• Title/Summary/Keyword: box-jenkins

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Statistical Analysis of Transfer Function Models with Conditional Heteroscedasticity

  • Baek, J.S.;Sohn, K.T.;Hwang, S.Y.
    • Journal of the Korean Statistical Society
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    • v.31 no.2
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    • pp.199-212
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    • 2002
  • This article introduces transfer function model (TFM) with conditional heteroscedasticity where ARCH concept is built into the traditional TFM of Box and Jenkins (1976). Model building strategies such as identification, estimation and diagnostics of the model are discussed and are illustrated via empirical study including simulated data and real data as well. Comparisons with the classical TFM are also made.

A study of short-term load forecasting in consideration of the weather conditions (대기상태를 고려한 단기부하예측에 관한 연구)

  • 김준현;황갑주
    • 전기의세계
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    • v.31 no.5
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    • pp.368-374
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    • 1982
  • This paper describes a combined algorithm for short-term-load forecating. One of the specific features of this algorithm is that the base, weather sensitive and residual components are predicted respectively. The base load is represented by the exponential smoothing approach and residual load is represented by the Box-Jenkins methodology. The weather sensitive load models are developed according to the information of temperature and discomfort index. This method was applied to Korea Electric Company and results for test periods up to three years are given.

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A Study on Development of Economic Instability Index

  • Do, Jong-Doo;Song, Gyu-Moon;Kim, Tae-Yoon
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.355-365
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    • 2004
  • Kim et al.. (2003) developed an Economic Instability Index (EII) by using mean squared error (MSE) from the neural network (NN) trained on the 1995 KOSPI. In this paper we study validity of the NN. For this we compare the NN with the well known Box-Jenkins linear auto-regressive processes. Our conclusive understanding of the problem is that the NN provides quite effective EII because it tends to overfit.

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Fuzzy Logic-based Modeling of a Score (퍼지 이론을 이용한 악보의 모델링)

  • 손세호;권순학
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.3
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    • pp.264-269
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    • 2001
  • In this paper, we interpret a score as a time series and deal with the fuzzy logic-based modeling of it. The musical notes in a score represent a lot of information about the length of a sound and pitches, etc. In this paper, using melodies, tones and pitches in a score, we transform data on a score into a time series. Once more, we foml the new Lime series by sliding a window through the time series. For analyzing the time series data, we make use of the Box-Jenkins s time series analysis. On the basis of the identified characteristics of time series, we construct the fuzzy model.

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An Automatic Fuzzy Rule Extraction using Fuzzy Equalization and GA (퍼지 균등화와 유전알고리즘에 의한 자동적인 퍼지 규칙 생성)

  • 곽근창;김승석;유정웅;전명근
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.121-125
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    • 2001
  • 본 논문에서는 자동적인 퍼지 규칙 생성을 위해 퍼지 균등화(Fuzzy Equalization)와 유전알고리즘(Genetic Algorithm)을 이용한 TSK 퍼지 시스템의 구축을 다룬다. Pedrycz에 의해 제안된 퍼지 균등화 방법은 수치적인 데이터로부터 확률분포함수를 구축한 후 전체공간상에서 이들을 적절히 표현할 수 있는 소속함수를 생성한다. 이렇게 구축된 각 입력에 대한 소속함수는 유전알고리즘에 의해 입력공간이 분할되며 결론부 파라미터는 최소자승법에 의해 추정되어 진다. 제안된 방법은 그리드 분할로 인해 규칙의 수가 증가하는 문제를 해결하고 학습데이터와 검증데이터에 의해 타당한 입력공간분할과 퍼지 규칙을 생성할 수 있다. 시뮬레이션의 예로서 Box-Jenkins의 가스로 데이터의 모델링에 적용하여 제안된 방법의 유용성을 알 수 있다.

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A Model for Groundwater Time-series from the Well Field of Riverbank Filtration (강변여과 취수정 주변 지하수위를 위한 시계열 모형)

  • Lee, Sang-Il;Lee, Sang-Ki;Hamm, Se-Yeong
    • Journal of Korea Water Resources Association
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    • v.42 no.8
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    • pp.673-680
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    • 2009
  • Alternatives to conventional water resources are being sought due to the scarcity and the poor quality of surface water. Riverbank filtration (RBF) is one of them and considered as a promising source of water supply in some cities. Changwon City has started RBF in 2001 and field data have been accumulated. This study is to develop a time-series model for groundwater level data collected from the pumping area of RBF. The site is Daesan-myeon, Changwon City, where groundwater level data have been measured for the last five years (Jan. 2003$\sim$Dec. 2007). Minute-based groundwater levels was averaged out to monthly data to see the long-term behavior. Time-series analysis was conducted according to the Box-Jenkins method. The resulted model turned out to be a seasonal ARIMA model, and its forecasting performance was satisfactory. We believe this study will provide a prototype for other riverbank filtration sites where the predictability of groundwater level is essential for the reliable supply of water.

Predictive Analysis of Traffic Accidents caused by Negligence of Safe Driving in Elderly using Seasonal ARIMA (계절 ARIMA 모형을 이용한 고령운전자의 안전운전불이행에 의한 교통사고건수 예측분석)

  • Kim, Jae-Moon;Chang, Sung-Ho;Kim, Sung-Soo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.1
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    • pp.65-78
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    • 2017
  • Even though cars have a good effect on modern society, traffic accidents do not. There are traffic laws that define the regulations and aim to reduce accidents from happening; nevertheless, it is hard to determine all accident causes such as road and traffic conditions, and human related factors. If a traffic accident occurs, the traffic law classifies it as 'Negligence of Safe Driving' for cases that are not defined by specific regulations. Meanwhile, as Korea is already growing rapidly elderly population with more than 65 years, so are the number of traffic accidents caused by this group. Therefore, we studied predictive and comparative analysis of the number of traffic accidents caused by 'Negligence of Safe Driving' by dividing it into two groups : All-ages and Elderly. In this paper, we used empirical monthly data from 2007 to 2015 collected by TAAS (Traffic Accident Analysis System), identified the most suitable ARIMA forecasting model by using the four steps of the Box-Jenkins method : Identification, Estimation, Diagnostics, Forecasting. The results of this study indicate that ARIMA $(1, 1, 0)(0, 1, 1)_{12}$ is the most suitable forecasting model in the group of All-ages; and ARIMA $(0, 1, 1)(0, 1, 1)_{12}$ is the most suitable in the group of Elderly. Then, with this fitted model, we forecasted the number of traffic accidents for 2 years of both groups. There is no large fluctuation in the group of All-ages, but the group of Elderly shows a gradual increase trend. Finally, we compared two groups in terms of the forecast, suggested a countermeasure plan to reduce traffic accidents for both groups.

Data Analysis and Mining for Fish Growth Data in Fish-Farms (양식장 어류 생육 데이터 분석 및 마이닝)

  • Seoung-Bin Ye;Jeong-Seon Park;Soon-Hee Han;Hyi-Thaek Ceong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.1
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    • pp.127-142
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    • 2023
  • The management of size and weight, which are the growth information of aquaculture fish in fish-farms, is the most basic goal. In this study, the epoch is defined in fish-farms from the time of stocking or dividing to the time of shipment, and the growth data for a total of three epoch is analyzed from a time series perspective. Growth information such as the size and weight of aquaculture fish that occur over time in fish-farms is compared and analyzed with water quality environmental information and feeding information, and a model is presented using the analysis results. In this study, linear, exponential, and logarithmic regression models are presented using the Box-Jenkins method for size and weight by epoch using data obtained in the field.

A Study on the Estimation of Economic Population Statistical Model by Computer Simulation (컴퓨터 시뮬레이션에 의한 경제인구 예측 통계 모형에 관한 연구)

  • 정관희
    • Journal of the Korea Computer Industry Society
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    • v.4 no.12
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    • pp.1033-1042
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    • 2003
  • In this study, the economic population prediction by computer simulation has been studied by using statistical model. The forecast of future population based on that of the past is a very difficult problem as uncertain conditions are modeled in it. Even if a thought forecast is possible, world-wide cultures and the local culture emotion the cultures of the world and out country can not be predicted due to rapid change and the estimation of population is ‘nowadays more and more’ difficult to be made good guess. In the estimation of economic population, by using the census population from 1960 to 1990, and using ARIMA model developed by Box and Jenkins, the estimation has been done on the economic population until 2021 according to age as appeared table and appendix. This kind of forecast would have both good point and weak point of ARIMA model theory saying that prediction can be done only by the economic population.

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Nonlinear System Modeling using Independent Component Analysis and Neuro-Fuzzy Method (독립 성분 분석기법과 뉴로-퍼지를 이용한 비선형 시스템 모델링)

  • 김성수;곽근창;유정웅
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.5
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    • pp.417-422
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    • 2000
  • In this paper, an efficient fuzzy rule generation scheme for adaptive neuro-fuzzy system modeling using the Independent Component Analysis(ICA) as a preprocessing is proposed. Correlation between inputs was not considered in the conventional neuro- fuzzy modeling schemes, such that enormous number of rules and large amount of error were unavoidable. The correlation between inputs is weakened by employing ICA so that the number of rules and the amount of error are reduced. In simulation, the Box-Jenkins furnace data is used to verify the effectiveness of the proposed method.

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