A TIME SERIES FORECASTING MODEL BASED ON LINGUISTIC FORECASTING RULES - TRƯỜNG ĐẠI HỌC HỒNG ĐỨC

This study proposes the so-called linguistic time series, in which words with their own semantics are used instead of fuzzy sets. By this, forecasting linguistic logical relationships can be established based on the time series variations and this is clearly useful for human users. The effect of the[r]

6.1.1 The Data
We make use of quantity and price data for automobiles, as well as an interest rate and a disposable income as aggregate variables. The quantity variable represents the aggregate production of new vehicles, excluding heavy trucks and machinery, obtained from the Bureau of Eco[r]

EXECUTIVE SUMMARY
Executives must include some form of forecasting in nearly all decisions they make as most
operating decisions rely on “the future” as a significant input. As a result, good forecasting is
a necessity. The more management understands forecasting techniques and processes and
how[r]

In this paper, a deep learning method is introduced, named as Long Short-Term Memory (LSTM) (Hochreiter and Schmidhuber, 1997), which ap- plies a sequence of observed va[r]

λiq eigenvalue of matrix Kq TRANG 13 m number of points in a complex q number of points in a sub-complex pmin minimum number of complexes required in population α number of consecutive o[r]

Ch. 15: Volatility and Correlation Forecasting 781
1.1. Basic notation and notions of volatility
We first introduce some notation that will allow us to formalize the discussion of the different models and volatility concepts considered throughout the chapter. As noted above, although it[r]

Chapter 2 – tsunami dynamics, forecasting, and mitigation Chapter 2 – tsunami dynamics, forecasting, and mitigation Chapter 2 – tsunami dynamics, forecasting, and mitigation Chapter 2 – tsunami dynamics, forecasting, and mitigation Chapter 2 – tsunami dynamics, forecasting, and mitigation Chapter 2[r]

In this study, _ three time series forecasting models, Artificial Neural Network ANN, ARIMAX and ARIMAX-ANN Hybrid models were compared to forecast the damage caused by Yellow Stem borer[r]

Consequently, That means determining the set of parameters of AX model needs to be consistent with the context of problem of the forecasting student enrollment number at the Alabama Univ[r]

Chapter 8 - Exchange rate forecasting, technical analysis and trading rules. The objectives of this chapter are: To explain why exchange rate forecasting is needed, to illustrate forecasting techniques, to explain how to evaluate the performance of forecasters,...

Next, we examine experiments using that data set by Stark and Croushore (2002), Journal of Macroeconomics 24, 507–531, to illustrate how the data revisions could have affected reasonable univariate forecasts. In doing so, we tackle the issues of what vari- ables are used as “actuals” in evaluating f[r]

REFIT= keyword
(for macro usage) refits a previously saved forecasting model by using the current fit range; that is, it reestimates the model parameters. Refitting also causes the model to be reevaluated (statistics of fit recomputed), and it causes the time<[r]

TRANG 1 880 ORIGINAL RESEARCH ARTICLE https://doi.org/10.20546/ijcmas.2018.712.110 TIME SERIES FORECASTING USING ARIMA AND ANN MODELS FOR PRODUCTION OF PEARL MILLET BAJRA CROP OF KARNATA[r]

 Screening a broad scope of information on global forces that Screening a broad scope of information on global forces that might affect the organization.
might affect the organization.
 Has value to firms with significant global interests. Has value to firms with[r]

Fig. 56.8. The TimeSearcher visual query interface. A user can filter away sequences that are
not interesting by insisting that all sequences have at least one data point within the query boxes
Cluster and Calendar-Based Visualization (Wijk and Selow, 1999) is a visualization[r]

There are two key problems with stress testing. The first is the lack of a mechanism to reliably judge the probability of a stress test scenario since they are both highly sub- jective and difficult to pinpoint. For example, it might sound interesting to create a scenario in which[r]

Lecture 9 - Forecasting exchange rates. After completing this chapter, students will be able to: To explain how firms can benefit from forecasting exchange rates; to describe the common techniques used for forecasting; and to explain how forecasting performance can be evaluated.

In practice, another common reason for refitting models is the availability of new data. For example, when data for a new month become available for a monthly series, you might add them to the input data set, then invoke the forecasting system, open the project containing[r]

Visualization plays an important role in epidemic time series analysis and forecasting. Viewing time series data plotted on a graph can help researchers identify anomalies and unexpected trends that could be overlooked if the data were reviewed in tabular form; these details can influence a research[r]

Very few of proposed approaches have explicitly addressed the problem of modeling spikes. Some authors have used data mining approach to model spikes uncertainty, their level and the associated confidence interval, while wavelet-neural cascade technique for normal level prices. Bayesian ex[r]