Posting predication system based on nerual network technique

A neural network and prediction system technology, applied in the field of Internet discussion, can solve problems such as time series that are not suitable for nonlinear

Inactive Publication Date: 2015-09-30
上海玻森数据科技有限公司
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Problems solved by technology

[0007] Traditional modeling and forecasting methods have bee

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  • Posting predication system based on nerual network technique
  • Posting predication system based on nerual network technique
  • Posting predication system based on nerual network technique

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[0100] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further elaborated below in conjunction with illustrations and specific embodiments.

[0101]The post prediction system based on neural network technology proposed by the present invention uses phase space reconstruction to realize nonlinear time series analysis. Phase space reconstruction is an important step in nonlinear time series analysis. The purpose of initially proposing phase space reconstruction is to Restoring chaotic attractors in high-dimensional phase spaces. As one of the characteristics of the chaotic system, the chaotic attractor embodies the regularity of the chaotic system, and it is believed that the chaotic system will eventually fall into a certain trajectory. This article uses the delayed vector method, which is defined as:

[0102] Definition 1: Suppose (N, ρ), (N1, ρ1) are two metric spac...

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Abstract

The invention provides a posting predication system based on a neural network technique. The system adopts phase-space reconstruction for realizing non-linear time sequence analysis and adopts a Browser/Server structure based on a J2EE platform. The system structurally includes a data pre-processing module, a predication analysis management module and predication modeling and simulation interface software and has characteristics of high convergence rate and low training error. The predication precision of established models is good. However, selection of a range of neural network training samples should be paid attention. Sample quantity can be reduced appropriately for predication of posting concerning to emergencies and samples of too early time may not be applied. In application, damage of models due to abnormal values should be paid attention and the abnormal values should be checked and adjusted, so that the model predication precision can be guaranteed. The established models adopt quantitative analysis and acquire a certain precision. Besides, the perception performance is good.

Description

technical field [0001] The invention relates to the technical field of Internet discussion, in particular to a post prediction system based on neural network technology. Background technique [0002] Since online posting has the characteristics of a time series, the time series of online posting has the following characteristics: [0003] Trend: A variable is continuously affected by certain factors, and its time series shows a continuous upward or downward overall change trend, which may be linear or non-linear. For example, the economic growth rate of our country in recent years, due to the influence of various factors, shows continuous growth. [0004] Seasonality: The considered time series takes a certain period of time as a period, and has obvious seasonal characteristics as the natural season changes. Such as air-conditioning sales, sales of various clothing and so on. [0005] Cyclical: More general than seasonal. A time series exhibits periodicity over a period ...

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Application Information

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IPC IPC(8): G06Q10/02G06N3/02
Inventor 李臻纪敏闵可锐
Owner 上海玻森数据科技有限公司
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