CN114971327B - Intelligent building material data management system based on characteristic analysis - Google Patents
Intelligent building material data management system based on characteristic analysis Download PDFInfo
- Publication number
- CN114971327B CN114971327B CN202210625145.5A CN202210625145A CN114971327B CN 114971327 B CN114971327 B CN 114971327B CN 202210625145 A CN202210625145 A CN 202210625145A CN 114971327 B CN114971327 B CN 114971327B
- Authority
- CN
- China
- Prior art keywords
- purchasing
- building materials
- building
- various
- unit price
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000004566 building material Substances 0.000 title claims abstract description 393
- 238000004458 analytical method Methods 0.000 title claims abstract description 27
- 238000013523 data management Methods 0.000 title claims description 12
- 239000002994 raw material Substances 0.000 claims abstract description 42
- 238000004519 manufacturing process Methods 0.000 claims abstract description 39
- 238000007726 management method Methods 0.000 claims abstract description 36
- 238000000034 method Methods 0.000 claims abstract description 19
- 238000010276 construction Methods 0.000 claims description 35
- 238000013461 design Methods 0.000 claims description 35
- 238000011156 evaluation Methods 0.000 claims description 32
- 238000004364 calculation method Methods 0.000 claims description 17
- 239000004035 construction material Substances 0.000 claims description 8
- 238000012854 evaluation process Methods 0.000 claims description 4
- 239000000463 material Substances 0.000 claims description 4
- 238000013439 planning Methods 0.000 claims description 4
- 238000012216 screening Methods 0.000 claims description 3
- 238000009435 building construction Methods 0.000 claims description 2
- 230000007547 defect Effects 0.000 abstract description 3
- 230000005484 gravity Effects 0.000 description 4
- 239000002699 waste material Substances 0.000 description 3
- 238000007792 addition Methods 0.000 description 1
- 238000004378 air conditioning Methods 0.000 description 1
- 238000007728 cost analysis Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0283—Price estimation or determination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/08—Construction
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Mathematical Physics (AREA)
- Tourism & Hospitality (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Algebra (AREA)
- Operations Research (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Software Systems (AREA)
- Computational Mathematics (AREA)
- Databases & Information Systems (AREA)
- Educational Administration (AREA)
- Pure & Applied Mathematics (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a building material data intelligent management system based on characteristic analysis, which is characterized in that in the process of setting the standby reserve rate of building materials for an assembly type building project, the use types of various building materials corresponding to the assembly type building project are classified, the standby reserve rate corresponding to various building materials is obtained according to the use types, the influence of the use types of the building materials on the standby reserve rate is fully considered, the flexible setting of the standby reserve rate of the building materials corresponding to the assembly type building project is realized, the reliable statistical basis is provided for the statistics of the actual demand of the building materials, meanwhile, in the process of predicting the purchasing unit price of the building materials, the comprehensive and reliable prediction of the purchasing unit price of the building materials is realized from two dimensions of the historical purchasing unit price of the building materials and the historical market guiding price of the manufacturing raw materials of the building materials respectively, and the defects of the single-dimension prediction are effectively overcome.
Description
Technical Field
The invention relates to the technical field of building material management, in particular to a building material cost data management technology, and specifically relates to a building material data intelligent management system based on characteristic analysis.
Background
Along with the development of social economy, the urbanization process of China is accelerated, and under the condition, the urban building industry is rapidly developed, so that a plurality of novel building engineering categories such as assembly type buildings appear, and the urban building becomes a relatively common building mode in the current building engineering by virtue of the advantages of high building standardization degree, low environmental pollution, high construction efficiency and the like.
Because the fabricated building engineering is fabricated by a plurality of building materials, the fabricated building engineering inevitably generates some building material data in the construction process, wherein the most important is the building material cost data, because the material cost usually has a large proportion of the whole cost in the whole fabricated building engineering construction process, and if the building material cost is not subjected to important management, the whole cost of the fabricated building engineering is directly influenced, so the cost important management of the building material of the fabricated building engineering is very important.
As is known, the construction material cost generally includes construction material procurement cost and construction material logistics transportation cost, wherein the construction material procurement cost is the most important, however, in the construction material procurement cost management process of the assembly type construction engineering, the accuracy of the construction material management result is not high due to lack of reliable management basis, and the construction material procurement cost management method is embodied in the following two points:
1. no matter what kind of building engineering, there will be extra consumption of the consumption of building material in the course of actual construction, this is that need to set for the reserve rate of building material before constructing, but the setting for reserve rate of building material is unified and fixed at present, do not consider the influence of the type of use of building material to the reserve rate of building material, the actual demand of building material that is counted out through this kind of setting mode is not high in precision, it is easy to appear the waste or shortage of building material in the course of actual construction;
2. the prediction dimension of the purchasing unit price of the building material is single: at present, the prediction of the purchasing unit price of the building material is basically performed according to the historical purchasing unit price of the building material, the influence of the manufacturing raw materials of the building material on the purchasing unit price is ignored, the purchasing unit price prediction dimension is too single, and the comprehensive and reliable prediction cannot be realized.
Disclosure of Invention
In order to solve the technical problems, the invention is realized by the following technical scheme:
a building material data intelligent management system based on feature analysis comprises:
the system comprises a target building engineering construction design drawing acquisition module, a building construction planning module and a building planning module, wherein the target building engineering construction design drawing acquisition module is used for recording the fabricated building engineering to be subjected to building material cost management as a target building engineering and acquiring a construction design drawing corresponding to the target building engineering;
the building material type and design demand statistical module is used for calculating the type of the building materials required by the target building engineering and the design demand corresponding to various building materials from the construction design drawing corresponding to the target building engineering, and meanwhile, marking the various building materials required by the target building engineering as 1,2,. So, i,. So, n respectively;
the building material classification module is used for classifying the use types of various building materials to obtain the use types corresponding to the various building materials;
the building material actual demand evaluation module is used for evaluating the actual demand corresponding to various building materials based on the design demand and the use type corresponding to various building materials;
the building material purchasing unit price prediction analysis module is used for acquiring purchasing suppliers corresponding to various building materials and analyzing the predicted purchasing unit prices corresponding to various building materials according to the purchasing suppliers;
the building material information base is used for storing the building use types of various building materials in the assembly type building engineering;
the management database is used for storing the use types corresponding to various building use types, storing the standby reserve rates corresponding to various use types and storing the logistics transportation cost of unit logistics transportation distance corresponding to various article types;
the building material purchasing cost evaluation module is used for evaluating purchasing costs corresponding to various building materials based on actual demand quantities corresponding to the various building materials and predicted purchasing unit prices corresponding to the various building materials;
the building material appearance parameter identification module is used for identifying appearance parameters corresponding to various building materials from a construction design drawing corresponding to a target building project;
the building material logistics transportation cost evaluation module is used for acquiring the purchasing addresses corresponding to various building materials and evaluating the logistics transportation cost corresponding to various building materials based on the purchasing addresses and the appearance parameters corresponding to various building materials;
and the building material comprehensive cost statistics and display module is used for counting the building material comprehensive cost corresponding to the target building engineering according to the purchase cost and the logistics transportation cost corresponding to various building materials and displaying the building material comprehensive cost in a background.
In a preferred embodiment of the present invention, the specific classification steps corresponding to the usage type classification of each building material are as follows:
a1, matching various building materials with the building use types of the various building materials in the building material information base in the assembly type building engineering to obtain the building use types corresponding to the various building materials;
and A2, comparing the building use types corresponding to various building materials with the use types corresponding to various building use types in the management database, and screening the use types corresponding to various building materials.
In the preferred embodiment of the present application, the usage types include a primary type, a secondary type, and a general type.
In a preferred embodiment of the present application, the evaluating the actual demand amount corresponding to each building material based on the design demand amount and the usage type corresponding to each building material specifically refers to the following steps:
b1, comparing the use types corresponding to the various building materials with the standby reserve rates corresponding to the various use types in the management database, thereby obtaining the standby reserve rates corresponding to the various building materials;
b2, evaluating the actual demand quantity corresponding to various building materials according to the design demand quantity and the reserve rate corresponding to various building materials, wherein the evaluation formula is AD i ＝DG i +DG i *η i ，AD i Expressed as the actual demand, DG, for the i-th building material i Expressed as the design demand, η, for the ith build material i Expressed as reserve for the ith building material.
In a preferred embodiment of the present application, the specific analysis process for analyzing the predicted purchase unit price corresponding to each building material includes the following steps:
c1, setting a plurality of historical purchasing years, and numbering the historical purchasing years as 1,2, a.
C2, respectively extracting market guide unit prices corresponding to various building materials in each historical purchasing year and the current purchasing year from the market guide price information issued by the building material cost management department;
c3, acquiring historical purchasing unit prices of purchasing suppliers corresponding to various building materials in various historical purchasing years;
c4, comparing the historical purchasing unit price of the purchasing suppliers corresponding to the various building materials in each historical purchasing year with the market guiding unit price corresponding to the various building materials in each historical purchasing year, and calculating the fluctuation degree of the purchasing unit price of the various building materials in each historical purchasing year relative to the market guiding unit price, wherein the calculation formula is
ε i t represents the fluctuation degree of the purchasing unit price of the ith building material in the t historical purchasing year relative to the market guiding unit price, p Guide i t is the market guiding unit price, p, corresponding to the ith building material in the tth historical purchasing year History i t represents the historical purchasing unit price of the ith building material corresponding to the purchasing supplier in the t historical purchasing year;
c5, calculating formula of average purchasing unit price fluctuation degree according to purchasing unit price fluctuation degree of various building materials relative to market guiding unit price in various historical purchasing years
Calculating the average purchased unit price fluctuation degree of various building materials relative to the market guide unit price, wherein mu i Expressed as average procurement unit price fluctuation, ε, of the ith building material relative to market-directed unit prices i max、ε i min is respectively expressed as the maximum purchasing unit price fluctuation degree and the minimum purchasing unit price fluctuation degree of the ith building material relative to the market guiding unit price in each historical purchasing year;
c6, obtaining key manufacturing raw materials corresponding to various building materials, and extracting market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in each historical purchasing year and the current purchasing year from market guiding price information released by a building raw material cost management department;
c7, corresponding the market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in each historical purchasing year and various buildings in the current purchasing yearComparing the market guiding unit price of the key manufacturing raw materials corresponding to the building materials, and calculating the average market guiding unit price fluctuation degree of various building materials corresponding to the key manufacturing raw materials in the current purchasing year relative to the historical purchasing year, wherein the calculation formula is
σ i Expressed as the average market-directed unit price volatility, q, of the i-th building material corresponding to the key manufacturing raw material for the current year of purchase relative to the historical year of purchase i t is market guide unit price, q 'of ith building material corresponding to key manufacturing raw material in the t historical purchasing year' i The market guiding unit price of the ith building material corresponding to the key manufacturing raw material in the current purchasing year is expressed;
c8, calculating the comprehensive purchasing unit price fluctuation degree of various building materials relative to the market guiding unit price according to the average purchasing unit price fluctuation degree of various building materials relative to the market guiding unit price and the average market guiding unit price fluctuation degree of various building materials corresponding to the key manufacturing raw materials of various building materials of the current purchasing year relative to the historical purchasing year, wherein the calculation formula is
The comprehensive purchasing unit price fluctuation degree of the ith building material relative to the market guiding unit price is expressed, a and b are respectively expressed as the building material and the weighting factor of the key manufacturing raw material corresponding to the building material, and a + b =1;
c9, according to the market guide unit price corresponding to various building materials in the current purchasing year and the comprehensive purchasing unit price fluctuation degree of various building materials relative to the market guide unit price, counting the predicted purchasing unit price corresponding to various building materials, wherein the calculation formula is
p Prediction i is the predicted purchase price, p, corresponding to the ith building material Current guide i represents the market guide unit price corresponding to the ith building material in the current purchasing year.
In a preferred embodiment of the present invention, the purchasing cost evaluation formula corresponding to each building material is PM i ＝AD i *p Prediction i，PM i Expressed as the procurement cost corresponding to the ith building material.
In a preferred embodiment of the present invention, the shape parameters include volume and mass.
In a preferred technical solution of the present application, the specific evaluation process for evaluating the logistics transportation cost corresponding to each building material based on the purchase address and the shape parameter corresponding to each building material performs the following steps:
d1, acquiring a building material storage warehouse address corresponding to the target building engineering, and acquiring logistics transportation distances corresponding to various building materials based on the purchasing addresses corresponding to various building materials and the building material storage warehouse address corresponding to the target building engineering;
d2, identifying the article types corresponding to the various building materials according to the appearance parameters corresponding to the various building materials;
d3, matching the article types corresponding to various building materials with the logistics transportation cost of the unit logistics transportation distance corresponding to various article types in the management database, so as to match the logistics transportation cost of the unit logistics transportation distance corresponding to various building materials;
d4, importing the logistics transportation distance corresponding to various building materials and the logistics transportation cost of the unit logistics transportation distance into a logistics transportation cost evaluation formula to obtain the logistics transportation cost corresponding to various building materials, wherein the logistics transportation cost evaluation formula is CT i ＝ct i *l i ，CT i Expressed as the logistics transportation cost, ct, corresponding to the i-th building material i 、l i Respectively representing the logistics transportation cost and the logistics transportation distance of the unit logistics transportation distance corresponding to the ith building material.
In a preferred embodiment of the present invention, the article types include a large type and a small type.
In a preferred embodiment of the present application, the calculation formula of the comprehensive construction cost of the building material corresponding to the target construction project is
CM represents the comprehensive construction cost of the building material corresponding to the target building engineering.
Compared with the prior art, the invention has the following advantages:
1. in the process of setting the standby reserve rate of the building materials for the assembly type building engineering, the standby reserve rate corresponding to various building materials is obtained according to the building use types corresponding to various building materials by classifying the use types of various building materials required by the assembly type building engineering and identifying the building use types corresponding to various building materials based on the classified use types, so that the influence of the use types of the building materials on the standby reserve rate is fully considered, the flexible setting of the standby reserve rate of the building materials corresponding to the assembly type building engineering is realized, the accuracy of the setting result is improved, a reliable statistical basis is provided for the statistics of the actual demand of the building materials, and the occurrence rate of the waste or shortage phenomenon of the building materials in the actual construction process is effectively reduced.
2. In the process of predicting the purchasing unit price of the building material, the invention starts from two dimensions of the historical purchasing unit price of the building material and the historical market designated price of the building material manufacturing raw material respectively, realizes the comprehensive and reliable prediction of the purchasing unit price of the building material through the two-dimensional prediction of the purchasing unit price of the building material, effectively makes up the defects of the single-dimensional prediction, and greatly improves the accuracy of the purchasing unit price prediction.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a schematic diagram of the system module connection according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an intelligent building material data management system based on feature analysis includes a target building engineering construction design drawing acquisition module, a building material type and design demand statistical module, a building material classification module, a building material actual demand evaluation module, a building material purchase unit price prediction analysis module, a building material information base, a management database, a building material purchase cost evaluation module, a building material appearance parameter identification module, a building material logistics transportation cost evaluation module, and a building material comprehensive cost statistical and display module.
The building material type and design demand quantity statistical module and the building material information base are connected with the building material classification module, the management database and the building material type and design demand quantity statistical module are connected with the building material actual demand quantity evaluation module, the building material actual demand quantity evaluation module and the building material purchase unit price prediction analysis module are connected with the building material purchase cost evaluation module, the building material appearance parameter recognition module and the management database are connected with the building material logistics transportation cost evaluation module, and the building material purchase cost evaluation module and the building material logistics transportation cost evaluation module are connected with the building material comprehensive cost statistics and display module.
The target building engineering construction design drawing acquisition module is used for recording the fabricated building engineering to be subjected to building material cost management as the target building engineering and acquiring a construction design drawing corresponding to the target building engineering.
The building material type and design demand quantity statistical module is used for calculating the type of the building materials required by the target building engineering and the design demand quantity corresponding to various building materials from the construction design drawing corresponding to the target building engineering, and meanwhile, marking the various building materials required by the target building engineering as 1,2, ·, i,..., n respectively.
In one embodiment, the building material includes external wall panels, internal wall panels, laminated slabs, air conditioning slabs, precast beams, precast columns, and the like.
The building material classification module is used for classifying the use types of various building materials to obtain the use types corresponding to the various building materials, and the concrete classification steps are as follows:
a1, matching various building materials with the building use types of the various building materials in the building material information base in the assembly type building engineering to obtain the building use types corresponding to the various building materials;
it is noted that the aforementioned categories of construction applications include, but are not limited to, load bearing applications, decorative applications, and permanent attachment applications.
And A2, comparing the building use types corresponding to the various building materials with the use types corresponding to the various building use types in the management database, and screening the use types corresponding to the various building materials, wherein the use types comprise a main type, a secondary type and a general type.
In the embodiment, the use types of the various building materials are classified, so that a reliable evaluation basis is provided for the subsequent analysis of the reserve rate of the various building materials, the use types of the various building materials directly reflect the importance degree of the building materials in the construction process, and if the reserve of the building materials with higher importance degree is insufficient, the whole construction progress of the building engineering is seriously influenced, so that the analysis of the reserve rate according to the use types of the building materials can be in practical application, and the method has higher practicability.
The building material actual demand quantity evaluation module is used for evaluating the actual demand quantity corresponding to various building materials based on the design demand quantity and the use type corresponding to various building materials, and the specific evaluation process refers to the following steps:
b1, comparing the use types corresponding to the various building materials with the standby reserve rates corresponding to the various use types in the management database, thereby obtaining the standby reserve rates corresponding to the various building materials;
b2, evaluating the actual demand quantity corresponding to various building materials according to the design demand quantity and the reserve rate corresponding to various building materials, wherein the evaluation formula is AD i ＝DG i +DG i *η i ，AD i Expressed as the actual demand, DG, for the i-th building material i Expressed as the design demand, η, for the ith build material i Expressed as reserve for the ith building material.
In the embodiment of the invention, in the process of setting the reserve storage rate of the building materials for the assembly type building engineering, the use types of various building materials required by the assembly type building engineering are classified, the building use types corresponding to the various building materials are identified based on the classified use types, and then the reserve storage rate corresponding to the various building materials is obtained according to the building use types corresponding to the various building materials, so that the influence of the use types of the building materials on the reserve storage rate is fully considered, the flexible setting of the reserve storage rate of the building materials corresponding to the assembly type building engineering is realized, the accuracy of the setting result is further improved, and a reliable statistical basis is provided for the statistics of the actual demand of the building materials, thereby effectively reducing the incidence rate of the waste or shortage phenomenon of the building materials in the actual construction process.
The building material purchasing unit price prediction analysis module is used for acquiring purchasing suppliers corresponding to various building materials and analyzing the predicted purchasing unit prices corresponding to the various building materials according to the purchasing suppliers, and the specific analysis process executes the following steps:
c1, setting a plurality of historical purchasing years, and numbering the historical purchasing years as 1,2, a.
In a specific embodiment, the set number of the historical purchasing years is not less than 3, because too few historical purchasing years are set, data errors are easy to occur, and the accuracy of an analysis result is further influenced;
c2, respectively extracting market guide unit prices corresponding to various building materials in each historical purchasing year and the current purchasing year from the market guide price information issued by the building material cost management department;
c3, acquiring historical purchasing unit prices of purchasing suppliers corresponding to various building materials in various historical purchasing years;
c4, comparing the historical purchasing unit prices of the purchasing suppliers corresponding to various building materials in each historical purchasing year with the market guiding unit prices corresponding to various building materials in each historical purchasing year, and calculating the fluctuation degree of the purchasing unit prices of various building materials in each historical purchasing year relative to the market guiding unit prices, wherein the calculation formula is
ε i t represents the fluctuation degree of the purchasing unit price of the ith building material in the t historical purchasing year relative to the market guiding unit price, p Guide i t is the market guiding unit price, p, corresponding to the ith building material in the tth historical purchasing year History i t represents the historical purchasing unit price of the ith building material corresponding to the purchasing supplier in the t historical purchasing year;
c5, calculating formula of average purchasing unit price fluctuation degree according to purchasing unit price fluctuation degree of various building materials relative to market guiding unit price in various historical purchasing years
Calculating the average purchased unit price fluctuation degree of various building materials relative to the market guide unit price, wherein mu i Expressed as the average purchased unit price fluctuation, epsilon, of the i-th building material relative to the market-directed unit price i max、ε i min is respectively expressed as the maximum purchasing unit price fluctuation degree and the minimum purchasing unit price fluctuation degree of the ith building material relative to the market guiding unit price in each historical purchasing year;
c6, obtaining key manufacturing raw materials corresponding to various building materials, and extracting market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in each historical purchasing year and the current purchasing year from market guiding price information released by a building raw material cost management department;
it should be noted that the above-mentioned key manufacturing raw materials refer to raw materials that play a key role in the manufacturing process of various building materials, and the key manufacturing raw materials are analyzed here because the key manufacturing raw materials play a representative role in all raw materials required in the manufacturing process of building materials.
C7, comparing the market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in each historical purchasing year with the market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in the current purchasing year, and calculating the average market guiding unit price fluctuation degree of the key manufacturing raw materials corresponding to various building materials in the current purchasing year relative to the historical purchasing year, wherein the calculation formula is
σ i Expressed as the average market-directed unit price volatility, q, of the i-th building material corresponding to the key manufacturing raw material for the current year of purchase relative to the historical year of purchase i t is the market-specific unit price, q 'of the ith building material corresponding to the key manufacturing raw material in the tth historical year of purchase' i The market guiding unit price of the ith building material corresponding to the key manufacturing raw material in the current purchasing year is expressed;
c8, calculating the comprehensive purchasing unit price fluctuation degree of various building materials relative to the market guiding unit price according to the average purchasing unit price fluctuation degree of various building materials relative to the market guiding unit price and the average market guiding unit price fluctuation degree of various building materials corresponding to the key manufacturing raw materials of various building materials of the current purchasing year relative to the historical purchasing year, wherein the calculation formula is
The comprehensive purchasing unit price fluctuation degree of the ith building material relative to the market guiding unit price is expressed, a and b are respectively expressed as the building material and the weighting factor of the key manufacturing raw material corresponding to the building material, and a + b =1;
c9, according to the market guide unit price corresponding to various building materials in the current purchasing year and the comprehensive purchasing unit price fluctuation degree of various building materials relative to the market guide unit price, counting the predicted purchasing unit price corresponding to various building materials, wherein the calculation formula is
p Prediction i represents the predicted purchase price, p, corresponding to the ith building material Current guidance i represents the market guide unit price corresponding to the ith building material in the current purchasing year.
In the building material purchasing unit price prediction process, the building material purchasing unit price is comprehensively and reliably predicted by the aid of the two-dimensional prediction of the building material purchasing unit price from two dimensions of the historical purchasing unit price of the building material and the historical market designated price of the building material manufacturing raw material, defects of single-dimensional prediction are effectively overcome, and accuracy of purchasing unit price prediction is greatly improved.
The building material information base is used for storing the building use categories of various building materials in the assembly type building engineering.
The management database is used for storing the use types corresponding to various building use types, storing the standby reserve rates corresponding to various use types and storing the logistics transportation cost of unit logistics transportation distance corresponding to various article types.
The building material purchasing cost evaluation module is used for evaluating purchasing costs corresponding to various building materials based on actual demand quantities corresponding to various building materials and predicted purchasing unit prices corresponding to various building materials, and the calculation formula of the purchasing cost evaluation module is PM i ＝AD i *p Prediction i，PM i And is expressed as the purchasing cost corresponding to the ith building material.
The building material appearance parameter identification module is used for identifying appearance parameters corresponding to various building materials from a construction design drawing corresponding to a target building project, wherein the appearance parameters comprise volume and quality.
The building material logistics transportation cost evaluation module is used for acquiring purchasing addresses corresponding to various building materials and evaluating logistics transportation costs corresponding to the various building materials based on the purchasing addresses and the appearance parameters corresponding to the various building materials, and the specific evaluation process executes the following steps:
d1, acquiring a building material storage warehouse address corresponding to the target building engineering, and acquiring logistics transportation distances corresponding to various building materials based on the purchasing addresses corresponding to various building materials and the building material storage warehouse address corresponding to the target building engineering;
d2, identifying the article types corresponding to the various building materials according to the appearance parameters corresponding to the various building materials, wherein the article types comprise large article types and small article types;
the specific identification method for identifying the types of the articles corresponding to the various building materials is to calculate the specific gravity corresponding to the various building materials according to the appearance parameters corresponding to the various building materials, wherein the specific gravity calculation formula is
Matching the specific gravities corresponding to various building materials with preset specific gravity ranges corresponding to various article types, thereby obtaining the article types corresponding to various building materials;
d3, matching the article types corresponding to various building materials with the logistics transportation cost of the unit logistics transportation distance corresponding to various article types in the management database, so as to match the logistics transportation cost of the unit logistics transportation distance corresponding to various building materials;
d4, introducing the logistics transportation distance corresponding to each building material and the logistics transportation cost of the unit logistics transportation distance into a logistics transportation cost evaluation formula to obtain the logistics transportation cost corresponding to each building material, wherein the logistics transportation cost evaluation formula isCT i ＝ct i *l i ，CT i Expressed as the logistics transportation cost, ct, corresponding to the i-th building material i 、l i Respectively representing the logistics transportation cost and the logistics transportation distance of the unit logistics transportation distance corresponding to the ith building material.
The building material comprehensive cost statistic and display module is used for counting the building material comprehensive cost corresponding to the target building engineering according to the purchase cost and the logistics transportation cost corresponding to various building materials, and the calculation formula is
CM represents the comprehensive construction cost of the corresponding building materials of the target building engineering and displays the comprehensive construction cost in the background.
According to the invention, the actual demand of the building materials and the purchasing unit price of the building materials are accurately analyzed in the process of analyzing the purchasing cost of the building materials of the assembly type building engineering, so that a reliable analysis basis is provided for the purchasing cost analysis of the building materials, and the accuracy of the building material purchasing cost management result is effectively improved.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (9)
1. A building material data intelligent management system based on feature analysis is characterized by comprising:
the system comprises a target building engineering construction design drawing acquisition module, a building construction planning module and a building planning module, wherein the target building engineering construction design drawing acquisition module is used for recording the fabricated building engineering to be subjected to building material cost management as a target building engineering and acquiring a construction design drawing corresponding to the target building engineering;
the building material type and design demand statistical module is used for calculating the type of the building materials required by the target building engineering and the design demand corresponding to various building materials from the construction design drawing corresponding to the target building engineering, and meanwhile, marking the various building materials required by the target building engineering as 1,2,. So, i,. So, n respectively;
the building material classification module is used for classifying the use types of various building materials to obtain the use types corresponding to the various building materials;
the building material actual demand evaluation module is used for evaluating the actual demand corresponding to various building materials based on the design demand and the use type corresponding to various building materials;
the building material purchasing unit price prediction analysis module is used for acquiring purchasing suppliers corresponding to various building materials and analyzing the predicted purchasing unit prices corresponding to various building materials according to the purchasing suppliers;
the building material information base is used for storing the building use types of various building materials in the assembly type building engineering;
the management database is used for storing the use types corresponding to various building use types, storing the standby reserve rates corresponding to various use types and storing the logistics transportation cost of unit logistics transportation distance corresponding to various article types;
the building material purchasing cost evaluation module is used for evaluating purchasing costs corresponding to various building materials based on actual demand quantities corresponding to the various building materials and predicted purchasing unit prices corresponding to the various building materials;
the building material appearance parameter identification module is used for identifying appearance parameters corresponding to various building materials from a construction design drawing corresponding to a target building project;
the building material logistics transportation cost evaluation module is used for acquiring the purchasing addresses corresponding to various building materials and evaluating the logistics transportation cost corresponding to various building materials based on the purchasing addresses and the appearance parameters corresponding to various building materials;
the building material comprehensive cost statistics and display module is used for counting the building material comprehensive cost corresponding to the target building engineering according to the purchase cost and the logistics transportation cost corresponding to various building materials and displaying the building material comprehensive cost in a background;
the specific analysis process for analyzing the predicted purchase unit price corresponding to various building materials executes the following steps:
c1, setting a plurality of historical purchasing years, and sequentially numbering the historical purchasing years as 1,2, a.
C2, respectively extracting market guide unit prices corresponding to various building materials in each historical purchasing year and the current purchasing year from the market guide price information issued by the building material cost management department;
c3, acquiring historical purchasing unit prices of purchasing suppliers corresponding to various building materials in various historical purchasing years;
c4, comparing the historical purchasing unit prices of the purchasing suppliers corresponding to various building materials in each historical purchasing year with the market guiding unit prices corresponding to various building materials in each historical purchasing year, and calculating the fluctuation degree of the purchasing unit prices of various building materials in each historical purchasing year relative to the market guiding unit prices, wherein the calculation formula is
ε i t represents fluctuation degree of purchasing unit price of ith building material in t historical purchasing year relative to market guiding unit price, p Guide i t is the market guiding unit price, p, corresponding to the ith building material in the tth historical purchasing year History i t represents the historical purchasing unit price of the ith building material corresponding to the purchasing supplier in the t historical purchasing year;
c5, calculating formula of average purchasing unit price fluctuation degree according to purchasing unit price fluctuation degree of various building materials relative to market guiding unit price in various historical purchasing years
Calculating the average fluctuation of purchasing unit price of various building materials relative to the market guiding unit price, wherein mu i Expressed as the average purchased unit price fluctuation, epsilon, of the i-th building material relative to the market-directed unit price i max、ε i min is respectively expressed as the maximum unit price of the ith building material relative to the market guide unit price in each historical purchasing yearThe fluctuation degree of the purchasing unit price and the minimum fluctuation degree of the purchasing unit price;
c6, obtaining key manufacturing raw materials corresponding to various building materials, and extracting market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in each historical purchasing year and the current purchasing year from market guiding price information released by a building raw material cost management department;
c7, comparing the market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in each historical purchasing year with the market guiding unit prices of the key manufacturing raw materials corresponding to various building materials in the current purchasing year, and calculating the average market guiding unit price fluctuation degree of the key manufacturing raw materials corresponding to various building materials in the current purchasing year relative to the historical purchasing year, wherein the calculation formula is
σ i Expressed as the average market-directed unit price volatility, q, of the i-th building material corresponding to the key manufacturing raw material for the current year of purchase relative to the historical year of purchase i t is market guide unit price, q 'of ith building material corresponding to key manufacturing raw material in the t historical purchasing year' i The market guiding unit price of the ith building material corresponding to the key manufacturing raw material in the current purchasing year is expressed;
c8, calculating the comprehensive purchasing unit price fluctuation degree of various building materials relative to the market guiding unit price according to the average purchasing unit price fluctuation degree of various building materials relative to the market guiding unit price and the average market guiding unit price fluctuation degree of various building materials corresponding to the key manufacturing raw materials of various building materials of the current purchasing year relative to the historical purchasing year, wherein the calculation formula is
The fluctuation degree of the comprehensive purchasing unit price of the ith building material relative to the market guiding unit price is expressed, and a and b are respectively expressed as the building material and the building material corresponding relationA weighting factor for the raw materials of key manufacture, and a + b =1;
c9, according to the market guide unit price corresponding to various building materials in the current purchasing year and the comprehensive purchasing unit price fluctuation degree of various building materials relative to the market guide unit price, counting the predicted purchasing unit price corresponding to various building materials, wherein the calculation formula is
p Prediction i is the predicted purchase price, p, corresponding to the ith building material Current guide i represents the market guiding unit price corresponding to the ith building material in the current purchasing year.
2. The intelligent building material data management system based on feature analysis as claimed in claim 1, wherein: the specific classification steps corresponding to the usage type classification of various construction materials are as follows:
a1, matching various building materials with the building use types of various building materials in a building material information base in the fabricated building engineering to obtain the building use types corresponding to the various building materials;
and A2, comparing the building use types corresponding to the various building materials with the use types corresponding to the various building use types in the management database, and screening the use types corresponding to the various building materials.
3. The intelligent building material data management system based on feature analysis as claimed in claim 1, wherein: the usage types include a primary type, a secondary type, and a general type.
4. The intelligent building material data management system based on feature analysis as claimed in claim 1, wherein: the evaluation of the actual demand corresponding to the various building materials based on the design demand and the usage type corresponding to the various building materials specifically refers to the following steps:
b1, comparing the use types corresponding to the various building materials with the standby reserve rates corresponding to the various use types in the management database, thereby obtaining the standby reserve rates corresponding to the various building materials;
b2, evaluating the actual demand quantity corresponding to various building materials according to the design demand quantity and the reserve rate corresponding to various building materials, wherein the evaluation formula is AD i ＝DG i +DG i *η i ，AD i Expressed as the actual demand, DG, for the ith building material i Expressed as the design demand, η, for the ith build material i Expressed as reserve for the ith building material.
5. The intelligent building material data management system based on feature analysis as claimed in claim 1, wherein: the purchasing cost evaluation formula corresponding to various building materials is PM i ＝AD i *p Prediction i，PM i Expressed as the procurement cost corresponding to the ith building material.
6. The intelligent building material data management system based on feature analysis as claimed in claim 1, wherein: the form parameters include volume and mass.
7. The intelligent building material data management system based on feature analysis as claimed in claim 5, wherein: the specific evaluation process for evaluating the logistics transportation cost corresponding to each building material based on the purchase address and the shape parameter corresponding to each building material executes the following steps:
d1, acquiring a building material storage warehouse address corresponding to the target building engineering, and acquiring logistics transportation distances corresponding to various building materials based on the purchasing addresses corresponding to various building materials and the building material storage warehouse address corresponding to the target building engineering;
d2, identifying the article types corresponding to the various building materials according to the appearance parameters corresponding to the various building materials;
d3, matching the article types corresponding to various building materials with the logistics transportation cost of the unit logistics transportation distance corresponding to various article types in the management database, so as to match the logistics transportation cost of the unit logistics transportation distance corresponding to various building materials;
d4, importing the logistics transportation distance corresponding to various building materials and the logistics transportation cost of the unit logistics transportation distance into a logistics transportation cost evaluation formula to obtain the logistics transportation cost corresponding to various building materials, wherein the logistics transportation cost evaluation formula is CT i ＝ct i *l i ，CT i Expressed as the logistics transportation cost, ct, corresponding to the i-th building material i 、l i Respectively representing the logistics transportation cost and the logistics transportation distance of the unit logistics transportation distance corresponding to the ith building material.
8. The intelligent building material data management system based on feature analysis according to claim 7, wherein: the article types include a major piece type and a minor piece type.
9. The intelligent building material data management system based on feature analysis according to claim 7, wherein: the calculation formula of the comprehensive construction cost of the building materials corresponding to the target construction engineering is
CM represents the comprehensive construction cost of the building material corresponding to the target construction project.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210625145.5A CN114971327B (en) | 2022-06-02 | 2022-06-02 | Intelligent building material data management system based on characteristic analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210625145.5A CN114971327B (en) | 2022-06-02 | 2022-06-02 | Intelligent building material data management system based on characteristic analysis |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114971327A CN114971327A (en) | 2022-08-30 |
| CN114971327B true CN114971327B (en) | 2023-03-24 |
Family
ID=82960181
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210625145.5A Active CN114971327B (en) | 2022-06-02 | 2022-06-02 | Intelligent building material data management system based on characteristic analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114971327B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116739642B (en) * | 2023-06-26 | 2024-01-26 | 广东华厦工程顾问有限公司 | Engineering cost analysis method, system and storage medium |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113010575B (en) * | 2021-03-19 | 2022-06-21 | 深圳市智筑工程咨询有限公司 | Intelligent management system for engineering cost evaluation and analysis based on cloud computing and big data |
| CN113034200A (en) * | 2021-04-17 | 2021-06-25 | 年畅(武汉)软件科技有限公司 | Power transmission and transformation project cost assessment method based on data characteristic mining and analysis |
| CN113919028A (en) * | 2021-10-13 | 2022-01-11 | 赵亮 | Engineering cost evaluation management system based on big data analysis |
| CN114493549A (en) * | 2022-02-23 | 2022-05-13 | 湖南三一工业职业技术学院 | Building engineering cost evaluation management system based on big data analysis |
-
2022
- 2022-06-02 CN CN202210625145.5A patent/CN114971327B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN114971327A (en) | 2022-08-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wu et al. | An integrated decision-making model for sustainable photovoltaic module supplier selection based on combined weight and cumulative prospect theory | |
| CN113487096B (en) | Method and system for accurate dynamic management and adjustment of commodity sales inventory and computer storage medium | |
| Lesinskyi et al. | Devising a toolset for assessing the potential of loan financing of projects aimed at implementing energy-saving technologies | |
| CN114971327B (en) | Intelligent building material data management system based on characteristic analysis | |
| CN111080356A (en) | Method for calculating residence price influence factors by using machine learning regression model | |
| Chen et al. | Forecasting financial crises for an enterprise by using the Grey Markov forecasting model | |
| Shodiyev et al. | WAYS TO SOLVE ECONOMIC PROBLEMS IN ANALYSIS OF ENTERPRISES | |
| CN111667090A (en) | Load prediction method based on deep belief network and weight sharing | |
| CN105844351A (en) | Prosperity index prediction method for electric power consumption market | |
| CN112529630A (en) | Construction method of multi-dimensional informatization label system of power consumer | |
| CN109993370A (en) | A kind of electric power sale day cash flow projections method based on nonstationary time series | |
| CN114648400A (en) | Financial data intelligent acquisition analysis management system based on mobile internet | |
| Sivarajah | Construction projects delays in Sri Lanka | |
| CN115829418A (en) | Power consumer load characteristic portrait construction method and system suitable for load management | |
| CN109711765A (en) | Distribution materials and equipment classification method based on Kraljic buying location model | |
| Hlushko et al. | Effective methodological tools for forecasting financial and economic stability | |
| CN114612800A (en) | Method and system for accounting urban building material stock and space-time change | |
| Mo et al. | Dynamic cost evaluation method of intelligent manufacturing enterprises based on dea model | |
| Ericson et al. | Regional house price index construction–the case of Sweden | |
| Protopapas et al. | Factors affecting the price of industrial land in the district of Nicosia, Cyprus | |
| Ellis et al. | Are UK Venture Capital and Private Equity Valuations Over-Optimistic? | |
| Song et al. | The research of capacity utilization measurement on manufacturing industry in China | |
| Wen et al. | Study of Residential Price Index Based on Quantile Regression Model—A Case Study on Hangzhou, China | |
| Rahman et al. | Identification of high significance product items through the analysis of energy consumption in steel factory | |
| Qiu | Research on Decision Optimization Based on Big Data Analysis and Calculation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |