CN115983808B - Project data intelligent management system and method based on digital construction - Google Patents
Project data intelligent management system and method based on digital construction Download PDFInfo
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Abstract
The invention relates to the technical field of big data management, in particular to a project data intelligent management system and method based on digital construction, comprising the steps of capturing all approval records generated in a digital project data management platform, extracting characteristic information of each approval record and combing all approval events; the main approval condition element information which needs to be met by each class of approval event is arranged; judging and identifying approval events with approval association; monitoring and capturing entry conditions of project data of project personnel in the digital project data management platform in real time, feeding back corresponding priority ordering in approval events with approval association relations by the digital project data management platform, controlling the digital project data management platform to generate corresponding to-be-approved events based on the priority ordering, and feeding back related authority users to carry out event approval.
Description
Technical Field
The invention relates to the technical field of big data management, in particular to a project data intelligent management system and method based on digital construction.
Background
Project personnel are main users in the digital project data management platform, and are mainly used for inputting, approving and rechecking basic data; the data service ranges of the docking of different project personnel are different, when a plurality of project personnel enter project data in a digital project data management platform at the same time, and because the composition of the project data to be inspected in a plurality of inspection events is formed in all the entered project data at the same time, the project personnel can generate a plurality of inspection works in the digital project data management platform at the same time when finishing the entry of the project data, and the same item of inspection batch data can be inspected in a plurality of inspection works, in this case, if the item of inspection batch data is displayed unqualified in one inspection work, the item of inspection batch data can be displayed unqualified in other inspection works, the related project personnel need to carry out multiple modification uploading on the item of inspection batch data, and the project personnel involved in the plurality of inspection works need to carry out the same inspection batch work, so that not only material resources are wasted, but also manpower is wasted.
Disclosure of Invention
The invention aims to provide a project data intelligent management system and method based on digital construction, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a project data intelligent management method based on digital construction comprises the following steps:
step S100: extracting a historical running log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, extracting characteristic information of each approval record, and combing all approval events existing in the digital project data management platform based on the characteristic information corresponding to each approval record;
step S200: respectively classifying and collecting all approval records based on approval conclusions as passing or failing in an approval record set corresponding to each type of approval event; according to approval records passing and failing approval, main approval condition element information which is required to be met by each type of approval event is arranged based on deviation distribution conditions on to-be-approved data;
step S300: judging and identifying the approval event with approval association based on the corresponding to-be-approved data and main approval condition element information in each approval event;
step S400: monitoring and capturing entry conditions of project data of project personnel in a digital project data management platform in real time, and extracting approval events with approval association relations between two or more approval events before triggering the digital project data management platform to generate the approval work corresponding to the two or more approval events whenever the entry conditions of the project data simultaneously meet the composition of the approval data in the two or more approval events;
step S500: the feedback digital project data management platform sets corresponding priority ordering in the approval events with approval association relation, controls the digital project data management platform to generate corresponding to-be-approved events based on the priority ordering, and feeds back related authority users to carry out event approval.
Further, step S100 includes:
step S101: capturing the data to be examined and approved corresponding to each examination and approval record and a permission account with approval permission for the data to be examined and approved; taking the data to be examined and approved and the authority account as first characteristic information corresponding to each examination and approval record; capturing a permission account number in each approval record to approve the data to be approved, obtaining approval material information which is referred when corresponding approval conclusion is obtained, and taking the approval material information as second characteristic information corresponding to each approval record;
step S102: respectively gathering approval records with the same first characteristic information and second characteristic information to obtain a plurality of approval record sets; corresponding one approval record set to one class of approval event, and taking all the approval records existing in each approval record set as all the approval records existing when the corresponding class of approval event occurs;
the feature information arrangement is mainly used for searching the approval records belonging to the same class of approval event in all the approval records, and the approval records can be understood as belonging to the same approval node, and the approval data required to be approved in the approval node and the approval requirements to be followed when the data are approved are consistent.
Further, step S200 includes:
step S201: in an approval record set corresponding to each type of approval event, each approval record with an approval conclusion not passing is sequentially used as a target approval record, the approval records are collected, and approval modification opinions fed back by a corresponding authority user based on the approval conclusion are extracted from the approval modification opinions to obtain opinion modification items aiming at batch data in the target approval record; performing deviation comparison between the target approval records and each approval record with the approval conclusion passing through based on the to-be-approved data to obtain a plurality of to-be-approved data items with data deviation, and reserving a plurality of to-be-approved data items with deviation times larger than a frequency threshold;
step S202: setting a plurality of data items to be examined and approved as examination and approval key items in each type of examination and approval event; respectively establishing a modification mapping relation between each approval key item reserved in the target approval record and each opinion modification item extracted from the target approval record to obtain a corresponding mapping formula: approval key item- & gt opinion modification item; respectively collecting all mapping formulas existing in each type of approval event, and taking the mapping formulas with the extraction times larger than the times threshold as main approval condition element information which is required to be met based on data to be approved in the corresponding each type of approval event;
the historical operation log based on the digital project data management platform intelligently captures the reason structure which is common in the type of approval event and causes approval to be failed based on the difference of approval conclusion and approval modification comments fed back by the authority user, and the reason structure is embodied as a mapping type between the approval key item and the comment modification item, namely the reason structure is disassembled into certain item of data to be approved and the requirement item corresponding to the item of data to be approved.
Further, step S300 includes:
step S301: extracting to-be-inspected batch data in any two inspection events, setting to-be-inspected data corresponding to the inspection event a as A, and setting to-be-inspected data corresponding to the inspection event B as B; if A and B=C is not equal to 0, capturing to-be-inspected batch data items to which each data in the set C belongs, and when at least one to-be-inspected batch data item exists in all the to-be-inspected batch data items in the set C and is an inspection key item corresponding to the inspection event A and the inspection event B, primarily judging that the inspection association exists between the inspection event a and the inspection event B;
step S302: extracting a plurality of to-be-examined data items which are simultaneously to-be-examined key items corresponding to the to-be-examined event a and the to-be-examined event b, and respectively setting the plurality of to-be-examined data items as target to-be-examined data items; respectively acquiring all mapping formulas Ya required to be met in an approval event a and mapping formulas Yb required to be met in an approval event b of each target to-be-approved data item, and judging that the approval event a and the approval event a form an approval association relationship on the target to-be-approved data item when ya=Yb;
the method comprises the steps of extracting the approval events with approval association relations and determining the corresponding associated to-be-approved data items, wherein the method aims at finding the data items which exist in more than two approval events and need repeated approval, and the approval standards of the approval data items in the approval events with approval association are consistent, so that necessary technical support is provided for the priority of the follow-up reasonable and safe to-be-approved work.
Further, step S500 includes:
step S501: if the project data recorded in the digital project data management platform by project personnel simultaneously meets the composition of the data to be inspected and approved in M inspected and approved events, wherein the inspected and approved association relationship is met among the N inspected and approved events; accumulating the number of the approval events taking all the data to be approved in each approval event as a part of the data to be approved for each approval event, and sequencing N approval events from small to large according to the corresponding number value to obtain a priority arrangement sequence formed among the N approval events;
because the priority is set in the approval event requiring approval of the same item of approval data, the failure of passing of multiple approval works caused by the same reason can be avoided, and the normal passing rate in the follow-up approval works is improved.
Step S402: and controlling the digital project data management platform to generate corresponding to-be-approved events based on the priority ordering, and feeding back related authority users to carry out event approval.
The intelligent project data management system comprises an approval event identification management module, an approval condition element information arrangement module, an approval association judgment and identification module, an approval event monitoring module and an approval priority setting module;
the approval event identification management module is used for extracting a historical operation log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, extracting characteristic information of each approval record, and combing all approval events existing in the digital project data management platform based on the characteristic information corresponding to each approval record;
the approval condition element information arrangement module is used for classifying and collecting all approval records based on approval conclusion as pass or fail in the approval record sets corresponding to each type of approval event respectively; according to approval records passing and failing approval, main approval condition element information which is required to be met by each type of approval event is arranged based on deviation distribution conditions on to-be-approved data;
the approval association judgment and identification module is used for judging and identifying approval events with approval association according to the corresponding to-be-approved data and main approval condition element information in each approval event;
the approval event monitoring module is used for monitoring and capturing the entry condition of project data in the digital project data management platform by project personnel in real time, and extracting approval events with approval association relation between two or more approval events before triggering the digital project data management platform to generate the approval work corresponding to the two or more approval events whenever the entered project data simultaneously meets the composition of the data to be approved in the two or more approval events;
the approval priority setting module is used for feeding back corresponding priority orders in approval events with approval association relations to the digital project data management platform, controlling the digital project data management platform to generate corresponding events to be approved based on the priority orders, and feeding back related authority users to conduct event approval.
Further, the approval event identification management module comprises a characteristic information extraction management unit and an approval event combing unit;
the characteristic information extraction management unit is used for extracting a historical operation log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, and extracting characteristic information of each approval record;
and the approval event combing unit is used for combing all approval events existing in the digital project data management platform according to the characteristic information corresponding to each approval record.
Further, the approval condition element information arrangement module comprises a data deviation identification unit and an approval condition element information arrangement unit;
the data deviation recognition unit is used for classifying and collecting all the approval records based on approval conclusion passing or non-passing in the approval record sets corresponding to each type of approval event respectively, and sequentially taking all the approval records with the approval conclusion not passing as target approval records; performing deviation comparison between the target approval records and each approval record with the approval conclusion passing through based on the to-be-approved data to obtain a plurality of to-be-approved data items with data deviation, and reserving a plurality of to-be-approved data items with deviation times larger than a frequency threshold;
and the approval condition element information arrangement unit is used for arranging main approval condition element information which is required to be met by each class of approval event according to approval records passing and failing approval based on deviation distribution conditions on the data to be approved.
Compared with the prior art, the invention has the following beneficial effects: the invention aims at the condition that a plurality of project personnel enter project data in a digital project data management platform at the same time, and because the composition of the data to be inspected in a plurality of inspection events is formed in all the entered project data, a plurality of inspection works are generated at the same time, and the same data to be inspected is possibly inspected in the plurality of inspection works, the invention reduces the phenomenon that a plurality of inspection works fail due to the same reason based on setting corresponding priority ordering in the inspection events with the inspection association relation, improves the normal passing rate in the subsequent inspection works, and improves the working operation speed in the digital project data management platform.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow diagram of an intelligent management method for project data based on digital construction;
FIG. 2 is a schematic diagram of the project data intelligent management system based on digital construction.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions:
a project data intelligent management method based on digital construction comprises the following steps:
step S100: extracting a historical running log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, extracting characteristic information of each approval record, and combing all approval events existing in the digital project data management platform based on the characteristic information corresponding to each approval record;
wherein, step S100 includes:
step S101: capturing the data to be examined and approved corresponding to each examination and approval record and a permission account with approval permission for the data to be examined and approved; taking the data to be examined and approved and the authority account as first characteristic information corresponding to each examination and approval record; capturing a permission account number in each approval record to approve the data to be approved, obtaining approval material information which is referred when corresponding approval conclusion is obtained, and taking the approval material information as second characteristic information corresponding to each approval record;
step S102: respectively gathering approval records with the same first characteristic information and second characteristic information to obtain a plurality of approval record sets; corresponding one approval record set to one class of approval event, and taking all the approval records existing in each approval record set as all the approval records existing when the corresponding class of approval event occurs;
step S200: respectively classifying and collecting all approval records based on approval conclusions as passing or failing in an approval record set corresponding to each type of approval event; according to approval records passing and failing approval, main approval condition element information which is required to be met by each type of approval event is arranged based on deviation distribution conditions on to-be-approved data;
wherein, step S200 includes:
step S201: in an approval record set corresponding to each type of approval event, each approval record with an approval conclusion not passing is sequentially used as a target approval record, the approval records are collected, and approval modification opinions fed back by a corresponding authority user based on the approval conclusion are extracted from the approval modification opinions to obtain opinion modification items aiming at batch data in the target approval record; performing deviation comparison between the target approval records and each approval record with the approval conclusion passing through based on the to-be-approved data to obtain a plurality of to-be-approved data items with data deviation, and reserving a plurality of to-be-approved data items with deviation times larger than a frequency threshold;
step S202: setting a plurality of data items to be examined and approved as examination and approval key items in each type of examination and approval event; respectively establishing a modification mapping relation between each approval key item reserved in the target approval record and each opinion modification item extracted from the target approval record to obtain a corresponding mapping formula: approval key item- & gt opinion modification item; respectively collecting all mapping formulas existing in each type of approval event, and taking the mapping formulas with the extraction times larger than the times threshold as main approval condition element information which is required to be met based on data to be approved in the corresponding each type of approval event;
step S300: judging and identifying the approval event with approval association based on the corresponding to-be-approved data and main approval condition element information in each approval event;
wherein, step S300 includes:
step S301: extracting to-be-inspected batch data in any two inspection events, setting to-be-inspected data corresponding to the inspection event a as A, and setting to-be-inspected data corresponding to the inspection event B as B; if A and B=C is not equal to 0, capturing to-be-inspected batch data items to which each data in the set C belongs, and when at least one to-be-inspected batch data item exists in all the to-be-inspected batch data items in the set C and is an inspection key item corresponding to the inspection event A and the inspection event B, primarily judging that the inspection association exists between the inspection event a and the inspection event B;
step S302: extracting a plurality of to-be-examined data items which are simultaneously to-be-examined key items corresponding to the to-be-examined event a and the to-be-examined event b, and respectively setting the plurality of to-be-examined data items as target to-be-examined data items; respectively acquiring all mapping formulas Ya required to be met in an approval event a and mapping formulas Yb required to be met in an approval event b of each target to-be-approved data item, and judging that the approval event a and the approval event a form an approval association relationship on the target to-be-approved data item when ya=Yb;
step S400: monitoring and capturing entry conditions of project data of project personnel in a digital project data management platform in real time, and extracting approval events with approval association relations between two or more approval events before triggering the digital project data management platform to generate the approval work corresponding to the two or more approval events whenever the entry conditions of the project data simultaneously meet the composition of the approval data in the two or more approval events;
step S500: the feedback digital project data management platform sets corresponding priority ordering in the approval event with approval association relation, controls the digital project data management platform to generate a corresponding to-be-approved event based on the priority ordering, and feeds back relevant authority users to carry out event approval;
wherein, step S500 includes:
step S501: if the project data recorded in the digital project data management platform by project personnel simultaneously meets the composition of the data to be inspected and approved in M inspected and approved events, wherein the inspected and approved association relationship is met among the N inspected and approved events; accumulating the number of the approval events taking all the data to be approved in each approval event as a part of the data to be approved for each approval event, and sequencing N approval events from small to large according to the corresponding number value to obtain a priority arrangement sequence formed among the N approval events;
for example, there is one approval event Q1, and all the to-be-approved data in the approval event includes H, the configuration of the to-be-approved data in the now captured approval event Q2 is h+g, where G represents other to-be-approved data than H, the configuration of the to-be-approved data in the captured approval event Q3 is h+f, where F represents other to-be-approved data than H, and the configuration of the to-be-approved data in the captured approval event Q4 is U, where U represents other to-be-approved data than H;
then, as summarized above, the approval event Q2 and the approval event Q3 are approval events satisfying that all the pending batch data in the approval event Q1 is used as a part of the pending batch data;
therefore, it can be seen that the number of approval events, in which all of the pending batch data in the approval event Q1 is accumulated as a part of the pending batch data, is 2;
step S502: and controlling the digital project data management platform to generate corresponding to-be-approved events based on the priority ordering, and feeding back related authority users to carry out event approval.
The intelligent project data management system comprises an approval event identification management module, an approval condition element information arrangement module, an approval association judgment and identification module, an approval event monitoring module and an approval priority setting module;
the approval event identification management module is used for extracting a historical operation log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, extracting characteristic information of each approval record, and combing all approval events existing in the digital project data management platform based on the characteristic information corresponding to each approval record;
the approval event identification management module comprises a characteristic information extraction management unit and an approval event combing unit;
the characteristic information extraction management unit is used for extracting a historical operation log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, and extracting characteristic information of each approval record;
the approval event combing unit is used for combing all approval events existing in the digital project data management platform according to the characteristic information corresponding to each approval record;
the approval condition element information arrangement module is used for classifying and collecting all approval records based on approval conclusion as pass or fail in the approval record sets corresponding to each type of approval event respectively; according to approval records passing and failing approval, main approval condition element information which is required to be met by each type of approval event is arranged based on deviation distribution conditions on to-be-approved data;
the approval condition element information arrangement module comprises a data deviation identification unit and an approval condition element information arrangement unit;
the data deviation recognition unit is used for classifying and collecting all the approval records based on approval conclusion passing or non-passing in the approval record sets corresponding to each type of approval event respectively, and sequentially taking all the approval records with the approval conclusion not passing as target approval records; performing deviation comparison between the target approval records and each approval record with the approval conclusion passing through based on the to-be-approved data to obtain a plurality of to-be-approved data items with data deviation, and reserving a plurality of to-be-approved data items with deviation times larger than a frequency threshold;
the approval condition element information arrangement unit is used for arranging main approval condition element information which is required to be met by each type of approval event according to approval records passing and failing approval based on deviation distribution conditions on the data to be approved;
the approval association judgment and identification module is used for judging and identifying approval events with approval association according to the corresponding to-be-approved data and main approval condition element information in each approval event;
the approval event monitoring module is used for monitoring and capturing the entry condition of project data in the digital project data management platform by project personnel in real time, and extracting approval events with approval association relation between two or more approval events before triggering the digital project data management platform to generate the approval work corresponding to the two or more approval events whenever the entered project data simultaneously meets the composition of the data to be approved in the two or more approval events;
the approval priority setting module is used for feeding back corresponding priority orders in approval events with approval association relations to the digital project data management platform, controlling the digital project data management platform to generate corresponding events to be approved based on the priority orders, and feeding back related authority users to conduct event approval.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. An intelligent project data management method based on digital construction, which is characterized by comprising the following steps:
step S100: extracting a historical operation log of a digital project data management platform, capturing all approval records generated in the digital project data management platform, extracting characteristic information of each approval record, and combing all approval events existing in the digital project data management platform based on the characteristic information corresponding to each approval record;
step S200: respectively classifying and collecting all approval records based on approval conclusions as passing or failing in an approval record set corresponding to each type of approval event; according to approval records passing and failing approval, main approval condition element information which is required to be met by each type of approval event is arranged based on deviation distribution conditions on to-be-approved data;
step S300: judging and identifying the approval event with approval association based on the corresponding to-be-approved data and main approval condition element information in each approval event;
step S400: monitoring and capturing entry conditions of project data of project personnel in a digital project data management platform in real time, and extracting approval events with approval association relations between two or more approval events before triggering the digital project data management platform to generate approval work corresponding to the two or more approval events whenever the entry conditions of the project data simultaneously meet the composition of the data to be approved in the two or more approval events;
step S500: the feedback digital project data management platform sets corresponding priority ordering in the approval events with approval association relation, controls the digital project data management platform to generate corresponding events to be approved based on the priority ordering, and feeds back related authority users to carry out event approval.
2. The method for intelligently managing project data based on digital construction according to claim 1, wherein said step S100 comprises:
step S101: capturing to-be-examined data corresponding to each examination and approval record and a permission account with approval permission for the to-be-examined data; taking the data to be examined and approved and the authority account as first characteristic information corresponding to each examination and approval record; capturing the authority account number in each approval record to approve the data to be approved, obtaining approval material information which is referred when corresponding approval conclusion is obtained, and taking the approval material information as second characteristic information corresponding to each approval record;
step S102: respectively gathering approval records with the same first characteristic information and second characteristic information to obtain a plurality of approval record sets; and (3) corresponding one approval record set to one type of approval event, and taking all the approval records existing in each approval record set as all the approval records existing when the corresponding type of approval event occurs.
3. The method for intelligently managing project data based on digital construction according to claim 2, wherein said step S200 comprises:
step S201: in an approval record set corresponding to each type of approval event, each approval record with an approval conclusion not passing is sequentially used as a target approval record, the approval records are collected, approval modification opinions fed back by a corresponding authority user based on the approval conclusion are extracted from the approval modification opinions, and opinion modification items aiming at batch data to be approved in the target approval record are obtained; performing deviation comparison between the target approval records and each approval record which passes the approval conclusion successively based on the to-be-approved data to obtain a plurality of to-be-approved data items with data deviation, and reserving the plurality of to-be-approved data items with deviation times larger than a frequency threshold;
step S202: setting the plurality of data items to be examined as examination key items in each examination event; respectively establishing a modification mapping relation between each approval key item reserved in the target approval record and each opinion modification item extracted from the target approval record to obtain a corresponding mapping formula: approval key item- & gt opinion modification item; and respectively collecting all the mapping formulas existing in each type of approval event, and taking the mapping formulas with the extraction times larger than the times threshold as main approval condition element information which is required to be met based on the data to be approved in the corresponding each type of approval event.
4. The method for intelligently managing project data based on digital construction according to claim 1, wherein said step S300 comprises:
step S301: extracting to-be-inspected batch data in any two inspection events, setting to-be-inspected data corresponding to the inspection event a as A, and setting to-be-inspected data corresponding to the inspection event B as B; if A and B=C is not equal to 0, capturing to-be-inspected batch data items to which each data item in the set C belongs, and when at least one to-be-inspected batch data item exists in all the to-be-inspected batch data items in the set C and is at the same time an inspection key item corresponding to the inspection event A and the inspection event B, primarily judging that the inspection association exists between the inspection event a and the inspection event B;
step S302: extracting a plurality of to-be-examined data items which are simultaneously to-be-examined key items corresponding to the examination event a and the examination event b, and respectively setting the plurality of to-be-examined data items as target to-be-examined data items; and respectively acquiring all mapping formulas Ya required to be met in the approval event a and the mapping formulas Yb required to be met in the approval event b of each target data item to be approved, and judging that the approval event a and the approval event a form an approval association relation on the target data item to be approved when ya=Yb.
5. The method for intelligently managing project data based on digital construction according to claim 4, wherein said step S500 comprises:
step S501: if the project data recorded in the digital project data management platform by project personnel simultaneously meets the composition of the data to be inspected and approved in M inspected and approved events, wherein the inspected and approved association relationship is met among N inspected and approved events; accumulating the number of the approval events taking all the data to be approved in each approval event as a part of the data to be approved, sequencing N approval events from small to large according to the corresponding number value, and obtaining a priority arrangement sequence formed among the N approval events;
step S502: and controlling the digital project data management platform to generate corresponding to-be-approved events based on the priority ordering, and feeding back related authority users to carry out event approval.
6. An item data intelligent management system applying the digitally built item data intelligent management method according to any one of claims 1-5, wherein the system comprises an approval event identification management module, an approval condition element information arrangement module, an approval association judgment identification module, an approval event monitoring module and an approval priority setting module;
the approval event identification management module is used for extracting a historical running log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, extracting characteristic information of each approval record, and combing all approval events existing in the digital project data management platform based on the characteristic information corresponding to each approval record;
the approval condition element information arrangement module is used for respectively classifying and collecting all approval records based on approval conclusion as pass or fail in the approval record sets corresponding to each type of approval event; according to approval records passing and failing approval, main approval condition element information which is required to be met by each type of approval event is arranged based on deviation distribution conditions on to-be-approved data;
the approval association judgment and identification module is used for judging and identifying approval events with approval association according to the corresponding to-be-approved data and main approval condition element information in each approval event;
the approval event monitoring module is used for monitoring and capturing the entry condition of project data in the digital project data management platform by project personnel in real time, and extracting approval events with approval association relations between two or more approval events before triggering the digital project data management platform to generate the approval work corresponding to the two or more approval events whenever the entry project data simultaneously meets the composition of the data to be approved in the two or more approval events;
the approval priority setting module is used for feeding back corresponding priority orders in approval events with approval association relations to the digital project data management platform, controlling the digital project data management platform to generate corresponding to-be-approved events based on the priority orders, and feeding back related authority users to carry out event approval.
7. The intelligent project data management system according to claim 6, wherein the approval event identification management module comprises a feature information extraction management unit and an approval event combing unit;
the characteristic information extraction management unit is used for extracting a historical operation log of the digital project data management platform, capturing all approval records generated in the digital project data management platform, and extracting characteristic information of each approval record;
and the approval event combing unit is used for combing all the approval events existing in the digital project data management platform according to the characteristic information corresponding to each approval record.
8. The intelligent project data management system according to claim 6, wherein the approval condition element information arrangement module comprises a data deviation recognition unit and an approval condition element information arrangement unit;
the data deviation recognition unit is used for classifying and collecting all approval records based on approval conclusion passing or non-passing in the approval record sets corresponding to each type of approval event respectively, and sequentially taking all approval records with the approval conclusion not passing as target approval records; performing deviation comparison between the target approval records and each approval record which passes the approval conclusion successively based on the to-be-approved data to obtain a plurality of to-be-approved data items with data deviation, and reserving the plurality of to-be-approved data items with deviation times larger than a frequency threshold;
the approval condition element information arrangement unit is used for arranging main approval condition element information which is required to be met by each class of approval event based on deviation distribution conditions on the data to be approved according to approval records which are approved and approved not to be approved.
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