Commodity price forecast method and device

A commodity price and commodity technology, applied in the field of data analysis, can solve the problems of low prediction accuracy and reliability, easy to obtain local extreme values, etc.

Inactive Publication Date: 2018-12-21
苏州仙度网络科技有限公司
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Problems solved by technology

The disadvantage of this type of algorithm is: in the process of solving the parameters, the gradient descent method is usually used. The inherent defect of this algorithm is that it is easy to get the local extremum instead of the global extremum we want. Therefore, the prediction accuracy and credibility not tall

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  • Commodity price forecast method and device
  • Commodity price forecast method and device
  • Commodity price forecast method and device

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Embodiment 1

[0079] An embodiment of the present invention provides a commodity price prediction method, see figure 1 As shown, the method includes:

[0080] S11: Obtain target sample data for commodity price prediction, the target sample data includes: training sample data and verification sample data.

[0081] Among them, the target sample data includes: the data corresponding to the first parameter and the second parameter; the first parameter is used as an input parameter; the first parameter includes: commodity attribute parameters, commodity environment parameters; the second parameter is used as an output parameter ; Wherein the second parameter includes: commodity price.

[0082] It should be noted that the commodities in the embodiments of the present invention may be daily necessities, houses or agricultural products and other economically significant commodities. In addition, part of the collected target sample data is used to train the model, which is called training sample d...

Embodiment 2

[0134] The embodiment of the present invention also provides a commodity price prediction device, see Figure 4 As shown, the device includes: a data acquisition module 41 , a priori distribution function determination module 42 , a prediction distribution function establishment module 43 and a data prediction module 44 .

[0135] Among them, the data acquisition module 41 is used to acquire target sample data for commodity price prediction; the target sample data includes: the data corresponding to the first parameter and the second parameter; the first parameter is used as an input parameter; wherein the first parameter includes: commodity Attribute parameters, commodity environment parameters; the second parameter is used as an output parameter; wherein the second parameter includes: commodity price; target sample data includes: training sample data and verification sample data; a priori distribution function determination module 42 for based on The preset input-output rela...

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Abstract

The invention provides a commodity price forecasting method and a device, which relate to the technical field of data analysis, and obtain target sample data of commodity price forecasting. Target sample data includes: training sample data; determining a prior distribution function of each parameter in the preset input-output relation function model based on the preset input-output relation function model; according to a priori distribution function, training sample data and Bayesian theorem, the commodity price forecast distribution function model is obtained. The new input parameter data isinputted into the commodity price forecast distribution function model, and the output result of the commodity price forecast distribution function model is calculated as the commodity forecast pricecorresponding to the new input parameter data. The invention establishes a commodity price prediction distribution function model based on the collected sample data of parameters related to commodityprice prediction, predicts the output result of new input data through the distribution function model, and improves the accuracy and credibility of the commodity price prediction result.

Description

technical field [0001] The invention relates to the technical field of data analysis, in particular to a commodity price prediction method and device. Background technique [0002] Commodity price forecasting method is the basis of market forecast analysis and commodity production and sales decision-making. It is an important issue in the field of market forecasting and plays a key role in many aspects such as commodity production and sales. [0003] The existing commodity price prediction methods based on neural network algorithms usually first estimate the internal weight parameters, bias parameters and external weight parameters, and then obtain the prediction function f(x), and then calculate f(x) for the new input parameter data x The output value of x) is used as the predicted value of commodity price. The disadvantage of this type of algorithm is: in the process of solving the parameters, the gradient descent method is usually used. The inherent defect of this algori...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
CPCG06Q30/0283G06Q30/0202
Inventor 王碧波董雪梅
Owner 苏州仙度网络科技有限公司
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