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Tax revenue prediction method and device based on hybrid model

A tax revenue and mixed model technology, applied in forecasting, biological neural network models, instruments, etc., can solve the problems of model parameters not having the ability of adaptive adjustment and low forecasting accuracy, and achieve the effect of improving accuracy and high forecasting accuracy

Inactive Publication Date: 2015-12-09
GUANGDONG IDATATECH CO LTD
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a method that can combine the advantages of various models in the prior art, the model parameters do not have the ability of self-adaptive adjustment, and the prediction accuracy is not high. The advantages of various models are well combined, the model parameters have the ability of adaptive adjustment, and the wireless Selfie system and method with high prediction accuracy

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  • Tax revenue prediction method and device based on hybrid model
  • Tax revenue prediction method and device based on hybrid model
  • Tax revenue prediction method and device based on hybrid model

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Embodiment Construction

[0065] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0066] In the hybrid model-based tax revenue prediction method and device embodiment of the present invention, the flow chart of the hybrid model-based tax revenue prediction method is as follows figure 1 shown. figure 1 In , the tax revenue prediction method based on the mixed model includes the following steps:

[0067] Step S01 Obtaining a sample sequence of tax revenue prediction and using it as a training data sequence: In this step, obtaining a sample sequen...

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Abstract

The present invention provides a tax revenue prediction method and device based on a hybrid model. The method comprises: testing a training data sequence by using a test data sequence of a support vector regression model, so as to acquire a prediction value of the support vector regression model; testing the training data sequence by using a test data sequence of an autoregression moving average model, so as to acquire a prediction value of the autoregression moving average model; testing the training data sequence by using a test data sequence of an artificial neural network model, so as to acquire a prediction value of the artificial neural network model; and inputting the prediction value of the support vector regression model, the prediction value of the autoregression moving average model and the prediction value of the artificial neural network model into a hybrid model, so as to calculate a prediction value of tax revenue. According to the present invention, the tax revenue prediction method and device based on the hybrid model have the following advantages that: the advantages of various models can be combined well, model parameters can be adaptively adjusted, and prediction accuracy is high.

Description

technical field [0001] The invention relates to the field of tax revenue prediction, in particular to a tax revenue prediction method and device based on a mixed model. Background technique [0002] At present, most of the statistical forecasting tools used by taxation agencies in my country are foreign software, such as EViews, SPSSmodeler and SAS, etc. These software are expensive, and the user experience is not in line with China's national conditions. The built-in algorithm model is more suitable for the system of Western developed countries, so , all parts of our country need a set of forecasting software and algorithm models suitable for each. [0003] my country's current tax revenue forecasting models include regression, time series and artificial neural networks. The establishment of these models either focuses on tax revenue and related economic factors, or explores the regular characteristics of tax revenue itself. Various models have their own scope of applicatio...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q40/00G06N3/02
Inventor 陈乐华张青涂继来黄晓晖
Owner GUANGDONG IDATATECH CO LTD
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