An information processing method and system for engineering quality detection

Abstract

The present invention provides an information processing method and system for project quality detection, which relates to the field of data processing technology. In the present invention, based on the confirmed construction project cluster, the corresponding current detection priority is obtained; from the remaining construction project clusters to be analyzed, each remaining construction project to be analyzed for which the construction quality detection priority has not yet been determined is obtained; based on the construction project description data to be analyzed of each construction project to be analyzed, the confirmed construction project cluster and the remaining construction project clusters to be analyzed, the internal priority coefficient corresponding to each remaining construction project to be analyzed is analyzed; based on the internal priority coefficient, at least one remaining construction project to be analyzed is determined in the remaining construction project clusters to be analyzed, and the current detection priority is used as the construction quality detection priority of at least one remaining construction project to be analyzed. Based on the above method, the reliability of priority determination in project quality detection can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an information processing method and system for engineering quality detection. Background Art

[0002] Project quality inspection is an important means in the field of engineering applications. Therefore, in the prior art, construction project data is generally analyzed to determine the corresponding project quality. In addition, in the prior art, a large amount of concurrency may be encountered, that is, the quality of more construction projects needs to be analyzed. Therefore, it is necessary to determine the corresponding priority, such as first analyzing the quality of construction project 1, and then analyzing construction project 2. However, in the prior art, the priority of the analysis is generally determined arbitrarily, which makes its reliability low. Summary of the invention

[0003] In view of this, an object of the present invention is to provide an information processing method and system for engineering quality inspection, so as to improve the reliability of priority determination in engineering quality inspection.

[0004] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0005] An information processing method for engineering quality detection, comprising:

[0006] Determine the construction project description data to be analyzed of each construction project to be analyzed in the construction project cluster to be analyzed, wherein the construction project cluster to be analyzed includes a plurality of construction projects to be analyzed;

[0007] According to the description data of each of the construction projects to be analyzed, based on the form of performing the target operation in turn, the engineering quality inspection priority of each of the construction projects to be analyzed is analyzed, and performing the target operation once includes:

[0008] Based on the confirmed construction project cluster, a corresponding current detection priority is obtained, wherein the confirmed construction project cluster includes each confirmed construction project for which a construction quality detection priority has been determined, and the current detection priority is the highest detection priority other than the construction quality detection priority of each confirmed construction project that has been determined so far;

[0009] From the remaining to-be-analyzed construction project clusters, each remaining to-be-analyzed construction project for which the construction quality inspection priority has not yet been determined is obtained;

[0010] Analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed according to the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project cluster and the remaining building project clusters to be analyzed;

[0011] Based on the internal priority coefficient, at least one remaining construction project to be analyzed is determined in the cluster of remaining construction projects to be analyzed, and the current detection priority is used as the project quality detection priority of the at least one remaining construction project to be analyzed.

[0012] In some preferred embodiments, in the above-mentioned information processing method for project quality detection, the step of analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed based on the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project clusters and the remaining building project clusters to be analyzed includes:

[0013] Extracting a first feature representation of the engineering data analyzed based on the description data of the construction engineering to be analyzed of each of the construction engineering to be analyzed;

[0014] Performing a related information mining operation based on the first feature representation of the engineering data and the first feature representation of the analysis situation to output a first feature representation of the related information between each of the confirmed construction projects, wherein the first feature representation of the related information is used to reflect the content correlation information between each of the confirmed construction projects, and the first feature representation of the analysis situation is obtained based on the analysis of each of the confirmed construction projects, and each feature representation parameter in the first feature representation of the analysis situation is used to reflect whether the corresponding construction project to be analyzed has analyzed the corresponding engineering quality detection priority;

[0015] An information mining operation is performed based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status, so as to output a first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed, wherein the first characteristic representation of the remaining information is used to reflect the engineering data information of each of the remaining construction projects to be analyzed, and the first characteristic representation of the analysis status is obtained based on the analysis of each of the remaining construction projects to be analyzed, and each characteristic representation parameter in the first characteristic representation of the analysis status is used to reflect whether the corresponding construction project to be analyzed has not yet analyzed the engineering quality detection priority;

[0016] Based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information, the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed is analyzed.

[0017] In some preferred embodiments, in the above-mentioned information processing method for project quality detection, the step of extracting the first feature representation of the project data analyzed based on the description data of the construction project to be analyzed of each of the construction projects to be analyzed comprises:

[0018] Loading the construction project description data to be analyzed of each of the construction projects to be analyzed to load into the engineering data encoding network formed by network optimization;

[0019] Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the construction engineering to be analyzed, so as to output a corresponding first feature representation of the engineering data;

[0020] The engineering data encoding network is formed by network optimization based on a typical engineering data cluster, wherein the typical engineering data in the typical engineering data cluster includes description data of the typical construction project to be analyzed and actual engineering quality inspection priority and actual internal priority coefficient corresponding to the typical construction project to be analyzed.

[0021] In some preferred embodiments, in the above-mentioned information processing method for engineering quality detection, the engineering data encoding network further includes an analysis output subnetwork and a linear processing subnetwork;

[0022] The step of performing a related information mining operation based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis situation to output the first characteristic representation of the related information between each of the confirmed construction projects includes:

[0023] The first feature representation of the engineering data is loaded to be loaded into the analysis output sub-network included in the engineering data encoding network, so as to use the analysis output sub-network to perform a multiplication operation on the first feature representation of the engineering data and the first feature representation of the analysis situation, and output the first feature representation of the relevant information between each of the confirmed construction projects;

[0024] The step of performing information mining operations based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status to output the first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed comprises:

[0025] According to the analysis output sub-network, a multiplication operation is performed on the first feature representation of the engineering data and the first feature representation of the analysis state, and a first feature representation of the remaining information corresponding to each of the remaining construction projects to be analyzed is output;

[0026] The step of analyzing the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information comprises:

[0027] The linear processing subnetwork is used to linearly process the cascaded combined first feature representation formed by cascading the first feature representation of the relevant information and the first feature representation of the remaining information, and output the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed.

[0028] In some preferred embodiments, in the above-mentioned information processing method for engineering quality detection, the network optimization of the engineering data encoding network includes:

[0029] Based on the typical engineering data in the typical engineering data cluster, the engineering data encoding network is subjected to multi-stage network optimization, and after the network optimization process is completed, an optimized engineering data encoding network is obtained. One stage of network optimization includes:

[0030] Determining a typical engineering data combination in the typical engineering data cluster;

[0031] Loading the construction project description data to be analyzed of each typical construction project to be analyzed in the typical engineering data combination, the current confirmed typical construction project cluster and the remaining typical construction project clusters to be analyzed, as well as the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed in the next stage, so as to load them into the engineering data encoding network, wherein the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed are obtained according to the actual engineering quality detection priority analysis;

[0032] Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the typical construction engineering to be analyzed, so as to output a second feature representation of the engineering data of the typical engineering data combination;

[0033] The second characteristic representation of the engineering data is loaded to the analysis output sub-network in the engineering data encoding network, so as to use the analysis output sub-network to analyze the first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster to be analyzed, and to analyze the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage;

[0034] According to the first analysis value of the internal priority coefficient, the second analysis value of the internal priority coefficient and the corresponding actual internal priority coefficient, a target error parameter is calculated, and based on the target error parameter, the engineering data encoding network is optimized.

[0035] In some preferred embodiments, in the above-mentioned information processing method for project quality detection, the process of confirming the typical building project clusters and the determination process of the remaining typical building project clusters to be analyzed includes:

[0036] Among the typical engineering data combinations, a randomly determined typical engineering data is marked to form typical engineering data to be processed;

[0037] Based on the actual engineering quality inspection priority and each typical construction project to be analyzed before the typical construction project to be analyzed in the typical engineering data to be processed, determine the current confirmed typical construction project cluster, and, based on the typical construction projects to be analyzed in other typical engineering data, determine the current remaining typical construction project clusters to be analyzed;

[0038] Based on the actual project quality inspection priority, the typical construction projects to be analyzed in the typical project data to be processed and each typical construction project to be analyzed before the typical construction project to be analyzed, the confirmed typical construction project clusters for the subsequent stage are determined, and, based on the typical construction projects to be analyzed in other typical project data, the remaining typical construction project clusters to be analyzed in the subsequent stage are determined.

[0039] In some preferred embodiments, in the above-mentioned information processing method for engineering quality detection, the analysis output subnetwork includes a first analysis output unit and a second analysis output unit;

[0040] The step of loading the second characteristic representation of the engineering data to load it into the analysis output sub-network in the engineering data encoding network, and using the analysis output sub-network to analyze the first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster to be analyzed, and analyzing the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage, comprises:

[0041] Utilizing the first analysis output unit, after multiplying the second feature representation of the engineering data and the second feature representation of the analysis situation, a focused feature analysis operation is performed to output the second feature representation of the related information between each confirmed typical construction project in the current confirmed typical construction project cluster, wherein the second feature representation of the related information is used to reflect the content correlation information between each currently confirmed typical construction project, and each feature representation parameter in the second feature representation of the analysis situation is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination has analyzed the engineering quality inspection priority;

[0042] Using the first analysis output unit, determine the residual information second feature representation formed by multiplying the second feature representation of the engineering data and the second feature representation of the analysis status, the residual information second feature representation is used to display the engineering data information of each remaining typical construction project to be analyzed, and each feature representation parameter in the second feature representation of the analysis status is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination has not yet analyzed the engineering quality detection priority;

[0043] Using the linear processing subnetwork in the first analysis output unit, a cascade combination second feature representation formed by cascading the second feature representation of the relevant information and the second feature representation of the remaining information is linearly processed to output a first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster;

[0044] Utilizing the second analysis output unit, after multiplying the second feature representation of the engineering data and the third feature representation of the analysis situation, a focused feature analysis operation is performed to output the third feature representation of the related information between each confirmed typical construction project in the confirmed typical construction project cluster at the next stage, wherein the third feature representation of the related information is used to reflect the content correlation information between each confirmed typical construction project at the next stage, and each feature representation parameter in the third feature representation of the analysis situation is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination at the next stage has been analyzed for the engineering quality inspection priority;

[0045] Using the second analysis output unit, determine the residual information third feature representation formed by multiplying the second feature representation of the engineering data and the third feature representation of the analysis status, the residual information third feature representation is used to reflect the engineering data information of each remaining typical construction project to be analyzed in the next stage, and each feature representation parameter in the third feature representation of the analysis status is used to reflect whether the construction project to be analyzed in the typical engineering data combination corresponding to the next stage has not yet analyzed the engineering quality detection priority;

[0046] Utilizing the linear processing subnetwork in the second analysis output unit, the cascaded combined third feature representation formed by the cascade combination of the third feature representation of the relevant information and the third feature representation of the residual information is linearly processed to output the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage.

[0047] The embodiment of the present invention further provides an information processing system for engineering quality detection, including:

[0048] A description data determination module, used to determine the description data of the building project to be analyzed for each building project to be analyzed in the building project cluster to be analyzed, wherein the building project cluster to be analyzed includes a plurality of building projects to be analyzed;

[0049] The detection priority analysis module is used to analyze the engineering quality detection priority of each of the construction projects to be analyzed based on the description data of the construction projects to be analyzed, based on the form of performing the target operation in turn, and performing the target operation once includes:

[0050] Based on the confirmed construction project cluster, a corresponding current detection priority is obtained, wherein the confirmed construction project cluster includes each confirmed construction project for which a construction quality detection priority has been determined, and the current detection priority is the highest detection priority other than the construction quality detection priority of each confirmed construction project that has been determined so far;

[0051] From the remaining to-be-analyzed construction project clusters, each remaining to-be-analyzed construction project for which the construction quality inspection priority has not yet been determined is obtained;

[0052] Analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed according to the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project cluster and the remaining building project clusters to be analyzed;

[0053] Based on the internal priority coefficient, at least one remaining construction project to be analyzed is determined in the cluster of remaining construction projects to be analyzed, and the current detection priority is used as the project quality detection priority of the at least one remaining construction project to be analyzed.

[0054] In some preferred embodiments, in the above-mentioned information processing system for engineering quality detection, the detection priority analysis module is specifically used to:

[0055] Extracting a first feature representation of the engineering data analyzed based on the description data of the construction engineering to be analyzed of each of the construction engineering to be analyzed;

[0056] Performing a related information mining operation based on the first feature representation of the engineering data and the first feature representation of the analysis situation to output a first feature representation of the related information between each of the confirmed construction projects, wherein the first feature representation of the related information is used to reflect the content correlation information between each of the confirmed construction projects, the first feature representation of the analysis situation is obtained based on the analysis of each of the confirmed construction projects, and each feature representation parameter in the first feature representation of the analysis situation is used to reflect whether the corresponding construction project to be analyzed has analyzed the corresponding engineering quality detection priority;

[0057] An information mining operation is performed based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status, so as to output a first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed, wherein the first characteristic representation of the remaining information is used to reflect the engineering data information of each of the remaining construction projects to be analyzed, and the first characteristic representation of the analysis status is obtained based on the analysis of each of the remaining construction projects to be analyzed, and each characteristic representation parameter in the first characteristic representation of the analysis status is used to reflect whether the corresponding construction project to be analyzed has not yet analyzed the engineering quality detection priority;

[0058] Based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information, the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed is analyzed.

[0059] In some preferred embodiments, in the above-mentioned information processing system for engineering quality detection, the first feature representation of the engineering data extracted from the analysis of the construction engineering description data to be analyzed of each of the construction engineering to be analyzed includes:

[0060] Loading the construction project description data to be analyzed of each of the construction projects to be analyzed to load into the engineering data encoding network formed by network optimization;

[0061] Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the construction engineering to be analyzed, so as to output a corresponding first feature representation of the engineering data;

[0062] The engineering data encoding network is formed by network optimization based on a typical engineering data cluster, wherein the typical engineering data in the typical engineering data cluster includes description data of the typical construction project to be analyzed and actual engineering quality inspection priority and actual internal priority coefficient corresponding to the typical construction project to be analyzed.

[0063] An information processing method and system for project quality inspection provided by an embodiment of the present invention can obtain the corresponding current inspection priority based on the confirmed construction project cluster; obtain each remaining construction project to be analyzed for which the engineering quality inspection priority has not yet been determined from the remaining construction project clusters to be analyzed; analyze the internal priority coefficient corresponding to each remaining construction project to be analyzed based on the construction project description data to be analyzed, the confirmed construction project cluster and the remaining construction project clusters to be analyzed of each construction project to be analyzed; based on the internal priority coefficient, determine at least one remaining construction project to be analyzed in the remaining construction project clusters to be analyzed, and use the current inspection priority as the engineering quality inspection priority of at least one remaining construction project to be analyzed. Based on the above content, since the engineering quality inspection priority is determined based on information such as the construction project description data to be analyzed, compared with the conventional technical solution of arbitrarily determining the inspection priority, the reliability of priority determination in engineering quality inspection can be improved, thereby improving the problem of low reliability existing in the prior art.

[0064] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 A structural block diagram of an information processing platform for engineering quality inspection provided in an embodiment of the present invention.

[0066] Figure 2 A flowchart of the steps included in the information processing method for engineering quality detection provided in an embodiment of the present invention.

[0067] Figure 3 A schematic diagram of various modules included in an information processing system for engineering quality inspection provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0069] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. 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.

[0070] like Figure 1 As shown, an embodiment of the present invention provides an information processing platform for engineering quality detection, wherein the information processing platform for engineering quality detection may include a memory and a processor, or may also include other devices.

[0071] In detail, the memory and the processor are electrically connected directly or indirectly to achieve data transmission or interaction. For example, they can be electrically connected to each other through one or more communication buses or signal lines. The memory can store at least one software function module (computer program) that can exist in the form of software or firmware. The processor can be used to execute the executable computer program stored in the memory, thereby realizing the information processing method for engineering quality detection provided by the embodiment of the present invention (as described later).

[0072] Optionally, in some embodiments, the memory may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), etc.

[0073] Optionally, in some embodiments, the processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a system on chip (SoC), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0074] Optionally, in some implementations, the information processing platform for engineering quality inspection may be a server with data processing capabilities.

[0075] Combination Figure 2The embodiment of the present invention further provides an information processing method for engineering quality detection, which can be applied to the above-mentioned information processing platform for engineering quality detection. Among them, the method steps defined in the process related to the information processing method for engineering quality detection can be implemented by the information processing platform for engineering quality detection.

[0076] The following will Figure 2 The specific process shown is explained in detail.

[0077] Step S110, determining the construction project description data to be analyzed of each construction project to be analyzed in the construction project cluster to be analyzed.

[0078] In an embodiment of the present invention, the information processing platform for project quality detection can determine the construction project description data to be analyzed of each construction project to be analyzed in the construction project cluster to be analyzed. The construction project cluster to be analyzed includes multiple construction projects to be analyzed. The construction project description data to be analyzed can be text data, image data, etc.

[0079] Step S120, analyzing the engineering quality inspection priority of each of the construction projects to be analyzed based on the form of executing the target operation in turn according to the construction project description data to be analyzed of each of the construction projects to be analyzed.

[0080] In an embodiment of the present invention, the information processing platform for engineering quality detection can analyze the engineering quality detection priority of each of the to-be-analyzed construction projects based on the form of sequentially performing target operations according to the to-be-analyzed construction project description data of each of the to-be-analyzed construction projects. Executing the target operation once may include the following steps:

[0081] First, based on the confirmed construction project cluster, the corresponding current detection priority is obtained, the confirmed construction project cluster includes each confirmed construction project for which the engineering quality detection priority has been determined, and the current detection priority is the highest detection priority other than the engineering quality detection priority of each confirmed construction project that has been determined so far; secondly, from the remaining construction project clusters to be analyzed, each remaining construction project for which the engineering quality detection priority has not yet been determined is obtained; then, based on the construction project description data to be analyzed of each construction project to be analyzed, the confirmed construction project cluster and the remaining construction project clusters to be analyzed, the internal priority coefficient corresponding to each remaining construction project to be analyzed is analyzed; finally, based on the internal priority coefficient, in the remaining construction project clusters to be analyzed, at least one remaining construction project to be analyzed (such as one or more with the largest internal priority coefficient) is determined, and the current detection priority is used as the engineering quality detection priority of the at least one remaining construction project to be analyzed.

[0082] Based on the above content, namely the above steps S110 and S120, since the priority of project quality inspection is determined based on information such as the description data of the construction project to be analyzed, compared with the conventional technical solution of arbitrarily determining the inspection priority, the reliability of priority determination in project quality inspection can be improved, thereby improving the problem of low reliability existing in the prior art.

[0083] Optionally, in some implementations, the step of analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed based on the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project clusters and the remaining building project clusters to be analyzed may further include the following contents:

[0084] Extracting a first feature representation of the engineering data analyzed based on the description data of the construction engineering to be analyzed of each of the construction engineering to be analyzed;

[0085] Performing a related information mining operation based on the first feature representation of the engineering data and the first feature representation of the analysis situation to output a first feature representation of the related information between each of the confirmed construction projects, wherein the first feature representation of the related information is used to reflect the content correlation information between each of the confirmed construction projects, and the first feature representation of the analysis situation is obtained based on the analysis of each of the confirmed construction projects, and each feature representation parameter in the first feature representation of the analysis situation is used to reflect whether the corresponding construction project to be analyzed has analyzed the corresponding engineering quality detection priority;

[0086] An information mining operation is performed based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status, so as to output a first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed, wherein the first characteristic representation of the remaining information is used to reflect the engineering data information of each of the remaining construction projects to be analyzed, and the first characteristic representation of the analysis status is obtained based on the analysis of each of the remaining construction projects to be analyzed, and each characteristic representation parameter in the first characteristic representation of the analysis status is used to reflect whether the corresponding construction project to be analyzed has not yet analyzed the engineering quality detection priority;

[0087] Based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information, the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed is analyzed.

[0088] Optionally, in some embodiments, the step of extracting the first feature representation of the engineering data analyzed based on the description data of the to-be-analyzed building project of each to-be-analyzed building project may further include the following contents:

[0089] Loading the construction project description data to be analyzed of each of the construction projects to be analyzed to load into a construction data coding network formed by network optimization, wherein the construction data coding network is formed by network optimization based on a typical construction data cluster, wherein the typical construction data in the typical construction data cluster includes the construction project description data to be analyzed of the typical construction project to be analyzed and the actual construction quality detection priority and actual internal priority coefficient corresponding to the typical construction project to be analyzed;

[0090] By utilizing the engineering data mining sub-network in the engineering data encoding network, information mining operations are performed on the construction project description data to be analyzed of each of the construction projects to be analyzed to output the corresponding first feature representation of the engineering data. That is to say, the construction project description data to be analyzed can be mapped into the feature space to form the corresponding first feature representation of the engineering data.

[0091] Optionally, in some embodiments, the engineering data encoding network also includes an analysis output subnetwork and a linear processing subnetwork. Based on this, the step of performing relevant information mining operations based on the first feature representation of the engineering data and the first feature representation of the analysis situation to output the first feature representation of the relevant information between each of the confirmed construction projects may further include the following: loading the first feature representation of the engineering data to load it into the analysis output subnetwork included in the engineering data encoding network, using the analysis output subnetwork to perform multiplication operations on the first feature representation of the engineering data and the first feature representation of the analysis situation, and outputting the first feature representation of the relevant information between each of the confirmed construction projects.

[0092] Furthermore, based on the above content, the step of performing information mining operations based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status to output the first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed may further include the following contents: based on the analysis output subnetwork, performing multiplication operations on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status, and outputting the first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed.

[0093] Furthermore, based on the above content, the step of analyzing the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information may further include the following contents:

[0094] The first feature representation of the cascade combination formed by cascading the first feature representation of the relevant information and the first feature representation of the remaining information is linearly processed by using a linear processing subnetwork, such as performing excitation mapping output through a softmax function, and outputting an internal priority coefficient corresponding to each of the remaining construction projects to be analyzed. Exceptionally, the cascade combination may refer to combining in dimension so that the number of dimensions of the first feature representation of the cascade combination is equal to the sum of the number of dimensions of the first feature representation of the relevant information and the number of dimensions of the first feature representation of the remaining information.

[0095] Optionally, in some embodiments, the network optimization of the engineering data encoding network may further include the following:

[0096] Based on the typical engineering data in the typical engineering data cluster, the engineering data encoding network is subjected to multi-stage network optimization, and after the network optimization process is completed, an optimized engineering data encoding network is obtained.

[0097] Among them, a stage of network optimization can further include the following contents:

[0098] Determining a typical engineering data combination in the typical engineering data cluster;

[0099] Loading the construction project description data to be analyzed of each typical construction project to be analyzed in the typical engineering data combination, the current confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed, as well as the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed in the next stage, so as to load them into the engineering data encoding network, wherein the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed are obtained according to the actual engineering quality detection priority analysis;

[0100] Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the typical construction engineering to be analyzed, so as to output a second feature representation of the engineering data of the typical engineering data combination;

[0101] The second characteristic representation of the engineering data is loaded to the analysis output sub-network in the engineering data encoding network, so as to use the analysis output sub-network to analyze the first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster to be analyzed, and to analyze the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage;

[0102] According to the first analysis value of the internal priority coefficient, the second analysis value of the internal priority coefficient and the corresponding actual internal priority coefficient (the difference between them), a target error parameter is calculated, and based on the target error parameter, the engineering data encoding network is optimized, such as optimizing the network in a direction of reducing the target error parameter.

[0103] Optionally, in some embodiments, the process of confirming the typical building project clusters and the process of determining the remaining typical building project clusters to be analyzed may further include the following:

[0104] Among the typical engineering data combinations, a randomly determined typical engineering data is marked to form typical engineering data to be processed;

[0105] Based on the actual engineering quality inspection priority and each typical construction project to be analyzed before the typical construction project to be analyzed in the typical engineering data to be processed, determine the current confirmed typical construction project cluster, and, based on the typical construction projects to be analyzed in other typical engineering data, determine the current remaining typical construction project clusters to be analyzed;

[0106] Based on the actual project quality inspection priority, the typical construction projects to be analyzed in the typical project data to be processed and each typical construction project to be analyzed before the typical construction project to be analyzed, the confirmed typical construction project clusters for the subsequent stage are determined, and, based on the typical construction projects to be analyzed in other typical project data, the remaining typical construction project clusters to be analyzed in the subsequent stage are determined.

[0107] Optionally, in some embodiments, the analysis output subnetwork includes a first analysis output unit and a second analysis output unit. Based on this, the step of loading the second feature representation of the engineering data to load it into the analysis output subnetwork in the engineering data encoding network, and using the analysis output subnetwork to analyze the first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster to be analyzed, and analyzing the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage, can further include the following contents:

[0108] Utilizing the first analysis output unit, after multiplying the second feature representation of the engineering data and the second feature representation of the analysis situation, a focused feature analysis operation is performed to output the second feature representation of the related information between each confirmed typical construction project in the current confirmed typical construction project cluster, wherein the second feature representation of the related information is used to reflect the content correlation information between each currently confirmed typical construction project (i.e., the relationship between each confirmed typical construction project), and each feature representation parameter in the second feature representation of the analysis situation is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination has been analyzed for the engineering quality inspection priority;

[0109] Using the first analysis output unit, determine the residual information second feature representation formed by multiplying the second feature representation of the engineering data and the second feature representation of the analysis status, the residual information second feature representation is used to display the engineering data information of each remaining typical construction project to be analyzed, and each feature representation parameter in the second feature representation of the analysis status is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination has not yet analyzed the engineering quality detection priority;

[0110] Using the linear processing subnetwork in the first analysis output unit, a cascade combination second feature representation formed by cascading the second feature representation of the relevant information and the second feature representation of the remaining information is linearly processed to output a first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster;

[0111] Utilizing the second analysis output unit, after multiplying the second feature representation of the engineering data and the third feature representation of the analysis situation, a focused feature analysis operation is performed to output the third feature representation of the related information between each confirmed typical construction project in the confirmed typical construction project cluster at the next stage, wherein the third feature representation of the related information is used to reflect the content correlation information between each confirmed typical construction project at the next stage, and each feature representation parameter in the third feature representation of the analysis situation is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination at the next stage has been analyzed for the engineering quality inspection priority;

[0112] Using the second analysis output unit, determine the residual information third feature representation formed by multiplying the second feature representation of the engineering data and the third feature representation of the analysis status, the residual information third feature representation is used to reflect the engineering data information of each remaining typical construction project to be analyzed in the next stage, and each feature representation parameter in the third feature representation of the analysis status is used to reflect whether the construction project to be analyzed in the typical engineering data combination corresponding to the next stage has not yet analyzed the engineering quality detection priority;

[0113] Utilizing the linear processing subnetwork in the second analysis output unit, the cascaded combined third feature representation formed by the cascade combination of the third feature representation of the relevant information and the third feature representation of the residual information is linearly processed to output the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage.

[0114] Wherein, it can be selected that, in some implementations, the step of calculating the target error parameter according to the first analysis value of the internal priority coefficient, the second analysis value of the internal priority coefficient and the corresponding actual internal priority coefficient, and the step of optimizing the engineering data encoding network based on the target error parameter, can further include the following contents:

[0115] Based on the difference between the reference priority coefficient in the first analysis value of each internal priority coefficient and the maximum value in the second analysis value of each internal priority coefficient, and combined with the corresponding actual internal priority coefficient, the corresponding target error parameter is calculated, and the reference priority coefficient belongs to the first analysis value of the internal priority coefficient corresponding to the typical construction project to be analyzed in the typical engineering data to be processed.

[0116] Combination Figure 3 The embodiment of the present invention further provides an information processing system for engineering quality detection, which can be applied to the above-mentioned information processing platform for engineering quality detection. The information processing system for engineering quality detection may include:

[0117] A description data determination module, used to determine the description data of the building project to be analyzed for each building project to be analyzed in the building project cluster to be analyzed, wherein the building project cluster to be analyzed includes a plurality of building projects to be analyzed;

[0118] The detection priority analysis module is used to analyze the engineering quality detection priority of each of the construction projects to be analyzed based on the description data of the construction projects to be analyzed, based on the form of performing the target operation in turn, and performing the target operation once includes:

[0119] Based on the confirmed construction project cluster, a corresponding current detection priority is obtained, wherein the confirmed construction project cluster includes each confirmed construction project for which a construction quality detection priority has been determined, and the current detection priority is the highest detection priority other than the construction quality detection priority of each confirmed construction project that has been determined so far;

[0120] From the remaining to-be-analyzed construction project clusters, each remaining to-be-analyzed construction project for which the construction quality inspection priority has not yet been determined is obtained;

[0121] Analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed according to the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project cluster and the remaining building project clusters to be analyzed;

[0122] Based on the internal priority coefficient, at least one remaining construction project to be analyzed is determined in the cluster of remaining construction projects to be analyzed, and the current detection priority is used as the project quality detection priority of the at least one remaining construction project to be analyzed.

[0123] It can be selected that, in some embodiments, the detection priority analysis module is specifically used to: extract the first feature representation of the engineering data analyzed based on the description data of the building project to be analyzed of each of the building projects to be analyzed; perform relevant information mining operations based on the first feature representation of the engineering data and the first feature representation of the analysis situation, so as to output the first feature representation of the relevant information between each of the confirmed building projects, the first feature representation of the relevant information is used to reflect the content correlation information between each of the confirmed building projects, the first feature representation of the analysis situation is obtained based on the analysis of each of the confirmed building projects, and each feature representation parameter in the first feature representation of the analysis situation is used to reflect whether the corresponding building project to be analyzed has been analyzed to obtain the corresponding engineering project. The first characteristic representation of the engineering data and the first characteristic representation of the analysis status are used to perform information mining operations to output the first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed, the first characteristic representation of the remaining information is used to reflect the engineering data information of each of the remaining construction projects to be analyzed, the first characteristic representation of the analysis status is obtained based on the analysis of each of the remaining construction projects to be analyzed, and each characteristic representation parameter in the first characteristic representation of the analysis status is used to reflect whether the engineering quality inspection priority of the corresponding construction project to be analyzed has not been analyzed; based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information, the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed is analyzed.

[0124] Optionally, in some embodiments, the first characteristic representation of the engineering data extracted based on the construction project description data to be analyzed of each construction project to be analyzed includes: loading the construction project description data to be analyzed of each construction project to be analyzed to load it into the engineering data encoding network formed by network optimization; using the engineering data mining sub-network in the engineering data encoding network to perform information mining operations on the construction project description data to be analyzed of each construction project to be analyzed, so as to output the corresponding first characteristic representation of the engineering data; the engineering data encoding network is formed by network optimization based on a typical engineering data cluster, and the typical engineering data in the typical engineering data cluster includes the construction project description data to be analyzed of the typical construction project to be analyzed and the actual engineering quality inspection priority and actual internal priority coefficient corresponding to the typical construction project to be analyzed.

[0125] In summary, the information processing method and system for engineering quality inspection provided by the present invention can obtain the corresponding current inspection priority based on the confirmed construction project cluster; obtain each remaining construction project to be analyzed for which the engineering quality inspection priority has not yet been determined from the remaining construction project clusters to be analyzed; analyze the internal priority coefficient corresponding to each remaining construction project to be analyzed based on the construction project description data to be analyzed, the confirmed construction project cluster and the remaining construction project clusters to be analyzed of each construction project to be analyzed; based on the internal priority coefficient, determine at least one remaining construction project to be analyzed in the remaining construction project clusters to be analyzed, and use the current inspection priority as the engineering quality inspection priority of at least one remaining construction project to be analyzed. Based on the above content, since the engineering quality inspection priority is determined based on information such as the construction project description data to be analyzed, compared with the conventional technical solution of arbitrarily determining the inspection priority, the reliability of priority determination in engineering quality inspection can be improved, thereby improving the problem of low reliability existing in the prior art.

[0126] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An information processing method for engineering quality detection, characterized in that: include: Determine the construction project description data to be analyzed of each construction project to be analyzed in the construction project cluster to be analyzed, wherein the construction project cluster to be analyzed includes a plurality of construction projects to be analyzed; According to the description data of each of the construction projects to be analyzed, based on the form of performing the target operation in turn, the engineering quality inspection priority of each of the construction projects to be analyzed is analyzed, and performing the target operation once includes: Based on the confirmed construction project cluster, a corresponding current detection priority is obtained, wherein the confirmed construction project cluster includes each confirmed construction project for which a construction quality detection priority has been determined, and the current detection priority is the highest detection priority other than the construction quality detection priority of each confirmed construction project that has been determined so far; From the remaining to-be-analyzed construction project clusters, each remaining to-be-analyzed construction project for which the construction quality inspection priority has not yet been determined is obtained; Analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed according to the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project cluster and the remaining building project clusters to be analyzed; Based on the internal priority coefficient, at least one remaining construction project to be analyzed is determined in the remaining construction project cluster to be analyzed, and the current detection priority is used as the construction quality detection priority of the at least one remaining construction project to be analyzed; The step of analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed based on the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project clusters and the remaining building project clusters to be analyzed comprises: Extracting a first feature representation of the engineering data analyzed based on the description data of the construction engineering to be analyzed of each of the construction engineering to be analyzed; Performing a related information mining operation based on the first feature representation of the engineering data and the first feature representation of the analysis situation to output a first feature representation of the related information between each of the confirmed construction projects, wherein the first feature representation of the related information is used to reflect the content correlation information between each of the confirmed construction projects, the first feature representation of the analysis situation is obtained based on the analysis of each of the confirmed construction projects, and each feature representation parameter in the first feature representation of the analysis situation is used to reflect whether the corresponding construction project to be analyzed has analyzed the corresponding engineering quality detection priority; An information mining operation is performed based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status, so as to output a first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed, wherein the first characteristic representation of the remaining information is used to reflect the engineering data information of each of the remaining construction projects to be analyzed, and the first characteristic representation of the analysis status is obtained based on the analysis of each of the remaining construction projects to be analyzed, and each characteristic representation parameter in the first characteristic representation of the analysis status is used to reflect whether the corresponding construction project to be analyzed has not yet analyzed the engineering quality detection priority; Analyze the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information; The step of extracting the first feature representation of the engineering data analyzed based on the description data of the construction engineering to be analyzed of each of the construction engineering to be analyzed comprises: Loading the construction project description data to be analyzed of each of the construction projects to be analyzed to load into the engineering data encoding network formed by network optimization; Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the construction engineering to be analyzed, so as to output a corresponding first feature representation of the engineering data; The engineering data encoding network is formed by network optimization based on a typical engineering data cluster, wherein the typical engineering data in the typical engineering data cluster includes description data of a typical construction project to be analyzed and actual engineering quality detection priority and actual internal priority coefficient corresponding to the typical construction project to be analyzed; The engineering data encoding network also includes an analysis output subnetwork and a linear processing subnetwork; The step of performing a related information mining operation based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis situation to output the first characteristic representation of the related information between each of the confirmed construction projects includes: The first feature representation of the engineering data is loaded to be loaded into the analysis output sub-network included in the engineering data encoding network, so as to use the analysis output sub-network to perform a multiplication operation on the first feature representation of the engineering data and the first feature representation of the analysis situation, and output the first feature representation of the relevant information between each of the confirmed construction projects; The step of performing information mining operations based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status to output the first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed comprises: According to the analysis output sub-network, a multiplication operation is performed on the first feature representation of the engineering data and the first feature representation of the analysis state, and a first feature representation of the remaining information corresponding to each of the remaining construction projects to be analyzed is output; The step of analyzing the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information comprises: Using a linear processing subnetwork, linearly processing a cascaded combined first feature representation formed by cascading the first feature representation of the relevant information and the first feature representation of the remaining information, and outputting an internal priority coefficient corresponding to each of the remaining building projects to be analyzed; The network optimization of the engineering data encoding network includes: Based on the typical engineering data in the typical engineering data cluster, the engineering data encoding network is subjected to multi-stage network optimization, and after the network optimization process is completed, an optimized engineering data encoding network is obtained. One stage of network optimization includes: Determining a typical engineering data combination in the typical engineering data cluster; Loading the construction project description data to be analyzed of each typical construction project to be analyzed in the typical engineering data combination, the current confirmed typical construction project cluster and the remaining typical construction project clusters to be analyzed, as well as the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed in the next stage, so as to load them into the engineering data encoding network, wherein the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed are obtained according to the actual engineering quality detection priority analysis; Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the typical construction engineering to be analyzed, so as to output a second feature representation of the engineering data of the typical engineering data combination; The second characteristic representation of the engineering data is loaded to the analysis output sub-network in the engineering data encoding network, so as to use the analysis output sub-network to analyze the first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster to be analyzed, and to analyze the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage; According to the first analysis value of the internal priority coefficient, the second analysis value of the internal priority coefficient and the corresponding actual internal priority coefficient, a target error parameter is calculated, and based on the target error parameter, the engineering data encoding network is optimized.

2. The information processing method for engineering quality detection according to claim 1, characterized in that: The process of confirming the typical construction engineering cluster and the determination process of the remaining typical construction engineering clusters to be analyzed includes: Among the typical engineering data combinations, a randomly determined typical engineering data is marked to form typical engineering data to be processed; Based on the actual engineering quality inspection priority and each typical construction project to be analyzed before the typical construction project to be analyzed in the typical engineering data to be processed, determine the current confirmed typical construction project cluster, and, based on the typical construction projects to be analyzed in other typical engineering data, determine the current remaining typical construction project clusters to be analyzed; Based on the actual project quality inspection priority, the typical construction projects to be analyzed in the typical project data to be processed and each typical construction project to be analyzed before the typical construction project to be analyzed, the confirmed typical construction project clusters for the subsequent stage are determined, and, based on the typical construction projects to be analyzed in other typical project data, the remaining typical construction project clusters to be analyzed in the subsequent stage are determined.

3. The information processing method for engineering quality detection according to claim 1, characterized in that: The analysis output subnetwork includes a first analysis output unit and a second analysis output unit; The step of loading the second characteristic representation of the engineering data to load it into the analysis output sub-network in the engineering data encoding network, and using the analysis output sub-network to analyze the first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster to be analyzed, and analyzing the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage, comprises: Utilizing the first analysis output unit, after multiplying the second feature representation of the engineering data and the second feature representation of the analysis situation, a focused feature analysis operation is performed to output the second feature representation of the related information between each confirmed typical construction project in the current confirmed typical construction project cluster, wherein the second feature representation of the related information is used to reflect the content correlation information between each currently confirmed typical construction project, and each feature representation parameter in the second feature representation of the analysis situation is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination has analyzed the engineering quality inspection priority; Using the first analysis output unit, determine the residual information second feature representation formed by multiplying the second feature representation of the engineering data and the second feature representation of the analysis status, the residual information second feature representation is used to display the engineering data information of each remaining typical construction project to be analyzed, and each feature representation parameter in the second feature representation of the analysis status is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination has not yet analyzed the engineering quality detection priority; Using the linear processing subnetwork in the first analysis output unit, a cascade combination second feature representation formed by cascading the second feature representation of the relevant information and the second feature representation of the remaining information is linearly processed to output a first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster; Utilizing the second analysis output unit, after multiplying the second feature representation of the engineering data and the third feature representation of the analysis situation, a focused feature analysis operation is performed to output the third feature representation of the related information between each confirmed typical construction project in the confirmed typical construction project cluster at the next stage, wherein the third feature representation of the related information is used to reflect the content correlation information between each confirmed typical construction project at the next stage, and each feature representation parameter in the third feature representation of the analysis situation is used to reflect whether the construction project to be analyzed in the corresponding typical engineering data combination at the next stage has been analyzed for the engineering quality inspection priority; Using the second analysis output unit, determine the residual information third feature representation formed by multiplying the second feature representation of the engineering data and the third feature representation of the analysis status, the residual information third feature representation is used to reflect the engineering data information of each remaining typical construction project to be analyzed in the next stage, and each feature representation parameter in the third feature representation of the analysis status is used to reflect whether the construction project to be analyzed in the typical engineering data combination corresponding to the next stage has not yet analyzed the engineering quality detection priority; Utilizing the linear processing subnetwork in the second analysis output unit, the cascaded combined third feature representation formed by the cascade combination of the third feature representation of the relevant information and the third feature representation of the residual information is linearly processed to output the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage.

4. An information processing system for engineering quality detection, characterized in that: include: A description data determination module, used to determine the description data of the building project to be analyzed for each building project to be analyzed in the building project cluster to be analyzed, wherein the building project cluster to be analyzed includes a plurality of building projects to be analyzed; The detection priority analysis module is used to analyze the engineering quality detection priority of each of the construction projects to be analyzed based on the description data of the construction projects to be analyzed, based on the form of performing the target operation in turn, and performing the target operation once includes: Based on the confirmed construction project cluster, a corresponding current detection priority is obtained, wherein the confirmed construction project cluster includes each confirmed construction project for which a construction quality detection priority has been determined, and the current detection priority is the highest detection priority other than the construction quality detection priority of each confirmed construction project that has been determined so far; From the remaining to-be-analyzed construction project clusters, each remaining to-be-analyzed construction project for which the construction quality inspection priority has not yet been determined is obtained; Analyzing the internal priority coefficient corresponding to each of the remaining building projects to be analyzed according to the building project description data to be analyzed of each of the building projects to be analyzed, the confirmed building project cluster and the remaining building project clusters to be analyzed; Based on the internal priority coefficient, at least one remaining construction project to be analyzed is determined in the remaining construction project cluster to be analyzed, and the current detection priority is used as the construction quality detection priority of the at least one remaining construction project to be analyzed; The detection priority analysis module is specifically used for: Extracting a first feature representation of the engineering data analyzed based on the description data of the construction engineering to be analyzed of each of the construction engineering to be analyzed; Performing a related information mining operation based on the first feature representation of the engineering data and the first feature representation of the analysis situation to output a first feature representation of the related information between each of the confirmed construction projects, wherein the first feature representation of the related information is used to reflect the content correlation information between each of the confirmed construction projects, the first feature representation of the analysis situation is obtained based on the analysis of each of the confirmed construction projects, and each feature representation parameter in the first feature representation of the analysis situation is used to reflect whether the corresponding construction project to be analyzed has analyzed the corresponding engineering quality detection priority; An information mining operation is performed based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis status, so as to output a first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed, wherein the first characteristic representation of the remaining information is used to reflect the engineering data information of each of the remaining construction projects to be analyzed, and the first characteristic representation of the analysis status is obtained based on the analysis of each of the remaining construction projects to be analyzed, and each characteristic representation parameter in the first characteristic representation of the analysis status is used to reflect whether the corresponding construction project to be analyzed has not yet analyzed the engineering quality detection priority; Analyze the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information; The first feature representation of the engineering data extracted from the analysis of the construction engineering description data to be analyzed of each of the construction engineering to be analyzed includes: Loading the construction project description data to be analyzed of each of the construction projects to be analyzed to load into the engineering data encoding network formed by network optimization; Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the construction engineering to be analyzed, so as to output a corresponding first feature representation of the engineering data; The engineering data encoding network is formed by network optimization based on a typical engineering data cluster, wherein the typical engineering data in the typical engineering data cluster includes description data of a typical construction project to be analyzed and actual engineering quality detection priority and actual internal priority coefficient corresponding to the typical construction project to be analyzed; The engineering data encoding network also includes an analysis output subnetwork and a linear processing subnetwork; The performing of the related information mining operation based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis situation to output the first characteristic representation of the related information between each of the confirmed construction projects includes: The first feature representation of the engineering data is loaded to be loaded into the analysis output sub-network included in the engineering data encoding network, so as to use the analysis output sub-network to perform a multiplication operation on the first feature representation of the engineering data and the first feature representation of the analysis situation, and output the first feature representation of the relevant information between each of the confirmed construction projects; The information mining operation is performed based on the first characteristic representation of the engineering data and the first characteristic representation of the analysis state to output the first characteristic representation of the remaining information corresponding to each of the remaining construction projects to be analyzed, including: According to the analysis output sub-network, a multiplication operation is performed on the first feature representation of the engineering data and the first feature representation of the analysis state, and a first feature representation of the remaining information corresponding to each of the remaining construction projects to be analyzed is output; Analyzing the internal priority coefficient corresponding to each of the remaining construction projects to be analyzed based on the first characteristic representation of the relevant information and the first characteristic representation of the remaining information includes: Using a linear processing subnetwork, linearly process a cascaded combined first feature representation formed by cascading the first feature representation of the relevant information and the first feature representation of the remaining information, and output an internal priority coefficient corresponding to each of the remaining building projects to be analyzed; The network optimization of the engineering data encoding network includes: Based on the typical engineering data in the typical engineering data cluster, the engineering data encoding network is subjected to multi-stage network optimization, and after the network optimization process is completed, an optimized engineering data encoding network is obtained. One stage of network optimization includes: Determining a typical engineering data combination in the typical engineering data cluster; Loading the construction project description data to be analyzed of each typical construction project to be analyzed in the typical engineering data combination, the current confirmed typical construction project cluster and the remaining typical construction project clusters to be analyzed, as well as the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed in the next stage, so as to load them into the engineering data encoding network, wherein the confirmed typical construction project clusters and the remaining typical construction project clusters to be analyzed are obtained according to the actual engineering quality detection priority analysis; Using the engineering data mining sub-network in the engineering data encoding network, an information mining operation is performed on the construction engineering description data to be analyzed of each of the typical construction engineering to be analyzed, so as to output a second feature representation of the engineering data of the typical engineering data combination; The second characteristic representation of the engineering data is loaded to the analysis output sub-network in the engineering data encoding network, so as to use the analysis output sub-network to analyze the first analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the current remaining typical building project cluster to be analyzed, and to analyze the second analysis value of the internal priority coefficient corresponding to each remaining typical building project to be analyzed in the remaining typical building project cluster to be analyzed in the next stage; According to the first analysis value of the internal priority coefficient, the second analysis value of the internal priority coefficient and the corresponding actual internal priority coefficient, a target error parameter is calculated, and based on the target error parameter, the engineering data encoding network is optimized.

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