• Title/Summary/Keyword: analysis of algorithm

Search Result 12,352, Processing Time 0.041 seconds

A Study on the Dynamics of Genetic Algorithm Based on Stochastic Differential Equation (유전 알고리즘의 확률 미분방정식에 의한 동역학 분석에 대한 연구)

  • 석진욱;조성원
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 1997.10a
    • /
    • pp.296-300
    • /
    • 1997
  • Recently, the genetic algorithm has been applied to the various types of optimization problems and these attempts have very successfully. However, in most cases on these approaches, there is not given by investigator about to the theoritical analysis. The reason that the analysis of the dynamics for genetic algorithm is not clear, is the probablitic aspect of genetic algorithm. In this paper, we investigate the analysis of the internal dynamics for genetic algorithm using stochastic differential method. In addition, we provide a new genetic algorithm, based on the study of the convergence property for the genetic algorithm.

  • PDF

A Study on Efficient Cluster Analysis of Bio-Data Using MapReduce Framework

  • Yoo, Sowol;Lee, Kwangok;Bae, Sanghyun
    • Journal of Integrative Natural Science
    • /
    • v.7 no.1
    • /
    • pp.57-61
    • /
    • 2014
  • This study measured the stream data from the several sensors, and stores the database in MapReduce framework environment, and it aims to design system with the small performance and cluster analysis error rate through the KMSVM algorithm. Through the KM-SVM algorithm, the cluster analysis effective data was used for U-health system. In the results of experiment by using 2003 data sets obtained from 52 test subjects, the k-NN algorithm showed 79.29% cluster analysis accuracy, K-means algorithm showed 87.15 cluster analysis accuracy, and SVM algorithm showed 83.72%, KM-SVM showed 90.72%. As a result, the process speed and cluster analysis effective ratio of KM-SVM algorithm was better.

Parallel O.C. Algorithm for Optimal design of Plane Frame Structures (평면골조의 최적설계를 위한 병렬 O.C. 알고리즘)

  • 김철용;박효선;박성무
    • Proceedings of the Computational Structural Engineering Institute Conference
    • /
    • 2000.04b
    • /
    • pp.466-473
    • /
    • 2000
  • Optimality Criteria algorithm based on the derivation of reciprocal approximations has been applied to structural optimization of large-scale structures. However, required computational cost for the serial analysis algorithm of large-scale structures consisting of a large number of degrees of freedom and members is too high to be adopted in the solution process of O.C. algorithm Thus, parallel version of O.C. algorithm on the network of personal computers is presented in this Paper. Parallelism in O.C. algorithm may be classified into two regions such as analysis and optimizer part As the first step of development of parallel algorithm, parallel structural analysis algorithm is developed and used in O.C. algorithm The algorithm is applied to optimal design of a 54-story plane frame structure

  • PDF

Crowd Psychological and Emotional Computing Based on PSMU Algorithm

  • Bei He
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.18 no.8
    • /
    • pp.2119-2136
    • /
    • 2024
  • The rapid progress of social media allows more people to express their feelings and opinions online. Many data on social media contains people's emotional information, which can be used for people's psychological analysis and emotional calculation. This research is based on the simplified psychological scale algorithm of multi-theory integration. It aims to accurately analyze people's psychological emotion. According to the comparative analysis of algorithm performance, the results show that the highest recall rate of the algorithm in this study is 95%, while the highest recall rate of the item response theory algorithm and the social network analysis algorithm is 68% and 87%. The acceleration ratio and data volume of the research algorithm are analyzed. The results show that when 400,000 data are calculated in the Hadoop cluster and there are 8 nodes, the maximum acceleration ratio is 40%. When the data volume is 8GB, the maximum scale ratio of 8 nodes is 43%. Finally, we carried out an empirical analysis on the model that compute the population's psychological and emotional conditions. During the analysis, the psychological simplification scale algorithm was adopted and multiple theories were taken into account. Then, we collected negative comments and expressions about Japan's discharge of radioactive water in microblog and compared them with the trend derived by the model. The results were consistent. Therefore, this research model has achieved good results in the emotion classification of microblog comments.

Optimal Spare Part Level in Multi Indenture and Multi Echelon Inventory Applying Marginal Analysis and Genetic Algorithm (한계분석법과 유전알고리즘을 결합한 다단계 다계층 재고모형의 적정재고수준 결정)

  • Jung, Sungtae;Lee, Sangjin
    • Korean Management Science Review
    • /
    • v.31 no.3
    • /
    • pp.61-76
    • /
    • 2014
  • There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.

A Study on the Face Recognition Using PCA Algorithm

  • Lee, John-Tark;Kueh, Lee-Hui
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.17 no.2
    • /
    • pp.252-258
    • /
    • 2007
  • In this paper, a face recognition algorithm system using Principal Component Analysis (PCA) is proposed. The algorithm recognized a person by comparing characteristics (features) of the face to those of known individuals of Intelligent Control Laboratory (ICONL) face database. Simulations are carried out to investigate the algorithm recognition performance, which classified the face as a face or non-face and then classified it as known or unknown one. Particularly, a Principal Components of Linear Discriminant Analysis (PCA + LDA) face recognition algorithm is also proposed in order to confirm the recognition performances and the adaptability of a proposed PCA for a certain specific system.

The Short Time Spectra Analysis System Using The Complex LMS Algorithm and It's Applications

  • Umemoto, Toshitaka;Fujisawa, Shoichiro;Yoshida, Takeo
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 1998.10a
    • /
    • pp.58-63
    • /
    • 1998
  • B.Widrow established fundamental relations between the least-mean-square (LMS) algorithm and the digital Fourier transform[1]. By extending these relations, we proposed the short time spectra analysis system using the LMS algorithm[2]. In that paper, we used the normal LMS algorithm on the thought of dealing with only real analytical signal. This algorithm minimizes the real mean-square by recursively altering the complex weight vector at each sampling instant. But, the short time spectra analysis sometimes deals with the complex signal that is outputted from complex analog filter. So, in order to optimize and develop this methods, furthermore it is necessary to derive an algorithm for the complex analytical signal. In this paper, we first discuss the new adaptive system for the spectra analysis using the complex LMS algorithm and then derive convergence condition, time constant of coefficient adjustment and frequency resolution by extending the discussion. Finally, the effectiveness of the proposed method is experimentally demonstrated by applying it to the measurement of transfer performance on complex analog filter.

  • PDF

Subband PRI analysis algorithm (Subband PRI 분석 알고리즘)

  • 윤원식
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.21 no.6
    • /
    • pp.1425-1429
    • /
    • 1996
  • A conventional sequence search algorithm for PRI analysis occurs the harmonic problem under missing pulses. An improved PRI analysis algorithm is proposedto remedy the harmonic problem. After dividing an overall PRI range into subbands withoug harmonic, a sequence search is done into forward and backward in time. The proposed algorithm increases the preformance compared with that of conventional sequence search algorithm.

  • PDF

Optimization for PSC Box Girder Bridges Using Design Sensitivity Analysis (설계 민감도 해석을 이용한 PSC 박스거더교의 최적설계)

  • 조선규;조효남;민대홍;이광민;김환기
    • Proceedings of the Korea Concrete Institute Conference
    • /
    • 2000.10a
    • /
    • pp.205-210
    • /
    • 2000
  • An optimum design algorithm of PSC box girder bridges using design sensitivity analysis is proposed in this paper. For the efficiency of the proposed algorithm, approximated reanalysis techniques using design sensitivity analysis are introduced. And also to save the numerical efforts, an efficient reanalysis technique through approximated structural responses is proposed. A design sensitivity analysis of structural response is executed by automatic differentiation(AD). The efficiency and robustness of the proposed algorithm, compared with conventional algorithm, is successfully demonstrated in the numerical example.

  • PDF

Estimation of Total Sound Pressure Level for Friction Noise Regarding a Driving Vehicle using the Extended Kalman Filter Algorithm (확장형 칼만필터 알고리즘을 활용한 차량 주행에 따른 마찰소음의 총 음압레벨 예측)

  • Dowan, Kim;Beomsoo, Han;Sungho, Mun;Deok-Soon, An
    • International Journal of Highway Engineering
    • /
    • v.16 no.5
    • /
    • pp.59-66
    • /
    • 2014
  • PURPOSES : This study is to predict the Sound Pressure Level(SPL) obtained from the Noble Close ProXimity(NCPX) method by using the Extended Kalman Filter Algorithm employing the taylor series and Linear Regression Analysis based on the least square method. The objective of utilizing EKF Algorithm is to consider stochastically the effect of error because the Regression analysis is not the method for the statical approach. METHODS : For measuring the friction noise between the surface and vehicle's tire, NCPX method was used. With NCPX method, SPL can be obtained using the frequency analysis such as Discrete Fourier Transform(DFT), Fast Fourier Transform(FFT) and Constant Percentage Bandwidth(CPB) Analysis. In this research, CPB analysis was only conducted for deriving A-weighted SPL from the sound power level in terms of frequencies. EKF Algorithm and Regression analysis were performed for estimating the SPL regarding the vehicle velocities. RESULTS : The study has shown that the results related to the coefficient of determination and RMSE from EKF Algorithm have been improved by comparing to Regression analysis. CONCLUSIONS : The more the vehicle is fast, the more the SPL must be high. But in the results of EKF Algorithm, SPLs are irregular. The reason of that is the EKF algorithm can be reflected by the error covariance from the measurements.