A large model data processing optimization system for design consultation

Abstract

The invention discloses a design consulting big model data processing optimization system, which belongs to the field of data processing technology; it is used to solve the technical problems of poor autonomous supervision effect of document data processing and poor autonomous evaluation management effect of processing optimization in the existing scheme of the design consulting big model; by performing supervision analysis of different aspects of the design consulting big model processing uploaded documents, local processing data corresponding to different aspects are obtained, and local processing data corresponding to different uploaded documents are combined to obtain corresponding document processing supervision data sets; according to the document processing supervision data sets, multi-dimensional data processing evaluation is performed on the different local processing abnormal impacts corresponding to all uploaded documents processed by the design consulting big model, and according to the evaluation results, the subsequent implementation of the existing first processing scheme corresponding to the design consulting big model processing data is dynamically optimized and managed.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a design consulting large model data processing optimization system. Background Art

[0002] Data processing optimization for large models refers to a series of improvements to data when training and deploying large artificial intelligence models to improve the performance, efficiency, and cost-effectiveness of the models; these optimization measures can involve multiple aspects such as data collection, preprocessing, storage, access, and interaction with the models.

[0003] When implementing existing design consulting big model data processing optimization solutions, most of them still remain at the data processing supervision and optimization at the communication and dialogue data level, but are unable to perform different aspects of document processing supervision on the documents uploaded by the design consulting big model processing users, and dynamically optimize the subsequent processing solutions of the design consulting big model processing documents based on the different aspects of document processing supervision results. As a result, the design consulting big model has poor autonomous supervision effect on the processing of document data and poor autonomous evaluation management effect on processing optimization. Summary of the invention

[0004] The purpose of the present invention is to provide a design consulting big model data processing optimization system, which is used to solve the technical problems of poor autonomous supervision of document data processing and poor autonomous evaluation management of processing optimization in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A design consulting large model data processing optimization system, comprising:

[0007] The design consulting big model document processing data supervision module is used to supervise and process the whole process of design consulting big model processing documents uploaded by different users in different aspects, obtain the document processing supervision data set and upload it to the data processing supervision platform; the document processing supervision data set is obtained by sorting and combining all the document processing supervision sequences obtained by supervision;

[0008] The design consulting big model document processing evaluation and optimization module is used to perform multi-dimensional data processing evaluation on the impact of different local processing anomalies corresponding to all uploaded documents processed by the design consulting big model based on the document processing supervision data set, and dynamically optimize the subsequent implementation of the existing first processing plan corresponding to the design consulting big model processing data based on the evaluation results;

[0009] Among them, the design consulting large model processing data corresponding to the first processing abnormal impact state is calculated for all document processing supervision sequences in the document processing supervision data set to obtain the first processing abnormal impact degree;

[0010] And, for all document processing supervision sequences in the document processing supervision data set, the design consulting large model processing data corresponding to the data processing calculation of the re-processing abnormal impact state is performed to obtain the re-processing abnormal impact degree;

[0011] Data analysis is performed on the first processing impact combination sequence obtained by sorting and combining the first processing abnormality impact and the second processing abnormality impact, and based on the analysis results, dynamic optimization management is performed on the subsequent implementation of the existing first processing plan corresponding to the design consulting large model processing data.

[0012] Preferably, documents uploaded by different users are obtained and numbered as i, i=1, 2, 3, ..., n; n is a positive integer;

[0013] According to the document number, the document storage and upload timestamps corresponding to different uploaded documents are obtained in sequence, and the completion receiving timestamps corresponding to different uploaded documents received by the design consulting large model are obtained;

[0014] Obtain the request processing timestamp corresponding to when the user requests to process the uploaded document, and obtain the completion processing timestamp corresponding to when the design consulting big model completes the request processing for the uploaded document;

[0015] Calculate the receiving processing time difference TCi between the uploaded document's corresponding completion processing timestamp and the request processing timestamp, and use the formula Calculate and obtain the first processing validity CXi of the design consulting large model receiving and processing corresponding to the uploaded document; where CZi is the document storage corresponding to the uploaded document; A is the receiving and processing standard value; [*] is the rounding function, which means obtaining the maximum integer that does not exceed the real number *.

[0016] Preferably, the total number of times the user continues to request processing of the output result is obtained, and if the total number of times the user continues to request processing is 0, the re-processing validity corresponding to the uploaded document is set to 0;

[0017] If the total number of continued request processing is not 0, obtain the re-request timestamp corresponding to when the user sends the re-request instruction, and obtain the re-output timestamp corresponding to when the design consulting large model re-outputs the content, and calculate the re-processing time difference TZi between the re-output timestamp and the re-request timestamp.

[0018] Preferably, when the user finishes processing the request for uploading the document, a processing end instruction is generated, and according to the processing end instruction, a plurality of reprocessing time differences are calculated by the formula Calculate the reprocessing validity ZCi of the design consulting large model receiving processing corresponding to the uploaded document; where N is the total number of continued request processing; N0 is the standard total number of continued request processing; TZ0 is the standard total time difference of reprocessing of continued request processing;

[0019] The first processing validity and the second processing validity obtained from the corresponding supervision processing of the user uploaded documents are sorted and combined to obtain the document processing supervision sequence corresponding to the uploaded documents.

[0020] Preferably, when data analysis is performed on the document processing supervision sequence to determine the data processing status of different aspects corresponding to the uploaded document;

[0021] If all elements in the document processing supervision sequence are 0, it indicates that the first processing status and the second processing status corresponding to the uploaded document are normal;

[0022] If there is an element with a value other than 0 in the document processing supervision sequence, it will be prompted that the first processing status and / or the second processing status of the element with a value other than 0 corresponding to the uploaded document is abnormal;

[0023] All document processing supervision sequences obtained by processing different document supervisions uploaded by users in the design consulting big model are sorted and combined to obtain the document processing supervision dataset.

[0024] Preferably, all document processing supervision sequences in the document processing supervision data set, as well as first processing status and reprocessing status associated with different document processing supervision sequences are obtained;

[0025] Count the total number of normal first processing status NSZ and the total number of abnormal first processing status NSY corresponding to all document processing supervision sequences;

[0026] The total number of normal first processing states and the total number of abnormal first processing states are calculated through the first processing reliable identification function to obtain the first processing reliable identification SK corresponding to the design consulting large model processing data;

[0027] According to the first processing reliable flag with a value of 0, the first processing abnormal impact corresponding to the design consulting large model processing data is set to 0.

[0028] Preferably, when calculating the first processing abnormal impact of the design consulting large model processing data according to the first processing reliable flag with a value of 1, all the first processing efficiencies with values ​​other than 0 are calculated by the formula Calculate and obtain the first processing abnormal impact SYY corresponding to the design consulting large model processing data; where CXi´ is the first processing validity with different non-zero values.

[0029] Preferably, the reprocessing validity ZCi of all document processing supervision sequences in the document processing supervision data set is obtained; and all reprocessing valences are calculated by the formula Calculate and obtain the reprocessing abnormal impact ZYY corresponding to the design consulting large model processing data;

[0030] The first processing abnormality impact degree and the second processing abnormality impact degree obtained by processing are sorted and combined to obtain a first processing impact combination sequence.

[0031] Preferably, data analysis is performed on the first processing impact combination sequence, and based on the analysis results, subsequent implementation of the existing first processing solution corresponding to the design consulting large model processing data is maintained, local optimization and upgrade management is performed on the existing first processing solution corresponding to the design consulting large model processing data, or overall optimization and upgrade management is performed on the existing first processing solution corresponding to the design consulting large model processing data.

[0032] Preferably, the expression of the reliable identification function for the first processing is ; In the formula, NSZ and NSY are the total number of normal and abnormal states in the first processing state respectively; B is the reliable standard value of the first processing.

[0033] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0034] The present invention obtains local processing data corresponding to different aspects by performing supervision analysis on the uploaded documents processed by the design consulting big model, and combines the local processing data corresponding to different aspects of different uploaded documents to obtain the corresponding document processing supervision data set. It can provide reliable multi-dimensional supervision processing data support for the subsequent design consulting big model processing of different local processing exception impact analysis corresponding to all uploaded documents, thereby improving the autonomous supervision effect of the design consulting big model on the processing of document data.

[0035] The present invention performs multi-dimensional data processing evaluation on the impact of different local processing exceptions corresponding to the design consulting big model processing all uploaded documents based on the document processing supervision data set, and dynamically optimizes the subsequent implementation of the existing first processing solution corresponding to the design consulting big model processing data based on the evaluation results, thereby realizing multi-dimensional data integration evaluation of the impact of first processing exceptions corresponding to the design consulting big model processing data, and improving the autonomous evaluation management effect of the design consulting big model for document data processing optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below in conjunction with the accompanying drawings.

[0037] Figure 1 The present invention is a flowchart of the steps for implementing a design consulting large model data processing optimization system.

[0038] Figure 2 A flowchart of the data analysis of the document processing supervision sequence in the present invention.

[0039] Figure 3 It is a flowchart of the data analysis of the first processing impact combination sequence in the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] like Figure 1 As shown, the present invention is a design consulting large model data processing optimization system, including a data processing supervision platform, and a design consulting large model document processing data supervision module and a design consulting large model document processing evaluation optimization module which are communicatively connected to the data processing supervision platform;

[0042] The design consulting big model document processing data supervision module is used to supervise and process the whole process of design consulting big model processing documents uploaded by different users in different aspects, obtain the document processing supervision data set and upload it to the data processing supervision platform; including:

[0043] Obtain documents uploaded by different users and mark them with numbers i, where i=1, 2, 3, ..., n; n is a positive integer; the documents uploaded by users may specifically be engineering design documents, and the specific type of the design documents may be customized according to the actual application requirements of the actual application scenario;

[0044] Among them, different users can upload documents through the data processing supervision platform and send processing requests to the data processing supervision platform;

[0045] According to the document number, the document storage and upload timestamps corresponding to different uploaded documents are obtained in sequence, and the completion receiving timestamps corresponding to different uploaded documents received by the design consulting large model are obtained;

[0046] The unit of the document storage is megabytes; the unit of the upload timestamp and the completion reception timestamp is milliseconds, and the units of the subsequent timestamps are also milliseconds;

[0047] Obtain the request processing timestamp corresponding to when the user requests to process the uploaded document, and obtain the completion processing timestamp corresponding to when the design consulting big model completes the request processing for the uploaded document;

[0048] Calculate the receiving processing time difference TCi between the uploaded document's corresponding completion processing timestamp and the request processing timestamp, and use the formula Calculate and obtain the first processing validity CXi of the design consulting large model receiving and processing corresponding to the uploaded document; where CZi is the document storage corresponding to the uploaded document; A is the receiving and processing standard value, which is determined according to the running design data corresponding to the design consulting large model document data processing; [*] is the rounding function, which means obtaining the maximum integer that does not exceed the real number *;

[0049] It should be noted that the first processing validity is used to calculate various data of different aspects of the design consulting large model receiving and processing uploaded documents, so as to digitally represent the first processing status corresponding to the uploaded documents;

[0050] And, obtaining the total number of times the user continues to request processing of the output result, if the total number of times the user continues to request processing is 0, setting the re-processing validity corresponding to the uploaded document to 0;

[0051] The determination of continuing the request processing can be determined based on the user's continued questioning of the processing result of the uploaded document and the content related to the document. The identification of the content that the user continues to ask can be implemented based on the existing text processing and analysis algorithms, including but not limited to text preprocessing, feature extraction, text classification, clustering, etc. The specific implementation steps are not repeated here;

[0052] If the total number of continued request processing is not 0, then obtain the re-request timestamp corresponding to when the user sends the re-request instruction, and obtain the re-output timestamp corresponding to when the design consulting large model re-outputs the content, and calculate the re-processing time difference TZi between the re-output timestamp and the re-request timestamp;

[0053] When the user completes the request processing of the uploaded document, a processing end instruction is generated, and according to the processing end instruction, several re-processing time differences are calculated by the formula Calculate and obtain the reprocessing validity ZCi of the design consulting large model receiving processing corresponding to the uploaded document; where N is the total number of continued request processing; N0 is the standard total number of continued request processing; TZ0 is the standard total time difference of reprocessing of continued request processing; the standard total number of times and the standard total time difference of reprocessing can be determined according to the running design data corresponding to the design consulting large model document data processing, or according to the median of the total number of all historical continued request processing corresponding to the design consulting large model document data processing, and the median of the reprocessing time difference of all historical continued request processing;

[0054] It should be noted that the reprocessing validity is used to calculate all the user's continued request processing data after the uploaded document is received and processed by the design consulting big model, so as to digitally represent the reprocessing status corresponding to the uploaded document;

[0055] It is worth noting that the larger the value of the reprocessing validity is, the worse the initial processing status of the uploaded document receiving process of the design consulting big model is from another aspect;

[0056] The first processing validity and the second processing validity obtained by the supervision processing of the user uploaded documents are sorted and combined to obtain the document processing supervision sequence corresponding to the uploaded documents;

[0057] In the embodiment of the present invention, by supervising and combining the processing data of different aspects of the design consulting large model receiving and processing uploaded documents, a document processing supervision sequence corresponding to a single uploaded document is obtained, which can not only realize the digital representation of different aspects of the first processing status of the design consulting large model receiving and processing uploaded documents, but also provide reliable multi-dimensional local supervision processing data support for the dynamic optimization management of the existing first processing scheme corresponding to the subsequent design consulting large model processing data;

[0058] like Figure 2 As shown, when data analysis is performed on the document processing supervision sequence to determine the data processing status of different aspects of the uploaded document;

[0059] If all elements in the document processing supervision sequence are 0, it indicates that the first processing status and the second processing status corresponding to the uploaded document are normal;

[0060] If there is an element with a value other than 0 in the document processing supervision sequence, it will be prompted that the first processing status and / or the second processing status of the element with a value other than 0 corresponding to the uploaded document is abnormal;

[0061] Among them, by analyzing the data of the document processing supervision sequence of the processing combination, the data processing status of different aspects corresponding to the uploaded document can be obtained, and reliable local processing status data support can also be provided for the subsequent first processing reliable identification processing calculation;

[0062] All document processing supervision sequences obtained by processing different document supervisions uploaded by the design consulting big model are sorted and combined to obtain a document processing supervision dataset;

[0063] With respect to the data processing of the existing design consulting big model, most of the existing technical solutions still stay at the level of dialogue supervision and data processing, and do not perform multidimensional data analysis on the design consulting big model processing documents uploaded by users, which leads to poor data processing and analysis effect and poor optimization management effect of the design consulting big model for documents. In the embodiment of the present invention, by performing supervision and analysis of different aspects of the uploaded documents processed by the design consulting big model, local processing data corresponding to different aspects are obtained, and the local processing data corresponding to different aspects of different uploaded documents are combined to obtain the corresponding document processing supervision data set, which can provide reliable multidimensional supervision processing data support for the subsequent design consulting big model processing of different local processing abnormality impact analysis corresponding to all uploaded documents, thereby improving the autonomous supervision effect of the design consulting big model on the processing of document data.

[0064] The design consulting big model document processing evaluation and optimization module is used to perform multi-dimensional data processing evaluation on the impact of different local processing anomalies corresponding to all uploaded documents processed by the design consulting big model based on the document processing supervision data set, and dynamically optimize the subsequent implementation of the existing first processing plan corresponding to the design consulting big model processing data based on the evaluation results; including:

[0065] Obtain all document processing supervision sequences in the document processing supervision data set, as well as the first processing status and the reprocessing status associated with different document processing supervision sequences;

[0066] Count the total number of normal first processing status NSZ and the total number of abnormal first processing status NSY corresponding to all document processing supervision sequences;

[0067] The total number of normal first processing states and the total number of abnormal first processing states are calculated through the first processing reliable identification function to obtain the first processing reliable identification SK corresponding to the design consulting large model processing data;

[0068] Among them, the expression of the reliable identification function for the first time is ; In the formula, NSZ and NSY are the total number of normal and abnormal states in the first treatment state respectively; B is the reliable standard value of the first treatment;

[0069] The first processing reliability flag includes a value of 0 or 1. The first processing reliability flag with a value of 0 indicates that the first processing reliability state corresponding to the design consulting large model processing data is normal;

[0070] The first processing reliability flag with a value of 1 indicates that the first processing reliability state corresponding to the design consulting large model processing data is abnormal;

[0071] In the embodiment of the present invention, by integrating and calculating the first processing status supervision data corresponding to all uploaded documents processed by the design consulting big model, the corresponding first processing reliable identification is obtained, which can not only realize the digital representation of the first processing abnormality impact of the design consulting big model processing data, but also provide reliable data support for the subsequent first processing abnormality impact degree processing analysis of the design consulting big model processing data;

[0072] Among them, the first processing abnormal impact corresponding to the design consulting large model processing data is set to 0 according to the first processing reliable flag with a value of 0;

[0073] When calculating the first processing abnormal impact of the design consulting large model processing data according to the first processing reliable flag with a value of 1, the first processing validity of all non-0 values ​​is calculated by the formula Calculate and obtain the first processing abnormal impact SYY corresponding to the design consulting large model processing data; where CXi´ is the first processing validity with different non-zero values, i´=1, 2, 3, ..., NSY;

[0074] It should be noted that the first processing anomaly impact is used to perform extended calculations on the first processing status supervision data corresponding to all first processing reliable status anomalies, so as to digitally represent the first processing anomaly impact of the design consulting large model processing data;

[0075] And, obtain the reprocessing validity ZCi contained in all document processing supervision sequences in the document processing supervision data set; and use the formula to sum up all the reprocessing validity Calculate and obtain the reprocessing abnormal impact ZYY corresponding to the design consulting large model processing data;

[0076] In the embodiment of the present invention, by integrating and calculating all the reprocessing exception data corresponding to the uploaded document of the design consulting large model processing, the impact degree of the first processing exception of the design consulting large model processing data is digitally represented from the aspect of reprocessing;

[0077] Sort and combine the first processing abnormality impact obtained by processing and the second processing abnormality impact, and obtain the first processing impact combination sequence [SYY, ZYY];

[0078] Different from the existing technical solutions, which only process and analyze the processing status of the design consulting large model processing data from a single dimension, and cannot verify and process the processing status of the design consulting large model processing data from different aspects, resulting in poor reliability of the supervision and analysis of the design consulting large model processing data; in the embodiment of the present invention, by digitally processing and combining the first processing abnormal impact degree of the design consulting large model processing data from different aspects, the first processing impact combination sequence corresponding to the design consulting large model processing data is obtained, which can provide reliable multi-dimensional supervision processing data support for the dynamic optimization management of the subsequent implementation of the existing first processing scheme corresponding to the subsequent design consulting large model processing data;

[0079] like Figure 3 As shown, the data analysis is performed on the combination sequence of the first processing influence, and the subsequent implementation of the existing first processing scheme corresponding to the design consulting large model processing data is dynamically optimized and managed according to the analysis results;

[0080] If the first processing impact combination sequence is [0, 0], then the subsequent implementation of the existing first processing solution corresponding to the design consulting large model processing data is maintained;

[0081] If the first processing impact combination sequence is [0, K] or [K, 0], local optimization and upgrade management is performed on the existing first processing scheme corresponding to the design consulting large model processing data; K is a real number greater than 0;

[0082] If the first processing impact combination sequence is [K, K], the existing first processing solution corresponding to the design consulting large model processing data is comprehensively optimized and upgraded.

[0083] In an embodiment of the present invention, a multidimensional data processing evaluation is performed on the impact of different local processing exceptions corresponding to the design consulting big model processing all uploaded documents based on the document processing supervision data set, and the subsequent implementation of the existing first processing solution corresponding to the design consulting big model processing data is dynamically optimized and managed based on the evaluation results, thereby realizing a multidimensional data integration evaluation of the impact of the first processing exceptions corresponding to the design consulting big model processing data, and improving the autonomous evaluation management effect of the design consulting big model on the processing optimization of document data.

[0084] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0085] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0086] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0088] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A design consulting large model data processing optimization system, characterized in that: include: The design consulting big model document processing data supervision module is used to supervise and process the whole process of design consulting big model processing documents uploaded by different users in different aspects, obtain the document processing supervision data set and upload it to the data processing supervision platform; the document processing supervision data set is obtained by sorting and combining all the document processing supervision sequences obtained by supervision; The design consulting big model document processing evaluation and optimization module is used to perform multi-dimensional data processing evaluation on the impact of different local processing anomalies corresponding to all uploaded documents processed by the design consulting big model based on the document processing supervision data set, and dynamically optimize the subsequent implementation of the existing first processing plan corresponding to the design consulting big model processing data based on the evaluation results; Among them, all document processing supervision sequences in the document processing supervision data set, as well as the first processing status and the reprocessing status associated with different document processing supervision sequences are obtained; Count the total number of normal first processing status NSZ and the total number of abnormal first processing status NSY corresponding to all document processing supervision sequences; The total number of normal first processing states and the total number of abnormal first processing states are calculated through the first processing reliable identification function to obtain the first processing reliable identification SK corresponding to the design consulting large model processing data; According to the first processing reliable flag with a value of 0, the first processing abnormal impact corresponding to the design consulting large model processing data is set to 0; When calculating the first processing abnormal impact of the design consulting large model processing data according to the first processing reliable flag with a value of 1, the first processing validity of all non-0 values ​​is calculated by the formula Calculate and obtain the first processing abnormal impact SYY corresponding to the design consulting large model processing data; where CXi´ is the first processing validity with different non-zero values; Get the reprocessing validity ZCi of all document processing supervision sequences in the document processing supervision data set; and use the formula to calculate all reprocessing validity Calculate and obtain the reprocessing abnormal impact ZYY corresponding to the design consulting large model processing data; Data analysis is performed on the first processing impact combination sequence obtained by sorting and combining the first processing abnormality impact and the second processing abnormality impact, and based on the analysis results, dynamic optimization management is performed on the subsequent implementation of the existing first processing plan corresponding to the design consulting large model processing data.

2. A design consulting large model data processing and optimization system according to claim 1, characterized in that: Get the documents uploaded by different users and mark them as i, i=1, 2, 3, ..., n; n is a positive integer; According to the document number, the document storage and upload timestamps corresponding to different uploaded documents are obtained in sequence, and the completion receiving timestamps corresponding to different uploaded documents received by the design consulting large model are obtained; Obtain the request processing timestamp corresponding to when the user requests to process the uploaded document, and obtain the completion processing timestamp corresponding to when the design consulting big model completes the request processing for the uploaded document; Calculate the receiving processing time difference TCi between the uploaded document's corresponding completion processing timestamp and the request processing timestamp, and use the formula Calculate and obtain the first processing validity CXi of the design consulting large model receiving and processing corresponding to the uploaded document; where CZi is the document storage corresponding to the uploaded document; A is the receiving and processing standard value; [*] is the rounding function, which means obtaining the maximum integer that does not exceed the real number *.

3. A design consulting large model data processing and optimization system according to claim 2, characterized in that: Get the total number of times the user continues to request processing of the output result. If the total number of times the user continues to request processing is 0, the re-processing validity corresponding to the uploaded document is set to 0; If the total number of continued request processing is not 0, obtain the re-request timestamp corresponding to when the user sends the re-request instruction, and obtain the re-output timestamp corresponding to when the design consulting large model re-outputs the content, and calculate the re-processing time difference TZi between the re-output timestamp and the re-request timestamp.

4. A design consulting large model data processing and optimization system according to claim 3, characterized in that: When the user completes the request processing of the uploaded document, a processing end instruction is generated, and according to the processing end instruction, several re-processing time differences are calculated by the formula Calculate the reprocessing validity ZCi of the received processing of the design consulting large model corresponding to the uploaded document; where N is the total number of continued request processing; N0 is the standard total number of continued request processing; TZ0 is the total time difference of the reprocessing standard for the continued request processing; The first processing validity and the second processing validity obtained from the corresponding supervision processing of the user uploaded documents are sorted and combined to obtain the document processing supervision sequence corresponding to the uploaded documents.

5. A design consulting large model data processing and optimization system according to claim 4, characterized in that: When analyzing the data of the document processing supervision sequence to determine the data processing status of different aspects of the uploaded documents; If all elements in the document processing supervision sequence are 0, it indicates that the first processing status and the second processing status corresponding to the uploaded document are normal; If there is an element with a value other than 0 in the document processing supervision sequence, it will be prompted that the first processing status and / or the second processing status of the element with a value other than 0 corresponding to the uploaded document is abnormal; All document processing supervision sequences obtained by processing different document supervisions uploaded by users in the design consulting big model are sorted and combined to obtain the document processing supervision dataset.

6. A design consulting large model data processing and optimization system according to claim 1, characterized in that: Conduct data analysis on the combination sequence that affects the first processing, and based on the analysis results, maintain the subsequent implementation of the existing first processing plan corresponding to the design consulting large model processing data, perform local optimization and upgrade management on the existing first processing plan corresponding to the design consulting large model processing data, or perform overall optimization and upgrade management on the existing first processing plan corresponding to the design consulting large model processing data.

7. A design consulting large model data processing and optimization system according to claim 1, characterized in that: The expression of the reliable identification function for the first treatment is ; In the formula, NSZ and NSY are the total number of normal and abnormal states in the first processing state respectively; B is the reliable standard value of the first processing.

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