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XGBoost-based inorganic arsenic content prediction method and device and medium

A prediction method and inorganic arsenic technology, applied in the field of data processing, can solve problems such as prediction, and achieve the effects of improving prediction efficiency, improving safety and high prediction accuracy

Pending Publication Date: 2022-05-06
INFINITUS (CHINA) CO LTD
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Problems solved by technology

[0003] At present, the industry has not yet established a method to predict the content of inorganic arsenic in health products through the content of total arsenic in raw materials

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  • XGBoost-based inorganic arsenic content prediction method and device and medium
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  • XGBoost-based inorganic arsenic content prediction method and device and medium

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Embodiment Construction

[0054] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0055] Since the current industry has not yet established a method for predicting the content of inorganic arsenic in health care products through the content of total arsenic in raw materials, the present invention adopts XGBoost (eXtreme Gradient Boosting, extreme gradient boosting) integrated learning algorithm to analyze data, through health care Predicting the content of inorganic arsenic based on the process conditions of the product and the total arsenic content in raw materials can greatly simplify the work of health product R&D personnel, shorten the development cy...

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Abstract

The invention discloses an inorganic arsenic content prediction method and device based on XGBoost and a medium. The method comprises the following steps: acquiring original data; preprocessing the original data to generate modeling data; according to the modeling data, an XGBoost model is trained, and a prediction model is formed; and inputting process condition information and raw material information of a to-be-detected object into the prediction model, and generating a predicted value of the inorganic arsenic content of the to-be-detected object. The XGBoost model is used for predicting the inorganic arsenic content of the to-be-detected object, the prediction precision is high, in addition, the XGBoost model has the unique advantages of short training time and the like, the prediction efficiency of the method can be further improved, the safety of the related to-be-detected object is further improved, and the method can be widely applied to the technical field of data processing.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to an XGBoost-based inorganic arsenic content prediction method, device and medium. Background technique [0002] In the production process of health care products, some products contain trace amounts of potentially toxic and harmful substances, such as arsenic. Differences in parameters set in the screening, processing, and extraction of raw materials will lead to differences in the arsenic content of the final product. Therefore, the industry needs to obtain the relationship between various parameters and the arsenic content of the product, and adjust various parameters in the processing process accordingly In order to achieve the effect of reducing arsenic content and improving product safety. [0003] At present, the industry has not yet established a method to predict the content of inorganic arsenic in health products through the content of total arsenic in raw materi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16C20/30G16C20/70G06K9/62G06N20/20
CPCG16C20/30G16C20/70G06N20/20G06F18/214
Inventor 陆智李亚贤李亚杰冯安祺
Owner INFINITUS (CHINA) CO LTD
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