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Stock prediction method based on artificial intelligence ultra-deep learning

A deep learning and artificial intelligence technology, applied in the field of information processing, can solve problems affecting the development of artificial intelligence and unclear concepts of artificial intelligence

Pending Publication Date: 2018-05-25
天津市阿波罗信息技术有限公司
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AI Technical Summary

Problems solved by technology

[0011] At present, the fundamental reason why ordinary pattern recognition and robot technology are confused with artificial intelligence in society is that the concept of artificial intelligence is not clear. Therefore, all advanced technologies are attributed to artificial intelligence, which will affect the development of artificial intelligence. develop

Method used

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  • Stock prediction method based on artificial intelligence ultra-deep learning
  • Stock prediction method based on artificial intelligence ultra-deep learning
  • Stock prediction method based on artificial intelligence ultra-deep learning

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Embodiment Construction

[0083] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings, but the embodiments of the present invention are illustrative rather than limiting.

[0084] figure 1 It is a schematic diagram of the composition of an artificial intelligence ultra-deep learning model.

[0085] First, the following definition of letter expression is performed:

[0086] Set the number of input information and the number of input layer nodes as h (h=1, 2, ..., k), and then set the number of learning times as z = 1, 2, ..., w, and the number of layers of neurons is p (p=1, 2, . . . , e). The image being learned should also be F z (z=1, 2, ..., w), the number of nodes in the hidden layer, that is, the number of nodes in the input layer corresponds to h (h = 1, 2, ..., k), the first learning The micro-machine learning that needs to be learned before the input information is sent to the input layer node is ML z ph , input layer p=1, ...

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Abstract

The invention relates to a stock prediction method based on artificial intelligence ultra-deep learning in the field of information processing. The stock prediction method is characterized in that allinformation related with the prediction is processed through micro machine learning and then sent to each node of input layers; then predicted values and thresholds are generated through micro machine learning and then sent to neural layers; and a brain layer acquires a predicted range according to the predicted values, put forwards a check value, sends the check value to each neural layer for excitement checking and finally acquires an optimal predicted value. The implementation effects are that all factors related with the prediction and prediction effects generated by various mathematicalmodels can be constructed into a prediction platform through ultra-deep learning, and multiple times of machine learning are performed on a prediction result so as to achieve the optimal prediction. Meanwhile, automatic or manual fuzzy parameter correction can be carried out, so that the stock prediction method has a breakthrough in stock prediction.

Description

【Technical field】 [0001] The invention belongs to the field of information processing, in particular to a stock prediction method of artificial intelligence ultra-deep learning. 【Background technique】 [0002] At present, artificial intelligence has become a hot topic all over the world, and patents related to artificial intelligence are also attracting attention. In this regard, the famous Japanese company Furukawa Electric Co., Ltd. published a patent application for "image processing method and image processing device" (patent document 1) , the patent proposes to select the processing threshold of the image through the artificial intelligence neural network algorithm to extract the outline of the image with high precision. [0003] In the application of automatic driving of automobiles, the famous Japanese Toyota Corporation published the patent of "Driving Direction Estimation Device" (Patent Document 2). In this case, through the machine learning algorithm of artificia...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q40/04
CPCG06Q10/04G06Q40/04
Inventor 顾泽苍
Owner 天津市阿波罗信息技术有限公司
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