Non-stationary fluctuating wind speed forecasting method based on EMD-ELM

A technology of fluctuating wind speed and prediction method, applied in instruments, character and pattern recognition, computer parts and other directions, can solve problems such as large analysis errors, influence analysis accuracy, wind speed records that do not meet the requirements of stability, and ensure accuracy. Effect

Inactive Publication Date: 2015-12-30
SHANGHAI UNIV
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Problems solved by technology

Analysis of a large number of actual test data shows that many wind speed records under complex terrain in strong wind environment do not meet this stability requirement
Especially in the non-stationary fluctuating wind environment with complex terrain and strong wind

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  • Non-stationary fluctuating wind speed forecasting method based on EMD-ELM
  • Non-stationary fluctuating wind speed forecasting method based on EMD-ELM
  • Non-stationary fluctuating wind speed forecasting method based on EMD-ELM

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Embodiment Construction

[0030] The idea of ​​the present invention is as follows: First, the non-stationary pulsating wind speed at this point is decomposed into a series of relatively stable components by empirical mode decomposition; then each component is predicted separately, and the method of each component prediction adopts the time-varying extreme learning machine Autoregressive moving average model; finally, the prediction results of each component at this point are superimposed to obtain the final predicted wind speed.

[0031] The non-stationary fluctuating wind speed prediction method based on EMD-ELM of the present invention comprises the following steps:

[0032] The first step is to use the time-varying autoregressive moving average model (TARMA) to simulate and generate non-stationary fluctuating wind speed samples, divide the fluctuating wind speed samples into training set and test set, and use Matlab to normalize the samples;

[0033] In the first step, the time-varying autoregressi...

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Abstract

The invention provides a non-stationary fluctuating wind speed forecasting method based on EMD-ELM. The method comprises the following steps: generating a non-stationary fluctuating wind speed sample by utilizing a TARMA model in a simulated manner, and dividing the fluctuating wind speed sample into a training set and a test set two parts, and carrying out normalization processing on the sample by utilizing Matlab; carrying out EMD processing on time sequence of the non-stationary fluctuating wind speed sample, and decomposing non-stationary nonlinear fluctuating wind signals into a group of stationary and linear sequence sets; carrying out phase-space reconstruction on the group of IMFs, and establishing corresponding ELM prediction models respectively; and carrying out superposition on the forecast results of the group of IMFs to obtain forecasted non-stationary fluctuating wind speed of the point, meanwhile, comparing the test sample with the forecasted non-stationary fluctuating wind speed result, and calculating average error, root-mean-square error and correlation coefficient of the forecasted wind speed and the actual wind speed. The invention provides a fast-speed and good-effect method for non-stationary fluctuating wind speed prediction.

Description

technical field [0001] The invention relates to a single-point non-stationary fluctuating wind speed prediction method using the combination of empirical mode decomposition (EMD) and extreme learning machine (ELM), specifically a non-stationary fluctuating wind speed prediction method based on EMD-ELM. Background technique [0002] For long-span space structures, long-span bridges, high-rise building structures, and high-rise structures, such as guyed masts, TV towers, chimneys and other buildings, wind load is one of the control loads for structural wind resistance design. The wind resistance analysis of the structure must first obtain the sample data of the wind load. At present, the main research methods to determine the wind engineering include theoretical analysis, numerical simulation, wind tunnel test and field measurement. With the rapid development of computer technology and people's in-depth research on numerical simulation technology of stochastic processes, the u...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2411
Inventor 李春祥钟旺
Owner SHANGHAI UNIV
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