CN117993953A

CN117993953A - Method, system, equipment and storage medium for calculating engineering construction cost

Info

Publication number: CN117993953A
Application number: CN202410123349.8A
Authority: CN
Inventors: 付巍巍
Original assignee: Beijing Yuanzun Engineering Management Consulting Co ltd
Current assignee: Beijing Yuanzun Engineering Management Consulting Co ltd
Priority date: 2024-01-29
Filing date: 2024-01-29
Publication date: 2024-05-07

Abstract

A method, a system, equipment and a storage medium for calculating engineering construction cost relate to the field of engineering cost. In the method, charging file data are acquired, characteristics of the charging file data are extracted to determine sub-charging file data corresponding to each charge category, and the charging file data comprise government charging file data and industry charging file data; evaluating the sub-charging file data according to a preset evaluation standard to determine a charging rule of each charging category; responding to the operation of inquiring the user cost, acquiring engineering project data corresponding to the user, and calculating and generating the cost of each cost category according to the charging rule of each cost category; and summarizing the cost of each cost category to obtain a comprehensive cost prediction table. By implementing the technical scheme provided by the application, the effects of improving the automation degree of the cost calculation and the comprehensiveness of the cost calculation are achieved.

Description

Method, system, equipment and storage medium for calculating engineering construction cost

Technical Field

The application relates to the technical field of engineering cost, in particular to a method, a system, electronic equipment and a storage medium for calculating engineering construction cost.

Background

With the development of science and technology, the requirements of infrastructure construction such as buildings, traffic, water conservancy and energy are continuously increased, and higher requirements are put on engineering cost. Under the market economy system, engineering cost becomes an important basis for enterprise investment decision-making and project management, and has important significance for ensuring engineering quality, controlling cost and improving benefit.

At present, for each cost calculation, a user is required to select a cost category which the user wants to calculate, and then a corresponding cost parameter is input according to a corresponding calculation formula, so that the cost parameter is calculated by combining the calculation formula, and a final cost value is obtained. The process can only realize calculation according to the category of the cost and by combining manual input parameters of a user, has low automation degree, and cannot summarize the cost under different categories according to the whole calculation requirement of the actual engineering cost, so as to obtain the comprehensive cost prediction condition.

Therefore, there is a need for a method that can automatically select a calculation formula to calculate each fee and can aggregate all the fees.

Disclosure of Invention

The application provides a method, a system, electronic equipment and a storage medium for calculating engineering construction cost, which improve the automation degree of cost calculation and the comprehensiveness of cost calculation.

In a first aspect of the present application, there is provided a method for calculating engineering construction costs, applied to an engineering construction management platform, the method comprising:

acquiring charging file data, extracting characteristics of the charging file data to determine sub-charging file data corresponding to each charge category, wherein the charging file data comprises government charging file data and industry charging file data;

Evaluating the sub-charging file data according to a preset evaluation standard to determine a charging rule of each charging category;

responding to the operation of inquiring the user cost, acquiring engineering project data corresponding to the user, and calculating and generating the cost of each cost category according to the charging rule of each cost category;

And summarizing the cost of each cost category to obtain a comprehensive cost prediction table.

By adopting the technical scheme, the charging rule of each expense category can be accurately determined, and calculation can be performed according to the charging rule of each expense category. The accuracy and the automation degree of the cost calculation are improved. The charging rule change of different areas, different industries and different engineering projects can be adapted because the charging file data are evaluated by adopting the preset evaluation standard. This makes the cost calculation more flexible and can be adapted to various complications. By responding to the operation of inquiring the user cost, the engineering project data corresponding to the user can be rapidly obtained, and the generated cost is calculated according to the charging rule. This greatly shortens the user latency, enhancing the user experience. Meanwhile, the working efficiency is improved due to the automation of the calculation process. By aggregating the costs for each cost category, the method is able to generate a comprehensive cost prediction table. This provides a comprehensive, clear cost budget to the user, helping the user to better conduct project planning and funding.

Optionally, the acquiring the charging file data, extracting the characteristics of the charging file data to determine sub-charging file data corresponding to each charging category includes:

Establishing a uniform resource locator set, wherein the uniform resource locator set comprises a plurality of uniform resource locators, and each uniform resource locator corresponds to one data source;

Determining the source reliability of the corresponding uniform resource locator according to the attribute of the data source, and acquiring the charging file data according to the uniform resource locator of which the source reliability exceeds a reliability threshold, wherein the attribute comprises the authority of a data issuing mechanism, the historical updating frequency of the file, the integrity and the accuracy of the content.

By adopting the technical scheme, the unified resource locator set is established, and a plurality of different data sources including charging file data issued by government, industry association, professional institutions and the like can be integrated. The method not only ensures the diversity of the data, but also enables the data source to be expanded at any time according to the needs, and improves the adaptability and the flexibility of the method. The reliability of the data source can be determined by evaluating the attribute of each url corresponding to the data source, such as authority of the data issuing authority, historical update frequency of the file, integrity and accuracy of the content, and the like. This helps to exclude unreliable or low quality sources of data, ensuring the accuracy and credibility of the acquired charging file data. By setting the reliability threshold, data with low source reliability can be automatically screened out, and the workload of subsequent data processing and analysis is reduced. This helps to improve the efficiency of data processing and shortens the period of cost calculation. By extracting features of the charging file data and determining sub-charging file data corresponding to each of the charge categories, different charge categories can be more accurately divided and identified. This helps to avoid the situation of misclassification or omission of the fee and to improve the accuracy of the fee calculation.

determining field characteristics to be extracted, wherein the field characteristics comprise a fee name, a fee charging standard, a fee charging basis and a fee charging period;

locating the field features from the charging file data using a preset rule or algorithm;

And extracting the positioned contextual data of the field characteristics, and integrating the contextual data to obtain sub-charging file data corresponding to each charge category.

By adopting the technical scheme, the field characteristics to be extracted, such as the cost name, the charging standard, the charging basis, the charging period and the like, are predetermined, and the related information can be extracted from the charging file data in a targeted manner. This avoids purposeless full-text scanning and processing of the data, improving the accuracy and efficiency of data extraction. The method for locating the field characteristics by using a preset rule or algorithm can adapt to charging file data with different formats and structures. Whether the data is presented in a form, text paragraph or other forms, the position of the required information can be accurately positioned, and the flexibility and the universality of the method are improved. By extracting the contextual data of the located field features and integrating these data, it is ensured that complete sub-charging file data with contextual relevance is obtained. This helps to better understand the specific meaning, applicable conditions and calculation mode of the cost, and provides a reliable data base for subsequent cost calculation. The fine management of the fees is facilitated by dividing the charging file data into different fee categories and extracting the corresponding sub-charging file data for each category. This allows the user to more clearly understand the composition and calculation basis of different fees, providing powerful support for project cost control and budget planning.

Optionally, the evaluating the sub-charging file data according to a preset evaluation criterion to determine a charging rule of each charging category includes:

Summarizing charging rules in sub-charging file data corresponding to each charging category to obtain a first charging rule set, and determining a standard evaluation value of each charging rule in the first charging rule set according to the preset evaluation standard, wherein the preset evaluation standard comprises the file category, the frequency and the file channel of the charging rule;

And selecting a charging rule under each charge category according to the standard evaluation value.

By adopting the technical scheme, the charging rules in the sub-charging file data corresponding to each charging category are summarized to form the first charging rule set, so that unified management and standardization of the charging rules are realized. This helps to eliminate charging rule differences and conflicts that may exist in different sources, different files, and improves accuracy and consistency of fee calculation. According to preset evaluation criteria, such as the types, the frequency and the channels of the files, and the like, the standard evaluation value of each charging rule is determined, so that the charging rule is more scientifically and reasonably selected. This avoids the situation of selecting charging rules only by subjective judgment or experience, and improves the objectivity and fairness of selection. By comprehensively considering a plurality of factors to evaluate the importance and applicability of the charging rules, the method can be better suitable for complex charging environments. Whether the charging rules originate from government documents, industry association regulations, or internal corporate regulations, they can be objectively evaluated and reasonably selected. And the charging rules under each expense category are selected according to the standard evaluation value, so that the optimization of the expense calculation flow and the improvement of the efficiency are facilitated. By eliminating those charging rules that are not important or applicable, redundancy and complexity in the calculation process can be reduced, and accuracy and response speed of calculation can be improved.

Optionally, the selecting the charging rule under each fee category according to the standard evaluation value includes:

the first standard evaluation value and the second standard evaluation value are standard evaluation values corresponding to any two charging rules in the charging rule set, the first standard evaluation value is larger than the second standard evaluation value, and the first charging rule corresponding to the first standard evaluation value is selected as the charging rule under the corresponding charging category.

By adopting the technical scheme, the charging rules with higher importance and applicability can be accurately identified by comparing the standard evaluation values of different charging rules. This avoids the selection of low quality or inapplicable charging rules, thereby improving the accuracy of the fee calculation. And the unified standard evaluation values are adopted for comparison and selection, so that the consistency and fairness of charging rules under different charge categories are ensured. This eliminates the influence of human factors or subjective judgment on the choice of charging rules, making the selection process more objective and fair. By selecting the charging rule with the highest standard evaluation value, redundancy and complexity in the charge calculation process can be reduced. This helps optimize the computational flow and increase computational efficiency, thereby providing faster, more accurate fee calculation services to the user.

Optionally, the selecting the charging rule under each fee category according to the standard evaluation value further includes:

determining a second charging rule with a standard evaluation value larger than an evaluation value threshold value, and constructing a second charging rule set through the second charging rule;

obtaining a user evaluation value corresponding to each second charging rule in the second charging rule set, and carrying out weighted summation on the standard evaluation value and the user evaluation value of each second charging rule to obtain a final evaluation value;

The first final evaluation value and the second final evaluation value are final evaluation values corresponding to any two second charging rules in the second charging rule set, the first final evaluation value is larger than the second final evaluation value, and the second charging rule corresponding to the first final evaluation value is selected as the charging rule under the corresponding charging category.

By adopting the technical scheme, the second charging rule with the standard evaluation value larger than the evaluation value threshold is determined, the second charging rule set is constructed, charging rules with certain quality and applicability can be screened out, the final evaluation value is obtained by combining the user evaluation values for weighted summation, the actual application condition and user feedback of the charging rules can be considered more comprehensively, and therefore the accuracy of charging rule selection is improved. By acquiring the user evaluation value and incorporating it into the calculation of the final evaluation value, the opinion and the demand of the user can be fully considered. This enhances the engagement and satisfaction of the user so that the selected charging rules more closely conform to the actual needs and desires of the user. And the unified standard evaluation value and the user evaluation value are adopted for weighted summation to obtain a final evaluation value, so that the objectivity and fairness of charging rule selection are ensured. This avoids the case of selecting charging rules only by subjective judgment or a single factor, making the selection process more scientific and reasonable.

Optionally, the method further comprises:

And when detecting that the charging file data has new data, redefining the charging rule of each charging category according to the new data.

By adopting the technical scheme, the change of the charging file data is continuously monitored, and the charging rule is timely redetermined when new data is detected, so that the charge calculation can be ensured to be always based on the latest and most accurate data. This enhances the real-time update capability of the method and the adaptability to different environments. The new data may contain new charging criteria, policy changes, or marketing adjustments, etc., which are critical to accurately calculating the cost. By redefining the charging rules according to the new data, the method can ensure that the charge calculation always meets the latest requirements and standards, thereby improving the accuracy of calculation. Accurate and timely fee calculation is critical to the user. By redefining the charging rules according to the new data, better user experience can be provided, and the requirements of users on the accuracy and timeliness of the fee calculation are met, so that the user satisfaction is improved.

In a second aspect of the present application, a system for calculating engineering construction costs is provided, including an acquisition module, a rule module, a calculation module, and a summary module, where:

The collection module is configured to obtain charging file data, extract characteristics of the charging file data to determine sub-charging file data corresponding to each charging category, wherein the charging file data comprises government charging file data and industry charging file data;

the rule module is configured to evaluate the sub-charging file data according to a preset evaluation standard to determine a charging rule of each charging category;

The calculation module is configured to respond to the operation of inquiring the user cost, acquire engineering project data corresponding to the user, and calculate and generate the cost of each cost category according to the charging rule of each cost category;

And the summarizing module is configured to summarize the cost of each cost category to obtain a comprehensive cost prediction table.

In a third aspect the application provides an electronic device comprising a processor, a memory for storing instructions, a user interface and a network interface, both for communicating with other devices, the processor being for executing instructions stored in the memory to cause the electronic device to perform a method as claimed in any one of the preceding claims.

In a fourth aspect of the application there is provided a computer readable storage medium storing instructions which, when executed, perform a method as claimed in any one of the preceding claims.

In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:

1. By acquiring and analyzing the diversified data comprising government and industry charging files, the charging information related to each charge category can be accurately extracted, so that the complicated process of manually searching and calculating the charge is avoided, and the accuracy and efficiency of charge calculation are greatly improved;

2. the charging rules adopted by the method always meet the latest policy and market requirements by evaluating the sub-charging file data through the preset evaluation criteria, so that the charge calculation can be flexibly adapted to the continuously changed policy and market environment;

3. By calculating the cost of each cost category and summarizing the cost to obtain a comprehensive cost prediction table, comprehensive and detailed cost budget information can be provided for the user, which is helpful for the user to make more intelligent decisions in the project planning and executing process;

4. By responding to the cost inquiry operation of the user and providing the instant cost calculation result, the experience and satisfaction degree of the user when using the engineering construction management platform can be greatly improved.

Drawings

FIG. 1 is a flow chart of a method of engineering construction cost calculation disclosed in an embodiment of the present application;

FIG. 2 is a schematic block diagram of a system for engineering construction cost calculation according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Reference numerals illustrate: 201. an acquisition module; 202. a rule module; 203. a computing module; 204. a summarizing module; 301. a processor; 302. a communication bus; 303. a user interface; 304. a network interface; 305. a memory.

Detailed Description

In order that those skilled in the art will better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments.

In describing embodiments of the present application, words such as "for example" or "for example" are used to mean serving as examples, illustrations, or descriptions. Any embodiment or design described herein as "such as" or "for example" in embodiments of the application should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.

In the description of embodiments of the application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

The embodiment discloses a method for calculating engineering construction cost, which is applied to an engineering construction management platform, and fig. 1 is a flow chart of the method for calculating engineering construction cost disclosed by the embodiment of the application, as shown in fig. 1, and the method comprises the following steps:

S110, acquiring charging file data, extracting characteristics of the charging file data to determine sub-charging file data corresponding to each fee category, wherein the charging file data comprises government charging file data and industry charging file data;

The charging file data mainly comprises two main types, namely government charging file data and industry charging file data. Government charge file data is typically derived from official files issued by various levels of government and its related departments, such as regulations of administrative charges, tax, etc. for construction projects. The industry charging file data is derived from charging standards, industry practices and the like issued by industry associations, professionals or market research companies. Methods of collecting such data may include downloading from an official website, subscribing to related services, collaborating with a data provider, and so forth. Furthermore, it may involve the use of automated tools such as web crawlers to periodically grab and update data.

All possible sources of charging file data are identified and listed, such as government officials networks at various levels, industry association websites, professional agency distribution platforms, and the like. Each data source is assigned a unique Uniform Resource Locator (URL), which constitutes a URL set. For example, the URL sets may include URLs pointing to the latest charging file data issued by "national development and reformulation committee price department", URLs pointing to industry standard charging files issued by "chinese construction association", and the like. For each URL's corresponding data source, its attributes are analyzed, including: 1. authority of the data issuing organization, and authority and creditability of the data source organization (such as government departments and industry associations) in issuing charging files are evaluated; 2. the historical update frequency of the file is analyzed, and the update frequency of the charging file issued by the data source is analyzed so as to judge the timeliness and the liveness of the charging file; 3. integrity and accuracy of content the integrity and accuracy of the charging file data is verified by manual inspection or automated means. Each URL is assigned a source reliability score based on the attributes. For example, weights may be set for authority, update frequency, integrity, and accuracy, respectively, and each attribute may be scored according to actual conditions, and finally weighted sum may be used to obtain a total score. A reliability threshold is set and only URLs whose total score exceeds this threshold are considered to be sufficiently reliable, the corresponding charging file data will be acquired. Using a web crawler or other automated tool, these URLs are automatically accessed and corresponding charging file data is downloaded based on the determined list of reliable URLs. The acquired charging file data is preprocessed, such as format conversion, data cleaning, etc., for subsequent feature extraction and classification operations. Key features such as a fee name, a charging unit, a rate, etc. are extracted from the preprocessed charging file data using Natural Language Processing (NLP) technology. Based on the extracted features, the charging file data is divided into different charge categories using a classification algorithm to form a sub-charging file data set.

By strictly screening the data sources, the acquired charging file data is ensured to come from an authoritative and reliable data issuing mechanism, and the data has higher integrity and accuracy. This greatly improves the accuracy and reliability of subsequent cost calculations. The historical updating frequency of the file is considered as one of indexes for evaluating the reliability of the data source, so that the latest and most timely charging file data can be acquired. This is critical to quick response to dynamic factors such as policy changes, market adjustments, etc., ensuring timeliness of the cost calculation. By establishing the URL set and automatically acquiring the data, the time cost of manually searching and downloading the data can be greatly reduced, and the data processing efficiency is improved. At the same time, processing only data of reliable source also avoids the interference of invalid or erroneous data to subsequent calculation. By extracting the characteristics of the screened charging file data, the sub-charging file data corresponding to each charging category can be more accurately determined. This provides a solid data base for subsequent cost calculations and comprehensive cost predictions.

According to the requirements of the fee calculation, the field characteristics required to be extracted from the fee charging file data are determined. In this example, these field characteristics include: (1) Cost names such as "construction project plan license fee", "city infrastructure mating fee", etc.; (2) A charging standard, a specific fee amount or rate, such as "10 yuan per square meter per building area" or "1% of contract amount"; (3) Charging basis, laws, regulations, policy documents and the like according to which charging is performed, such as "city planning" in section XX; (4) Charging period, time interval of charging fee, such as "one-time charging", "charging by year", etc. These field features are located in the charging file data using preset rules or algorithms. Techniques that this may involve include: (1) Text segmentation and Named Entity Recognition (NER) that segments the billing file data into words or phrases and identifies entities therein, such as fee names, legal names, etc.; (2) Regular expression matching, namely compiling a regular expression for pattern matching according to format characteristics of field characteristics; (3) Semantic analysis and context understanding, analyzing semantic relationships in text, understanding context to more accurately locate field features. For example, NER techniques can be used to identify cost names in text and then combine contextual understanding and regular expression matching to locate charging criteria, basis and period associated therewith. Once field features are located, contextual data of the features needs to be extracted and integrated. The method specifically comprises the following steps: extracting sentences or paragraphs with field features; the extracted data is cleaned and formatted, so that the consistency and the readability of the data are ensured; classifying and integrating the extracted data according to the fee categories to form sub-charging file data corresponding to each fee category. For example, for a recognized fee name, the entire sentence in which it resides, including information such as fee criteria, basis, and period, may be extracted, and then the data formatted into a unified structure, such as a table or database record, and categorized into the corresponding fee category.

By definitely requiring extracted field characteristics and positioning by using preset rules or algorithms, key information can be accurately and rapidly obtained from a large amount of charging file data, and the complicated process of manual searching and sorting is avoided. And extracting the context data of the field characteristics, integrating the data, and helping to keep the context information in the original file and ensuring the integrity and accuracy of the extracted data in terms of semantics. Meanwhile, the unified data integration mode also ensures that the data with different sources and different formats have consistency after being processed. By integrating the extracted data, sub-charging file data corresponding to each of the charge categories can be more easily determined. This classification facilitates subsequent cost calculation, budget planning, and cost control, making cost management more refined. The whole data extraction and integration process can realize automation through programming, reduce manual intervention, improve the speed and the scale of data processing, and is suitable for processing a large amount of complex charging file data.

S120, evaluating the sub-charging file data according to a preset evaluation standard to determine a charging rule of each charging category;

And summarizing the charging rules in the sub-charging file data corresponding to each charging category. This means that all charging rules collected from multiple sources and documents that are associated with a particular category of charges are sorted into a collection, which is referred to as the "first collection of charging rules". Before evaluating the charging rules, explicitly preset evaluation criteria are required. In the embodiment of the application, the preset evaluation criteria include: (1) The types of files in which charging rules occur, such as laws, regulations, policy files, administrative notices, etc., different types of files having different authority and legal effectiveness; (2) The frequency of occurrence of charging rules, which may be repeated in multiple documents, may be more important or universally applicable; (3) Document channel, authority and credibility of the institution or platform that publishes the document, such as government official website, industry association bulletin, etc. A standard rating value is calculated for each charging rule in the first set of charging rules according to a preset rating criterion. The evaluation value comprehensively considers the occurrence condition, the occurrence frequency and the authority of the file sources of the charging rules in different file categories. For example, a weight may be set for each document category, frequency of occurrence, and document channel, and then the standard evaluation value of each charging rule may be calculated by means of weighted summation. And selecting a final charging rule from each fee category according to the calculated standard evaluation value. The selection principle can be to select the rule with the highest evaluation value or set a threshold value of the evaluation value according to the actual requirement, and only select the rule with the evaluation value exceeding the threshold value. The charging rules of n (n is a positive integer) before the standard evaluation value is sequenced can be pushed to the background expert equipment end, and the final charging calculation rule selected from the charging rules by the background expert equipment end can be received.

By summarizing the charging rules under each fee category and determining standard evaluation values according to preset evaluation standards such as file categories, occurrence frequencies, file channels and the like, more accurate, authoritative and applicable charging rules can be screened. This helps to ensure that the finally determined charging rules meet legal regulations, while being easier to implement and accept in practice. The introduction of the standard evaluation value enables the selection of the charging rule to be more objective and scientific. By comparing standard evaluation values of different charging rules, it is easier to identify which rules perform better in multiple dimensions, thereby making a more reasonable choice. The whole evaluation process can realize automatic processing through programming, so that the workload of manual screening and evaluation is greatly reduced. The working efficiency is improved, the possibility of human errors is reduced, and the accuracy of data processing is improved. By performing comprehensive evaluation and standardization processing on the sub-charging file data, the consistency and comparability of charging rules under different charge categories can be ensured. This helps to enhance transparency of charge management, reduce ambiguity and disputes, and promote user satisfaction.

And comparing standard evaluation values corresponding to any two charging rules in the first charging rule set. It is assumed that a first standard evaluation value and a second standard evaluation value are respectively corresponding to the first charging rule a and the first charging rule B. If the first standard evaluation value is larger than the second standard evaluation value, a first charging rule A corresponding to the first standard evaluation value is selected as a charging rule under the corresponding fee category. This is because a higher rating means that the charging rule performs better under the preset rating criteria, is more likely to meet regulatory requirements, has higher authority and wider applicability. The comparison and selection process is repeated until all the charging rules in the first charging rule set are traversed, so that the charging rule with the highest evaluation value can be selected under each charging category.

By directly comparing the standard evaluation values, charging rules with better performance can be rapidly and accurately identified. The method avoids the complicated manual analysis and comparison process, and greatly improves the decision efficiency. Since a charging rule with a higher evaluation value is selected, it is possible to ensure that the selected rule has a better performance under a preset evaluation criterion. This helps to promote the authority, compliance and applicability of the charging rules, reducing the risk of improper rule selection. Through the clear evaluation standard and the public evaluation process, the transparency and fairness of charging rule selection are enhanced. This helps to reduce human intervention and subjective bias, and promote user perception and satisfaction of charging rules.

The evaluation value threshold is set based on historical data, industry standards, or expert opinions. Traversing the standard evaluation values of all the charging rules, and constructing the charging rules with the standard evaluation values larger than the evaluation value threshold value into a new set, namely a second charging rule set. And further acquiring a corresponding user evaluation value for each charging rule in the second charging rule set. The user evaluation value can be obtained through the modes of user investigation, online feedback, historical use data and the like, and reflects the acceptance degree and satisfaction degree of the user on the charging rule. And carrying out weighted summation on the standard evaluation value and the user evaluation value of each second charging rule to obtain the final evaluation value of each charging rule. The weight setting can be adjusted according to the actual situation to reflect the importance of the standard evaluation value and the user evaluation value in the final decision. And comparing the final evaluation values of any two charging rules in the second charging rule set. And selecting the charging rule with the highest final evaluation value as the charging rule under the corresponding cost category.

By comprehensively considering the standard evaluation value and the user evaluation value, the merits of the charging rule can be evaluated more comprehensively. This avoids the one-sidedness that may result from relying on only a single evaluation criterion, thereby improving the accuracy of the decision. The user evaluation value is used as one of important decision factors, so that the selected charging rule is ensured to be more in line with the expectations and demands of the user. This helps to promote user satisfaction and enhance the relationship between the enterprise and the user. The charging rules with standard evaluation values higher than the threshold value are screened out, and further weighted evaluation is carried out by combining the user evaluation values, so that the charging rules which are both compliant and popular with users can be selected. This helps to optimize the cost management for the enterprise and reduce the risk of improper charging rules.

S130, responding to the operation of inquiring the user fees, acquiring engineering project data corresponding to the user, and calculating and generating the fees of each fee category according to the charging rule of each fee category;

Integrating each fee category and the final charging calculation rule under each fee category in an engineering construction management platform mobile phone APP interface. And providing a one-key expense inquiry function key on the APP interface of the mobile phone, responding to clicking operation of a user, combining engineering project data bound in the APP by the user, automatically calling a final expense calculation rule under each expense category, and generating expense corresponding to each expense category. After the user registers the mobile phone APP, when the related information inquiry of the construction cost is carried out, various project data uploaded by the user can be received, and the project data are associated with the user and used for subsequent cost calculation, so that the intelligent degree of the cost calculation is improved.

And S140, summarizing the cost of each cost category to obtain a comprehensive cost prediction table.

Summarizing the fees corresponding to each fee category to obtain a comprehensive fee prediction table; wherein the comprehensive cost prediction table comprises cost types, cost values under the cost types and final charge calculation rules.

Optionally, the method further comprises:

The engineering construction management platform needs to detect whether charging file data has new data or not periodically or in real time. This can be achieved by setting up a data monitoring mechanism, which triggers the process of re-determining charging rules once new data is detected. After the engineering construction management platform obtains the new data, the new data needs to be analyzed and analyzed. This includes identifying the category of charges to which the new data belongs, extracting the relevant charging rules information, and evaluating the impact of the new data on the existing charging rules. Based on the analysis of the new data, the engineering construction management platform needs to redetermine the charging rules for each of the cost categories. This may involve updating, modifying or replacing existing rules to ensure that the rules remain consistent with the new data. For example, assuming that the new data contains the latest charging criteria for a service, the system needs to update the charging rules for the corresponding fee categories to reflect this change. After the charging rules are redetermined, the engineering construction management platform also needs to verify the new rules, so that the accuracy and compliance of the new rules are ensured. This may be achieved by comparing with preset evaluation criteria, making an internal audit or inviting an expert to evaluate, etc. Once the new rule passes the verification, the engineering construction management platform can release the new rule to the corresponding expense category for subsequent expense accounting and management.

By detecting new data periodically or in real time and redefining the charging rules, it is ensured that the rules always remain consistent with the latest data, thereby maintaining the real-time nature of the rules. The analysis and processing of new data, and the updating, modification or replacement of existing rules are all helpful to improve the accuracy of charging rules and reduce the risk caused by improper rules. As market conditions and business requirements change, the charging rules also need to be continually adjusted and optimized. By redefining the flow of the charging rules, the enterprise can more flexibly cope with these changes, enhancing its own strain capacity.

The embodiment also discloses a system for calculating engineering construction cost, and fig. 2 is a schematic block diagram of the system for calculating engineering construction cost disclosed in the embodiment of the application, as shown in fig. 2, the system includes an acquisition module 201, a rule module 202, a calculation module 203 and a summarization module 204, wherein:

an acquisition module 201 configured to acquire charging file data, extract characteristics of the charging file data to determine sub-charging file data corresponding to each of the charge categories, the charging file data including government charging file data and industry charging file data;

a rule module 202 configured to evaluate the sub-charging file data according to a preset evaluation criterion to determine a charging rule for each charging category;

the calculating module 203 is configured to respond to the operation of inquiring the user cost, acquire engineering project data corresponding to the user, and calculate and generate the cost of each cost category according to the charging rule of each cost category;

And a summarizing module 204 configured to summarize the fees of each of the fee categories to obtain a comprehensive fee prediction table.

Optionally, the acquisition module 201 is further configured to:

Optionally, the rule module 202 is further configured to:

Optionally, the system further comprises an update module configured to:

It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.

The embodiment also discloses an electronic device, referring to fig. 3, the electronic device may include: at least one processor 301, at least one communication bus 302, a user interface 303, a network interface 304, at least one memory 305.

Wherein the communication bus 302 is used to enable connected communication between these components.

The user interface 303 may include a Display screen (Display), a Camera (Camera), and the optional user interface 303 may further include a standard wired interface, and a wireless interface.

The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.

Wherein the processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and lines to connect various portions of the overall server, perform various functions of the server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and invoking data stored in the memory 305. Alternatively, the processor 301 may be implemented in at least one hardware form of digital signal Processing (DIGITAL SIGNAL Processing, DSP), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 301 may integrate one or a combination of several of a central processor 301 (Central Processing Unit, CPU), an image processor 301 (Graphics Processing Unit, GPU), a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 301 and may be implemented by a single chip.

The Memory 305 may include a random access Memory 305 (Random Access Memory, RAM), or may include a Read-Only Memory 305 (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 305 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. Memory 305 may also optionally be at least one storage device located remotely from the aforementioned processor 301. As shown, the memory 305, which is a type of computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a method of engineering construction cost calculation.

In the electronic device shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 301 may be used to invoke an application of the method of storing engineering construction cost calculations in the memory 305, which when executed by the one or more processors 301, causes the electronic device to perform the method as in one or more of the embodiments described above.

It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all of the preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory 305. Based on this understanding, the technical solution of the present application may be embodied essentially or partly in the form of a software product, or all or part of the technical solution, which is stored in a memory 305, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned memory 305 includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.

The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.

Claims

1. A method for calculating engineering construction cost, which is applied to an engineering construction management platform, the method comprising:

2. The method of claim 1, wherein the obtaining charging file data, extracting features of the charging file data to determine sub-charging file data corresponding to each of the fee categories comprises:

3. The method of claim 2, wherein the obtaining charging file data, extracting features of the charging file data to determine sub-charging file data corresponding to each of the fee categories comprises:

4. The method of claim 1, wherein evaluating the sub-charging file data according to a preset evaluation criterion to determine a charging rule for each charging category comprises:

5. The method of claim 4, wherein selecting a charging rule under each of the fee categories according to the standard evaluation value comprises:

6. The method for calculating construction costs according to claim 4, wherein the selecting the charging rule under each of the cost categories according to the standard evaluation value further comprises:

7. The method of engineering construction cost calculation according to claim 1, further comprising:

8. The system for calculating the engineering construction cost is characterized by comprising an acquisition module, a rule module, a calculation module and a summarizing module, wherein:

9. An electronic device comprising a processor, a memory, a user interface, and a network interface, the memory for storing instructions, the user interface and the network interface each for communicating with other devices, the processor for executing instructions stored in the memory to cause the electronic device to perform the method of any of claims 1-7.

10. A computer readable storage medium storing instructions which, when executed, perform the method of any one of claims 1-7.