Digitization-based geological data intelligent classification management system

Abstract

The invention relates to the field of geological data classification management, and particularly discloses a digitization-based geological data intelligent classification management system, which can automatically identify and classify new geological data and improve the input efficiency and classification accuracy by learning a large amount of classified geological data and establishing a geological data intelligent classification model. By performing access authority management and access information registration on the geological data and identifying and early warning risk access behaviors, the safety of the geological data can be better protected; according to the retrieval content input by the user, the geological data which the user intends to query is analyzed, and a powerful retrieval function can be provided, so that the user can quickly find the required geological data; by obtaining the access record, the browsing record and the downloading record of the geological data, the value degree grade of the geological data is evaluated, important geological data is labeled, and efficient classification, storage, retrieval and application of the geological data are achieved.

Description

Technical Field

[0001] The present invention relates to the field of classification management of geological data, and relates to an intelligent classification management system for geological data based on digitization. Background Art

[0002] With the continuous deepening of geological exploration work and the progress of technology, the quantity of geological data has increased explosively. The traditional manual classification management method is difficult to cope with such a huge amount of data, with low efficiency and prone to errors, and it is difficult to meet the growing demand of the geological industry for the efficient utilization and rapid retrieval of data. Moreover, the rapid development of information technology, especially the emergence of technologies such as artificial intelligence, big data, and cloud computing, provides technical support for the intelligent classification management of geological data. Therefore, the precise intelligent classification management of geological data can improve the efficiency of geological work and provide a more accurate basis for decision-making, which is of great significance.

[0003] However, the existing geological data management methods still have some limitations and deficiencies in practical applications.

[0004] For example, the existing Chinese patent with the publication number CN112633707A discloses an engineering geology management system, including an engineering geology management system, a server, a mobile terminal, a database, a construction site geological data collection module, a three-dimensional geological modeling system, a geological information data management system, and an engineering geology drawing system. The engineering geology management system includes a database, a construction site geological data collection module, a three-dimensional geological modeling system, a geological information data management system, and an engineering geology drawing system. This invention can combine geological data management with information technology, so as to be able to adapt to the management of massive and diversified geological data. The provided geological data management system responds to the relevant national policies on geological data. This system can comprehensively keep confidential the confidential geological data and is a modern, diversified, and multidisciplinary comprehensive management system serving the public. This system combines various concepts in the information age and comprehensively applies big data storage and data structure technology.

[0005] The above patent does not involve the intelligent classification and storage of geological data, and requires manual classification and entry of geological data, with low efficiency and prone to errors. Summary of the Invention

[0006] In view of the above problems, the present invention proposes an intelligent classification management system for geological data based on digitization to realize the function of classifying and managing geological data.

[0007] The technical solution adopted by the present invention to solve its technical problems is as follows: The present invention provides an intelligent classification management system for geological data based on digitization, including: a geological data collection and preprocessing module, an intelligent classification model construction module for geological data, an automatic classification and storage module for geological data, an access management module for geological data, a retrieval and query module for geological data, a value evaluation module for geological data, and a database.

[0008] The intelligent classification model construction module for geological data is respectively connected to the geological data collection and preprocessing module and the automatic classification and storage module for geological data. The automatic classification and storage module for geological data is respectively connected to the access management module for geological data, the retrieval and query module for geological data, and the value evaluation module for geological data. The database is connected to the intelligent classification model construction module for geological data.

[0009] Geological data collection and preprocessing module: It is used to collect each piece of geological data to be entered into the geological data management platform, record it as each piece of to-be-entered geological data, and further preprocess each piece of to-be-entered geological data, where the preprocessing includes data sorting and data cleaning.

[0010] Intelligent classification model construction module for geological data: It is used to obtain the historical data sets of various types of geological data, construct the training sets and test sets of the intelligent classification models for various types of geological data, analyze the typical feature sets of various types of geological data, train the intelligent classification models for various types of geological data, further determine whether the accuracy of the intelligent classification models for various types of geological data meets the requirements, and perform optimization.

[0011] Automatic classification and storage module for geological data: It is used to automatically classify each piece of to-be-entered geological data according to the intelligent classification models of various types of geological data, and further store it in the corresponding file system of the geological data management platform.

[0012] Access management module for geological data: It is used to manage the access permissions and register the access information of the geological data stored in the geological data management platform, further identify risk access behaviors, and give early warnings.

[0013] Retrieval and query module for geological data: It is used to analyze the geological data that the user intends to query according to the retrieval content input by the user in the geological data management platform, and perform intelligent push.

[0014] Value evaluation module for geological data: It is used to obtain the access records, browsing records, and download records of each piece of geological data in the geological data management platform during the evaluation period, evaluate the value degree levels of each piece of geological data in the geological data management platform, and perform marking and feedback.

[0015] Database: It is used to store the historical data sets of various types of geological data.

[0016] Compared with the prior art, the intelligent classification management system for geological data based on digitization of the present invention has the following beneficial effects: 1. Based on historical geological data, the present invention utilizes artificial intelligence and machine learning technologies to learn a large number of classified geological data, establish an intelligent classification model for geological data, and input new geological data into the trained intelligent classification model, which can automatically identify and classify new geological data, realizing the automatic input and storage of the collected geological data according to the classification criteria, thereby reducing the workload of manual classification and human errors, and improving the input efficiency and the classification accuracy of geological data.

[0017] 2. The present invention can better protect the security of geological data by managing access permissions and registering access information for geological data, and identifying and warning of risky access behaviors, preventing data leakage and loss.

[0018] 3. According to the retrieval content input by the user in the geological data management platform, the present invention analyzes the geological data that the user intends to query and performs intelligent push, providing a powerful retrieval function, enabling the user to quickly find the required geological data.

[0019] 4. By obtaining the access records, browsing records, and download records of geological data, the present invention evaluates the value degree level of geological data and marks important geological data for subsequent retrieval and analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0021] Figure 1 It is the system module connection diagram of the present invention.

[0022] Figure 2 It is the structural block diagram of the geological data access management module of the present invention.

[0023] Figure 3 It is the structural block diagram of the geological data retrieval and query module of the present invention.

[0024] Figure 4 It is the structural block diagram of the geological data value evaluation module of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0025] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0026] Please refer to Figure 1 As shown, the present invention provides an intelligent classification management system for geological data based on digitization, including a geological data collection and preprocessing module, a geological data intelligent classification model construction module, a geological data automatic classification and storage module, a geological data access management module, a geological data retrieval and query module, a geological data value evaluation module, and a database.

[0027] The geological data intelligent classification model construction module is respectively connected to the geological data collection and preprocessing module and the geological data automatic classification and storage module. The geological data automatic classification and storage module is respectively connected to the geological data access management module, the geological data retrieval and query module, and the geological data value evaluation module. The database is connected to the geological data intelligent classification model construction module.

[0028] The geological data collection and preprocessing module is used to collect each piece of geological data to be entered into the geological data management platform, record it as each piece of to-be-entered geological data, and further preprocess each piece of to-be-entered geological data, where the preprocessing includes data sorting and data cleaning.

[0029] Further, the specific working process of the geological data collection and preprocessing module is: obtaining each piece of geological data to be entered into the geological data management platform and recording it as each piece of to-be-entered geological data.

[0030] As a preferred solution, the source channels of geological data include but are not limited to: field exploration data, laboratory analysis data, historical archives, etc.

[0031] Perform operations of digitizing paper materials by scanning, converting to spreadsheets, and unifying the electronic data formats on each piece of to-be-entered geological data in sequence, and then sort the data of each piece of to-be-entered geological data.

[0032] As a preferred solution, the operations of digitizing paper materials by scanning, converting to spreadsheets, and unifying the electronic data formats are selectively performed, and not all to-be-entered geological data have these three operations.

[0033] As a preferred solution, digitizing paper materials by scanning refers to the process of converting paper documents in geological data into digital formats, using technical principles such as optical recognition and digital conversion.

[0034] As a preferred solution, converting a spreadsheet refers to performing an operation to change the form of the data in the spreadsheet in geological data, such as changes in data format, data content, or data structure, etc., which is commonly seen in the conversion between different data types, such as the conversion between numerical values and text, and the conversion of date or time data, etc.

[0035] As a preferred solution, unifying the electronic data format means converting electronic data in different formats in geological data into one or several specific, widely recognized, and compatible formats. There are numerous formats for electronic data. For example, for document types, there are.doc,.docx,.pdf, etc.; for image types, there are.jpg,.png,.tiff, etc.; for video types, there are.mp4,.avi,.mkv, etc. In a specific embodiment, the geological data of the document type is unified into the.docx format, and the geological data of the image type is unified into the.jpg format.

[0036] As a preferred solution, operations such as digitizing and scanning paper materials, converting spreadsheets, and unifying the electronic data format in data collation are relatively mature existing technologies and will not be elaborated here.

[0037] Perform the operation of cleaning invalid data on each piece of geological data to be entered, and then perform data cleaning on each piece of geological data to be entered.

[0038] As a preferred solution, cleaning invalid data refers to the process of identifying, detecting, and removing inaccurate, incomplete, irrelevant, duplicate, or geological data that does not conform to specific rules from geological data.

[0039] As a preferred solution, the operation of cleaning invalid data in data cleaning is a relatively mature existing technology and will not be elaborated here.

[0040] The intelligent classification model construction module for geological data is used to obtain the historical data sets of various types of geological data, construct the training sets and test sets of the intelligent classification models for various types of geological data, analyze the typical feature sets of various types of geological data, train the intelligent classification models for various types of geological data, further determine whether the accuracy of the intelligent classification models for various types of geological data meets the requirements, and perform optimization.

[0041] Furthermore, the specific working process of the intelligent classification model construction module for geological data includes: extracting the historical data sets of various types of geological data stored in the database and recording them as the data sets of the intelligent classification models for various types of geological data.

[0042] Set the ratio between the training set and the test set of the intelligent classification model for geological data, divide the data sets of the intelligent classification models for various types of geological data, and obtain the training sets and test sets of the intelligent classification models for various types of geological data.

[0043] As a preferred solution, a classification standard for geological data is formulated in combination with the characteristics of geological data and actual requirements, and it has the characteristics of clarity, operability, and stability, so that the subsequent classification work can proceed smoothly. For example, classification is carried out according to factors such as geological type, geological age, geographical location, project type, etc.

[0044] In a specific embodiment, the types of geological data include but are not limited to: mineral exploration, marine geological survey, hydrogeology, engineering geology and environmental geology exploration, geophysical, geochemical and remote sensing geology, scientific research, theoretical research, applied research, soft science research, technical method research, etc.

[0045] Based on the training sets of intelligent classification models for various types of geological data, obtain the forms of each historical data in the training sets of intelligent classification models for various types of geological data, extract the features of each historical data in the training sets of intelligent classification models for various types of geological data based on their forms, summarize them, use machine learning algorithms to analyze the typical features of various types of geological data, construct a set of typical features for various types of geological data, and train the intelligent classification models for various types of geological data.

[0046] As a preferred solution, for geological data in different forms, the methods of extracting features are different.

[0047] In a specific embodiment, the forms of geological data include but are not limited to: text type, approval type, attached drawing type, attached table type, attachment type, database type, multimedia type, etc.

[0048] In a specific embodiment, the typical features of each type of geological data refer to the common features of each historical data in each type of geological data.

[0049] As a preferred solution, various algorithms such as decision trees, support vector machines, and neural networks can be used to train the intelligent classification models for various types of geological data. These algorithms can accurately classify according to the characteristics of geological data, such as text content, image features, data structure, etc.

[0050] Furthermore, the specific working process of the geological data intelligent classification model construction module further includes: obtaining the features of each historical data in the test sets of intelligent classification models for various types of geological data, substituting them into the intelligent classification models for various types of geological data, and matching to obtain the predicted types of each historical data in the test sets of intelligent classification models for various types of geological data.

[0051] As a preferred solution, the method of obtaining the features of each historical data in the test sets of intelligent classification models for various types of geological data is the same in principle as the method of obtaining the features of each historical data in the training sets of intelligent classification models for various types of geological data.

[0052] If the predicted type of a certain historical data in the test set of the intelligent classification model for a certain type of geological data is the same as its actual type, then this historical data is recorded as correctly identified historical data. Count the number of correctly identified historical data in the test sets of the intelligent classification models for various types of geological data, and obtain the ratio between the number of correctly identified historical data and the total number of historical data in the test sets of the intelligent classification models for various types of geological data, and record it as the recognition accuracy rate of the intelligent classification models for various types of geological data.

[0053] According to the recognition accuracy rate of the intelligent classification models for various types of geological data, judge whether the accuracy of the intelligent classification models for various types of geological data meets the requirements, and count the intelligent classification models for various types of geological data whose accuracy does not meet the requirements.

[0054] As a preferred solution, the process of judging whether the accuracy of the intelligent classification models for various types of geological data meets the requirements is as follows: Compare the recognition accuracy rate of the intelligent classification models for various types of geological data with a preset recognition accuracy rate threshold. If the recognition accuracy rate of the intelligent classification model for a certain type of geological data is less than the preset recognition accuracy rate threshold, then the accuracy of the intelligent classification model for this type of geological data does not meet the requirements.

[0055] Furthermore, the specific working process of the geological data intelligent classification model construction module also includes: Integrate the training sets and test sets of the intelligent classification models for various types of geological data whose accuracy does not meet the requirements to obtain a new training set for the intelligent classification models for various types of geological data whose accuracy does not meet the requirements.

[0056] Based on the new training sets of the intelligent classification models for various types of geological data whose accuracy does not meet the requirements, reconstruct the intelligent classification models for various types of geological data whose accuracy does not meet the requirements, and then optimize the intelligent classification models for various types of geological data whose accuracy does not meet the requirements.

[0057] As a preferred solution, the method of retraining the intelligent classification models for various types of geological data whose accuracy does not meet the requirements based on the new training set is the same in principle as the method of training the intelligent classification models for various types of geological data based on the training set.

[0058] As a preferred solution, optimize the performance of the geological data intelligent classification model by increasing the training set, and improve the accuracy and generalization ability of the geological data intelligent classification model.

[0059] The geological data automatic classification and storage module is used to automatically classify each piece of geological data to be entered according to the intelligent classification models for various types of geological data, and further store it in the corresponding file system of the geological data management platform.

[0060] Furthermore, the specific working process of the geological data automatic classification and storage module is as follows: extract the features of each piece of geological data to be entered, compare the features of each piece of geological data to be entered with the intelligent classification models of various types of geological data, analyze the number of matching features between each piece of geological data to be entered and various types of geological data, take the type corresponding to the largest number of matching features as the type of the geological data to be entered, screen out the types of each piece of geological data to be entered, automatically classify each piece of geological data to be entered, and further store it in the corresponding file system of the geological data management platform.

[0061] As an optimal solution, to analyze the number of matching features between each piece of geological data to be entered and various types of geological data, the specific method is as follows: compare the features of each piece of geological data to be entered with the intelligent classification models of various types of geological data. If a certain feature of a piece of geological data to be entered is the same as a certain typical feature in the intelligent classification model of a certain type of geological data, then mark this feature as the matching feature between this piece of geological data to be entered and this type of geological data, and count the number of matching features between each piece of geological data to be entered and various types of geological data.

[0062] As an optimal solution, the geological data management platform stores geological data using distributed storage technology to ensure the security and reliability of the data.

[0063] As an optimal solution, various types of geological data are stored in the corresponding file system of the geological data management platform, which is convenient for subsequent retrieval and management.

[0064] It should be noted that based on historical geological data, this invention uses artificial intelligence and machine learning technologies to learn a large number of classified geological data, establish an intelligent classification model for geological data, input new geological data into the trained intelligent classification model, and can automatically identify and classify new geological data, realizing the automatic entry and storage of the collected geological data according to the classification criteria, thereby reducing the workload and human errors of manual classification and improving the entry efficiency and classification accuracy of geological data.

[0065] The geological data access management module is used to manage the access permissions and register the access information of the geological data stored in the geological data management platform, further identify risk access behaviors, and issue warnings.

[0066] Furthermore, referring to Figure 2 As shown, the specific working process of the geological data access management module includes: setting the authorized access geological data sets corresponding to each user role, and then managing the access permissions of the geological data stored in the geological data management platform.

[0067] As a preferred solution, different users can access and use geological data according to their permissions, realizing the sharing of geological data and promoting the collaboration and cooperation in geological work.

[0068] Obtain the access time, access network, and each piece of geological data accessed by the user on the geological data management platform, summarize to obtain the user's access information, and further register the access information for the geological data stored in the geological data management platform.

[0069] Set the sensitivity factors corresponding to each access time period, each access network type, and each type of geological data, and set the hazard factors corresponding to authorized access to geological data and unauthorized access to geological data. Analyze the risk coefficient of the user's access according to the user's access information.

[0070] As a preferred solution, the specific method for analyzing the risk coefficient of the user's access is as follows: According to the user's access information, filter out the sensitivity factors corresponding to the access time and access network of the user on the geological data management platform, and record them as 、 respectively, and obtain the sensitivity factors and hazard factors corresponding to each piece of geological data accessed by the user on the geological data management platform, and record them as 、 respectively, represents the serial number of the th piece of geological data, = 1, 2,..., .

[0071] Through the analysis formula obtain the risk coefficient of the user's access, where represents the correction factor of the preset risk coefficient.

[0072] Further, the specific working process of the geological data access management module further includes: comparing the risk coefficient of the user's access with the preset risk coefficient threshold. If the risk coefficient of the user's access is greater than the preset risk coefficient threshold, the user's access behavior is a risk access behavior, and a warning is given.

[0073] It should be noted that by managing the access permissions of geological data, registering access information, and identifying and warning risk access behaviors, the present invention can better protect the security of geological data, prevent data leakage and loss.

[0074] The geological data retrieval and query module is used to analyze the geological data that the user intends to query according to the retrieval content input by the user on the geological data management platform and perform intelligent push.

[0075] Further, refer to Figure 3As shown in the figure, the specific working process of the geological data retrieval and query module is as follows: Obtain the retrieval content input by the user in the geological data management platform, use keyword recognition technology to obtain each keyword of the retrieval content input by the user in the geological data management platform, and record them as each search keyword.

[0076] As a preferred solution, the keyword recognition technology is a relatively mature existing technology and will not be elaborated here.

[0077] Obtain each keyword of each piece of geological data in the geological data management platform, and analyze the cumulative number of associated keywords between each piece of geological data in the geological data management platform and the search keywords.

[0078] As a preferred solution, to analyze the cumulative number of associated keywords between each piece of geological data in the geological data management platform and the search keywords, the specific method is as follows: Obtain each keyword of each piece of geological data in the geological data management platform. If a certain keyword of a certain piece of geological data in the geological data management platform is the same as or a synonym of a certain search keyword, then record the keyword of this piece of geological data in the geological data management platform as the associated keyword of this search keyword, count the number of associated keywords between each piece of geological data in the geological data management platform and each search keyword, and perform accumulation to obtain the cumulative number of associated keywords between each piece of geological data in the geological data management platform and the search keywords.

[0079] Obtain the user's query records through the background system of the geological data management platform, obtain the query popularity ranking of each piece of geological data in the geological data management platform, set the query popularity coefficient corresponding to each query popularity ranking, and screen the query popularity coefficients of each piece of geological data in the geological data management platform.

[0080] Substitute the cumulative number of associated keywords between each piece of geological data in the geological data management platform and the search keywords and the query popularity coefficients of each piece of geological data into the relationship function between the cumulative number of associated keywords of geological data and search keywords, query popularity coefficients, and the query tendency index of geological data, and obtain the query tendency index of each piece of geological data in the geological data management platform.

[0081] Compare the query tendency indices of each piece of geological data in the geological data management platform with each other, and record the geological data corresponding to the maximum query tendency index as the geological data that the user intends to query, and perform intelligent push.

[0082] It should be noted that according to the retrieval content input by the user in the geological data management platform, the present invention analyzes the geological data that the user intends to query and performs intelligent push, which can provide a powerful retrieval function, enabling the user to quickly find the required geological data.

[0083] The geological data value evaluation module is used to obtain the access records, browsing records, and download records of each piece of geological data in the geological data management platform during the evaluation period, evaluate the value degree level of each piece of geological data in the geological data management platform, and perform marking and feedback.

[0084] Further, refer to Figure 4 As shown, the specific working process of the geological data value evaluation module is as follows: Set the duration of the evaluation period, and obtain the access records, browsing records, and download records of each piece of geological data in the geological data management platform during the evaluation period through the background system of the geological data management platform, so as to obtain the access times, access people, access frequency, browsing times, browsing people, browsing frequency, download times, download people, and download frequency of each piece of geological data in the geological data management platform during the evaluation period, and analyze the value evaluation index of each piece of geological data in the geological data management platform.

[0085] As an optimal solution, to analyze the value evaluation index of each piece of geological data in the geological data management platform, the specific method is: Substitute the access times, access people, and access frequency of each piece of geological data in the geological data management platform during the evaluation period into the relationship function between the preset access times, access people, access frequency, and access heat factor, so as to obtain the access heat factor of each piece of geological data in the geological data management platform.

[0086] Similarly, according to the analysis method of the access heat factor of each piece of geological data in the geological data management platform, obtain the browsing heat factor and download heat factor of each piece of geological data in the geological data management platform.

[0087] Calculate the weighted average value of the access heat factor, browsing heat factor, and download heat factor of each piece of geological data in the geological data management platform to obtain the value evaluation index of each piece of geological data in the geological data management platform.

[0088] As an optimal solution, the weights of the access heat factor, browsing heat factor, and download heat factor are set values, and the sum is 1.

[0089] Set the value degree level corresponding to each value evaluation index range, screen out the value degree level of each piece of geological data in the geological data management platform, and perform marking and feedback.

[0090] It should be noted that the present invention evaluates the value degree level of geological data by obtaining the access records, browsing records, and download records of geological data, and marks important geological data for subsequent retrieval and analysis.

[0091] The database is used to store the historical data sets of various types of geological data.

[0092] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should fall within the protection scope of the present invention.

Claims

1. A digital geological data intelligent classification management system, characterized in that: include: Geological data collection and preprocessing module: used to collect various geological data to be entered into the geological data management platform, record them as various geological data to be entered, and further preprocess each geological data to be entered, wherein the preprocessing includes data sorting and data cleaning; Geological data intelligent classification model construction module: used to obtain historical data sets of various types of geological data, build training sets and test sets of intelligent classification models of various types of geological data, analyze typical feature sets of various types of geological data, train intelligent classification models of various types of geological data, further determine whether the accuracy of intelligent classification models of various types of geological data meets the requirements, and optimize them; Automatic classification and storage module for geological data: used to automatically classify each type of geological data to be entered according to the intelligent classification model of each type of geological data, and further store it in the corresponding file system of the geological data management platform; Geological data access management module: used to manage access rights and register access information for geological data stored in the geological data management platform, further identify risky access behaviors, and issue early warnings; Geological data search and query module: used to analyze the geological data that users intend to query based on the search content entered by users in the geological data management platform, and perform intelligent push; Geological data value assessment module: used to obtain the access records, browsing records and download records of each geological data in the geological data management platform during the assessment period, assess the value level of each geological data in the geological data management platform, and make annotations and feedback; Database: A historical data set used to store various types of geological data.

2. According to claim 1, a digital geological data intelligent classification management system is characterized by: The specific working process of the geological data acquisition and preprocessing module is as follows: Obtaining various pieces of geological data to be entered into the geological data management platform, and recording them as various pieces of geological data to be entered; Digitally scan the paper data, convert them into electronic forms, and unify the electronic data formats for each geological data to be entered, and then organize the data for each geological data to be entered; Invalid data cleaning operations are performed on each copy of geological data to be entered, and then data cleaning is performed on each copy of geological data to be entered.

3. The digital geological data intelligent classification management system according to claim 1 is characterized by: The specific working process of the geological data intelligent classification model construction module includes: Extracting historical data sets of various types of geological data stored in the database and recording them as data sets for intelligent classification models of various types of geological data; The ratio between the training set and the test set of the geological data intelligent classification model is set, and the data sets of each type of geological data intelligent classification model are divided to obtain the training set and the test set of each type of geological data intelligent classification model; Based on the training set of each type of intelligent classification model for geological data, the form of each piece of historical data in the training set of each type of intelligent classification model for geological data is obtained, and the various features of each piece of historical data in the training set of each type of intelligent classification model for geological data are extracted based on its form and summarized. The typical features of each type of geological data are analyzed by machine learning algorithms, and a typical feature set of each type of geological data is constructed to train intelligent classification models for each type of geological data.

4. The digital geological data intelligent classification management system according to claim 3 is characterized by: The specific working process of the geological data intelligent classification model construction module also includes: Obtain various features of each piece of historical data in the test set of each type of geological data intelligent classification model, substitute them into the intelligent classification model of each type of geological data, and match and obtain the prediction type of each piece of historical data in the test set of each type of geological data intelligent classification model; If the predicted type of a piece of historical data in the test set of a certain type of geological data intelligent classification model is consistent with its actual type, then the piece of historical data is recorded as correctly identified historical data, and the number of correctly identified historical data in the test set of each type of geological data intelligent classification model is counted, and the ratio between the number of correctly identified historical data in the test set of each type of geological data intelligent classification model and the total number of historical data is obtained, which is recorded as the recognition accuracy rate of each type of geological data intelligent classification model; According to the recognition accuracy of the intelligent classification model of each type of geological data, it is judged whether the accuracy of the intelligent classification model of each type of geological data meets the requirements, and the intelligent classification model of each type of geological data whose statistical accuracy does not meet the requirements is determined.

5. The digital geological data intelligent classification management system according to claim 4 is characterized by: The specific working process of the geological data intelligent classification model construction module also includes: The training set and the test set of the intelligent classification model of each type of geological data whose precision does not meet the requirements are integrated to obtain a new training set of the intelligent classification model of each type of geological data whose precision does not meet the requirements; Based on the new training set of the intelligent classification model of various types of geological data whose accuracy does not meet the requirements, the intelligent classification model of various types of geological data whose accuracy does not meet the requirements is reconstructed, and then the intelligent classification model of various types of geological data whose accuracy does not meet the requirements is optimized.

6. The digital geological data intelligent classification management system according to claim 1 is characterized by: The specific working process of the geological data automatic classification and storage module is as follows: Extract various features of each piece of geological data to be entered, compare the various features of each piece of geological data to be entered with the intelligent classification model of each type of geological data, analyze the number of matching features between each piece of geological data to be entered and each type of geological data, take the type corresponding to the largest number of matching features as the type of geological data to be entered, screen out the type of each piece of geological data to be entered, automatically classify each piece of geological data to be entered, and further store it in the corresponding file system of the geological data management platform.

7. The digital geological data intelligent classification management system according to claim 1 is characterized by: The specific working process of the geological data access management module includes: Set the authorized access to geological data sets corresponding to each user role, and then manage the access rights to the geological data stored in the geological data management platform; Obtain the user's access time, accessed network and each piece of geological data accessed on the geological data management platform, summarize the user's access information, and further register the access information of the geological data stored in the geological data management platform; Set the sensitivity factors corresponding to each access time period, each access network type, and each type of geological data, and set the hidden danger factors corresponding to authorized access to geological data and unauthorized access to geological data. Analyze the risk factor of user access based on the user's access information.

8. The digital geological data intelligent classification management system according to claim 7 is characterized by: The specific working process of the geological data access management module also includes: The risk factor of the user's access is compared with the preset risk factor threshold. If the risk factor of the user's access is greater than the preset risk factor threshold, the user's access behavior is a risky access behavior and an early warning is issued.

9. The digital geological data intelligent classification management system according to claim 1 is characterized by: The specific working process of the geological data retrieval query module is as follows: Acquire the search content entered by the user in the geological data management platform, and use the keyword recognition technology to acquire the keywords of the search content entered by the user in the geological data management platform, and record them as the search keywords; Obtain each keyword of each geological data in the geological data management platform, and analyze the cumulative number of associated keywords between each geological data in the geological data management platform and the search keyword; Obtain user query records through the backend system of the geological data management platform, obtain the query heat ranking of each geological data in the geological data management platform, set the query heat coefficient corresponding to each query heat ranking, and screen the query heat coefficient of each geological data in the geological data management platform; Substituting the cumulative number of keywords associated with each piece of geological data and the search keyword in the geological data management platform and the query heat coefficient of each piece of geological data into a preset relationship function between the cumulative number of keywords associated with each piece of geological data and the search keyword, the query heat coefficient and the query tendency index of the geological data, to obtain the query tendency index of each piece of geological data in the geological data management platform; The query tendency indexes of various geological data in the geological data management platform are compared with each other, and the geological data corresponding to the maximum query tendency index is recorded as the geological data that the user intends to query, and intelligently pushed.

10. The digital geological data intelligent classification management system according to claim 1, characterized in that: The specific working process of the geological data value assessment module is as follows: Set the duration of the evaluation cycle, obtain the access records, browsing records and download records of each geological data in the geological data management platform during the evaluation period through the background system of the geological data management platform, obtain the number of visits, number of visitors, visit frequency, number of browsing, number of browsers, browsing frequency, number of downloads, number of downloaders and download frequency of each geological data in the geological data management platform during the evaluation period, and analyze the value evaluation index of each geological data in the geological data management platform; Set the value level corresponding to each value evaluation index range, filter out the value level of each geological data in the geological data management platform, and mark and feedback it.

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