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Traditional Chinese medicinal material supply and demand relationship prediction method and device based on machine learning and medium

A supply-demand relationship and machine learning technology, applied in the field of neural networks, can solve problems such as the vicious influence of the industrial chain and the uncertainty of the industrial chain

Pending Publication Date: 2022-03-22
荃豆数字科技有限公司
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Problems solved by technology

And this method of manual judgment has brought great uncertainty to the operation of the entire industrial chain, and may even have a vicious impact on the entire industrial chain due to the malicious hoarding of goods by some manufacturers.

Method used

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  • Traditional Chinese medicinal material supply and demand relationship prediction method and device based on machine learning and medium

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Embodiment

[0045] Such as figure 1 As shown, in the first aspect, the present invention provides a method for predicting the relationship between supply and demand of Chinese medicinal materials based on machine learning, including but not limited to the realization of steps S101-S104:

[0046] Step S101. Obtain the ecological environment data sets and output data sets of each traditional Chinese medicinal material production area over the years, and input the ecological environment data sets and the output data sets over the years into the CNN-LSTM network model based on the attention mechanism. train;

[0047]Wherein, the ecological environment data set over the years includes weather data and soil data over the years; preferably, the weather data over the years includes but not limited to precipitation data, solar radiation data, snow water equivalent data, maximum temperature data, minimum temperature data and Water vapor pressure data. Among them, the above-mentioned weather data ...

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Abstract

The invention discloses a traditional Chinese medicinal material supply and demand relationship prediction method based on machine learning, and the method comprises the steps: obtaining a past year ecological environment data set and a past year yield data set of each traditional Chinese medicinal material production area, and inputting the data sets into a CNN-LSTM network model based on an attention mechanism for training; the CNN-LSTM network model based on the attention mechanism is used for predicting the yield data of the traditional Chinese medicinal materials in the next year; acquiring a past year sales volume data set of the traditional Chinese medicinal materials, inputting past year sales volume data into the hybrid prediction model, and predicting the sales volume data of the traditional Chinese medicinal materials in the next year; and determining a supply-demand relationship according to the predicted traditional Chinese medicinal material yield data and the traditional Chinese medicinal material sales volume data. The method can accurately predict the excess and sales volume of the medicinal materials in the next year based on the machine learning algorithm according to the yield data and sales volume data of the medicinal materials over the years, and determines the production-marketing-supply-demand relationship of the medicinal materials in the next year according to the prediction result, thereby providing reliable data support for employees in the medicinal material industry, and improving the medicinal material quality. And a correct operation decision can be made.

Description

technical field [0001] The invention belongs to the technical field of neural networks, and in particular relates to a method, device and medium for predicting the relationship between supply and demand of medicinal materials based on machine learning. Background technique [0002] The source of the Chinese herbal medicine industry lies in the planting of Chinese herbal medicines, and Chinese herbal medicines are the most special economic crops. Most of the Chinese herbal medicines have a longer growth cycle than ordinary crops, so they are much more affected by their ecological environment than ordinary crops, and different medicinal materials are affected by their The influence of growing conditions in the place of origin may also be different. However, if the current planting of medicinal materials in the place of origin is violated by the harsh ecological environment, the output, sales volume and price of the entire Chinese herbal medicine industry chain will be greatly ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q30/02G06N20/00G06N3/04G06N3/08
CPCG06Q10/04G06Q30/0202G06N20/00G06N3/08G06N3/044G06N3/045
Inventor 赵源
Owner 荃豆数字科技有限公司
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