Power distribution network business expansion project investment review method and system, and medium

Abstract

The invention relates to a power distribution network business expansion project investment review method and system and a medium, and the method comprises the following steps: extracting the cost data of a to-be-reviewed power distribution network business expansion project, carrying out the classification according to a five-calculation data standard system, and constructing a power distribution network business expansion project cost database; an improved multiple character string mode matching algorithm is adopted, data in the power distribution network business expansion project cost database and data in a reference database are compared and analyzed, a power distribution network business expansion project investment review result is obtained, and the reference database comprises a material information sub-database, a cost index sub-database and a policy and regulation sub-database; in the improved multi-character string mode matching algorithm, the number of times of matching attempts in the character string matching process is minimized based on a skip list and a double hash technology. Compared with the prior art, intelligent standard checking can be efficiently carried out on the cost data, and the efficiency and accuracy of power distribution network business expansion project cost management are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data analysis, and in particular relates to a method, system and medium for reviewing investment in distribution network expansion projects. Background Art

[0002] Investment review for distribution network expansion projects is a crucial step in ensuring the economic viability and feasibility of distribution network projects. It is primarily based on five key data sets: estimates, preliminary estimates, budgets, settlements, and final accounts. Traditional methods for reviewing distribution network expansion investments rely primarily on industry experience or simple forecasting models, lacking scientific theoretical foundations and methodological support. This makes it difficult to ensure the accuracy of market analysis and forecasts in the context of macroeconomic fluctuations and increasingly fierce market competition. Due to issues such as missing data, fragmented data, and delayed data updates, traditional methods present the following challenges to investment review for distribution network expansion projects:

[0003] (1) Imperfect data and information sharing mechanism: The data and information sharing mechanism among various departments and institutions is still imperfect, which may lead to problems such as poor information acquisition, inaccurate data or inconsistent data standards during the investment review process of distribution network expansion projects.

[0004] (2) Delayed updating of technical standards and specifications: With the continuous advancement of technology and the rapid development of the market, the technical standards and specifications currently in use may no longer be adapted to new needs, causing the review basis to deviate from the actual situation and affecting the reliability of the review results.

[0005] (3) Imperfect investment effect evaluation mechanism: Although power supply companies have proposed corresponding comprehensive analysis business modules for post-investment evaluation, they lack a complete evaluation feedback system. The conclusions of project effect evaluations are difficult to effectively influence the formulation of subsequent investment decisions and the arrangement of project establishment, and resource utilization efficiency is difficult to ensure.

[0006] Therefore, it is necessary to design a new type of distribution network expansion project investment review scheme that can efficiently and intelligently verify cost data and improve the efficiency and accuracy of distribution network expansion project cost management. Summary of the Invention

[0007] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method, system and medium for reviewing investment in distribution network expansion projects.

[0008] The purpose of the present invention can be achieved by the following technical solutions:

[0009] The present invention provides a method for reviewing investment in a distribution network expansion project, comprising the following steps:

[0010] Extract the cost data of the distribution network expansion projects to be reviewed, classify them according to the five-cost data standard system, and build a distribution network expansion project cost database. The five-cost data standard system includes feasibility study estimate cost indicators, preliminary design estimate cost indicators, construction drawing budget cost indicators, completion settlement cost indicators, and financial final settlement cost indicators;

[0011] An improved multiple string pattern matching algorithm is used to compare and analyze the data in the distribution network expansion project cost database with the data in the reference database to obtain the investment review results of the distribution network expansion project. The reference database includes a material information sub-library, a cost index sub-library, and a policy and regulations sub-library. In the improved multiple string pattern matching algorithm, the number of matching attempts in the string matching process is minimized based on the skip table and double hashing technology.

[0012] Furthermore, optical character recognition technology is used to extract cost data.

[0013] Furthermore, the reference database is connected to an external database using a sqoop tool to update the reference database in real time.

[0014] Furthermore, through the distributed data technology of HDFS, each sub-database in the reference database is uniformly interfaced with the distribution network expansion project cost database.

[0015] Furthermore, the improved multiple string pattern matching algorithm runs based on the Mapreduce framework.

[0016] Furthermore, the specific process of comparing and analyzing the data in the distribution network expansion project cost database with the data in the reference database is as follows:

[0017] The data in the database is converted into data tables through Hive technology, and the data in the database is represented at a high level through Pig technology, and then online analytical processing is performed.

[0018] Furthermore, in the five-calculation data standard system, each indicator item includes construction project fees, installation project fees, building demolition fees, installation and demolition fees, residual material cleaning and installation fees, residual material cleaning and construction fees and other additional fees.

[0019] Furthermore, the construction project charges in each indicator item include direct costs, measures costs, indirect costs, profits, price differences in the preparation base period, price of equipment supplied by Party B, price of equipment supplied by Party A, construction costs, main material costs and equipment costs. The construction project charges in the preliminary design cost estimate indicator item, the construction drawing budget cost indicator item and the completion settlement cost indicator item also include value-added tax.

[0020] The present invention also provides a distribution network expansion project investment review system, comprising a data integration module, a data storage module and a data analysis module;

[0021] Wherein, the data integration module includes a reference database, and the reference database includes a material information sub-library, a cost index sub-library and a policy and regulation sub-library;

[0022] The data storage module is used to extract the cost data of the distribution network expansion project to be reviewed, and classify it according to the five-calculation data standard system to build a distribution network expansion project cost database. The five-calculation data standard system includes feasibility study estimate cost indicators, preliminary design estimate cost indicators, construction drawing budget cost indicators, completion settlement cost indicators and financial final settlement cost indicators;

[0023] The data analysis module is used to use an improved multiple string pattern matching algorithm to compare and analyze the data in the distribution network expansion project cost database with the data in the reference database to obtain the investment review results of the distribution network expansion project. In the improved multiple string pattern matching algorithm, the number of matching attempts in the string matching process is minimized based on the skip table and double hashing technology.

[0024] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the program implements the above method when executed by a processor.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. The present invention proposes a method for reviewing the investment of distribution network expansion projects. First, the cost data of the distribution network expansion projects to be reviewed are extracted and classified according to the five-calculation data standard system to construct a distribution network expansion project cost database. Then, an improved multiple string pattern matching algorithm is used to compare and analyze the data in the distribution network expansion project cost database with the data in the reference database to obtain the investment review results of the distribution network expansion project. In the improved multiple string pattern matching algorithm, the number of matching attempts in the string matching process is minimized based on the skip table and double hashing technology, which can accelerate the string pattern matching. Through the above method, the cost data can be efficiently and intelligently standardized, and the corresponding data analysis report can be fed back to assist in improving the efficiency and accuracy of the distribution network expansion project cost management, ensuring the cost control and investment benefit maximization of the project.

[0027] 2. The present invention classifies cost data according to the five-calculation data standard system, which includes feasibility study estimate cost indicators, preliminary design estimate cost indicators, construction drawing budget cost indicators, completion settlement cost indicators and financial final settlement cost indicators. It can improve the integrity and accuracy of basic data, thereby ensuring the quality of cost analysis sample data.

[0028] 3. The present invention uses the sqoop tool to connect the reference database with the external database, thereby updating the reference database in real time, which can further improve the accuracy and reliability of the investment review results of the distribution network expansion project. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a flow chart of the method of the present invention;

[0030] Figure 2 Schematic diagram of the structure of the system of the present invention. DETAILED DESCRIPTION

[0031] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0032] Example 1

[0033] This embodiment provides a method for reviewing investment in distribution network expansion projects. Figure 1 As shown, the following steps are included:

[0034] S1. Extract the cost data of the distribution network expansion projects to be reviewed, classify them according to the five-calculation data standard system, and build a distribution network expansion project cost database.

[0035] This embodiment uses optical character recognition technology (OCR) to extract cost data from paper documents (project books, contracts, etc.), converting printed text into a computer-readable text format, which is convenient for subsequent serial collection of various types of project data. The five-calculation data standard system includes feasibility study estimate cost indicators, preliminary design estimate cost indicators, construction drawing budget cost indicators, completion settlement cost indicators and financial final settlement cost indicators. Through the classification of the five-calculation data standard system, the cost data of each detailed item can be calculated according to the statistical dimensions and algorithm research of construction, installation, demolition and other costs under the management methods and requirements related to the investment in the distribution network industry expansion project, and the corresponding detailed item costs can be calculated for subsequent data comparison projects. The specific indicators of the five-calculation data standard system are shown in Table 1.

[0036] Table 1 Five-calculation data standard system

[0037]

[0038]

[0039]

[0040]

[0041] S2. Use an improved multiple string pattern matching algorithm to compare and analyze the data in the distribution network expansion project cost database with the data in the reference database to obtain the investment review results of the distribution network expansion project.

[0042] The reference database includes a materials information sub-library, a cost index sub-library, and a policy and regulation sub-library. Using HDFS's distributed data technology, each sub-library in the reference database is connected to the distribution network expansion project cost database through a unified interface. In a preferred embodiment, the Sqoop tool is used to connect the reference database to an external database for real-time updates.

[0043] The equipment information extracted from the feasibility study, preliminary design, construction drawings, completion settlement and final accounting reports, and cost books of distribution network expansion projects has the characteristics of a large number of equipment description specifications and models, but the equipment types are unified. A multiple string pattern matching algorithm can be used to make judgments by searching for text keywords in the files. The efficiency of the above process mainly depends on the performance of the multiple string pattern matching method. In order to use the extracted equipment information as a unified reference indicator and to efficiently match and compare it with the equipment information of the pending project, this embodiment improves the multiple string pattern matching algorithm. In the improved multiple string pattern matching algorithm, the number of matching attempts in the string matching process is minimized based on skip tables and double hashing technology, thereby accelerating string pattern matching. The improved algorithm has lower time and space complexity than the classic multi-pattern string matching algorithm, and therefore has higher computational efficiency.

[0044] The improved multiple string pattern matching algorithm runs on the MapReduce framework. Its specific data processing process is as follows: Hive technology is used to convert database data into tables, providing complete SQL data query capabilities. Pig technology is used to create a high-level abstract representation of the database data, which is then used for online analytical processing (OLAP).

[0045] If the above method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0046] Example 2

[0047] This embodiment provides a system for implementing the method described in embodiment 1. Figure 2 As shown, it includes data integration module, data storage module, data analysis module and data display module. The specific composition and functions of each module are as follows:

[0048] (1) Data integration module: Its main function is to provide basic data and perform classification processing to form a reference database containing a material information sub-library, a cost index sub-library, and a policy and regulation sub-library. Mapreduce is used to perform data analysis to distinguish between data that can be directly stored and data that needs to be converted and processed. At the same time, the sqoop tool is used to realize data exchange with external databases.

[0049] (2) Data storage module: This module is used to extract the cost data of the distribution network expansion projects to be reviewed (data structures include structured data, unstructured data, semi-structured data, etc., and data formats include text, images, etc.), classify them according to the five-calculation data standard system, and build a distribution network expansion project cost database. This module uses components such as HDFS, HCatalog (mainly responsible for data table and storage management), and Hbase (mainly responsible for unstructured big data storage) in the Hadoop technology system. Through HDFS's distributed data technology, it unifies the interface processing of storage devices in different regions and provides unified data for the data processing and analysis module.

[0050] (3) Data analysis module: This module mainly uses Hadoop technology system Mapreduce (mainly responsible for data parallel processing), Hive (data warehouse tool) and Pig and other technologies, and adopts an improved multiple string pattern matching algorithm to compare and analyze the data in the distribution network expansion project cost database with the data in the reference database to obtain the investment review results of the distribution network expansion project.

[0051] (4) Data display module: Display and output the investment review results of distribution network expansion projects on PC and mobile terminals through the web server.

[0052] The above description of the embodiments is intended to facilitate understanding and use of the invention by those skilled in the art. It will be apparent that those skilled in the art can readily make various modifications to these embodiments and apply the general principles described herein to other embodiments without requiring inventive effort. Therefore, the present invention is not limited to the above-described embodiments. Improvements and modifications made by those skilled in the art based on the disclosure of the present invention, without departing from the scope of the present invention, should be within the scope of protection of the present invention.

Claims

1. A method for reviewing investment in a distribution network expansion project, characterized in that: The following steps are involved: Extract the cost data of the distribution network expansion projects to be reviewed, classify them according to the five-cost data standard system, and build a distribution network expansion project cost database. The five-cost data standard system includes feasibility study estimate cost indicators, preliminary design estimate cost indicators, construction drawing budget cost indicators, completion settlement cost indicators, and financial final settlement cost indicators; An improved multiple string pattern matching algorithm is used to compare and analyze the data in the distribution network expansion project cost database with the data in the reference database to obtain the investment review results of the distribution network expansion project. The reference database includes a material information sub-library, a cost index sub-library, and a policy and regulations sub-library. In the improved multiple string pattern matching algorithm, the number of matching attempts in the string matching process is minimized based on the skip table and double hashing technology.

2. A method for reviewing investment in a distribution network expansion project according to claim 1, characterized in that: Optical character recognition technology is used to extract cost data.

3. A method for reviewing investment in a distribution network expansion project according to claim 1, characterized in that: The reference database is connected to an external database using the sqoop tool to update the reference database in real time.

4. A method for reviewing investment in a distribution network expansion project according to claim 1, characterized in that: Through the distributed data technology of HDFS, each sub-database in the reference database is unified with the distribution network expansion project cost database for interface processing.

5. A method for reviewing investment in a distribution network expansion project according to claim 1, characterized in that: The improved multiple string pattern matching algorithm is run based on the Mapreduce framework.

6. A method for reviewing investment in a distribution network expansion project according to claim 5, characterized in that: The specific process of comparing and analyzing the data in the distribution network expansion project cost database with the data in the reference database is as follows: The data in the database is converted into data tables through Hive technology, and the data in the database is represented at a high level through Pig technology, and then online analytical processing is performed.

7. A method for reviewing investment in a distribution network expansion project according to claim 1, characterized in that: In the five-calculation data standard system, each indicator item includes construction project fees, installation project fees, building demolition fees, installation and demolition fees, residual material cleaning and installation fees, residual material cleaning and construction fees and other additional fees.

8. A method for reviewing investment in a distribution network expansion project according to claim 7, characterized in that: The construction project charges in each indicator item include direct costs, measures costs, indirect costs, profits, price differences in the preparation base period, price of equipment supplied by Party B, price of equipment supplied by Party A, construction costs, main material costs and equipment costs. The construction project charges in the preliminary design estimate cost indicator item, the construction drawing budget cost indicator item and the completion settlement cost indicator item also include value-added tax.

9. A distribution network expansion project investment review system, characterized in that: Including data integration module, data storage module and data analysis module; Wherein, the data integration module includes a reference database, and the reference database includes a material information sub-library, a cost index sub-library and a policy and regulation sub-library; The data storage module is used to extract the cost data of the distribution network expansion project to be reviewed, and classify it according to the five-calculation data standard system to build a distribution network expansion project cost database. The five-calculation data standard system includes feasibility study estimate cost indicators, preliminary design estimate cost indicators, construction drawing budget cost indicators, completion settlement cost indicators and financial final settlement cost indicators; The data analysis module is used to use an improved multiple string pattern matching algorithm to compare and analyze the data in the distribution network expansion project cost database with the data in the reference database to obtain the investment review results of the distribution network expansion project. In the improved multiple string pattern matching algorithm, the number of matching attempts in the string matching process is minimized based on the skip table and double hashing technology.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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