Time Series Prediction of Earthquake Input by using Soft Computing Hitoshi FURUTA‚ Yasutoshi NOMURA Department of Informatics‚ Kansai University‚ Takatsuki‚ Osaka569-1095‚ Japan nomura@sc.kutc.kansai-u.ac.jp Abstract Time series analysis is one of important issues in science‚ engineering‚ and so on. Up to the present statistical methods[1] such as AR model[2] and Kalman filter[3] have been successfully applied‚ however‚ those statistical methods may have problems for solving highly nonlinear
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As the operations manager of Colsam Company Limited‚ I have been tasked to make a presentation to management on the importance of forecasting. The presentation would be done along the following lines. * THE MEANING OF FORECASTING * STEPS USED TO DEVELOP A FORECASTING SYSTEM * QUALITATIVE FORECASTING * QUANTITATIVE FORECASTING * BENEFITS OF FORECASTING THE MEANING OF FORECASTING A planning tool that helps management in its attempts to cope with the uncertainty of the future
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report on the time-series analysis of continuously compounded returns for Ford and GM for the periods January 2002 till April 2007 using monthly stock prices. This analysis is aimed at estimating the ARIMA model that provides the best forecast for the series. This paper will be divided into 2 sections; the first section showing the Ford analysis and the second the GM analysis. Section 1: Ford Figure 1: Time series plot for raw Ford data. Figure 1 shows a time series plot of the raw
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Series FOURIER SERIES Graham S McDonald A self-contained Tutorial Module for learning the technique of Fourier series analysis q Table of contents q Begin Tutorial c 2004 g.s.mcdonald@salford.ac.uk Table of contents 1. 2. 3. 4. 5. 6. 7. Theory Exercises Answers Integrals Useful trig results Alternative notation Tips on using solutions Full worked solutions Section 1: Theory 3 1. Theory q A graph of periodic function f (x) that has period L exhibits the same pattern every L units along the
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Secondary Research Time Series Analysis VARIABLE FACTOR THAT INCREASING MALAYSIA GDP Prepared by: Dina Maya Avinati Wery Astuti Faculty of Business UNIVERSITAS SISWA BANGSA INTERNATIONAL Mulia Business Park‚ JL. MT. Haryono Kav. 58-60 Pancoran- South Jakarta Page | 1 CONTENT I. Introduction 1.1 Back Ground of Study 1.2 Problem 1.3 Research Problem 1.4 Research Objective 1.5 Scope and Limitation 1.6 Significant of Study II. Literature Review
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Chapter 4 Chapter 4 Electric Circuits Fundamentals - Floyd © Copyright 2007 Prentice-Hall Chapter 4 Series circuits Summary All circuits have three common attributes. These are: 1. A source of voltage. 2. A load. 3. A complete path. VS + R3 R1 R2 Electric Circuits Fundamentals - Floyd © Copyright 2007 Prentice-Hall Chapter 4 Series circuits Summary A series circuit is one that has only one current path. R1 R1 R2 R3 VS R3 R2 VS R1 R2 R3 VS
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PART 2 : FOURIER SERIES Objective : 1. To show that any periodic function (or signal) can be represented as a series of sinusoidal (or complex exponentials) function. 2. To show and to study hot to approximate periodic functions using a finite number of sinusoidal function and run the simulation using MATLAB. Scope : In experiment 1‚ students need to learn using MATLAB by connect it with Fourier series‚ where students must know how the output changes as higher order terms are added
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Fourier Series Fourier series started life as a method to solve problems about the flow of heat through ordinary materials. It has grown so far that if you search our library’s data base for the keyword “Fourier” you will find 425 entries as of this date. It is a tool in abstract analysis and electromagnetism and statistics and radio communication and . . . . People have even tried to use it to analyze the stock market. (It didn’t help.) The representation of musical sounds as sums of waves of various
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TIME SERIES MODELS Time series analysis provides tools for selecting a model that can be used to forecast of future events. Time series models are based on the assumption that all information needed to generate a forecast is contained in the time series of data. The forecaster looks for patterns in the data and tries to obtain a forecast by projecting that pattern into the future. A forecasting method is a (numerical) procedure for generating a forecast. When such methods are not based upon
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Regression with Time Series Data Week 10 Main features of Time series Data Observations have temporal ordering Variables may have serial correlation‚ trends and seasonality Time series data are not a random sample because the observations in time series are collected from the same objects at different points in time For time series data‚ because MLR2 does not hold‚ the inference tools are valid under a set of strong assumptions (TS1-6) for finite samples While TS3-6 are often too restrictive
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