CN112800281A - Method and device for processing engineering cost data - Google Patents
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Abstract
The invention discloses a method and a device for processing engineering cost data, relates to the technical field of data processing, and mainly aims to solve the problem of low processing efficiency of the existing engineering cost data. The method comprises the following steps: acquiring a marking range of the engineering cost data, wherein the marking range is used for representing price fluctuation range values of different resource data of engineering project construction; extracting the associated information of the collected project cost data matched with the resource data from different network resource databases; identifying price values and/or adjustment data in the associated information that match the marker ranges; and adjusting the project cost data according to the price value and/or the adjusting data. The method is mainly used for processing the project cost data.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a device for processing engineering cost data.
Background
The construction cost in the building field refers to the construction cost of the project predicted or actually paid in the construction period, and the work processes of predicting, planning, controlling, accounting, analyzing, evaluating and the like of the construction cost become indispensable flows and steps in the building industry. The prices of different material resources in each work project are determined by manual market research and recording into a computer by technicians, so that budgets, settlement and other results corresponding to the prices of the selected material resources are calculated by combining various project cost calculation formulas written in the computer.
At present, when the existing engineering cost data is calculated, because the prices of different material resources change along with market regulation, in the whole engineering cost process, program developers need to re-input information such as the prices of different material resources at any time, so that the calculated engineering cost data conforms to the actual expenditure of an actual engineering project, the processing of the engineering cost data greatly consumes human resources, the real-time performance is poor, the calculation timeliness and the accuracy of the construction cost are influenced, and the processing efficiency of the engineering cost data is reduced.
Disclosure of Invention
In view of this, the present invention provides a method and an apparatus for processing engineering cost data, and mainly aims to solve the problem of low processing efficiency of the existing engineering cost data.
According to an aspect of the present invention, there is provided a method for processing construction cost data, including:
acquiring a marking range of the engineering cost data, wherein the marking range is used for representing price fluctuation range values of different resource data of engineering project construction;
extracting the associated information of the collected project cost data matched with the resource data from different network resource databases;
identifying price values and/or adjustment data in the associated information that match the marker ranges;
and adjusting the project cost data according to the price value and/or the adjusting data.
Further, the method further comprises:
acquiring market transaction text information which is published by a news website and corresponds to the engineering cost data;
identifying resource data from the market transaction text information using natural language processing techniques;
clustering the resource data through a trained k-means clustering model to obtain associated information of different engineering cost data, wherein the k-means clustering model is obtained by training a first training data set based on the characteristics of unmarked resource data and a second training data set based on the characteristics of marked resource data;
and storing the associated information in the network resource database, and marking an acquisition time identifier.
Further, the clustering the resource data by the trained k-means clustering model to obtain the associated information of different engineering cost data includes:
in the clustering process, randomly extracting 3 resource contents from the resource data to serve as a first centroid, a second centroid and a third centroid;
respectively calculating Euclidean distances between the content of each residual resource in the resource data and the first centroid, the second centroid and the third centroid;
dividing the resource content of which the Euclidean distance from the first centroid is greater than that from the second centroid into first associated information, dividing the resource content of which the Euclidean distance from the second centroid is greater than that from the first centroid into second associated information, dividing the resource content of which the Euclidean distance from the third centroid is greater than that from the first centroid and the second centroid into third associated information, and obtaining 3 associated information of different engineering cost data.
Further, the extracting the associated information of the collected project cost data matched with the resource data from the different network resource databases comprises:
determining time characteristics corresponding to the marking range, and matching the time characteristics with time marks in the network resource database one by one;
and when the time identification is matched with the time characteristic, extracting the associated information of the project cost data matched with the resource data according to the time identification.
Further, the adjusting the engineering cost data according to the price value comprises:
extracting a project cost calculation model matched with the price value, and re-executing the project cost calculation model based on the price value to obtain adjusted project cost data, wherein the project cost calculation model is used for representing a calculation formula for calculating the project cost data based on different price values; and/or the presence of a gas in the gas,
and extracting unit characteristics corresponding to the engineering cost calculation model matched with the adjusting data, and carrying out conversion adjustment on the unit characteristics based on the adjusting data to obtain adjusted engineering cost data.
Further, the method further comprises:
judging whether the adjusted project cost data exceeds the marking range;
if the price value exceeds the marking range, updating the maximum value or the minimum value of the marking range as the price value and/or the adjusting data;
sending the updated price value and/or the adjustment data to a user side so as to verify the price value and/or the adjustment data;
and when a verification result fed back by the user side is received, determining whether to execute the step of adjusting the construction cost data again according to the verification result.
Further, the adjustment data includes at least one of time units, price units, and usage units.
According to another aspect of the present invention, there is provided a construction cost data processing apparatus, comprising:
the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring a mark range of the engineering cost data, and the mark range is used for representing the price fluctuation range values of different resource data of engineering project construction;
the extraction module is used for extracting the associated information of the collected project cost data matched with the resource data from different network resource databases;
the identification module is used for identifying the price value and/or the adjustment data matched with the mark range in the associated information;
and the adjusting module is used for adjusting the project cost data according to the price value and/or the adjusting data.
Further, the apparatus further comprises: the processing module, the storage module,
the acquisition module is also used for acquiring market transaction text information which is released by the news website and corresponds to the project cost data;
the identification module is further used for identifying resource data from the market transaction text information by using a natural language processing technology;
the processing module is used for clustering the resource data through a trained k-means clustering model to obtain the associated information of different engineering cost data, and the k-means clustering model is obtained by training a first training data set based on the characteristics of the resource data which are not marked and a second training data set based on the characteristics of the resource data which are marked;
and the storage module is used for storing the associated information in the network resource database and marking a collection time identifier.
Further, the processing module comprises:
the extraction unit is used for randomly extracting 3 resource contents from the resource data as a first centroid, a second centroid and a third centroid in the clustering process;
the calculating unit is used for calculating Euclidean distances between the remaining resource contents in the resource data and the first centroid, the second centroid and the third centroid respectively;
the determining unit is used for dividing the resource content of which the Euclidean distance from the first centroid is greater than that from the second centroid into first associated information, dividing the resource content of which the Euclidean distance from the second centroid is greater than that from the first centroid into second associated information, and dividing the resource content of which the Euclidean distance from the third centroid is greater than that from the first centroid and the second centroid into third associated information, so as to obtain 3 pieces of associated information of different engineering cost data.
Further, the extraction module comprises:
the matching unit is used for determining the time characteristics corresponding to the marking range and matching the time characteristics with the time marks in the network resource database one by one;
and the extraction unit is used for extracting the associated information of the engineering cost data matched with the resource data according to the time identification when the time identification is matched with the time characteristic.
Further, the adjustment module includes:
a first execution unit, configured to extract a project cost calculation model matched with the price value, and re-execute the project cost calculation model based on the price value to obtain adjusted project cost data, where the project cost calculation model is used to represent a calculation formula for calculating project cost data based on different price values; and/or the presence of a gas in the gas,
and the second execution unit is used for extracting unit characteristics corresponding to the engineering cost calculation model matched with the adjusting data, and carrying out conversion adjustment on the unit characteristics based on the adjusting data to obtain adjusted engineering cost data.
Further, the apparatus further comprises:
the judging module is used for judging whether the adjusted construction cost data exceeds the marking range;
the updating module is used for updating the maximum value or the minimum value of the marking range as the price value and/or the adjusting data if the marking range is exceeded;
the sending module is used for sending the updated price value and/or the adjusted data to the user side so as to verify the price value and/or the adjusted data;
and the execution module is used for determining whether to execute the step of adjusting the engineering cost data again according to the verification result when receiving the verification result fed back by the user side.
According to still another aspect of the present invention, there is provided a storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to perform operations corresponding to the above-mentioned engineering cost data processing method.
According to still another aspect of the present invention, there is provided a computer apparatus including: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the processing method of the engineering cost data.
By the technical scheme, the technical scheme provided by the embodiment of the invention at least has the following advantages:
the invention provides a method and a device for processing engineering cost data, compared with the prior art, the embodiment of the invention obtains the marking range of the engineering cost data, and the marking range is used for representing the price fluctuation range values of different resource data of engineering project construction; extracting the associated information of the collected project cost data matched with the resource data from different network resource databases; identifying price values and/or adjustment data in the associated information that match the marker ranges; the engineering cost data is adjusted according to the price value and/or the adjustment data, automatic collection of the affected engineering cost data is achieved, the purpose of timely updating engineering operation data is met, human resources are greatly saved, instantaneity is strong, timeliness and accuracy of construction cost calculation are improved, and accordingly processing efficiency of the engineering cost data is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart of a method for processing construction cost data according to an embodiment of the present invention;
FIG. 2 is a block diagram of a construction cost data processing apparatus according to an embodiment of the present invention;
fig. 3 shows a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the invention provides a method for processing engineering cost data, which comprises the following steps of:
101. and acquiring the marking range of the engineering cost data.
In the embodiment of the present invention, the project cost data is all data of the cost required for calculating the project in a building project, and may include the usage amount of building concrete steel, the budget index, the steel clearing algorithm, the construction efficiency, the price of the clearing work, and the like. Generally, due to the influence of market environments such as different seasons, engineering stages, and manpower prices, prices of different resource data fluctuate, for example, the prices of the manpower resources in winter are higher than those of the manpower resources in spring and autumn, and therefore, a mark range for the engineering cost data, that is, a value of the price fluctuation range of the different resource data for representing the construction of the engineering project is preset corresponding to different image factors, and the resource data is data of different materials, manpower, and the like required in one construction project.
It should be noted that, since the construction cost includes forms such as investment estimation, design approximate calculation, construction budget, construction settlement, completion settlement, and the like, in the process of calculating the construction cost data, the resource data may be calculated by each calculation formula pre-recorded in the computer, or may be calculated manually, and the embodiment of the present invention is not particularly limited. The corresponding engineering cost data can be directly obtained from the calculation result in the computer or manually input so as to be matched with the obtained mark range.
102. And extracting the associated information of the collected project cost data matched with the resource data from different network resource databases.
The network resource database is a pre-constructed database and is used for storing associated information collected from different websites and related to the engineering cost data, wherein the associated information is text content or image content which affects the calculation of the engineering cost data, for example, the engineering cost data is calculated once, however, if a human price is recorded in a certain news website and each person subsidizes 30 yuan per day, the associated information of the human resource affects the engineering cost data, and the engineering cost data needs to be adjusted or updated according to the associated information, that is, the associated information may include changed data of different resource data, so as to process the engineering cost data in time.
103. Identifying price values and/or adjustment data in the associated information that match the marker ranges.
In the embodiment of the invention, in order to accurately acquire the price value and/or the adjustment data which can adjust the engineering cost data within the marking range from the associated information, the associated information is identified to acquire the matched price value and/or the adjustment data. The adjustment data at least includes one of a time unit, a price unit, and a usage unit, that is, the time unit, the price unit, and the usage unit in the calculated engineering cost data can be adjusted by the adjustment data, and the embodiment of the present invention is not particularly limited.
It should be noted that, because the associated information is text content and image content collected from different news websites, and the identification of the price value and the adjustment data may be based on a natural language processing technology or an image identification technology, for example, a natural language processing technology is used to identify that the price value of human resource data is increased by 30 yuan from "human price subsidy 30 yuan per person per day", which is not specifically limited in the embodiment of the present invention. In addition, in order to limit the price value and the adjustment data, if the marked range is exceeded, the extreme value of the marked range is used as the price value and the adjustment data, and if the marked range is not exceeded, the process of step 104 may be executed.
104. And adjusting the project cost data according to the price value and/or the adjusting data.
For the embodiment of the invention, when the bid price value and/or the adjustment data are determined, the project cost data are obtained by calculating different resource data based on each calculation project, so that the adjustment of the project cost data according to the price value and the adjustment data is realized by integrating the price value, the adjustment data and the parameters of the original calculated project cost data and recalculating the project cost data, thereby timely and automatically obtaining the project cost data which is in line with the market data change.
In another embodiment, in order to improve the matching accuracy of the associated information and thus improve the processing efficiency of the construction cost data, the method further comprises: acquiring market transaction text information which is published by a news website and corresponds to the engineering cost data; identifying resource data from the market transaction text information using natural language processing techniques; clustering the resource data through a trained k-means clustering model to obtain associated information of different engineering cost data, wherein the k-means clustering model is obtained by training a first training data set based on the characteristics of unmarked resource data and a second training data set based on the characteristics of marked resource data; and storing the associated information in the network resource database, and marking an acquisition time identifier.
In the embodiment of the invention, the market transaction text information corresponding to the engineering cost data, such as the news content of government for adjusting the price of a certain resource in the building industry, is collected from all news event text information published by news websites in real time, so that the market transaction text information is acquired. Further, resource data is identified from the market transaction text information based on natural language processing technology, namely, text contents such as materials, manpower and the like are identified from the market transaction text information. In addition, in order to determine the identified text content such as materials, human resources and the like is the associated information of which resource data specifically belongs to, the identified resource data in the character form is clustered based on the trained k-means clustering model, so that associated information corresponding to materials and human resources with different clustering characteristics (that is, matching different resource data) is obtained and stored in the network resource database. In the storage process, in order to make the construction cost data processed by the associated information the latest and most effective, the associated information stored in the network resource database is marked with the acquisition time identifier so as to identify the bid price and the adjustment data from the most recent associated information.
In addition, the k-means clustering model is trained in advance, in the training process, in order to improve the accuracy of clustering different resource data, the training data set is divided into a first training data set based on the resource data characteristics which are not marked and a second training data set with the resource data characteristics which are marked, namely the first training data set and the second training data set are combined, and a specific number of training data are respectively extracted to train the k-means clustering model until the accuracy of the k-means training model meets the condition. In this process, the number of training data acquired from the first training data set and the second training data set includes: 1. finishing one-time training according to the fact that the number of data extracted from the first training data set is twice of the number of data extracted from the second training data set; 2. all data are extracted from the second training data set for training, and secondary training is completed; 3. and (3) circulating the extraction modes in the step (1) and the step (2) to train the k-means clustering model until the model meets the requirements.
In another embodiment, in order to improve the accuracy of obtaining the association information according to the clustering process, the clustering process is performed on the resource data through the trained k-means clustering model, and obtaining the association information of different engineering cost data includes: in the clustering process, randomly extracting 3 resource contents from the resource data to serve as a first centroid, a second centroid and a third centroid; respectively calculating Euclidean distances between the content of each residual resource in the resource data and the first centroid, the second centroid and the third centroid; dividing the resource content of which the Euclidean distance from the first centroid is greater than that from the second centroid into first associated information, dividing the resource content of which the Euclidean distance from the second centroid is greater than that from the first centroid into second associated information, dividing the resource content of which the Euclidean distance from the third centroid is greater than that from the first centroid and the second centroid into third associated information, and obtaining 3 associated information of different engineering cost data.
The euclidean distance, also called the euclidean distance, is the most common distance metric, and measures the absolute distance between two points in a multidimensional space, i.e., the true distance between two points in an m-dimensional space, or the natural length of a vector. The euclidean distance in two and three dimensions is the actual distance between two points. The specific calculation formula is as follows:
wherein xi and yi respectively represent the horizontal and vertical coordinates of the vector.
The resource data are clustered into 3 pieces of associated information by carrying out k-means clustering processing on the resource data, so that 3 different resource contents can be stored respectively by utilizing the 3 pieces of associated information in the following process, wherein the resource contents can include price change data, material change data and manpower change data which are 3 types.
In another embodiment, for further elaboration and explanation, the extracting the associated information of the collected engineering cost data matching the resource data from the different network resource database comprises: determining time characteristics corresponding to the marking range, and matching the time characteristics with time marks in the network resource database one by one; and when the time identification is matched with the time characteristic, extracting the associated information of the project cost data matched with the resource data according to the time identification.
In the embodiment of the invention, because the marking range is preset according to time factors, different marking ranges can be matched with one time characteristic, for example, the marking range of the winter manpower price, the matched time characteristic is 11 months to 3 months, the time marking is matched from the network resource database based on the time characteristic, and when the time mark corresponding to the time characteristic is matched, the associated information of the engineering cost data is extracted according to the time mark, so that the invalid processing is avoided.
In another embodiment, in order to effectively process the construction cost data and improve the processing accuracy, the adjusting the construction cost data according to the price value comprises: extracting a project cost calculation model matched with the price value, and re-executing the project cost calculation model based on the price value to obtain adjusted project cost data, wherein the project cost calculation model is used for representing a calculation formula for calculating the project cost data based on different price values; and/or extracting unit characteristics corresponding to the engineering cost calculation model matched with the adjusting data, and carrying out conversion adjustment on the unit characteristics based on the adjusting data to obtain adjusted engineering cost data.
In the embodiment of the invention, all calculation formulas for calculating the engineering cost data, such as a floor tile dosage formula and a ceiling dosage formula, are stored in the local storage position in advance, and the precalculated value in the engineering cost data is calculated by combining the floor tile unit price and the ceiling unit price. Therefore, after the bid price value is determined, the matched engineering cost calculation model is extracted, and the calculation of the engineering cost data is executed again, of course, the engineering cost calculation model not only can be a mathematical calculation formula, but also can be a deep learning model capable of performing artificial intelligent calculation, and the like, and the embodiment of the invention is not limited in particular. Because the adjustment data at least comprises one of time unit, price unit and dosage unit, after the adjustment data is determined, the unit characteristics corresponding to the matched engineering cost calculation model are extracted, namely the time unit, the price unit or the dosage unit is determined, and the unit conversion is carried out on the original engineering cost data based on the unit characteristics in the adjustment data to obtain the adjusted engineering cost data. The unit conversion is based on the existing measurement unit, and the conversion is directly performed by calling a unit conversion program, and the embodiment of the present invention is not particularly limited.
In another embodiment, in order to make the processing of the construction cost data meet the actual settlement requirement of the construction project, thereby optimizing the processing accuracy of the construction cost data, the method further comprises: judging whether the adjusted project cost data exceeds the marking range; if the price value exceeds the marking range, updating the maximum value or the minimum value of the marking range as the price value and/or the adjusting data; sending the updated price value and/or the adjustment data to a user side so as to verify the price value and/or the adjustment data; and when a verification result fed back by the user side is received, determining whether to execute the step of adjusting the construction cost data again according to the verification result.
Specifically, the adjusted construction cost data is used for judging and comparing with the marking range, if the construction cost data exceeds the marking range, the maximum value and the minimum value in the marking range are directly used as the price value or the adjustment data for updating, wherein the unit in the adjustment data is updated according to the maximum unit and the minimum unit in the marking range, and the embodiment of the invention is not particularly limited. And then sending the updated price value and the adjustment data to a user side for verification, receiving a feedback verification result after the user confirms the verification result, wherein the verification result comprises the steps of determining the updated price value and the adjustment data information, or re-inputting the price value and the adjustment data, and re-executing the adjustment step of the engineering cost data according to the verification result, thereby improving the processing accuracy of the engineering cost data.
The embodiment of the invention provides a method for processing engineering cost data, which comprises the steps of obtaining a marking range of the engineering cost data, wherein the marking range is used for representing price fluctuation range values of different resource data of engineering project construction; extracting the associated information of the collected project cost data matched with the resource data from different network resource databases; identifying price values and/or adjustment data in the associated information that match the marker ranges; the engineering cost data is adjusted according to the price value and/or the adjustment data, automatic collection of the affected engineering cost data is achieved, the purpose of timely updating engineering operation data is met, human resources are greatly saved, instantaneity is strong, timeliness and accuracy of construction cost calculation are improved, and accordingly processing efficiency of the engineering cost data is improved.
Further, as an implementation of the method shown in fig. 1, an embodiment of the present invention provides an apparatus for processing engineering cost data, as shown in fig. 2, the apparatus includes:
the acquisition module 21 is configured to acquire a mark range of the engineering cost data, where the mark range is used to represent price fluctuation range values of different resource data of engineering project construction;
an extraction module 22, configured to extract, from different network resource databases, the associated information of the collected project cost data that matches the resource data;
the identification module 23 is configured to identify price values and/or adjustment data in the associated information, which match the mark range;
an adjusting module 34, configured to adjust the engineering cost data according to the price value and/or the adjustment data.
Further, the apparatus further comprises: the processing module, the storage module,
the acquisition module is also used for acquiring market transaction text information which is released by the news website and corresponds to the project cost data;
the identification module is further used for identifying resource data from the market transaction text information by using a natural language processing technology;
the processing module is used for clustering the resource data through a trained k-means clustering model to obtain the associated information of different engineering cost data, and the k-means clustering model is obtained by training a first training data set based on the characteristics of the resource data which are not marked and a second training data set based on the characteristics of the resource data which are marked;
and the storage module is used for storing the associated information in the network resource database and marking a collection time identifier.
Further, the processing module comprises:
the extraction unit is used for randomly extracting 3 resource contents from the resource data as a first centroid, a second centroid and a third centroid in the clustering process;
the calculating unit is used for calculating Euclidean distances between the remaining resource contents in the resource data and the first centroid, the second centroid and the third centroid respectively;
the determining unit is used for dividing the resource content of which the Euclidean distance from the first centroid is greater than that from the second centroid into first associated information, dividing the resource content of which the Euclidean distance from the second centroid is greater than that from the first centroid into second associated information, and dividing the resource content of which the Euclidean distance from the third centroid is greater than that from the first centroid and the second centroid into third associated information, so as to obtain 3 pieces of associated information of different engineering cost data.
Further, the extraction module comprises:
the matching unit is used for determining the time characteristics corresponding to the marking range and matching the time characteristics with the time marks in the network resource database one by one;
and the extraction unit is used for extracting the associated information of the engineering cost data matched with the resource data according to the time identification when the time identification is matched with the time characteristic.
Further, the adjustment module includes:
a first execution unit, configured to extract a project cost calculation model matched with the price value, and re-execute the project cost calculation model based on the price value to obtain adjusted project cost data, where the project cost calculation model is used to represent a calculation formula for calculating project cost data based on different price values; and/or the presence of a gas in the gas,
and the second execution unit is used for extracting unit characteristics corresponding to the engineering cost calculation model matched with the adjusting data, and carrying out conversion adjustment on the unit characteristics based on the adjusting data to obtain adjusted engineering cost data.
Further, the apparatus further comprises:
the judging module is used for judging whether the adjusted construction cost data exceeds the marking range;
the updating module is used for updating the maximum value or the minimum value of the marking range as the price value and/or the adjusting data if the marking range is exceeded;
the sending module is used for sending the updated price value and/or the adjusted data to the user side so as to verify the price value and/or the adjusted data;
and the execution module is used for determining whether to execute the step of adjusting the engineering cost data again according to the verification result when receiving the verification result fed back by the user side.
The embodiment of the invention provides a processing device of engineering cost data, which is characterized in that a marking range of the engineering cost data is obtained, and the marking range is used for representing price fluctuation range values of different resource data of engineering project construction; extracting the associated information of the collected project cost data matched with the resource data from different network resource databases; identifying price values and/or adjustment data in the associated information that match the marker ranges; the engineering cost data is adjusted according to the price value and/or the adjustment data, automatic collection of the affected engineering cost data is achieved, the purpose of timely updating engineering operation data is met, human resources are greatly saved, instantaneity is strong, timeliness and accuracy of construction cost calculation are improved, and accordingly processing efficiency of the engineering cost data is improved.
According to an embodiment of the present invention, there is provided a storage medium storing at least one executable instruction, where the computer executable instruction is capable of executing the method for processing the construction cost data in any of the above method embodiments.
Fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the computer device.
As shown in fig. 3, the computer apparatus may include: a processor (processor)302, a communication Interface 304, a memory 306, and a communication bus 308.
Wherein: the processor 302, communication interface 304, and memory 306 communicate with each other via a communication bus 308.
A communication interface 304 for communicating with network elements of other devices, such as clients or other servers.
The processor 302 is configured to execute the program 310, and may specifically execute the relevant steps in the above-mentioned method for processing construction cost data.
In particular, program 310 may include program code comprising computer operating instructions.
The processor 302 may be a central processing unit CPU, or an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement an embodiment of the present invention. The computer device includes one or more processors, which may be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
And a memory 306 for storing a program 310. Memory 306 may comprise high-speed RAM memory and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 310 may specifically be configured to cause the processor 302 to perform the following operations:
acquiring a marking range of the engineering cost data, wherein the marking range is used for representing price fluctuation range values of different resource data of engineering project construction;
extracting the associated information of the collected project cost data matched with the resource data from different network resource databases;
identifying price values and/or adjustment data in the associated information that match the marker ranges;
and adjusting the project cost data according to the price value and/or the adjusting data.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for processing construction cost data is characterized by comprising the following steps:
acquiring a marking range of the engineering cost data, wherein the marking range is used for representing price fluctuation range values of different resource data of engineering project construction;
extracting the associated information of the collected project cost data matched with the resource data from different network resource databases;
identifying price values and/or adjustment data in the associated information that match the marker ranges;
and adjusting the project cost data according to the price value and/or the adjusting data.
2. The method of claim 1, further comprising:
acquiring market transaction text information which is published by a news website and corresponds to the engineering cost data;
identifying resource data from the market transaction text information using natural language processing techniques;
clustering the resource data through a trained k-means clustering model to obtain associated information of different engineering cost data, wherein the k-means clustering model is obtained by training a first training data set based on the characteristics of unmarked resource data and a second training data set based on the characteristics of marked resource data;
and storing the associated information in the network resource database, and marking an acquisition time identifier.
3. The method of claim 2, wherein the clustering the resource data through the trained k-means clustering model to obtain the associated information of different construction cost data comprises:
in the clustering process, randomly extracting 3 resource contents from the resource data to serve as a first centroid, a second centroid and a third centroid;
respectively calculating Euclidean distances between the content of each residual resource in the resource data and the first centroid, the second centroid and the third centroid;
dividing the resource content of which the Euclidean distance from the first centroid is greater than that from the second centroid into first associated information, dividing the resource content of which the Euclidean distance from the second centroid is greater than that from the first centroid into second associated information, dividing the resource content of which the Euclidean distance from the third centroid is greater than that from the first centroid and the second centroid into third associated information, and obtaining 3 associated information of different engineering cost data.
4. The method of claim 2, wherein extracting the associated information of the collected project cost data matching the resource data from the different network resource database comprises:
determining time characteristics corresponding to the marking range, and matching the time characteristics with time marks in the network resource database one by one;
and when the time identification is matched with the time characteristic, extracting the associated information of the project cost data matched with the resource data according to the time identification.
5. The method of claim 1, wherein said adjusting said construction cost data according to said price value comprises:
extracting a project cost calculation model matched with the price value, and re-executing the project cost calculation model based on the price value to obtain adjusted project cost data, wherein the project cost calculation model is used for representing a calculation formula for calculating the project cost data based on different price values; and/or the presence of a gas in the gas,
and extracting unit characteristics corresponding to the engineering cost calculation model matched with the adjusting data, and carrying out conversion adjustment on the unit characteristics based on the adjusting data to obtain adjusted engineering cost data.
6. The method of claim 1, further comprising:
judging whether the adjusted project cost data exceeds the marking range;
if the price value exceeds the marking range, updating the maximum value or the minimum value of the marking range as the price value and/or the adjusting data;
sending the updated price value and/or the adjustment data to a user side so as to verify the price value and/or the adjustment data;
and when a verification result fed back by the user side is received, determining whether to execute the step of adjusting the construction cost data again according to the verification result.
7. The method according to any of claims 1-6, wherein the adjustment data comprises at least one of time units, price units, usage units.
8. A processing apparatus for construction cost data, comprising:
the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring a mark range of the engineering cost data, and the mark range is used for representing the price fluctuation range values of different resource data of engineering project construction;
the extraction module is used for extracting the associated information of the collected project cost data matched with the resource data from different network resource databases;
the identification module is used for identifying the price value and/or the adjustment data matched with the mark range in the associated information;
and the adjusting module is used for adjusting the project cost data according to the price value and/or the adjusting data.
9. A storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the method of processing construction cost data according to any one of claims 1 to 7.
10. A computer device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the processing method of the construction cost data according to any one of claims 1-7.
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