• Title/Summary/Keyword: forecasting spectrum

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Forecasting Methodology of the Radio Spectrum Demand (무선자원 서비스 수요예측 방안)

  • Kim Jeom-Gu;Jang Hee-Seon;shin Hyun-Cheul
    • The Journal of Information Technology
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    • v.5 no.4
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    • pp.173-183
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    • 2002
  • In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group.

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The Forecasting Power Energy Demand by Applying Time Dependent Sensitivity between Temperature and Power Consumption (시간대별 기온과 전력 사용량의 민감도를 적용한 전력 에너지 수요 예측)

  • Kim, Jinho;Lee, Chang-Yong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.1
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    • pp.129-136
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    • 2019
  • In this study, we proposed a model for forecasting power energy demand by investigating how outside temperature at a given time affected power consumption and. To this end, we analyzed the time series of power consumption in terms of the power spectrum and found the periodicities of one day and one week. With these periodicities, we investigated two time series of temperature and power consumption, and found, for a given hour, an approximate linear relation between temperature and power consumption. We adopted an exponential smoothing model to examine the effect of the linearity in forecasting the power demand. In particular, we adjusted the exponential smoothing model by using the variation of power consumption due to temperature change. In this way, the proposed model became a mixture of a time series model and a regression model. We demonstrated that the adjusted model outperformed the exponential smoothing model alone in terms of the mean relative percentage error and the root mean square error in the range of 3%~8% and 4kWh~27kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric energy together with the outside temperature.

A Study on the Seasonal Decomposition of the Railway Passenger Demand (철도수요의 시계열 분해 방법에 대한 연구)

  • 오석문;김동희
    • Proceedings of the KSR Conference
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    • 2001.10a
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    • pp.111-116
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    • 2001
  • This paper introduces how to adopt the X-12-ARIMA to decompose the railway passenger demand of the Korea National Railroad Especially, selecting on proper filters is focused. The trend filter is identical to the low pass filter in the signal Processing field, and so the seasonal filter is to band pass filter too. Some considerations, selecting a filter, are provided from the view-point of the spectrum analysis. The technique introduced in this paper will be adopted to the project that is to develope the forecasting system of Korea railway passenger demand which is a part of the high speed rail information system.

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Ocean Wave Forecasting and Hindercasting Method to Support for Navigational Safety of Ship (선박의 항행안전지원을 위한 파랑추산에 관한 연구)

  • Shin, Seung-Ho;Hashimoto, Noriaki
    • Journal of Navigation and Port Research
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    • v.27 no.2
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    • pp.111-119
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    • 2003
  • In order to improve navigational safety of ships, an ocean wave prediction model of high precision within a short time, dealing with multi-directional random waves from the information of the sea surface winds encountered at the planned ship's course, was introduced for construction of ocean wave forecasting system on the ship. In this paper, we investigated a sea disaster occurred by a stormy weather in the past. We analyzed the sea surface wind first and then carried out ocean wave hindercasting simulations according to the routes the sunken vessel. From the result of this study, we concluded that the sea disaster was caused by rapidly developed iou pressure system Okhotsk Sea and the predicted values by the third generation wave prediction model(WAM) was agreed well with the observed significant wave height, wave period, and directional wave spectrum. It gives a good applicability for construction of a practical on-board calculation system.

Ocean wave forecasting and hindercasting method to support for navigational safety of ship (선박의 항행안전지원을 위한 파낭추산에 관한 연구)

  • 신승호;교본전명
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2003.05a
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    • pp.147-156
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    • 2003
  • In order to improve navigational safety of ships, on ocean wave prediction model of high precision within a short time, dealing with multi-directional random waves from the information of the sea surface winds encountered at the planned ship's course, was introduced for construction of ocean wave forecasting system on the ship. In this paper, we investigated a sea disaster occurred by a stormy weather in the past. We analyzed the sea surface winds first and then carried out ocean wave hindercasting simulations according to the routes of the sunken vessel. From the result of this study, we concluded that the sea disaster was caused by rapidly developed low pressure system in Okhotsk Sea and the predicted values by the third generation wave prediction model(WAM) was agreed well with the observed significant wave height, was period, and directional wave spectrum. It gives a good applicability for construction of a practical on-board calculation system.

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Fatigue wind load spectrum construction based on integration of turbulent wind model and measured data for long-span metal roof

  • Liman Yang;Cong Ye;Xu Yang;Xueyao Yang;Jian-ge Kou
    • Wind and Structures
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    • v.36 no.2
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    • pp.121-131
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    • 2023
  • Aiming at the problem that fatigue characteristics of metal roof rely on local physical tests and lacks the cyclic load sequence matching with regional climate, this paper proposed a method of constructing the fatigue load spectrum based on integration of wind load model, measured data of long-span metal roof and climate statistical data. According to the turbulence characteristics of wind, the wind load model is established from the aspects of turbulence intensity, power spectral density and wind pressure coefficient. Considering the influence of roof configuration on wind pressure distribution, the parameters are modified through fusing the measured data with least squares method to approximate the actual wind pressure load of the roof system. Furthermore, with regards to the wind climate characteristics of building location, Weibull model is adopted to analyze the regional meteorological data to obtain the probability density distribution of wind velocity used for calculating wind load, so as to establish the cyclic wind load sequence with the attributes of regional climate and building configuration. Finally, taking a workshop's metal roof as an example, the wind load spectrum is constructed according to this method, and the fatigue simulation and residual life prediction are implemented based on the experimental data. The forecasting result is lightly higher than the design standards, consistent with general principles of its conservative safety design scale, which shows that the presented method is validated for the fatigue characteristics study and health assessment of metal roof.

Seismic damage potential described by intensity parameters based on Hilbert-Huang Transform analysis and fundamental frequency of structures

  • Tyrtaiou, Magdalini;Elenas, Anaxagoras
    • Earthquakes and Structures
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    • v.18 no.4
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    • pp.507-517
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    • 2020
  • This study aims to present new frequency-related seismic intensity parameters (SIPs) based on the Hilbert-Huang Transform (HHT) analysis. The proposed procedure is utilized for the processing of several seismic accelerograms. Thus, the entire evaluated Hilbert Spectrum (HS) of each considered seismic velocity time-history is investigated first, and then, a delimited area of the same HS around a specific frequency is explored, for the proposition of new SIPs. A first application of the suggested new parameters is to reveal the interrelation between them and the structural damage of a reinforced concrete frame structure. The index of Park and Ang describes the structural damage. The fundamental frequency of the structure is considered as the mentioned specific frequency. Two statistical methods, namely correlation analysis and multiple linear regression analysis, are used to identify the relationship between the considered SIPs and the corresponding structural damage. The results confirm that the new proposed HHT-based parameters are effective descriptors of the seismic damage potential and helpful tools for forecasting the seismic damages on buildings.

Field Wave Data Analysis for Investigation of Freak wave Characteristics (Freak wave 특성 파악을 위한 파랑관측 자료의 분석)

  • Shin, Seung-Ho;Hong, Key-Yong;Moon, Jae-Seung
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.175-180
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    • 2006
  • This study is carried out the investigation of nonlinear characteristics of the ocean based on the field wave observation data acquired the western sea area in Jeju island during one year. It is aimed to offer the fundamental data for Freak wave forecasting in real sea. For this, the nonlinearity parameters of ocean waves, which are Skewness, Atiltness, Kurtosis and Spectrum band width parameter, are introduced, and the parameters are compared and discussed with some characteristic wave components, ie, significant wave height, maximum wave height, and so on.

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Wave Data Analysis for Investigation of Freak wave Characteristics (Freak Wave 특성 파악을 위한 파랑관측 자료의 분석)

  • Shin, Seung-Ho;Hong, Key-Yong;Moon, Jae-Seung
    • Journal of Navigation and Port Research
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    • v.31 no.6
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    • pp.471-478
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    • 2007
  • This study is carried out the investigation of nonlinear characteristics of the field wave observation data acquired in the western sea area in Jeju island during one year. It is aimed to offer the fundamental data for Freak wave forecasting in real sea. For this, the nonlinear parameters of ocean waves, which are Skewness, Atiltness, Kurtosis and Spectrum band width parameter et al., are introduced, and the parameters are compared and discussed with some characteristics wave components, ie, significant wave height, maximum wave height, and so on. As a results, we know that the parameters describe nonlinear characteristics of observed wave spectrum broadly, are feebly related with occurrence of abnormal maximum wave height, namely freak event, however the Kurtosis, $K_t$ which is a degree of peakness of mode of surface elevation distribution, has better relationship than others.

Stochastic Properties of Air Quality Variation in Seoul (서울시 광화물 지역의 대기질 변동 특성의 추계학적 분석)

  • Han, Hong;Kim, Young-Sik
    • 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.

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