existing algorithms, and this method renew the best-fit value in every routine with out setting the initial value of step-size. In modeling power amplifier, the memory polynomial model which can model the memory effect of the power amplifier is used. And the overall structure of linearizer is based on an indirect learning architecture. In order to verify for performance of proposed algorithm, we compared with LMS(Least Mean-Squares), RLS(Recursive Least squares) algorithm.

Development of the Machine Vision System for Inspection the Front-Chassis Module of an Automobile (자동차 프런트 샤시 모듈 측정을 위한 머신 비전 시스템 개발)

  • 이동목;이광일;양승한
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.3
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    • pp.84-90
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    • 2004
  • Today, automobile world market is highly competitive. In order to strengthen the competitiveness, quality of automobile is recognized as important and efforts are being made to improve the quality of manufactured components. The directional ability of automobile has influence on driver directly and hence it must be solved on the preferential basis. In the present research, an automated vision system has been developed to inspect the front chassis module. To interpret the inspection data obtained for front chassis module, new interpreting algorithm have been developed. Previously the control of tolerance of front chassis module was done manually. With the help of the new algorithm developed, the dimension is calculated automatically to check whether the front chassis module is within the tolerance limit or not.

Hybrid PSO-Complex Algorithm Based Parameter Identification for a Composite Load Model

  • Del Castillo, Manuelito Y. Jr.;Song, Hwachang;Lee, Byongjun
    • Journal of Electrical Engineering and Technology
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    • v.8 no.3
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    • pp.464-471
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    • 2013
  • This paper proposes a hybrid searching algorithm based on parameter identification for power system load models. Hybrid searching was performed by the combination of particle swarm optimization (PSO) and a complex method, which enhances the convergence of solutions closer to minima and takes advantage of global searching with PSO. In this paper, the load model of interest is composed of a ZIP model and a third-order model for induction motors for stability analysis, and parameter sets are obtained that best-fit the output measurement data using the hybrid search. The origin of the hybrid method is to further apply the complex method as a local search for finding better solutions using the selected particles from the performed PSO procedure.