• Title/Summary/Keyword: Autocorrelation method

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Massive Music Resources Retrieval Method Based on Ant Colony Algorithm

  • Yun Meng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.5
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    • pp.1208-1222
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    • 2024
  • Music resources are characterized by quantization, diversification and complication. With the rapid increase of the demand for music resources, the storage of music resources is very large. In order to improve the retrieval effect of music resources, a massive music resources retrieval method based on ant colony algorithm is proposed to effectively use music resources. This paper constructs autocorrelation function to extract pitch feature of music resource, classifies the music resource information by calculating feature similarity. Using ant colony algorithm to correlate the feature of music resource, gain the result of correlative, locate the result of detection and get the result of multi-module. Simulation results show that the proposed method has high precision and recall, short retrieval time and can effectively retrieve massive music resources.

A Comparison of Neighborhood Definition Methods for Spatial Autocorrelation (공간자기상관 산출을 위한 인접성 정의 방법 비교)

  • Park, Jae-Moon;Hwang, Do-Hyun;Yoon, Hong-Joo
    • Journal of Fisheries and Marine Sciences Education
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    • v.23 no.3
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    • pp.477-485
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    • 2011
  • For the identifying of spatial distribution pattern, Moran's Index(I) which has the range of values from -1 to +1 is common method for the spatial autocorrelation measurement. When I is close to 1, all neighboring features have close to the same value, indicating clustered pattern. Conversely, if the spatial pattern is dispersed, I is close to -1. And I closing to 0 means spatially random pattern. However, this index equation is influenced by how defining the neighboring features for target feature. To compare and understand the difference of neighborhood definition methods, fixed distance neighboring method and Gabriel Network method were used for I. In this study, these two methods were applied to two marine environments with water quality data. One is Gwangyang Bay which has complex geometric coastal structure located in South Sea of Korea. Another is Uljin area adjacent to open sea located in east coast of Korea. The distances between water quality observed locations were relatively regular in Gwangyang Bay, however, irregular in Uljin area. And for the fixed distance method popular Arc GIS tool was used, but, for the Gabriel Network, Visual Basic program was developed to produce Gabriel Network and calculate Moran's I and its Z-score automatically. According to this experimental results, different spatial pattern was showed differently for some data with using of neighboring definition methods. Therefore there is need to choose neighboring definition method carefully for spatial pattern analysis.

Analysis on the Characteristics of Urban Decline Using GIS and Spatial Statistical Method : The Case of Gwangju Metropolitan City (GIS와 공간통계기법을 활용한 도시쇠퇴 특성 분석 - 광주광역시를 중심으로 -)

  • Jang, Mun-Hyun
    • Journal of the Korean association of regional geographers
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    • v.22 no.2
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    • pp.424-438
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    • 2016
  • In an effort to prevent urban decline and hollowing-out phenomenon and to vitalize stagnant local economy, a new urban regeneration paradigm is on the rise. This study aims to analyze urban decline characteristics using the spatial statistical method and GIS on the basis of decline standards in the Urban Regeneration Special Act, and spatial autocorrelation technique. The Gwangju Metropolitan City was set as a research target, and the decline standards in the Urban Regeneration Special Act - population reduction, business declines, and outworn buildings - were applied as the indicator to secure the objectivity. In particular, this study has a distinctive feature from the other existing ones, as applying GIS and the spatial statistical technique, in a sense to make urban decline characteristics analysis by the spatial autocorrelation technique. The overall analysis procedure was carried out by applying the standards of designating urban regeneration regions, and following the spatial exploratory procedure step by step. Therefore, the spatial statistical method procedure and the urban decline characteristics analysis data being presented in this study, as the results, are expected to contribute to the urban decline diagnosis at the level of metropolitan city, as well as to provide useful information for spatial decision making in accordance with urban regeneration.

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Adaptively selected autocorrelation structure-based Kriging metamodel for slope reliability analysis

  • Li, Jing-Ze;Zhang, Shao-He;Liu, Lei-Lei;Wu, Jing-Jing;Cheng, Yung-Ming
    • Geomechanics and Engineering
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    • v.30 no.2
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    • pp.187-199
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    • 2022
  • Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

Functional Separation of Myoelectric Signal of Human Arm Movements Using Time Series Analysis (시계열 해석을 이용한 팔운동 근전신호의 기능분리)

  • 홍성우;남문현
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1051-1059
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    • 1992
  • In this paper, two general methods using time-series analysis in the functional separation of the myoelectric signal of human arm movements are developed. Autocorrelation, covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation-out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squared error. With the error signals of autoregressive(AR) model, the result showed that the highest success rate was obtained in the case of 4th order, and success rate was decreased with increase of order. Autocorrelation was the method of choice for better success rate. This technique might be applied to biomedical and rehabilitation engineering.

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$\bar{X}$ control charts of automcorrelated process using threshold bootstrap method (분계점 붓스트랩 방법을 이용한 자기상관을 갖는 공정의 $\bar{X}$ 관리도)

  • Kim, Yun-Bae;Park, Dae-Su
    • Journal of Korean Society for Quality Management
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    • v.28 no.2
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    • pp.39-56
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    • 2000
  • ${\overline{X}}$ control chart has proven to be an effective tool to improve the product quality. Shewhart charts assume that the observations are independent and normally distributed. Under the presence of positive autocorrelation and severe skewness, the control limits are not accurate because assumptions are violated- Autocorrelation in process measurements results in frequent false alarms when standard control chats are applied in process monitoring. In this paper, Threshold Bootstrap and Moving Block Bootstrap are used for constructing a confidence interval of correlated observations. Monte Carlo simulation studies are conducted to compare the performance of the bootstrap methods and that of standard method for constructing control charts under several conditions.

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A Analysis on the Spatial Features of the Neighborhood Trade Area using Positive Spatial Autocorrelation Method (공간자기상관기법을 이용한 근린상권의 공간특성분석)

  • Jung, Dae-Young;Son, Young-Gi
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.1
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    • pp.141-147
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    • 2009
  • A analysis on the spatial features is required for exploratory spatial data analysis of information about space location(population ecological factor, social ecological factor) to manage the store factors, the service industry, etc. Therefore, the purpose of this study is to provide correlation analysis method between the types of service trade using dependence between spatial objects on the geographical space and statistical correlation and to analyze the spatial features through the deduction of correlation analysis between the types of the neighborhood trade area.

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Effect of Spatial Distribution of Material Properties on its Experimental Estimation (재질의 공간적 변동이 재료강도시험결과에 미치는 영향)

  • Kim, S.J.
    • Journal of Power System Engineering
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    • v.4 no.2
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    • pp.40-45
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    • 2000
  • Some engineering materials are often known to have considerable spatial variation in their resisting strength and other properties. The objective of this study is to investigate the averaging effect and the applicability of extremal statistic for the statistical size effect. In the present study, it is assumed that the material property is a stationary random process in space. The theoretical autocorrelation function of the material strength are discussed for several correlation lengths. And, in order to investigate the statistical size effect, the material properties was simulated by using the non-Gaussian random process method. The material properties were plotted on the Weibull probability papers. The main results are summarized as follows: The autocorrelation function of the material properties are almost independent of the averaging length. The variance decreases with increasing the averaging length. As correlation length is smaller, the slope is larger. And also, it was found that Weibull statistics based on the weakest-link model could not explain the spatial variation of material properties with respect to the size effect satisfactory.

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A Study on Assessing Disaster Response Capacity for Coastal Residents (연안거주민에 대한 재해대응능력 평가 연구)

  • Kang, Tae-Soon;Lee, Seung-Rok;Lee, Jong-Sup;Kim, Jongkyu
    • Journal of Fisheries and Marine Sciences Education
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    • v.26 no.5
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    • pp.979-990
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    • 2014
  • Recently the frequency of coastal disasters caused by global warming is increasing and the damage is becoming greater. Therefore, the Korean government is establishing various policies and measures to minimize damage. For disaster prevention, this study will evaluate the disaster response capacity of each local resident(Eup/Myeun/Dong) in coastal areas through the survey. The purpose of this study is to quantitatively understand the disaster response capacity and analyze spatial autocorrelation between hot spots(vulnerable area) and cold spots. Thus this study was conducted a survey of 311 towns(Eup/Myeun/Dong) about the disaster response capacity of coastal residents. As a result, Namhae has the highest average score(4.9). On the contrary, Hampyeong has the lowest(1.6). Coastal residents in Namhae seem to have better understanding of first aid and preventive maintenance. But coastal residents in Hampyeong seem to not have these characteristics. Afterwards, this study builds a database of disaster response capacity, and analyzes it using the spatial autocorrelation method. Finally, the area of hot spots and cold spots for disaster response capacity was quantitatively detected.