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Study of Short Term Climatic Prediction Method Based on EMD and Ensemble Prediction

Author: ChenZhu
Tutor: BiShuoBen
School: Nanjing University of Information Engineering
Course: Applied Computer Technology
Keywords: Mean generating function Support Vector Machine Fuzzy time series prediction Empirical Mode Decomposition Ensemble forecasting technology
CLC: P456
Type: Master's thesis
Year: 2011
Downloads: 119
Quote: 0
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Abstract


The climate system is a typical non-stationary system , climate observation data processing , however , is usually done under the assumption of steady time series , such as temperature and precipitation forecasts . This has led to the prediction accuracy is usually low , and most of the forecasting methods belong to a single method to predict the results uncertain . In this paper, the three classical time series prediction method to improve the defect and for the characteristics of each of the two new time series forecasting improved method , select the Guangxi autonomous region 88 meteorological observation stations the 1957-2005 February year-on-year temperature anomalies Percentage 6-8 months yearly precipitation anomaly percentage sequence as the experimental data , the content and preliminary conclusions of the study are as follows : (1) empirical mode decomposition (EMD) in the raw data input of the new method of processing data sequence , combined with the ordinary time series forecasting method algorithm for initial improvement . By contrast proven that the original time series smoothing treatment did reduce non-stationary characteristics of the sequence prediction results to improve prediction accuracy . (2 ) the predictions side join the ensemble prediction techniques , different predictions integrated to achieve further improved algorithm , experiments show that relative to the direct prediction , the final prediction model is effective in the case of using only historical data to forecast grasp of climate change trends and sudden changes of climate , having a high prediction accuracy . (3 ) This paper describes the algorithm and improved algorithm prediction model for forecasting systems , various system modules and special modules run time series complexity of the requirements and the atmosphere for climate prediction , design , has a certain practical generalization ability .

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CLC: > Astronomy,Earth Sciences > Atmospheric science (meteorology ) > Weather Forecast > Forecasting Methods
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