CN116805208B - Engineering project data analysis system and method based on artificial intelligence - Google Patents
Engineering project data analysis system and method based on artificial intelligence Download PDFInfo
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Abstract
The invention relates to the field of artificial intelligence, in particular to an engineering project data analysis system and method based on the artificial intelligence, wherein the system comprises an engineering project data preprocessing module, an engineering material optimal selection module, a construction period assessment module and an early warning condition value setting module, wherein the engineering material optimal selection module is used for acquiring material supply channels involved in each construction link by combining historical data, and constructing an engineering material priority sequence model according to a combination scheme of different supply channels in a corresponding construction link.
Description
Technical Field
The invention relates to the field of artificial intelligence, in particular to an engineering project data analysis system and method based on artificial intelligence.
Background
With the development of science and technology, artificial intelligence is gradually popularized in the life of people, namely intelligence machinery and machine intelligence, and refers to a machine which is manufactured by people and can represent intelligence, and generally, the artificial intelligence refers to a technology for representing the human intelligence through a common computer program, and core problems of the artificial intelligence comprise the establishment of reasoning, knowledge planning, learning, communication, perception, object moving, tool use, mechanical control and the like which can be similar to or even super-tall with human beings.
In engineering projects, analysis of engineering project schemes and establishment of optimal schemes by artificial intelligence technology are still important points to be studied at present, so that an engineering project data analysis system and method based on artificial intelligence are needed.
Disclosure of Invention
The invention aims to provide an engineering project data analysis system and method based on artificial intelligence, which are used for solving the problems in the background technology, and the invention provides the following technical scheme:
an engineering project data analysis method based on artificial intelligence, the method comprising the steps of:
s1, extracting a bill of materials of each construction link in the project and mechanical equipment required to be equipped for each construction link in the project according to project content with definite project setting stage of the project, and preprocessing the extracted data;
s2, acquiring material supply channels involved in a bill of materials of each construction link through historical data, and constructing an engineering material priority sequence model by combining a combination scheme of different supply channels in the corresponding construction link;
s3, analyzing fault risk values of corresponding mechanical equipment when the mechanical equipment is put into use in an engineering development stage by combining the mechanical equipment equipped in each construction link, judging the influence degree of the mechanical equipment fault on the adjacent construction links according to the fault risk values, and constructing a risk assessment model by combining the influence degree;
s4, judging the rationality of the scheme adopted by each construction link in the current engineering project by combining the analysis results of the S2 and the S3, and setting an early warning condition value by combining the judgment results.
Further, the method of S1 includes the following steps:
step 1001, acquiring a bill of materials of each construction link in the engineering project, sequencing the bill of materials according to the construction order of the engineering project, marking as a set A,
A＝(A 1 ，A 2 ，A 3 ，...，A n )，
wherein A is n A bill of materials of an nth construction link in the engineering project is represented, and n represents the total number of construction links of the engineering project;
step 1002, obtaining a bill of materials of each construction link, combining the bill of materials of each construction link with mechanical equipment related to the corresponding construction link, marking as a set B,
wherein the method comprises the steps ofRepresents a material set required to be commonly used in an nth construction link in engineering projects, S n Represents the set of mechanical equipment required to be applied in the nth construction link in the engineering project,
wherein the method comprises the steps ofI represents the i-th material required to be used in the nth construction link in the engineering project, i represents the total number of the types of materials applied in the engineering project,
the j-th mechanical equipment required to be applied in the nth construction link in the engineering project is represented, and j represents the total number of the mechanical equipment applied in the engineering project.
According to the invention, the bill of materials of each construction link in engineering projects is collected, the materials and mechanical equipment related to the corresponding construction link are obtained through the bill of materials, the bill of materials of each construction link is bound with the related mechanical equipment, and data reference is provided for the follow-up analysis of the optimal preferable scheme of each construction link.
Further, the method of S2 includes the following steps:
step 2001, acquiring a bill of materials of an nth construction link in the engineering project, acquiring suppliers related to an ith kind of materials in the bill of materials of the nth construction link in the engineering project through historical data, marking the suppliers as a set C,
wherein the method comprises the steps ofA kth supplier corresponding to an ith kind of material in a bill of materials representing an nth construction link in the engineering project;
step 2002, acquiring prices of corresponding materials by combining the price list of each provider, and marking the prices as a set C * ，
Wherein the method comprises the steps ofRepresenting the price of the ith class of materials at the kth provider in the bill of materials of the nth construction link in the engineering project;
will set C * The medium elements are sequenced from large to small according to the size of the corresponding material to obtain a sequence C ** ，
Wherein the method comprises the steps ofRepresenting a sequence updated projectThe price of the ith kind of material at the kth supplier in the bill of materials of the nth construction link;
step 2003, obtaining user feedback tables corresponding to different suppliers of the ith kind of materials in the bill of materials of the nth construction link through historical data, and combining the user feedback tables with the sequence C ** Analyzing the price of the ith class of material in the kth supplier and analyzing the preferred integrated value corresponding to the user feedback list, recorded as
Wherein omega 1 、ω 2 And omega 3 Representing a proportionality coefficient, wherein the proportionality coefficient is a database preset value,representing the price of the ith class of material in the kth supplier, < >>Indicating that the material of the ith category is satisfactory to the user in the corresponding L-th user feedback list in the kth provider, wherein the experience of the user using the corresponding material provided by the corresponding provider is recorded in the user feedback list, and the experience is divided into satisfaction and dissatisfaction Zk (i) indicating the total number of the corresponding user feedback list in the kth provider>Indicating the durability of the material recorded in the corresponding L-th user feedback list in the kth supplier for the ith category of material, said durability indicating the time required for the material to fail in service;
step 2004, repeating step 2003 to obtain the preferred integrated values of the ith material in the bill of materials of the nth construction link relative to the supply schemes of different suppliers, sequencing the preferred integrated values of the supply schemes according to the sequence from large to small, generating an engineering material priority sequence model, and taking the supplier corresponding to the maximum value of the preferred integrated values of the corresponding supply schemes as the preferred supplier of the ith material;
step 2005, cycling step 2001-step 2004 to obtain preferred suppliers of each kind of material in the corresponding bill of materials of each construction link, and combining the preferred suppliers of the corresponding materials in the corresponding construction links to obtain supply channels of each material in the corresponding construction links.
According to the invention, suppliers related to any kind of materials in the corresponding bill of materials of each construction link are obtained by combining historical data, the preferred comprehensive value of the corresponding supplier is obtained by comprehensively analyzing the price provided by each supplier and the feedback result of different users when the materials provided by the corresponding suppliers are used, and an engineering material preferred sequence model is generated by combining the preferred comprehensive value, so that data reference is provided for the subsequent construction of a risk assessment model.
Further, the method of S3 includes the following steps:
step 3001, randomly extracting a set of mechanical equipment equipped in two adjacent construction links in the engineering project, and recording the set as a combination (S n-1 ，S n )；
3002, obtaining the j-th mechanical equipment in the mechanical equipment set equipped in the (n-1) -th construction link in the engineering project, analyzing the fault risk value of the corresponding mechanical equipment when the corresponding mechanical equipment is put into use, and recording as
Wherein the method comprises the steps ofRepresenting a weight value, which is a database preset value, +.>Indicates rated service life of the j-th mechanical equipment nameplate and is +.>Indicating the total number of days the j-th machine was put into operation, < > in->The number of times of faults occurring during the period that the j-th mechanical equipment is put into use is represented;
step 3003, repeating step 3002 to obtain fault risk values of each piece of mechanical equipment in the (n-1) th construction link in the engineering project,
the point o is used as an origin, the operation time length of the mechanical equipment is used as an x axis, the mechanical equipment is used as a Y axis, a plane rectangular coordinate system is constructed, the time length of each mechanical equipment in the n-1 th construction link is mapped into the plane rectangular coordinate system in the plane rectangular coordinate system, a corresponding mechanical equipment operation time length curve is generated, wherein if the mechanical equipment has a fault condition, the corresponding mechanical equipment operation time length curve is intermittent, if the mechanical equipment does not have a fault condition, the corresponding mechanical equipment operation time length curve is continuous, the operation time length corresponding to the longest-duration curve is used as the finishing time of the mechanical equipment in the n-1 th construction link in the engineering project in combination with each mechanical equipment operation time length curve, and the finishing time of the mechanical equipment in the n-1 th construction link is marked as Y n-1 ；
Step 3003, combining the finishing time of the n-1 th construction link mechanical equipment in the engineering project, judging the influence degree of the finishing time of the n-1 th construction link mechanical equipment on the n-th construction link in the engineering project, and constructing a risk assessment model by combining the influence degree, and recording as
Wherein τ represents a scaling factor, which is a database preset value,and the finishing time preset for the (n-1) th construction link mechanical equipment in the project setting stage is represented.
According to the invention, by analyzing the fault risk values of the mechanical equipment of each construction link and combining the fault risk conditions of the mechanical equipment related to the corresponding construction link, whether the fault risk degree of the mechanical equipment of the current construction link influences the construction progress of the subsequent construction link is judged, and then, data reference is provided for the subsequent judgment of whether the currently adopted project construction scheme is optimal.
Further, the method of S4 includes the following steps:
step 4001, binding and combining the analysis result of step 2005 with the risk assessment model in step 3003, wherein the binding and combining result represents the material combination scheme of the corresponding construction link and the influence condition of mechanical equipment on the progress of the adjacent construction link;
step 4002, judging whether a scheme adopted by the (n-1) th construction link in the current engineering project is reasonable or not by combining a risk assessment model, wherein the reasonable judgment basis is as follows: comprehensively analyzing the selected price and durability of each construction link, taking the analysis result as a first judgment condition, taking the time length of mechanical equipment involved in each construction link as a second judgment condition, judging whether the current construction link has a delayed finishing phenomenon or not according to whether the mechanical equipment has a fault risk when being put into use or not and the fault maintenance time length, influencing the finishing time of the subsequent construction link or not,
if it isWhen the method is used, the optimal value of the construction material is met in the currently adopted scheme, but the construction rationality requirement is not met, an early warning signal is sent, and related departments are informed to adjust the use condition of mechanical equipment according to the corresponding construction links;
if it isThe method shows that the optimal value of the construction material is met in the currently adopted scheme, the optimal value meets the construction rationality requirement, and no early warning signal is sent.
An artificial intelligence based engineering project data analysis system, the system comprising the following modules:
the project data preprocessing module is used for: the project pretreatment module is used for extracting a bill of materials and mechanical equipment required to be equipped in each construction link according to project contents in project setting stages, and integrating the extracted data;
and an engineering material optimal selection module: the engineering material optimal selection module is used for acquiring material supply channels involved in each construction link by combining historical data, and constructing an engineering material priority sequence model according to a combination scheme of different supply channels in the corresponding construction link;
and a construction period assessment module: the construction period assessment module is used for combining mechanical equipment equipped in each construction link, analyzing fault risk values of corresponding mechanical equipment when the corresponding mechanical equipment is put into use in an engineering development stage, judging the influence degree of the mechanical equipment fault on adjacent construction links according to the fault risk values, and constructing a risk assessment model by combining influence on vehicle blocking;
the early warning condition value setting module: the early warning condition value setting module is used for judging the reasonability of the scheme adopted in each construction link in the current engineering project by combining the analysis results of the engineering material optimal selection module and the construction period assessment module, and setting an early warning condition value by combining the judgment results.
Further, the engineering project data preprocessing module comprises a bill of materials data analysis unit and a data integration unit:
the bill of materials data analysis unit is used for acquiring bill of materials of each construction link in the engineering project, and analyzing material suppliers related to the corresponding construction link in each bill of materials by combining historical data;
the data integration unit is used for integrating the material process suppliers related to the corresponding construction links with the mechanical equipment by combining the analysis results of the bill of materials data analysis unit.
Further, the engineering material optimal selection module comprises a material supplier analysis unit, a preferred integrated value calculation unit and an engineering material preferred sequence model construction unit:
the material provider analysis unit is used for acquiring providers related to each material in the corresponding construction link by combining the historical data;
the preferred integrated value calculation unit is used for analyzing the preferred integrated value of the supply scheme provided by each supplier corresponding to the same material by combining a user feedback table in the historical data;
and the engineering material optimal sequence model construction unit is used for combining the analysis results of the optimal comprehensive value calculation unit, carrying out sequence calibration on each supply scheme, and generating an engineering material optimal sequence model.
Further, the construction period assessment module comprises a mechanical fault risk analysis unit, a construction progress influence analysis unit and a risk assessment model construction unit:
the mechanical fault risk analysis unit is used for acquiring nameplate parameters of the corresponding equipment through historical data and analyzing fault risk degree of the corresponding mechanical equipment by combining the service duration of the corresponding equipment and the number of faults in the overhaul report data;
the construction progress influence analysis unit is used for judging the influence condition of the mechanical equipment faults related in the current construction link on the construction period of the adjacent construction link according to the analysis result of the mechanical fault risk analysis unit;
the risk assessment model construction unit is used for constructing a risk assessment model by combining the analysis results of the construction progress influence analysis unit.
Further, the early warning condition value setting module comprises a comprehensive factor analysis unit and an early warning signal setting unit:
the comprehensive factor analysis unit is used for comprehensively analyzing the analysis result of the engineering material optimal selection module and the construction period assessment module;
the early warning signal setting unit is used for setting an early warning signal value by combining the analysis result of the comprehensive factor analysis unit.
According to the invention, the engineering material priority sequence model is constructed by analyzing the material selection scheme of the engineering project, the risk assessment model is constructed by analyzing the influence condition of the relevant mechanical equipment of each construction link on the corresponding construction link progress, and the rationality is judged by combining the scheme adopted by the current engineering project, so that the rationality of the engineering project construction scheme is improved, and the cost and expense of the engineering project are reduced.
Drawings
FIG. 1 is a flow chart of an artificial intelligence based engineering project data analysis method of the present invention;
FIG. 2 is a schematic block diagram of an artificial intelligence based engineering project data analysis system of the present invention.
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.
Example 1: referring to fig. 1, in this embodiment:
an engineering project data analysis method based on artificial intelligence is realized, and the method comprises the following steps:
s1, extracting a bill of materials of each construction link in the project and mechanical equipment required to be equipped for each construction link in the project according to project content with definite project setting stage of the project, and preprocessing the extracted data;
the method of S1 comprises the following steps:
step 1001, acquiring a bill of materials of each construction link in the engineering project, sequencing the bill of materials according to the construction order of the engineering project, marking as a set A,
A＝(A 1 ，A 2 ，A 3 ，...，A n )，
wherein A is n A bill of materials of an nth construction link in the engineering project is represented, and n represents the total number of construction links of the engineering project;
step 1002, obtaining a bill of materials of each construction link, combining the bill of materials of each construction link with mechanical equipment related to the corresponding construction link, marking as a set B,
wherein the method comprises the steps ofRepresents a material set required to be commonly used in an nth construction link in engineering projects, S n Represents the set of mechanical equipment required to be applied in the nth construction link in the engineering project,
wherein the method comprises the steps ofI represents the i-th material required to be used in the nth construction link in the engineering project, i represents the total number of the types of materials applied in the engineering project,
the j-th mechanical equipment required to be applied in the nth construction link in the engineering project is represented, and j represents the total number of the mechanical equipment applied in the engineering project.
S2, acquiring material supply channels involved in a bill of materials of each construction link through historical data, and constructing an engineering material priority sequence model by combining a combination scheme of different supply channels in the corresponding construction link;
the method of S2 comprises the following steps:
step 2001, acquiring a bill of materials of an nth construction link in the engineering project, acquiring suppliers related to an ith kind of materials in the bill of materials of the nth construction link in the engineering project through historical data, marking the suppliers as a set C,
wherein the method comprises the steps ofA kth supplier corresponding to an ith kind of material in a bill of materials representing an nth construction link in the engineering project;
step 2002, acquiring prices of corresponding materials by combining the price list of each provider, and marking the prices as a set C * ，
Wherein the method comprises the steps ofRepresenting the price of the ith class of materials at the kth provider in the bill of materials of the nth construction link in the engineering project;
will set C * The medium elements are sequenced from large to small according to the size of the corresponding material to obtain a sequence C ** ，
Wherein the method comprises the steps ofRepresenting the price of the ith type of material at the kth provider in the bill of materials of the nth construction link in the engineering project after the sequence updating;
step 2003, obtaining user feedback tables corresponding to different suppliers of the ith kind of materials in the bill of materials of the nth construction link through historical data, and combining the user feedback tables with the sequence C ** Analyzing the price of the ith class of material in the kth supplier and analyzing the preferred integrated value corresponding to the user feedback list, recorded as
Wherein omega 1 、ω 2 And omega 3 Representing a proportionality coefficient, wherein the proportionality coefficient is a database preset value,representing the price of the ith class of material in the kth supplier, < >>Indicating that the ith class of material is satisfactory to the corresponding L-th user feedback list in the kth supplier, Z k(i) Indicating the total number of user feedback tables corresponding to the ith category of material in the kth supplier,indicating the durability of the material recorded in the corresponding L-th user feedback list in the kth supplier for the ith type of material;
step 2004, repeating step 2003 to obtain the preferred integrated values of the ith material in the bill of materials of the nth construction link relative to the supply schemes of different suppliers, sequencing the preferred integrated values of the supply schemes according to the sequence from large to small, generating an engineering material priority sequence model, and taking the supplier corresponding to the maximum value of the preferred integrated values of the corresponding supply schemes as the preferred supplier of the ith material;
step 2005, cycling step 2001-step 2004 to obtain preferred suppliers of each kind of material in the corresponding bill of materials of each construction link, and combining the preferred suppliers of the corresponding materials in the corresponding construction links to obtain supply channels of each material in the corresponding construction links.
S3, analyzing fault risk values of corresponding mechanical equipment when the mechanical equipment is put into use in an engineering development stage by combining the mechanical equipment equipped in each construction link, judging the influence degree of the mechanical equipment fault on the adjacent construction links according to the fault risk values, and constructing a risk assessment model by combining the influence degree;
the method of S3 comprises the following steps:
step 3001, randomly extracting a set of mechanical equipment equipped in two adjacent construction links in the engineering project, and recording the set as a combination (S n-1 ，S n )；
3002, obtaining the j-th mechanical equipment in the mechanical equipment set equipped in the (n-1) -th construction link in the engineering project, analyzing the fault risk value of the corresponding mechanical equipment when the corresponding mechanical equipment is put into use, and recording as
Wherein the method comprises the steps ofRepresenting a weight value, which is a database preset value, +.>Indicates rated service life of the j-th mechanical equipment nameplate and is +.>Indicating the total number of days the j-th machine was put into operation, < > in->The number of times of faults occurring during the period that the j-th mechanical equipment is put into use is represented;
step 3003, repeating step 3002 to obtain fault risk values of each piece of mechanical equipment in the (n-1) th construction link in the engineering project,
the point o is used as an origin, the operation time length of the mechanical equipment is used as an x axis, the mechanical equipment is used as a y axis, a plane rectangular coordinate system is constructed, and the plane rectangular coordinate system is formedMapping the time length of each mechanical equipment in the n-1 construction link into a plane rectangular coordinate system in the coordinate system, generating a corresponding mechanical equipment operation time length curve, combining the operation time length curves of the mechanical equipment, taking the operation time length corresponding to the curve with the longest duration as the finishing time of the mechanical equipment in the n-1 construction link in the engineering project, and marking as Y n-1 ；
Step 3003, combining the finishing time of the n-1 th construction link mechanical equipment in the engineering project, judging the influence degree of the finishing time of the n-1 th construction link mechanical equipment on the n-th construction link in the engineering project, and constructing a risk assessment model by combining the influence degree, and recording as
Wherein τ represents a scaling factor, which is a database preset value,and the finishing time preset for the (n-1) th construction link mechanical equipment in the project setting stage is represented.
S4, judging the rationality of the scheme adopted by each construction link in the current engineering project by combining the analysis results of the S2 and the S3, and setting an early warning condition value by combining the judgment results.
The method of S4 comprises the following steps:
step 4001, binding and combining the analysis result of step 2005 with the risk assessment model in step 3003;
step 4002, combining the risk assessment model to judge whether the scheme adopted by the (n-1) th construction link in the current engineering project is reasonable or not, if soWhen the method is used, the current adopted scheme is shown to meet the optimal value of the construction material, but not meet the rationality of constructionThe method comprises the steps of requiring sending out an early warning signal, and adjusting the service condition of mechanical equipment according to the corresponding construction link by informing related departments;
if it isThe method shows that the optimal value of the construction material is met in the currently adopted scheme, the optimal value meets the construction rationality requirement, and no early warning signal is sent.
In this embodiment: an artificial intelligence based engineering project data analysis system (as shown in fig. 2) for implementing specific scheme content of a method is disclosed.
Example 2: setting the a-th type material in the current construction link to be 4 suppliers, wherein the a-th type material is marked by the supplier 1 as tau 1 The supplier 2 marks the class a material as tau 2 The supplier 3 marks the class a material as tau 3 The supplier 4 marks the class a material as tau 4 The number of the elements is the number of the elements,
obtaining user satisfaction degree corresponding to each provider through investigation, and obtaining optimal comprehensive value corresponding to each provider through calculation, and marking asAnd->Wherein->The supplier 1 is taken as a delivery channel for the category a material,
the fault risk value of the jth mechanical equipment in the current construction link is obtained and recorded as
Combining the completion time of the mechanical equipment of the current construction link in the engineering project, judging the influence degree of the completion time of the mechanical equipment of the current construction link on the subsequent construction link, and constructing a risk assessment model by combining the influence degree, and recording asWherein->And judging that the selection scheme in the current engineering project and the selection of the mechanical equipment meet the construction rationality requirement.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
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 (7)
1. An engineering project data analysis method based on artificial intelligence, which is characterized by comprising the following steps:
s1, extracting a bill of materials of each construction link in the project and mechanical equipment required to be equipped for each construction link in the project according to project content with definite project setting stage of the project, and preprocessing the extracted data;
s2, acquiring material supply channels involved in a bill of materials of each construction link through historical data, and constructing an engineering material priority sequence model by combining a combination scheme of different supply channels in the corresponding construction link;
s3, analyzing fault risk values of corresponding mechanical equipment when the mechanical equipment is put into use in an engineering development stage by combining the mechanical equipment equipped in each construction link, judging the influence degree of the mechanical equipment fault on the adjacent construction links according to the fault risk values, and constructing a risk assessment model by combining the influence degree;
s4, judging the reasonability of the scheme adopted by each construction link in the current engineering project by combining the analysis results of the S2 and the S3, and setting an early warning condition value by combining the judgment results;
the method of S1 comprises the following steps:
step 1001, acquiring a bill of materials of each construction link in the engineering project, sequencing the bill of materials according to the construction order of the engineering project, marking as a set A,
A＝(A 1 ，A 2 ，A 3 ，...，A n )，
wherein A is n A bill of materials of an nth construction link in the engineering project is represented, and n represents the total number of construction links of the engineering project;
step 1002, obtaining a bill of materials of each construction link, combining the bill of materials of each construction link with mechanical equipment related to the corresponding construction link, marking as a set B,
wherein the method comprises the steps ofRepresents a material set required to be commonly used in an nth construction link in engineering projects, S n Represents the set of mechanical equipment required to be applied in the nth construction link in the engineering project,
wherein the method comprises the steps of I represents the i-th material required to be used in the nth construction link in the engineering project, i represents the total number of the types of materials applied in the engineering project,
j represents the j-th mechanical equipment required to be applied in the nth construction link in the engineering project, and j represents the total number of the mechanical equipment applied in the engineering project;
the method of S2 comprises the following steps:
step 2001, acquiring a bill of materials of an nth construction link in the engineering project, acquiring suppliers related to an ith kind of materials in the bill of materials of the nth construction link in the engineering project through historical data, marking the suppliers as a set C,
wherein the method comprises the steps ofA kth supplier corresponding to an ith kind of material in a bill of materials representing an nth construction link in the engineering project;
step 2002, acquiring prices of corresponding materials by combining the price list of each provider, and marking the prices as a set C * ，
Wherein the method comprises the steps ofRepresenting the price of the ith class of materials at the kth provider in the bill of materials of the nth construction link in the engineering project;
will set C * The medium elements are sequenced from large to small according to the size of the corresponding material to obtain a sequence C ** ，
Wherein the method comprises the steps ofRepresenting the price of the ith type of material at the kth provider in the bill of materials of the nth construction link in the engineering project after the sequence updating;
step 2003, obtaining user feedback tables corresponding to different suppliers of the ith kind of materials in the bill of materials of the nth construction link through historical data, and combining the user feedback tables with the sequence C ** Analyzing the price of the ith class of material in the kth supplier and analyzing the preferred integrated value corresponding to the user feedback list, recorded as
Wherein omega 1 、ω 2 And omega 3 Representing a proportionality coefficient, wherein the proportionality coefficient is a database preset value,representing the price of the ith class of material in the kth supplier, < >>Indicating that the ith class of material is satisfactory to the corresponding L-th user feedback list in the kth supplier, Z k(i) Indicating the total number of corresponding user feedback lists of the ith class of material in the kth supplier,/->Indicating the durability of the material recorded in the corresponding L-th user feedback list in the kth supplier for the ith type of material;
step 2004, repeating step 2003 to obtain the preferred integrated values of the ith material in the bill of materials of the nth construction link relative to the supply schemes of different suppliers, sequencing the preferred integrated values of the supply schemes according to the sequence from large to small, generating an engineering material priority sequence model, and taking the supplier corresponding to the maximum value of the preferred integrated values of the corresponding supply schemes as the preferred supplier of the ith material;
step 2005, cycling step 2001-step 2004 to obtain preferred suppliers of various materials in the corresponding bill of materials of each construction link, and combining the preferred suppliers of the corresponding materials in the corresponding construction links to obtain supply channels of the materials in the corresponding construction links;
the method of S3 comprises the following steps:
step 3001, randomly extracting a set of mechanical equipment equipped in two adjacent construction links in the engineering project, and recording the set as a combination (S n-1 ，S n )；
3002, obtaining the j-th mechanical equipment in the mechanical equipment set equipped in the (n-1) -th construction link in the engineering project, analyzing the fault risk value of the corresponding mechanical equipment when the corresponding mechanical equipment is put into use, and recording as
Wherein the method comprises the steps ofRepresenting a weight value, which is a database preset value, +.>Indicates rated service life of the j-th mechanical equipment nameplate and is +.>Indicating the total number of days the j-th machine was put into operation, < > in->The number of times of faults occurring during the period that the j-th mechanical equipment is put into use is represented;
step 3003, repeating step 3002 to obtain fault risk values of each piece of mechanical equipment in the (n-1) th construction link in the engineering project,
the point o is used as an origin, the operation time length of the mechanical equipment is used as an x axis, the mechanical equipment is used as a y axis, a plane rectangular coordinate system is constructed, the operation time length of each mechanical equipment in the n-1 construction links is mapped into the plane rectangular coordinate system in the plane rectangular coordinate system, a corresponding mechanical equipment operation time length curve is generated,combining the operation time length curves of the mechanical equipment, taking the operation time length corresponding to the curve with the longest duration as the finishing time of the mechanical equipment in the (n-1) th construction link in the engineering project, and marking as Y n-1 ；
Step 3003, combining the finishing time of the n-1 th construction link mechanical equipment in the engineering project, judging the influence degree of the finishing time of the n-1 th construction link mechanical equipment on the n-th construction link in the engineering project, and constructing a risk assessment model by combining the influence degree, and recording as
Wherein τ represents a scaling factor, which is a database preset value,and the finishing time preset for the (n-1) th construction link mechanical equipment in the project setting stage is represented.
2. The engineering project data analysis method based on artificial intelligence according to claim 1, wherein the method of S4 comprises the steps of:
step 4001, binding and combining the analysis result of step 2005 with the risk assessment model in step 3003;
step 4002, judging whether the scheme adopted in the (n-1) th construction link in the current engineering project is reasonable or not by combining the risk assessment model,
if it isWhen the construction material is adopted, the optimal value of the construction material is met in the currently adopted scheme, but the construction material is not met with the reasonable requirement, an early warning signal is sent out, and related departments are informed to carry out mechanical equipment making according to the corresponding construction linksAdjusting the use condition;
if it isThe method shows that the optimal value of the construction material is met in the currently adopted scheme, the optimal value meets the construction rationality requirement, and no early warning signal is sent.
3. An engineering project data analysis system based on artificial intelligence, which is applied to the engineering project data analysis method implementation of any one of claims 1 to 2, and is characterized in that the system comprises the following modules:
the project data preprocessing module is used for: the project pretreatment module is used for extracting a bill of materials and mechanical equipment required to be equipped in each construction link according to project contents in project setting stages, and integrating the extracted data;
and an engineering material optimal selection module: the engineering material optimal selection module is used for acquiring material supply channels involved in each construction link by combining historical data, and constructing an engineering material priority sequence model according to a combination scheme of different supply channels in the corresponding construction link;
and a construction period assessment module: the construction period assessment module is used for combining mechanical equipment equipped in each construction link, analyzing fault risk values of corresponding mechanical equipment when the corresponding mechanical equipment is put into use in an engineering development stage, judging the influence degree of the mechanical equipment fault on adjacent construction links according to the fault risk values, and constructing a risk assessment model by combining influence on vehicle blocking;
the early warning condition value setting module: the early warning condition value setting module is used for judging the reasonability of the scheme adopted in each construction link in the current engineering project by combining the analysis results of the engineering material optimal selection module and the construction period assessment module, and setting an early warning condition value by combining the judgment results.
4. An artificial intelligence based project data analysis system according to claim 3, wherein the project data pre-processing module comprises a bill of materials data analysis unit and a data integration unit:
the bill of materials data analysis unit is used for acquiring bill of materials of each construction link in the engineering project, and analyzing material suppliers related to the corresponding construction link in each bill of materials by combining historical data;
the data integration unit is used for integrating the material process suppliers related to the corresponding construction links with the mechanical equipment by combining the analysis results of the bill of materials data analysis unit.
5. The engineering project data analysis system based on artificial intelligence according to claim 4, wherein the engineering material optimal selection module comprises a material supplier analysis unit, a preference integrated value calculation unit and an engineering material preference sequence model construction unit:
the material provider analysis unit is used for acquiring providers related to each material in the corresponding construction link by combining the historical data;
the preferred integrated value calculation unit is used for analyzing the preferred integrated value of the supply scheme provided by each supplier corresponding to the same material by combining a user feedback table in the historical data;
and the engineering material optimal sequence model construction unit is used for combining the analysis results of the optimal comprehensive value calculation unit, carrying out sequence calibration on each supply scheme, and generating an engineering material optimal sequence model.
6. The engineering project data analysis system based on artificial intelligence according to claim 5, wherein the construction period assessment module comprises a mechanical failure risk analysis unit, a construction progress influence analysis unit and a risk assessment model construction unit:
the mechanical fault risk analysis unit is used for acquiring nameplate parameters of the corresponding equipment through historical data and analyzing fault risk degree of the corresponding mechanical equipment by combining the service duration of the corresponding equipment and the number of faults in the overhaul report data;
the construction progress influence analysis unit is used for judging the influence condition of the mechanical equipment faults related in the current construction link on the construction period of the adjacent construction link according to the analysis result of the mechanical fault risk analysis unit;
the risk assessment model construction unit is used for constructing a risk assessment model by combining the analysis results of the construction progress influence analysis unit.
7. The engineering project data analysis system based on artificial intelligence according to claim 6, wherein the early warning condition value setting module comprises a comprehensive factor analysis unit and an early warning signal setting unit:
the comprehensive factor analysis unit is used for comprehensively analyzing the analysis result of the engineering material optimal selection module and the construction period assessment module;
the early warning signal setting unit is used for setting an early warning signal value by combining the analysis result of the comprehensive factor analysis unit.
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