Time sequence prediction method based on GRU neural network

A neural network and time series technology, applied in the field of time series forecasting based on GRU neural network, can solve the problem of high complexity, nonlinear time series forecasting without good results, unfavorable commodity sales, and increased inventory management. cost, etc.

A neural network and time series technology, applied in the field of time series forecasting based on GRU neural network, can solve the problem of high complexity, nonlinear time series forecasting without good results, unfavorable commodity sales, and increased inventory management. cost, etc.

CN110647980APending Publication Date: 2020-01-03CHENGDU UNIVERSITY OF TECHNOLOGY

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Time sequence prediction method based on GRU neural network
  • Time sequence prediction method based on GRU neural network
  • Time sequence prediction method based on GRU neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0103] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0104] The technical solutions and technical effects of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0105] Such as figure 1 As shown, the time series prediction method based on the GRU neural network provided by the embodiment of the present invention includes:

[0106] S101. Collect raw data that needs to be predicted.

[0107] S102. Perform cleaning, integration, conversion, discretization, and reduction related data preprocessing on the collected raw data.

[0108] S103, standardize the preprocessed data by using the Z-score method, and use the standardized d...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention belongs to the technical field of network information prediction, and discloses a time sequence prediction method based on a GRU neural network. The method comprises the following steps:collecting original data needing to be predicted; carrying out data preprocessing on the collected original data; performing standardization processing on the preprocessed data; performing dimensionraising processing on the original time series data form by using the code; training the input data by using a GRU neural network to obtain a trained time sequence prediction model, and storing the trained time sequence prediction model; predicting the time series data by using a GRU-SES model to obtain a preliminary prediction value; performing secondary exponential smoothing processing on the obtained preliminary prediction data to obtain a final prediction data value; output of prediction results. The prediction method provided by the invention improves the precision of time sequence prediction, and is of great significance to time sequence analysis in industrial production or actual life.

Description

technical field [0001] The invention belongs to the technical field of network information prediction, and in particular relates to a time series prediction method based on a GRU neural network. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: time series are widely present in daily life and production, and the development of everything in the world develops with time, such as in weather, finance, transportation, industry, agriculture, etc. There are variable series formed according to the time dimension in various fields. Changes in daily temperature in weather, changes in passenger traffic in traffic, changes in stock prices in finance, etc., all exist in the form of time series. At the same time, some data in life can also be converted into a time series representation, such as genetic data, etc. Time series are a special form of stochastic process. Time series is a series of numbers that arranges the sta...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
03 Jan 2020
Publication
CN110647980A
IPC
G06N3/04; G06N3/08; G06Q10/04
CPC
G06N3/084; G06Q10/04; G06N3/044
Inventors
柳丽召; 蔡彪