• Title/Summary/Keyword: frequency forecasting

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Development of a sow voice analysis system for forecasting parturition time (임신돈의 분만시기 예측을 위한 음성 분석 시스템 개발)

  • Chang, Dong Il;Lim, Zung Taek
    • Korean Journal of Agricultural Science
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    • v.27 no.2
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    • pp.107-116
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    • 2000
  • Pure voice characteristics of sow were analyzed to predict parturition time. These were analyzed by using oscilloscope and Sound Forge and the results showed that the voice frequency and amplitude of sow were in the range of 30~2,500Hz and -35~-75dB. According to the sound analysis results, the frequencies of sound appearance from farrowing sow in the farrowing pen for three days prior to delivery day and eight hours of prior to time were around 85% and 46%, respectively of the total appearance during eight days to delivery. Forecasting of delivery time of farrowing sow using the number of sound occurrences showed a promising result such that those have been increased whenever the delivery time was approached. The forecasting success rates were 100% for both of one day and six hours prior to the actual delivery.

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Comovement and Forecast of won/dollar, yuan/dollar, yen/dollar: Application of Fractional Cointegration approach and Causal Analysis of Frequency Domain (한·중·일 환율 사이의 움직임 분석 - 분수공적분과 진동수영역의 인과성 -)

  • Jung, Sukwan;Won, DooHwan
    • International Area Studies Review
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    • v.21 no.2
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    • pp.3-20
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    • 2017
  • Traditional co-integration analysis method is known to be difficult to clearly determine the relationship between the cointegrated variables. This study utilizes a fractional cointegation method and a causal analysis of time and frequency domain among the exchange rates of Korea, China and Japan. The results show that even though traditional cointegration methods did not clarify the existence of cointegration, exchange rates were fractionally cointegrated. Causal analysis of time domain and frequency domain provided somewhat different results, but the yen/dollar was useful for forecasting won/dollar and yuan/dollar. Proper use of causal analysis of frequency domain and fractional cointegration emthods may provide useful information that can not be explained from the traditional method.

A Study on WTP of Mobile Telephone Service Using the Contingent Valuation Method in Korea (조건부가치 추정법(CVM)을 이용한 국내 이동통신서비스에 대한 소비자 WTP 추정에 관한 연구)

  • Jeong, Woo-Soo;Rim, Myung-Hwan;Sawng, Yeong-Wha
    • Korean Management Science Review
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    • v.25 no.2
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    • pp.43-55
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    • 2008
  • Contingent valuation method(hereafter CVM) is generally believed to be one of the most popular methods used for quantifying the value of non-market goods or services particularly by asking respondents of willingness to pay. This study deals with how to use CVM in calculating the value of mobile telephone service by suggesting methodology of estimation and eliminating biases. This study represents an attempt to estimate the WTP(Willingness To Pay) of the mobile telephone service using the face-to-face interview which is the qualitative technique is used. In this study, by using the single bound dichotomous choice model(SBDC) in order to analyze the valuation of mobile telephone service, WTP was estimated. Also we analyze the factors to pay for mobile service in which it becomes the important factor of demanding services. We used logit model. In order to provide robust estimates of WTP, we have used the Method of Montecarlo Simulation. Consequently, consumers showed that WTP about the mobile communications service is generally high. And it could know that the WTP will fell down as the specialized knowledge about the mobile communications frequency was high. It will be able to become the important part to not only the business carrier but also the policy maker to estimate the economic value of mobile telephone service.

Analysis of Typhoon Storm Occurrence and Runoff Characteristics by Typhoon Tracks in Nakdong River Basin (낙동강유역의 태풍경로별 호우발생특성 및 유출특성 분석)

  • 한승섭
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.38 no.5
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    • pp.64-73
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    • 1996
  • When typhoon occurs, the meteorological conditions get worse and can cause a large damage from storm and flood . This damage, however, can be minimized if a precise analysis of the runoff characteristics by typhoon tracks is used in the flood contorl This paper aims at the analysis of storm occurrence and runoff characteristics by typhoon tracks in Nakdong river basin. Therefore, the data of 14 typhoons which invaded Nakdong river basin during the period from 1975 to 1991 were collected, analyzed, and studied. The major results of this study are as followings; 1) The frequency of the typhoon occurrence here in Korea was affected by the storms three times a year on the average. The highest-recorded frequency was during the months of July to September. 2) The survey of the track characteristics depending on the forms of the storm in the Nakdong river basin showed that typhoon storm advanced from the south of the basin to the north, while the frontal type storm was most likely to advanced from the west to the north. 3) Typhoon tracks are classified into three categories, 6 predictors with high correlation coefficient are finally selected, and stepwise multiple regression method are used to establish typhoon strom forecasting models. 4) The riview on the directions of progress of the storm made it clear that the storm moving downstream from upstream of the basin could develop into peak discharge for ca short time and lead to more flood damage than in any other direction.

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Comparison of EMD and HP Filter for Cycle Extraction with Korean Macroeconomic Indices (순환성분 추출을 위한 EMD와 HP 필터의 비교분석: 한국의 거시 경제 지표에의 응용)

  • Park, Minjeong;Seong, Byeongchan
    • The Korean Journal of Applied Statistics
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    • v.27 no.3
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    • pp.431-444
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    • 2014
  • We introduce the empirical model decomposition (EMD) to decompose a time series into a set of components in the time-frequency domain. By using EMD, we also extract cycle and trend components from major Korean macroeconomic indices and forecast the indices with the components combined. In order to evaluate their efficiencies, we investigate volatility, autocorrelation, persistence, Granger causality, nonstationarity, and forecasting performance. They are then compared with those by Hodrick-Prescott filter which is the most commonly used method.

SUNSPOT AREA PREDICTION BASED ON COMPLEMENTARY ENSEMBLE EMPIRICAL MODE DECOMPOSITION AND EXTREME LEARNING MACHINE

  • Peng, Lingling
    • Journal of The Korean Astronomical Society
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    • v.53 no.6
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    • pp.139-147
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    • 2020
  • The sunspot area is a critical physical quantity for assessing the solar activity level; forecasts of the sunspot area are of great importance for studies of the solar activity and space weather. We developed an innovative hybrid model prediction method by integrating the complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM). The time series is first decomposed into intrinsic mode functions (IMFs) with different frequencies by CEEMD; these IMFs can be divided into three groups, a high-frequency group, a low-frequency group, and a trend group. The ELM forecasting models are established to forecast the three groups separately. The final forecast results are obtained by summing up the forecast values of each group. The proposed hybrid model is applied to the smoothed monthly mean sunspot area archived at NASA's Marshall Space Flight Center (MSFC). We find a mean absolute percentage error (MAPE) and a root mean square error (RMSE) of 1.80% and 9.75, respectively, which indicates that: (1) for the CEEMD-ELM model, the predicted sunspot area is in good agreement with the observed one; (2) the proposed model outperforms previous approaches in terms of prediction accuracy and operational efficiency.

Research Trends Analysis on ESG Using Unsupervised Learning

  • Woo-Ryeong YANG;Hoe-Chang YANG
    • The Journal of Economics, Marketing and Management
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    • v.11 no.3
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    • pp.47-66
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    • 2023
  • Purpose: The purpose of this study is to identify research trends related to ESG by domestic and overseas researchers so far, and to present research directions and clues for the possibility of applying ESG to Korean companies in the future and ESG practice through comparison of derived topics. Research design, data and methodology: In this study, as of October 20, 2022, after searching for the keyword 'ESG' in 'scienceON', 341 domestic papers with English abstracts and 1,173 overseas papers were extracted. For analysis, word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and OLS regression analysis were performed to confirm trends for each topic using Python 3.7. Results: As a result of word frequency analysis, It was found that words such as management, company, performance, and value were commonly used in both domestic and overseas papers. In domestic papers, words such as activity and responsibility, and in overseas papers, words such as sustainability, impact, and development were included in the top 20 words. As a result of analyzing the co-occurrence frequency of words, it was confirmed that domestic papers were related mainly to words such as company, management, and activity, and overseas papers were related to words such as investment, sustainability, and performance. As a result of topic modeling, 3 topics such as named ESG from the corporate perspective were derived for domestic papers, and a total of 7 topics such as named sustainable investment for overseas papers were derived. As a result of the annual trend analysis, each topic did not show a relatively increasing or decreasing tendency, confirming that all topics were neutral. Conclusions: The results of this study confirmed that although it is desirable that domestic papers have recently started research on consumers, the subject diversity is lower than that of overseas papers. Therefore, it is suggested that future research needs to approach various topics such as forecasting future risks related to ESG and corporate evaluation methods.

A study on the efficient early warning method using complex event processing (CEP) technique (복합 이벤트 처리기술을 적용한 효율적 재해경보 전파에 관한 연구)

  • Kim, Hyung-Woo;Kim, Goo-Soo;Chang, Sung-Bong
    • 한국정보통신설비학회:학술대회논문집
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    • 2009.08a
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    • pp.157-161
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    • 2009
  • In recent years, there is a remarkable progress in ICTs (Information and Communication Technologies), and then many attempts to apply ICTs to other industries are being made. In the field of disaster managements, ICTs such as RFID (Radio Frequency IDentification) and USN (Ubiquitous Sensor Network) are used to provide safe environments. Actually, various types of early warning systems using USN are now widely used to monitor natural disasters such as floods, landslides and earthquakes, and also to detect human-caused disasters such as fires, explosions and collapses. These early warning systems issue alarms rapidly when a disaster is detected or an event exceeds prescribed thresholds, and furthermore deliver alarm messages to disaster managers and citizens. In general, these systems consist of a number of various sensors and measure real-time stream data, which requires an efficient and rapid data processing technique. In this study, an event-driven architecture (EDA) is presented to collect event effectively and to provide an alert rapidly. A publish/subscribe event processing method to process simple event is introduced. Additionally, a complex event processing (CEP) technique is introduced to process complex data from various sensors and to provide prompt and reasonable decision supports when many disasters happen simultaneously. A basic concept of CEP technique is presented and the advantages of the technique in disaster management are also discussed. Then, how the main processing methods of CEP such as aggregation, correlation, and filtering can be applied to disaster management is considered. Finally, an example of flood forecasting and early alarm system in which CEP is incorporated is presented It is found that the CEP based on the EDA will provide an efficient early warning method when disaster happens.

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Comparison of flood inundation simulation between one- and two-dimensional numerical models for an emergency action plan of agricultural reservoirs

  • Kim, Jae Young;Jung, Sung Ho;Yeon, Min Ho;Lee, Gi Ha;Lee, Dae Eop
    • Korean Journal of Agricultural Science
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    • v.48 no.3
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    • pp.515-526
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    • 2021
  • The frequency of typhoons and torrential rainfalls has increased due to climate change, and the concurrent risk of breakage of dams and reservoirs has increased due to structural aging. To cope with the risk of dam breakage, a more accurate emergency action plan (EAP) must be established, and more advanced technology must be developed for the prediction of flooding. Hence, the present study proposes a method for establishing a more effective EAP by performing flood and inundation analyses using one- and two-dimensional models. The probable maximum flood (PMF) under the condition of probable maximum precipitation (PMP) was calculated for the target area, namely the Gyeong-cheon reservoir watershed. The breakage scenario of the Gyeong-cheon reservoir was then built up, and breakage simulations were conducted using the dam-break flood forecasting (DAMBRK) model. The results of the outflow analysis at the main locations were used as the basis for the one-dimensional (1D) and two-dimensional (2D) flood inundation analyses using the watershed modeling system (WMS) and the FLUvial Modeling ENgine (FLUMEN), respectively. The maximum inundation area between the Daehari-cheon confluence and the Naeseong-cheon location was compared for each model. The 1D flood inundation analysis gave an area of 21.3 km2, and the 2D flood inundation analysis gave an area of 21.9 km2. Although these results indicate an insignificant difference of 0.6 km2 in the inundation area between the two models, it should be noted that one of the main locations (namely, the Yonggung-myeon Administrative and Welfare Center) was not inundated in the 1D (WMS) model but inundated in the 2D (FLUMEN) model.

Assessment of Performance on the Asian Dust Generation in Spring Using Hindcast Data in Asian Dust Seasonal Forecasting Model (황사장기예측자료를 이용한 봄철 황사 발생 예측 특성 분석)

  • Kang, Misun;Lee, Woojeong;Chang, Pil-Hun;Kim, Mi-Gyeong;Boo, Kyung-On
    • Atmosphere
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    • v.32 no.2
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    • pp.149-162
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    • 2022
  • This study investigated the prediction skill of the Asian dust seasonal forecasting model (GloSea5-ADAM) on the Asian dust and meteorological variables related to the dust generation for the period of 1991~2016. Additionally, we evaluated the prediction skill of those variables depending on the combination of the initial dates in the sub-seasonal scale for the dust source region affecting South Korea. The Asian dust and meteorological variables (10 m wind speed, 1.5 m relative humidity, and 1.5 m air temperature) from GloSea5-ADAM were compared to that from Synoptic observation and European Centre for medium range weather forecasts reanalysis v5, respectively, based on Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC) as evaluation criteria. In general, the Asian dust and meteorological variables in the source region showed high ACC in the prediction scale within one month. For all variables, the use of the initial dates closest to the prediction month led to the best performances based on MBE, RMSE, and ACC, and the performances could be improved by adjusting the number of ensembles considering the combination of the initial date. ACC was as high as 0.4 in Spring when using the closest two initial dates. In particular, the GloSea5-ADAM shows the best performance of Asian dust generation with an ACC of 0.60 in the occurrence frequency of Asian dust in March when using the closest initial dates for initial conditions.