• Title/Summary/Keyword: Time Factor Model

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6-Parametric factor model with long short-term memory

  • Choi, Janghoon
    • Communications for Statistical Applications and Methods
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    • v.28 no.5
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    • pp.521-536
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    • 2021
  • As life expectancies increase continuously over the world, the accuracy of forecasting mortality is more and more important to maintain social systems in the aging era. Currently, the most popular model used is the Lee-Carter model but various studies have been conducted to improve this model with one of them being 6-parametric factor model (6-PFM) which is introduced in this paper. To this new model, long short-term memory (LSTM) and regularized LSTM are applied in addition to vector autoregression (VAR), which is a traditional time-series method. Forecasting accuracies of several models, including the LC model, 4-PFM, 5-PFM, and 3 6-PFM's, are compared by using the U.S. and Korea life-tables. The results show that 6-PFM forecasts better than the other models (LC model, 4-PFM, and 5-PFM). Among the three 6-PFMs studied, regularized LSTM performs better than the other two methods for most of the tests.

Forecasting Total Marine Production through Multiple Time Series Model

  • Cho, Yong-Jun
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.63-76
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    • 2006
  • Marine production forecasting in fisheries is a crucial factor for managing and maintaining fishery resources. Thus this paper aims to generate a forecasting model of total marine production. The most generally method of time series model is to generate the most optimal single forecasting model. But the method could induce a different forecasting results when it does not properly infer a model To overcome the defect, I am trying to propose a single forecasting through multiple time series model. In other word, by comparing and integrating the output resulted from ARIMA and VAR model (which are typical method in a forecasting methodology), I tried to draw a forecasting. It is expected to produce more stable and delicate forecasting prospect than a single model. Through this, I generated 3 models on a yearly and monthly data basis and then here I present a forecasting from 2006 to 2010 through comparing and integrating 3 models. In conclusion, marine production is expected to show a decreasing tendency for the coming years.

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Channel Routing Model for Streamflow Forecasting (유출예측을 위한 하도추적 모형)

  • 지홍기;박기호
    • Water for future
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    • v.27 no.1
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    • pp.141-150
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    • 1994
  • The purpose of this study is develope the algorithm of channel routing model which can be used for flood forecasting. In routing model, the hydrulic technique of the implicit scheme in the dynamic equation is chosen to route the unsteady varied flow. The channel routing model is connected with conceptual watershed model which is able to compute the flood hydrograph from each subbasin. The comparative study shows that the conceptual model can simulate the watershed runoff accurately. As a result of investigating the channel routing model, the optimal weighting factor $\theta$ which fixes two points between time line is selected. And also, the optimal error tolerance which satisfies computing time and converge of solution is chosen.

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Proposal of Practical Reference-Model and It's Performance Improvement for PID Control (PID제어를 위한 실용적인 기준 모델 제안과 성능개선)

  • Hur, J.G.;Yang, K.U.
    • Journal of Power System Engineering
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    • v.11 no.3
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    • pp.66-72
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    • 2007
  • This study proposed new method to decide the reference model necessary for design PID controller. In generally, control design problems using the reference model have the following two factors. One factor is that numerical model of the controlled system can be obtained extremely, and the other is that specification for the closed-loop dynamic performance is pure moderate. Therefore, the control design procedure is essentially based on the partial reference model matching which offers a reasonable method to simplify the design and the controller configuration under the controlled system uncertainty. ITAE(Integral of time-multiplied absolute error) performance index and Kitamori method etc. which were used a reference model method had a limit to settling time and rising time of reference model that it arrived to steady state response according to the controlled system. On this study, if it only knew peak time of overshoot and settling time by measurement signal of the controlled system, it can be made the reference model easily. We proposed new method to improve performance index of the reference model superior to existing reference model index and illustrate the numerical simulation results to show the effectiveness of proposed control method design.

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Design and Elucidation of Integrated Forecasting Model for Information Factor Analysis (정보인자분석(情報因子分析)을 위한 통합예측(統合豫測)모델의 설계(設計) 및 해석(解析))

  • Kim, Hong-Jae;Lee, Tae-Hui
    • Journal of Korean Society for Quality Management
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    • v.21 no.1
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    • pp.181-189
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    • 1993
  • Over the past two decades, forecasting has gained widespread acceptance as an integral part of business planning and decision making. Accurate forecasting is a prerequisite to successful planning. Accordingly, recent advances in forecasting techniques are of exceptional value to corporate planners. But most of forecasting mothods are reveal its limit and problem for precision and reliability duing to each relationship for raw data and possibility of explanation for each variable. Therefore, to construct the Integrated Forecasting Model(IFM) for Information Factor Analysis, it shoud be considered that whether law data has time lag and variables are explained. For this. following several method can be used : Least Square Method, Markov Process, Fibonacci series, Auto-Correlation, Cross-Correlation, Serial Correlation and Random Walk Theory. Thus, the unified property of these several functions scales the safety and growth of the system which may be varied time-to-time.

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The Comparative Study of Software Optimal Release Time of Finite NHPP Model Considering Log Linear Learning Factor (로그선형 학습요인을 이용한 유한고장 NHPP모형에 근거한 소프트웨어 최적방출시기 비교 연구)

  • Cheul, Kim Hee;Cheul, Shin Hyun
    • Convergence Security Journal
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    • v.12 no.6
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    • pp.3-10
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    • 2012
  • In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, finite failure non-homogeneous Poisson process model, considering learning factor, presented and propose release policies of the life distribution, log linear type model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameters estimation using maximum likelihood estimation of failure time data, make out estimating software optimal release time.

Characterization of gas-water flow in tight sandstone based on authentic sandstone micro-model

  • Liu, Yuqiao;Lyu, Qiqi;Luo, Shunshe
    • Geosystem Engineering
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    • v.21 no.6
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    • pp.318-325
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    • 2018
  • Eight tight sandstone reservoir samples from $He_8$ and $Shan_1$ Formations of the Sulige Gas field were selected to perform gas-water micro-displacement experiment based on authentic sandstone micro-model. The gas pressure-relief experiment was proposed for the first time to simulate the pressure change and gas-water percolation characteristics in the process of gas exploitation. The experiment results show that: (1) In the process of gas accumulation, the gas preferentially flows into the well-connected pores and throats with large radius, but rarely flows into the area without pores and throats. (2) Under sufficient gas drive, the water in pores and throats usually exists in the forms of 'thin water film', 'thick water film', and 'water column', but under insufficient gas drive, gas fails to flow into new pathways in time, so that the reservoirs with large pores and throats are high in water cut. (3) Under the same water saturation, the reservoirs with better petrophysical properties has higher gas recovery factor within unit time. Under the same petrophysical conditions, the reservoirs with lower water saturation show higher gas recovery factor within unit time. The higher the permeability, the stronger the liquid carrying capacity of reservoirs.

A Study on the Methodology for Expanding Collected Sampling Data with the RFID System and Applying in National Road Traffic Volume Survey (RFID 표본데이터의 전수화방법 및 '국가도로교통량조사'에 활용방안 연구)

  • Park, Bum-Jin;Lee, Seung-Hun;Moon, Byeong-Sup
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.7 no.3
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    • pp.29-37
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    • 2008
  • In this parer, we purpose for applying the RFID(Radio Frequency IDentification) system in National Road Traffic Volume Survey. Because there is limitation for shipping RFID Tag on every car, we firstly defined Expansion (process of making the number of all cars which passed survey point from sampling data) and determined the best methodology among 3 methodologies (Time factor Model, Fuzzy Model, Artificial Neural Network). As a result of analysis, Time Factor Model was chosen as the best methodology for Expansion. Also, we analyzed to find an application of the RFID system in National Road Traffic Volume Survey and obtained a possibility applying it. It is expected that if the RFID system is used in Traffic Volume Survey, the survey cost is saved than before.

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Optimal Pipe Replacement Analysis with a New Pipe Break Prediction Model (새로운 파괴예측 모델을 이용한 상수도 관의 최적 교체)

  • Park, Suwan;Loganathan, G.V.
    • Journal of Korean Society of Water and Wastewater
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    • v.16 no.6
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    • pp.710-716
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    • 2002
  • A General Pipe Break Prediction Model that incorporates linear and exponential models in its form is developed. The model is capable of fitting pipe break trends that have linear, exponential or in between of linear and exponential trend by using a weighting factor. The weighting factor is adjusted to obtain a best model that minimizes the sum of squared errors of the model. The model essentially plots a best curve (or a line) passing through "cumulative number of pipe breaks" versus "break times since installation of a pipe" data points. Therefore, it prevents over-predicting future number of pipe breaks compared to the conventional exponential model. The optimal replacement time equation is derived by using the Threshold Break Rate equation by Loganathan et al. (2002).

Facility Location Planning with Realistic Operation Times in Supply Chain (공급사슬에서 실제 시설물 운영시간을 고려한 시설배치계획에 관한 연구)

  • Lee Sang Heon;Kim Sook Han
    • Journal of the Korean Operations Research and Management Science Society
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    • v.30 no.2
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    • pp.143-156
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    • 2005
  • Facility location planning (FLP) problem is the strategic level planning in supply chain. The FLP is significantly affected by the operation time of each facility. In most of the FLP researches, operation time of facility has been treated as a fixed value. However, the operation time is not a static factor in real situations and the fixed operation time may lead unrealistic FLP. In this paper, a mixed integer programming (MIP) model is proposed for solving the 3-stage FLP problem and operation times are adjusted by the results from the simulation model and an iterative approach combining the analytic model and simulation model is proposed to obtain more realistic operation plans for FLP problems.