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Establishment method for wavelet analysis and rank set pair analysis of medium and long-term hydrological forecast model

A technology of hydrological forecasting and wavelet analysis, which is applied in special data processing applications, instruments, electrical digital data processing, etc., and can solve the problems that the forecasting method does not consider the influence of noise sequence characteristics, the distribution of useful signals is uneven, and the purpose of forecasting cannot be achieved, etc. , to achieve the effects of high model prediction accuracy, clear construction concept, and improved pass rate

Inactive Publication Date: 2012-11-21
NANJING UNIV
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  • Application Information

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Problems solved by technology

[0005] From a comprehensive analysis, it can be seen that the current traditional forecasting methods mainly have the following two problems: First, each method has its own limitations, so a single method cannot achieve good forecasting purposes, and it is necessary to explore the advantages and disadvantages of multiple methods. joint use
Although the set pair analysis method has many advantages over other traditional hydrological sequence forecasting methods, there are still problems such as low forecasting accuracy and inaccurate extreme value forecasting.
Second, most forecasting methods do not consider the impact of noise on sequence characteristics. Traditional hydrological time series denoising methods have their own deficiencies in denoising sequences. How to reasonably and effectively eliminate sequence noise and restore sequence characteristics is a key issue for hydrological time series. A key point of the forecast
Therefore, the useful signal is unevenly distributed in the time domain

Method used

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  • Establishment method for wavelet analysis and rank set pair analysis of medium and long-term hydrological forecast model
  • Establishment method for wavelet analysis and rank set pair analysis of medium and long-term hydrological forecast model
  • Establishment method for wavelet analysis and rank set pair analysis of medium and long-term hydrological forecast model

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Embodiment 1

[0040] A method for establishing a medium- and long-term hydrological forecast model by wavelet analysis and rank set pair analysis, comprising the following steps:

[0041] (1) The known continuous n-year hydrological time series {rf t},t=1,2,...,n as the input data of the model; select the appropriate number of decomposition layers according to the basic characteristics of the hydrological time series to be analyzed, and perform wavelet decomposition and denoising on the hydrological time series through different wavelet functions According to the similarity between the original hydrological sequence and the initial denoising sequence, the appropriate wavelet function is selected, the threshold value and quantification method are determined, and the hydrological time series is analyzed Denoise processing to get the final denoising sequence {x t},t=1,2,...,n;

[0042] (2) Set the denoising sequence {x t},t=1,2,...,n in x t and its previous T historical values ​​x t-1 ,x ...

Embodiment 2

[0047] Based on the annual runoff sequence from 1956 to 2010 at Sanmenxia Station on the Yellow River, the annual runoff from 2002 to 2010 was forecasted. The forecast method is one-step forecasting, that is, when forecasting the annual runoff in 2002, use the data from 1956 to 2001, when forecasting the annual runoff in 2007, use the data from 1956 to 2006, and so on. The db6 wavelet function and the dmey wavelet function are selected as the denoising wavelet function of the annual runoff sequence of the Sanmenxia Station, and the number of layers is decomposed into one layer. The threshold is obtained by using Stein's unbiased likelihood estimation and the soft threshold is denoised. For T=4, 5, 6 respectively established the WD-RSPA model.

[0048] Number of contacts S is the two sets B' in the set pair i and Y' share the number of characteristics; P is the set B' i The number of characteristics opposite to Y'; the remaining F=N-S-P is the number of characteristics that...

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Abstract

The invention discloses an establishment method for wavelet analysis and rank set pair analysis of a medium and long-term hydrological forecast model, which comprises the following steps of: combining a wavelet analysis method and a rank set pair analysis method, wherein the wavelet analysis method is mainly used for denoising an actually-measured hydrological time sequence to obtain a denoising sequence; and the rank set pair analysis method is mainly used for establishing a rank set pair forecast model and forecasting the subsequent value of the sequence. The establishment method has the beneficial effects that a WD-RSPA model, i.e. the medium and long-term hydrological forecast model established on the wavelet denoising basis is clear in establishment concept, simple in calculation and high in model forecasting precision; and the percent of pass is also improved. Therefore, the establishment method is a model forecasting method which is worth popularizing and applying.

Description

technical field [0001] The invention relates to a modeling method, in particular to a method for establishing a medium and long-term hydrological forecast model based on wavelet denoising and rank set pair analysis. Background technique [0002] The various hydrological time series obtained through hydrological tests are the output of the hydrological system under the combined effects of meteorology, the underlying surface of the watershed, and human activities, and have deterministic and random changing laws. Hydrology and water resources forecasting is based on the measured data and change characteristics of the hydrology and water resources system, combined with people's experience, judgment and knowledge, etc., on the basis of analyzing and describing the development and change laws of the system, using hydrology and water resources disciplines as well as mathematics, physics, computer, etc. Forecasting the possible changes of the hydrology and water resources system in ...

Claims

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Application Information

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IPC IPC(8): G06F17/00
Inventor 王栋何菡丹吴吉春
Owner NANJING UNIV
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