Metallogenic prediction method and system based on fuzzy logic and machine learning

A machine learning and fuzzy logic technology, applied in fuzzy logic-based systems, machine learning, logic circuits, etc., to solve problems such as difficulty in accurately expressing prediction results and unclear geological significance.

Active Publication Date: 2020-10-30
INST OF MINERAL RESOURCES CHINESE ACAD OF GEOLOGICAL SCI
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Problems solved by technology

However, similar to methods such as the weight of evidence method, if different predictor variables are directly processed by machine learning algorithms, the geological significance is not clear, and the prediction results are difficult to express accurately

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  • Metallogenic prediction method and system based on fuzzy logic and machine learning
  • Metallogenic prediction method and system based on fuzzy logic and machine learning
  • Metallogenic prediction method and system based on fuzzy logic and machine learning

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Embodiment Construction

[0084] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0085] The object of the present invention is to provide a metallogenic prediction method and system based on fuzzy logic and machine learning, so as to improve the accuracy of mineralization prediction.

[0086] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0087] ...

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Abstract

The invention relates to a metallogenic prediction method based on fuzzy logic and machine learning. The method comprises the following steps: establishing an ore deposit model, wherein the ore deposit model comprises mineralization geological elements, a mineralization process and a mineralization effect; obtaining mineralization prediction elements related to mineralization based on the ore deposit model; preprocessing the mineralization prediction elements; fuzzy processing is carried out on the preprocessed metallogenic prediction elements; determining training data based on the mineralization prediction elements after fuzzy processing; establishing a machine learning model; training the machine learning model based on the training data to obtain a trained machine learning model; and performing metallogenic prediction based on the trained machine learning model. According to the method provided by the invention, the prediction accuracy can be improved.

Description

technical field [0001] The invention relates to the field of metallogenic prediction, in particular to a method and system for metallogenic prediction based on fuzzy logic and machine learning. Background technique [0002] Metallogenic prediction is a hotspot in the study of ore deposits, and it is a bridge and tool to guide ore prospecting. At present, the main metallogenic prediction methods can be divided into two categories: knowledge-driven and data-driven. Among them, the knowledge-driven method is suitable for metallogenic prediction in areas with few known mineral deposits, while the data-driven method is suitable for metallogenic prediction in areas with more known mineral deposits. [0003] The commonly used data-driven metallogenic prediction method (such as the weight of evidence method) is to directly import each variable into the prediction model to generate a mineralization favorable map for metallogenic prediction. When applying variables, directly applyin...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06N20/00G06N7/02
CPCG06N7/02G06N20/00G06F30/27
Inventor 孙莉高阳
Owner INST OF MINERAL RESOURCES CHINESE ACAD OF GEOLOGICAL SCI
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