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Economic prediction method based on neural network

A forecasting method and neural network technology, applied in the field of economic forecasting, can solve problems such as non-linear economic forecasting schemes without neural networks, and achieve the effect of increasing speed

Inactive Publication Date: 2022-06-03
杭州博晟科技有限公司
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Problems solved by technology

But at present, there is no scheme to use neural network to predict nonlinear economy

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  • Economic prediction method based on neural network
  • Economic prediction method based on neural network
  • Economic prediction method based on neural network

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Embodiment Construction

[0119] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and through specific implementation methods.

[0120] Wherein, the accompanying drawings are only for illustrative purposes, showing only schematic diagrams, rather than physical drawings, and should not be construed as limitations on this patent; in order to better illustrate the embodiments of the present invention, some parts of the accompanying drawings will be omitted, Enlargement or reduction does not represent the size of the actual product; for those skilled in the art, it is understandable that certain known structures and their descriptions in the drawings may be omitted.

[0121] In the drawings of the embodiments of the present invention, the same or similar symbols correspond to the same or similar components; , "inner", "outer" and other indicated orientations or positional relationships are based on the orientations or positional ...

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Abstract

The invention discloses an economic prediction method based on a neural network. The method comprises the following steps: S1, constructing an economic prediction index system; s2, acquiring economic data corresponding to each index in the index system; s3, carrying out data normalization processing on the obtained economic data; s4, determining the number of hidden layer neurons of the BP neural network; s5, taking the economic data subjected to data normalization processing in the step S3 as a training sample of the BP neural network, adaptively searching the step size in each iteration of network training by using a search optimal step size algorithm, and finally training to obtain an economic prediction model; and S6, inputting the obtained economic data into an economic prediction model, and outputting an economic prediction result by the model. According to the method, the proper number of neurons of the hidden layer is determined, and the proper step length is searched in a self-adaptive manner during each iteration training, so that the model training speed is ensured, and the performance of the trained model is also ensured.

Description

technical field [0001] The invention relates to the technical field of economic forecasting, in particular to an economic forecasting method based on a neural network. Background technique [0002] Gross domestic product (GDP for short) is the most important indicator to measure the development of the national economy, and it is also a comprehensive reflection of the economic operation. It is of great practical significance to accurately predict GDP or regional gross product and provide policy reference for economic development. [0003] GDP forecast is the forecast of GDP time series, and GDP time series is a set of data in a special form. In this set of data, the previous data will have an impact on the subsequent data. This influence relationship is expressed as a certain trend change or cycle. changes etc. However, the influence relationship is generally nonlinear, and it is difficult to establish a quantitative and fixed mathematical relationship. At present, there a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06N3/04G06N3/08
CPCG06Q10/04G06Q10/06393G06N3/04G06N3/084
Inventor 王邵辉洪辉阳杨晓庆
Owner 杭州博晟科技有限公司
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