• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.71-78
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• 2016

This paper proposes the new electric power demand forecast model which is based on an artificial neural network and considers time and weather factors. Time factors are selected by measuring the autocorrelation coefficients of load demand in summer and winter seasons. Weather factors are selected by using Pearson correlation coefficient The important weather factors are temperature and dew point because the correlation coefficients between these factors and load demand are much higher than those of the other factors such as humidities, air pressures and wind speeds. The experimental results show that the proposed model using time and seasonal weather factors improves the load demand forecasts to a great extent.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.33-41
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• 1994

A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

• Journal of Environmental Health Sciences
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• v.17 no.2
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• pp.1-8
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• 1991

The stochastic variance and structures of time series data on air quality were examined by employing the techniques of autocorrelation function, variance spectrum, fourier series, ARIMA model. Among the air quality properties of atmosphere, SO$_{2}$ is one of the most siginificant and widely measured parameters. In the study, the air quality data were included hourly observations on SO$_{2}$ TSP and O$_{3}$. The data were measured by automatic recording instrument installed in Kwanghwamoon during February and March in 1991. The results of study were as follows 1. Hourly air quality series varied with the domiant 24 hour periodicity and the 12 hour periodic variation was also observed. 2. The correlation coefficients between SO$_{2}$ and O$_{3}$ is -0.4735. 3. In simulating or forecasting variation in SO$_{2}$ ARIMA models are on a useful tools. The multiplicative seasonal ARIMA (1, 1, 0) (0, 2, 1)$_{24}$ model provided satisfactory results for hourly SO$_{2}$ time series.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.5 no.4
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• pp.108-114
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• 1972

The present paper deals with secular analysis of zooplankton biomass by statistical method in the south sea of Korea during the period of nine years from 1963 through 1971. Data were taken from the Annual Report of Oceanographic Observations, Fisheries Research and Development Agency, Korea. The trend value of annual variations in the 108 month period above was calculated by method of 12 month moving average, and a period analysis was made by ore of correlogram method using autocorrelation coefficients. The trend of zooplankton biomass shows periodical fluctuation for the period of 63 months with high interrelationships. The seasonal variation has teen obvious with growth phase twice a year, in April and October.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.565-569
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• 2003

One-year-long groundwater-level data have been collected from 18 wells in Cheon-an area. The result of barometric efficiency, autocorrelation, cross-correlation and statistical distribution evaluated from the measurement data shows that groundwater-level measurements from observation wells are the principal source of information about aquifer characteristics. Data from WA-2 has high barometric efficiency as well as steady decreasing auto-correlation coefficient, which means nonleaky confined aquifer, Most aquifers in this study show the unconfined properties so that barometric efficiencies are mostly low and the coefficients of cross-correlation between groundwater-level and precipitation are commonly high. This study showed that the long-term groundwater-level monitoring data without artificial stress such as pumping would give accurate information about aquifer characteristics.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.723-726
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• 1988

This paper is a study about the automatic control of wheelchairs. This is realized by joystick, and is simulated by voice signal recognition. The control system by joystick is designed as follows: joystick paddle is connected with a timer and this timer ouput is high only when the joystick is moved. A computer reads the duration of this high state, and ouputs motor control word decided from this value using look-up table. The control system by voice signal is designed as follows: partial autocorrelation coefficients are computed from A/D converted signals and these values are compared with referance patterns. From this, the motor control word is decided on by the neareast neighbor rule.

• The Journal of the Acoustical Society of Korea
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• v.6 no.1
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• pp.23-28
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• 1987

This paper discusses a reference pattern creation for a speaker-independent Korean isolated word by using the clustering. Tn this paper we permitted to top 3 clusters and created reference pattern by Minimax Criterion. The features parameter used the LPC Coefficients and Autocorrelation and simple Itakura distance measure was used to measure similarity between patterns. With word reference patterns obtained as described above the recognition rate was within one choice only $55.9\%$, two choice only $76.9\%$, three choice only $89.5\%$.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.5
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• pp.905-913
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• 1987

This paper presents a speaker dependent isolated digit recognition algorithm using the Mellin transform. Since the Mellin transform converts a scale information into a phase information, attempts have been made to utilize this scale invariance property of the Mellin transform in order to alleviate a time-normalization procedure required for a speech recognition. It has been found that good results can be obtained by taking the Mellin transform to the features such as a ZCR, log energy, normalized autocorrelation coefficients, first predictor coefficient and normalized prediction error. We employed a difference function for evaluating a similarity between two patterns. When the proposed algorithm was tested on Korean digit words, a recognition rate of 83.3% was obtained. The recognition accuracy is not compatible with the other technique such as LPC distance however, it is believed that the Mellin transform can effectively perform the time-normalization processing for the speech recognition.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.222-226
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• 2007

This study developed the Korean roundwood import prediction model using vector autoregressive (VAR) method. The roundwood was divided into softwood and hardwood by species. The VAR model of roundwood import was specified with two lagged endogenous variables, that is, roundwood import volume and roundwood import price. The results showed that the significance levels of F-statistics in the softwood and hardwood roundwood import equations rejected the hypothesis that all coefficients are zero. So, we concluded that roundwood import volume can be explained by lagged import volume and lagged import price in Korea. The coefficient signs of all variables were as expected. Also, the model has good explanatory power, and there is no autocorrelation.

• Geomechanics and Engineering
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• v.23 no.5
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• pp.419-429
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• 2020

To investigate the effect of spatial variability on hydraulic properties of unsaturated soils, a numerical model is set up which can simulate seepage process in an unsaturated heterogeneous soil. The unsaturated heterogeneous soil is composed of matrix sand embedded with a small proportion of clay for simulating the heterogeneity. Soil-water characteristic curve and unsaturated hydraulic conductivity curve of the unsaturated soil are expressed by Van Genuchten model. Hydraulic parameters of the matrix sand are considered as random fields. Different autocorrelation lengths (ACLs) of hydraulic parameter of the matrix sand and different proportions of clay are assumed to investigate the influence of spatial variability on the equivalent hydraulic properties of the heterogeneous soil. Four model sizes are used in the numerical experiments to investigate the influence of scale effects and to determine the sizes of representative volume element (RVE) in the numerical simulations. Through a number of Monte Carlo simulations of unsaturated seepage analysis, the means and the coefficients of variations (COVs) of the equivalent hydraulic parameters of the heterogeneous soil are calculated. Simulations show that the ACL and model size has little influence on the means of the equivalent hydraulic parameters, but they have a large influence on the COVs of the equivalent hydraulic parameters. The size of an RVE is mainly affected by the ACL and the proportion of heterogeneity. The influence of spatial variability on the hydraulic parameters of the heterogeneous unsaturated soil can be used as a guidance for geotechnical reliability analysis and design related to unsaturated soils.