CN111444446A - Engineering cost data collection method and system based on big data, computer equipment and computer readable storage medium - Google Patents
Engineering cost data collection method and system based on big data, computer equipment and computer readable storage medium Download PDFInfo
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Abstract
The invention relates to a method, a system, computer equipment and a computer readable storage medium for collecting engineering cost data based on big data, wherein the method comprises the following steps: s1, automatically acquiring engineering data of the preset engineering field through the uniform resource locator; s2, analyzing the engineering data to obtain an analysis result and storing the analysis result in a database; s3, generating construction cost data corresponding to the preset engineering field based on the engineering data in the database; and S4, displaying the construction cost data of the preset engineering field generated in the step S3. The invention has the effects of facilitating different decision makers to master the cost data of each stage of each engineering field, obtaining the total cost of the engineering integrally and finally making a reasonable decision.
Description
Technical Field
The invention relates to the technical field of construction cost, in particular to a construction cost data collection method, a construction cost data collection system, computer equipment and a computer readable storage medium based on big data.
Background
At present, the construction cost refers to the construction price of a project, and refers to the total sum of all the expenses expected or actually required for completing the construction of one project. The project cost, defined from the perspective of the owner (investor), refers to the construction cost of the project, i.e., the total capital investment cost expected or actually paid for constructing a project. These costs include equipment and tool acquisition costs, construction and installation costs, material costs, other costs of construction, preparation costs, interest in construction life, fixed asset investment direction adjustment taxes (which are currently on hold). These costs are necessary to complete the construction of the fixed assets, although not all of them form the value of the new added assets when the value of the added assets is calculated in accordance with the new financial system and the accounting criteria of the enterprise in the completion settlement of the construction project. Thus, in this sense, the construction cost is the capital investment of the construction project. The project cost is defined from the perspective of a launch packet, and is the project price, namely the price of the building installation project and the total price of the building project, which are predicted or actually formed in the markets such as land, equipment, technical labor, contract and the like through the trading modes such as bidding and the like. The bid may be a construction project, a single project, or a certain stage in the whole construction project, such as feasibility study of the construction project, design of the construction project, and construction stage of the construction project. It can be seen that the completion of a construction project is divided into a plurality of phases, involving a large number of market roles, and requires and generates a large amount of data, which is essential for efficient and low-cost completion of the project.
The conventional CN 109447522A-a method for applying large data to the internet based on engineering cost, obtains unit price information, address information, etc. of a supplier according to the required materials, and then calculates the total price of the materials and the freight to obtain the total cost.
The above prior art solutions have the following drawbacks: the cost of the material in the construction project is only calculated, and the cost of other projects of the project cannot be known, so that the total cost of the project is not beneficial to be obtained integrally.
Disclosure of Invention
In view of the shortcomings of the prior art, one of the purposes of the invention is to provide a construction cost data collection method based on big data, the other purpose is to provide a construction cost data collection system based on big data, the third purpose is to provide computer equipment, and the fourth purpose is to provide a computer readable storage medium.
One of the purposes of the invention is realized by the following technical scheme:
the engineering cost data collection method based on big data comprises the following steps:
s1, automatically acquiring engineering data of the preset engineering field through the uniform resource locator;
s2, analyzing the engineering data to obtain an analysis result and storing the analysis result in a database;
s3, generating construction cost data corresponding to the preset engineering field based on the engineering data in the database;
and S4, displaying the construction cost data of the preset engineering field generated in the step S3.
By adopting the technical scheme, the corresponding resources are accessed through the uniform resource locators, so that the engineering data corresponding to the preset engineering field can be automatically acquired, then the engineering data is analyzed, various types of supplier data of each stage of the engineering are extracted from the engineering data, corresponding engineering cost data is respectively calculated based on the data and then displayed, different decision makers can conveniently master the cost data of each stage of each engineering field, the total cost of the engineering is integrally acquired, and finally a reasonable decision is made.
The present invention in a preferred example may be further configured to: the preset engineering field comprises one or more of real estate engineering, bridge engineering and road engineering, and the engineering data comprises one or more of consulting design data, bidding data, raw material data and equipment data.
By adopting the technical scheme, the data of each stage in a certain engineering field can be collected more comprehensively and completely, and more accurate information can be provided for the decision of the engineering project, so that the construction cost of the engineering is reduced, and the cost is saved.
The present invention in a preferred example may be further configured to: the uniform resource locator is prestored in the database, and the automatically acquiring engineering data of the preset engineering field through the uniform resource locator comprises:
scanning the uniform resource locator from the database;
and accessing a corresponding website through the scanned uniform resource locator, and extracting the engineering data of the preset engineering field from the information returned by the website.
By adopting the technical scheme, the uniform resource locator can be stored in a local database in advance so as to accelerate the scanning speed; the information of each stage of the engineering project such as engineering bid, engineering sub-package, building materials, engineering mechanical equipment and the like can be conveniently obtained from the network by accessing the uniform resource locator, so that the engineering data of each engineering field can be quickly extracted from the information.
The present invention in a preferred example may be further configured to: the analyzing the engineering data to obtain an analysis result and storing the analysis result in a database comprises:
preprocessing the engineering data;
and extracting data of each supplier from the preprocessed engineering data and writing the data into the database, wherein the data of the suppliers at least comprises names, quotation data, preferential data and address data of the suppliers.
By adopting the technical scheme, the obtained engineering data is preprocessed, the engineering data is processed into a format conforming to the database, the rapid storage is convenient, the data of each supplier in the data is extracted and stored, and the data of each supplier in each stage can be conveniently and rapidly inquired.
The present invention in a preferred example may be further configured to: generating cost data corresponding to the preset engineering field based on the engineering data in the database comprises the following steps:
reading each supplier data in the database;
processing the data of each supplier by using a big data frame, and calculating various types of construction cost data of each preset engineering field;
and adding the various types of construction cost data of each preset engineering field respectively to obtain the construction cost data of each preset engineering field.
By adopting the technical scheme, the data of each supplier in the database is read and processed by using the big data frame, and various types of engineering cost data of each engineering field are calculated, so that the processing speed of a large amount of data can be improved; and accumulating the construction cost data of each type to obtain the construction cost data of each engineering field, so that a decision maker can conveniently master the construction cost data of each stage of each engineering field and finally make a reasonable decision.
The present invention in a preferred example may be further configured to: and displaying the cost data of the preset engineering field through a webpage.
By adopting the technical scheme, the cost data in the preset engineering field are displayed in a webpage form, so that a plurality of people can conveniently obtain the cost data from different devices through uniform webpage addresses, and the data obtaining efficiency is improved.
The present invention in a preferred example may be further configured to: the big data framework comprises MapReduce, and the database is a distributed database.
By adopting the technical scheme, the MapReduce can simultaneously read, process and write a large amount of data and also support distributed processing, namely the MapReduce can be matched with an HDFS (Hadoop distributed file system) to simultaneously perform data processing on a plurality of hosts, so that large-scale data processing is realized, and the data processing efficiency is improved; the database comprises a distributed database installed on a plurality of hosts, and the data processing speed and the storage safety are improved.
The second purpose of the invention is realized by the following technical scheme:
provided is a big data construction cost data collection system, including:
the acquisition module is used for automatically acquiring engineering data of a preset engineering field through the uniform resource locator;
the analysis module is used for analyzing the engineering data to obtain an analysis result and storing the analysis result in a database;
the generating module is used for generating construction cost data corresponding to the preset engineering field based on the engineering data in the database;
and the display module is used for displaying the construction cost data of the preset engineering field generated in the generation module.
By adopting the technical scheme, the acquisition module scans the uniform resource locators stored locally and accesses the corresponding resources through the obtained uniform resource locators, so that the engineering data corresponding to the preset engineering field is automatically acquired; and then analyzing the engineering data through an analysis module, extracting various types of supplier data of each stage of the engineering from the engineering data, respectively calculating corresponding engineering cost data based on the supplier data through a generation module and then displaying the corresponding engineering cost data, so that different decision makers can conveniently master the cost data of each stage of each engineering field, integrally obtain the total cost of the engineering and finally make a reasonable decision. .
The third purpose of the invention is realized by the following technical scheme:
providing a computer device, the computer device comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the big-data based project cost data collection method when executing the computer program.
By adopting the technical scheme, the step of the engineering cost data collection method based on the big data is executed by the processor, the function of the method is realized, different decision makers can conveniently master the cost data of each stage of each engineering field, the total cost of the engineering is integrally obtained, and a reasonable decision is finally made.
The fourth purpose of the invention is realized by the following technical scheme:
there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the big-data based project cost data collection method.
By adopting the technical scheme, the processor executes the steps of the engineering cost data collection method based on the big data stored in the computer readable storage medium, so that the method has the functions of facilitating different decision makers to master the cost data of each stage of each engineering field, integrally obtaining the total cost of the engineering and finally making a reasonable decision.
In summary, the invention includes at least one of the following beneficial technical effects:
1. different decision makers can master the cost data of each stage in each engineering field conveniently, the total cost of the engineering is obtained integrally, and finally a reasonable decision is made;
2. the distributed big data framework and the database can improve the processing speed of a large amount of data.
Drawings
FIG. 1 is a flow chart of a big data based project cost data collection method disclosed in the present invention;
FIG. 2 is a schematic diagram of a big data based project cost data collection system according to the present disclosure;
fig. 3 is a schematic structural diagram of a computer device provided by the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
In a first aspect, referring to fig. 1, a flow chart of a big data-based engineering cost data collection method disclosed by the present invention is shown, and the method includes the following steps:
s1, automatically acquiring engineering data of the preset engineering field through the uniform resource locator;
s2, analyzing the engineering data to obtain an analysis result and storing the analysis result in a database;
s3, generating construction cost data corresponding to the preset engineering field based on the engineering data in the database;
and S4, displaying the construction cost data of the preset engineering field generated in the step S3.
The method comprises the steps of scanning the uniform resource locators stored locally and accessing corresponding resources through the obtained uniform resource locators, so that project data corresponding to preset project fields are automatically obtained, then the project data are analyzed, various types of supplier data of all stages of a project are extracted from the project data, corresponding project cost data are respectively calculated based on the data and then displayed, different decision makers can conveniently master the cost data of all stages of all the project fields, the total cost of the project is integrally obtained, and finally a reasonable decision is made.
Example one
The preset engineering field comprises one or more of real estate engineering, bridge engineering and road engineering fields, and the engineering data comprises one or more of consulting design data, bidding data, raw material data and equipment data.
The implementation principle of the embodiment is as follows: in any engineering field, a complete project life cycle generally comprises a plurality of stages, from initial demonstration, consultation design, bid, equipment and raw material purchase, to management in engineering construction and the like, each stage needs related data and generates some data, the data acquisition of each stage is more comprehensive and complete, and more accurate information can be provided for the decision of the engineering project, so that the construction cost is reduced, for example, the information of material suppliers is collected as much as possible, and higher suppliers are excavated from the information, so that the expenditure in the aspect of engineering materials can be reduced, and the cost is saved.
Example two
The step S1 of pre-storing the uniform resource locator in the database, where the automatically obtaining the engineering data in the preset engineering field through the uniform resource locator includes:
scanning said uniform resource locator from said database;
and accessing a corresponding website through the scanned uniform resource locator, and extracting the engineering data of the preset engineering field from the information returned by the website.
The implementation principle of the embodiment is that under the large situation of the internet +, business information of a plurality of companies is provided outwards through the internet, including all stages of engineering construction in the first embodiment, such as design consultation, bid, raw material suppliers, equipment suppliers and the like, and efficiency is improved by means of online consultation and offline extraction, each Resource information has a Uniform and online unique address, namely UR L (Uniform Resource L atom), namely a network address of a Resource, on the internet, the Uniform Resource locator UR L comprises a domain name and a path, the domain name is a host on the internet where the Resource is located, the path is a specific position of the Resource on the host, and information of all engineering stages and all construction projects, such as engineering bid, engineering sub-package, construction materials, engineering mechanical equipment and the like, can be conveniently obtained by accessing the UR L, so that engineering data of all engineering fields can be quickly extracted from the information.
The uniform resource locator can be pre-stored in a local database to accelerate the scanning speed, and a search engine (such as a hundred degree) can be used for searching for related terms and accessing the terms, and then UR L of the terms is obtained.
EXAMPLE III
The step S2, analyzing the engineering data to obtain an analysis result and storing the analysis result in a database, includes:
preprocessing the engineering data;
and extracting data of each supplier from the preprocessed engineering data and writing the data into the database, wherein the data of the suppliers at least comprises names, quotation data, preferential data and address data of the suppliers.
The implementation principle of the embodiment is as follows: preprocessing each acquired engineering data, including any one or more of data cleaning, data conversion, data integration or data reduction, processing the engineering data into a format conforming to the database, and facilitating quick storage; furthermore, each supplier data can be matched from the processed engineering data in a regular expression mode and the like, for example, from each information section of the engineering data, information such as names, quotation data, preferential data, address data and the like of all raw material suppliers of the field is matched through a raw material supplier field, then a corresponding raw material supplier table is established in the database, and the data is stored in the table, so that each supplier data of each stage can be conveniently and quickly inquired.
Example four
In the step S3, the generating of the construction cost data corresponding to the preset engineering field based on the engineering data in the database includes:
reading each supplier data in the database;
processing the data of each supplier by using a big data frame, and calculating various types of construction cost data of each preset engineering field;
and adding the various types of construction cost data of each preset engineering field respectively to obtain the construction cost data of each preset engineering field.
The implementation principle of the embodiment is as follows: reading and processing data of each supplier in the database in batch by using a big data frame (such as Hadoop), and calculating various types of construction cost data (such as design consultation price, equipment, material price and the like) of each engineering field according to the requirement of actual engineering, so that the processing speed of a large amount of data can be improved, for example, when a certain amount of raw materials need to be purchased, price quoted data of corresponding suppliers of the raw materials are obtained from the database, and the cost of each raw material supplier is calculated; and then accumulating the construction cost data of each type to obtain the total construction cost data of each engineering field, so that a decision maker can conveniently master the construction cost data of each stage of each engineering field and finally make a reasonable decision.
EXAMPLE five
And displaying the cost data of the preset engineering field through a webpage.
The implementation principle of the embodiment is as follows: related data are inquired through keywords in a webpage form and are displayed back to the webpage, so that multiple persons can conveniently acquire the cost data from different devices through uniform webpage addresses at the same time, and the data acquisition efficiency is improved; for example, when the construction cost data of the preset engineering field needs to be acquired, the name of the engineering field is input on a webpage, and the construction cost data of each stage, including the relevant data of each supplier, can be displayed back on the webpage in a list form; further, the actual demand can be input in each stage, so that the cost quotations of a plurality of suppliers in the stage are calculated and compared, and the optimal one is conveniently selected; and finally, summarizing and adding the actual cost price data of each stage to obtain the total cost data of the preset engineering field, so that decision makers in each stage can quickly obtain the cost data of the corresponding stage and finally make a reasonable decision.
EXAMPLE six
The big data framework comprises a batch processing engine MapReduce and an HDFS distributed file system, and the database is a distributed database.
The implementation principle of the embodiment is as follows: the batch processing engine MapReduce can read, process and write a large amount of data simultaneously, has high data processing speed, and supports distributed processing, namely the batch processing engine MapReduce can be matched with an HDFS (Hadoop distributed file system) to process data on a plurality of hosts simultaneously, so that the processing of large-scale data is realized, and the data processing efficiency is improved. Similarly, the database includes distributed databases installed on multiple hosts, and the databases may be homogeneous (i.e. the same type of database) or heterogeneous (i.e. different types of databases), so as to improve the speed of data processing and the security of storage.
In a second aspect, referring to fig. 2, a schematic structural diagram of a big data-based project cost data collection system disclosed in the present invention is shown, where the system 100 includes:
an obtaining module 101, configured to automatically obtain engineering data of a preset engineering field through a uniform resource locator;
the analysis module 102 is used for analyzing the engineering data to obtain an analysis result and storing the analysis result in a database;
a generating module 103, configured to generate cost data corresponding to the preset engineering field based on the engineering data in the database;
and the display module 104 is configured to display the construction cost data of the preset engineering field generated in the generation module.
The acquisition module 101 scans the uniform resource locators stored locally and accesses corresponding resources through the obtained uniform resource locators, so as to automatically acquire engineering data corresponding to a preset engineering field; then, the engineering data is analyzed through the analysis module 102, various types of supplier data of each stage of the engineering are extracted from the engineering data, corresponding engineering cost data are respectively calculated and displayed through the generation module 103 based on the supplier data, different decision makers can conveniently master the cost data of each stage of each engineering field, the total cost of the engineering is integrally obtained, and a reasonable decision is finally made.
In a third aspect, referring to fig. 3, which is a schematic structural diagram of a computer device provided in the present invention, the computer device 200 includes: the system comprises a memory 202, a processor 201 and a computer program stored on the memory 202 and capable of running on the processor 201, wherein the processor 201 realizes the steps and corresponding functions of the big data-based project cost data collection method when executing the computer program, and can achieve the same or similar beneficial effects. The processor 201 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data Processing chip in some embodiments.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps and corresponding functions of the above engineering cost data collection method based on big data are implemented, and all the same or similar beneficial effects can be achieved. Illustratively, the computer program of the computer-readable storage medium comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, and the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc.
The embodiments of the present invention are preferred embodiments of the present invention, and the scope of the present invention is not limited by these embodiments, so: all equivalent changes made according to the structure, shape and principle of the invention are covered by the protection scope of the invention.
Claims (10)
1. A construction cost data collection method based on big data is characterized by comprising the following steps:
s1, automatically acquiring engineering data of the preset engineering field through the uniform resource locator;
s2, analyzing the engineering data to obtain an analysis result and storing the analysis result in a database;
s3, generating construction cost data corresponding to the preset engineering field based on the engineering data in the database;
and S4, displaying the construction cost data of the preset engineering field generated in the step S3.
2. The big-data-based construction cost data collection method according to claim 1, wherein: the preset engineering field comprises one or more of real estate engineering, bridge engineering and road engineering, and the engineering data comprises one or more of consulting design data, bidding data, raw material data and equipment data.
3. The big-data-based construction cost data collection method according to claim 2, wherein: the uniform resource locator is prestored in the database, and the automatically acquiring engineering data of the preset engineering field through the uniform resource locator comprises:
scanning the uniform resource locator from the database;
and accessing a corresponding website through the scanned uniform resource locator, and extracting the engineering data of the preset engineering field from the information returned by the website.
4. A big data based construction cost data collection method according to claim 3, wherein: the analyzing the engineering data to obtain an analysis result and storing the analysis result in a database comprises:
preprocessing the engineering data;
and extracting data of each supplier from the preprocessed engineering data and writing the data into the database, wherein the data of the suppliers at least comprises names, quotation data, preferential data and address data of the suppliers.
5. The big-data-based construction cost data collection method according to claim 4, wherein: generating cost data corresponding to the preset engineering field based on the engineering data in the database comprises the following steps:
reading each supplier data in the database;
processing the data of each supplier by using a big data frame, and calculating various types of construction cost data of each preset engineering field;
and adding the various types of construction cost data of each preset engineering field respectively to obtain the construction cost data of each preset engineering field.
6. The big-data-based construction cost data collection method according to claim 5, wherein: and displaying the cost data of the preset engineering field through a webpage.
7. The big-data-based construction cost data collection method according to claim 6, wherein: the big data framework comprises MapReduce, and the database is a distributed database.
8. A construction cost data collection system based on big data, comprising:
the acquisition module is used for automatically acquiring engineering data of a preset engineering field through the uniform resource locator;
the analysis module is used for analyzing the engineering data to obtain an analysis result and storing the analysis result in a database;
the generating module is used for generating construction cost data corresponding to the preset engineering field based on the engineering data in the database;
and the display module is used for displaying the construction cost data of the preset engineering field generated in the generation module.
9. A computer device, characterized by: the computer device includes: memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the big data based project cost data collection method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium characterized by: the computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the big data based project cost data collection method according to any of claims 1 to 7.
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