Intelligent bid evaluation score table configuration management system

Abstract

The invention provides an intelligent bid evaluation score table configuration management system, and belongs to the technical field of information, and the system comprises a construction module which determines the application demands of a bid evaluation score table, obtains the basic information of the bid evaluation score table and associated evaluation indexes, and constructs an evaluation index library; the definition module is used for acquiring related information of the bid invitation project and defining a scoring rule based on a scoring standard; the acquisition module is used for acquiring automatic adjustment scoring strategies of different scenes based on a machine learning technology according to an evaluation index library and scoring rules, and intelligently scoring a target proposal; and the display module is used for analyzing the intelligent scoring process and result, obtaining scoring data and displaying the scoring data through a visual tool. The problems that traditional bid evaluation work is time-consuming and labor-consuming and is easily influenced by human factors, meanwhile, scoring table design differences under different items and different rules are large, bid evaluation personnel need to spend a lot of time to learn new scoring rules each time, and the efficiency of the bid evaluation process is low are solved.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to an intelligent bidding evaluation score sheet configuration management system. Background Art

[0002] With the development of my country's economy and the increasing number of bidding projects, the efficiency and safety of bid evaluation work have received more and more attention.

[0003] Traditional bid evaluation work mainly relies on manual paper scoring sheets, which is not only time-consuming and labor-intensive, but also easily affected by human factors. At the same time, the scoring sheet designs for different projects and different rules vary greatly. Evaluators need to spend a lot of time to familiarize themselves with and learn new scoring rules during each bid evaluation process, which makes scoring errors more likely to occur, resulting in inefficient bid evaluation process.

[0004] Therefore, the present invention proposes an intelligent bidding evaluation score sheet configuration management system. Summary of the invention

[0005] The present invention provides an intelligent bid evaluation score sheet configuration management system to solve the problem that the traditional bid evaluation work in the prior art is not only time-consuming and labor-intensive, but also easily affected by human factors. At the same time, the design of score sheets under different projects and different rules is quite different. The evaluators need to spend a lot of time to familiarize themselves with and learn new scoring rules during each bid evaluation process, which makes it easier to make scoring errors, resulting in the defect of low efficiency of the bid evaluation process.

[0006] In one aspect, the present invention provides an intelligent bidding evaluation score sheet configuration management system, comprising:

[0007] Construction module: determine the application requirements of the bid evaluation score sheet, obtain the basic information of the bid evaluation score sheet and the associated evaluation indicators according to the application requirements, and build an evaluation indicator library;

[0008] Definition module: obtain relevant information of the bidding project, and define scoring rules based on the scoring criteria according to the relevant information;

[0009] Acquisition module: Acquires automatic adjustment scoring strategies for different scenarios based on the evaluation index library and scoring rules based on machine learning technology, and performs intelligent scoring on target proposals;

[0010] Display module: Analyze the intelligent scoring process and results, obtain scoring data, generate visual reports, and display them through visualization tools.

[0011] According to the present invention, an intelligent bidding evaluation score sheet configuration management system is provided, and a building module is provided, including:

[0012] A first acquisition unit: acquires the evaluation purpose and evaluation object of the bid evaluation score sheet, and determines the application scenario of the bid evaluation score sheet according to the evaluation purpose and evaluation object;

[0013] A first determining unit: determining application requirements of the bid evaluation score sheet according to the application scenario;

[0014] Reading unit: reading basic information of the relevant scoring table from the database based on the API interface according to the application requirements;

[0015] Parsing unit: Determine the classification and attributes of the rating information by parsing the basic information and extracting the keywords, data types, and descriptions in the rating table;

[0016] The second acquisition unit is configured to acquire corresponding associated evaluation indicators according to the classification and attributes of the scoring information.

[0017] According to the present invention, an intelligent bidding evaluation score sheet configuration management system is provided, and a definition module is provided, including:

[0018] The third acquisition unit: searches for the corresponding bidding announcement on the bidding website using the relevant keywords of the bidding project, and acquires the relevant information of the bidding project according to the bidding announcement;

[0019] The second determination unit: determines the characteristics and needs of the bidding project according to the relevant information, and determines the corresponding scoring criteria;

[0020] A third determining unit: determining the weight of each evaluation item in the scoring process according to the scoring criteria;

[0021] Definition Unit: Define scoring rules based on industry standards and best practices according to the weight of each evaluation item.

[0022] According to an intelligent bidding evaluation score sheet configuration management system provided by the present invention, an acquisition module includes:

[0023] Preprocessing unit: obtain scene images, corresponding evaluation indicators and existing scoring labels under different scenes according to the third-party platform, and preprocess the evaluation indicator data and existing scoring label data;

[0024] Partitioning unit: divides the preprocessed data into feature columns and target columns;

[0025] Fourth acquisition unit: acquiring useful features based on the feature column and the target column according to the evaluation index library and the scoring rules, and performing model training through a convolutional neural network;

[0026] Evaluation unit: evaluates the precision and recall of the trained model to obtain the generalization performance of the model;

[0027] Intelligent scoring unit: Deploy the trained model to the actual scenario, obtain the automatic adjustment scoring strategy for different scenarios in real time, and perform intelligent scoring on the target proposals.

[0028] According to the present invention, an intelligent bidding evaluation score sheet configuration management system and a display module are provided, including:

[0029] The fifth acquisition unit: obtains the intelligent scoring process and results according to the scoring log, and obtains the corresponding data analysis tools according to the analysis purpose;

[0030] Import unit: import the intelligent scoring process and results into the data analysis tool, perform data analysis in different dimensions, and obtain scoring data based on the analysis results;

[0031] Creation unit: generating a visualization report from the scoring data, obtaining the purpose and audience of the report, selecting a corresponding visualization tool, and creating visualization elements;

[0032] A display unit displays the visualization report based on visualization elements.

[0033] An intelligent bidding evaluation score sheet configuration management system provided by the present invention also includes:

[0034] Verification module: authenticates the identity of users who access the intelligent bid evaluation score sheet configuration management system, and protects the privacy and data security of users through a security authentication mechanism;

[0035] Authorization module: authorizes authenticated users and assigns role- and task-based permission levels;

[0036] Restriction module: restricts user access to specific resources and functions based on access control lists according to the permission levels;

[0037] Monitoring and Auditing Module: Real-time monitoring and auditing of access activities and behaviors, and identification of security vulnerabilities and abuse behaviors.

[0038] According to the present invention, an intelligent bidding evaluation score sheet configuration management system, an authorization module, includes:

[0039] Fourth determination unit: obtaining the position information of the user who has passed the identity authentication, and determining the position level of the user according to the position information;

[0040] Fifth determination unit: Determine the basic authority and highest authority of the user based on the position level and position structure;

[0041] The sixth determination unit: determines the user's operable authority scope according to the user's basic authority and highest authority;

[0042] Authorization unit: Authorize users based on the scope of their operational permissions.

[0043] According to an intelligent bidding evaluation score sheet configuration management system provided by the present invention, the second determination unit includes:

[0044] The first determination subunit: determine the project plan of the bidding project based on relevant information, and determine the project management parameters and project construction parameters based on the project plan;

[0045] The second determination subunit: determines the project process based on the project management parameters and the project construction parameters, and determines the construction label according to the project process;

[0046] A first acquisition subunit: acquiring construction data from a preset database according to the construction label, and determining a plurality of engineering factors according to the construction data;

[0047] The third determination subunit: obtaining the global non-transferable construction characteristics and local transferable construction characteristics of each engineering factor, and determining the project characteristics and project needs of the bidding project based on the global non-transferable construction characteristics and local transferable construction characteristics;

[0048] The second acquisition subunit: determines the project quality supervision rules according to the project characteristics and project needs, and obtains the supervision indicators corresponding to the project quality supervision rules;

[0049] Extension subunit: obtain multiple scoring project vectors according to the supervision indicators, and expand the project vector to be evaluated into an augmented vector;

[0050] Solving subunit: Establish a local weighted linear regression model based on the augmented vector, and use the stochastic gradient descent algorithm to solve the local weighted linear regression model to obtain the optimized solution;

[0051] The fourth determination subunit: obtains the scoring weight of each scoring project vector according to the optimization solution, and determines the scoring criteria based on the scoring weight of each project score and the project application attributes.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] By building an evaluation index library through the evaluation indicators obtained from application requirements, and combining the scoring rules with machine learning technology to obtain scoring strategies for different scenarios, and intelligently scoring the target proposals, it can save time and effort, and is not easily affected by human factors. At the same time, the scoring strategy can be changed according to different scenarios. There is no need to spend a lot of time to familiarize and learn new scoring rules in each bid evaluation process, and there will be no scoring errors and injustices, which improves the bid evaluation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 It is a structural diagram of an intelligent bidding evaluation score sheet configuration management system provided by an embodiment of the present invention;

[0056] Figure 2 It is a schematic diagram of the structure of the building module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Embodiment 1:

[0059] An intelligent bidding evaluation score sheet configuration management system provided by an embodiment of the present invention is Figure 1 As shown, the system mainly includes the following modules:

[0060] Construction module: determine the application requirements of the bid evaluation score sheet, obtain the basic information of the bid evaluation score sheet and the associated evaluation indicators according to the application requirements, and build an evaluation indicator library;

[0061] Definition module: obtain relevant information of the bidding project, and define scoring rules based on the scoring criteria according to the relevant information;

[0062] Acquisition module: Acquires automatic adjustment scoring strategies for different scenarios based on the evaluation index library and scoring rules based on machine learning technology, and performs intelligent scoring on target proposals;

[0063] Display module: Analyze the intelligent scoring process and results, obtain scoring data, generate visual reports, and display them through visualization tools.

[0064] In this embodiment, the bid evaluation score sheet is a tool for scoring and evaluating bid or tender documents, which can help the purchaser or the evaluation committee to systematically compare different bid or tender documents and determine which document best meets the procurement requirements.

[0065] In this embodiment, the application requirements of the bid evaluation score sheet refer to the specific requirements of the score sheet in actual application, such as ensuring a fair and transparent evaluation process and providing clear evaluation standards and guidelines.

[0066] In this embodiment, the basic information of the bid evaluation score sheet includes: table name and template structure.

[0067] In this embodiment, the scoring criteria refers to what each project is scored on, for example: Project implementation capability: Evaluate the bidder's project implementation capability, such as project experience, team organization capability, and management methods. It can be evaluated from aspects such as project implementation cases, team composition, and project management methods. A percentage system can be used, where 0-5 points represent no advantage and 6-10 points represent a clear advantage.

[0068] In this embodiment, the evaluation index refers to the standard used to measure the technical, economic, service and other capabilities of the bidder or the bidding document during the procurement process, such as:

[0069] Technical capabilities: including the feasibility, innovation, efficiency, maturity and other aspects of the technical solution.

[0070] Service quality: including service quality, response speed, customer satisfaction and other aspects.

[0071] Price: includes fixed price, total price, unit price, discount and other aspects.

[0072] Delivery time: includes delivery date, delivery time, transportation time and other aspects.

[0073] Company reputation: including the company's history, scale, performance, reputation and other aspects.

[0074] In this embodiment, the evaluation index library is used to store and manage evaluation indexes of various projects, including information such as their names, definitions, weights, and calculation formulas.

[0075] In this embodiment, the relevant information of the bidding project includes:

[0076] Project Overview: includes project name, project number, project description, and project budget.

[0077] Procurement scope: includes the scope of items or services purchased, such as design, construction, and equipment.

[0078] Bidder qualification requirements: including the bidder's qualifications, such as registered capital, experience, and qualification level.

[0079] In this embodiment, the scoring rules refer to the scoring method and calculation method used in the bidding process, which are used to evaluate the technical performance, price, and service of the bidder or the bidding product, such as:

[0080] Lowest price method: Sort the bids in order from high to low, and select the bidder with the lowest bid as the successful bidder.

[0081] Comprehensive scoring method: The weighted average of the technical score, price score and business score are ranked in descending order, and the bidder with the highest score is selected as the successful bidder. Among them, the technical score accounts for the highest proportion, generally accounting for 40%-60% of the total score, the price score accounts for the second highest proportion, generally accounting for 20%-30%, and the business score accounts for the lowest proportion, generally accounting for 10%-20%.

[0082] Best match method: Score the bidder or the bidding product based on the degree of match with the technical specifications, performance indicators, delivery time and other requirements listed in the bidding documents, and select the bidder with the highest best match as the successful bidder.

[0083] In this embodiment, the scoring strategy refers to the method and decision-making process by which the evaluators score each bidder or bidding product in terms of technical performance, price, service, etc. according to the scoring rules during the bid evaluation process.

[0084] In this embodiment, the scoring data refers to the data used in the bid evaluation process, including specific indicator values ​​or descriptive information of each bidder or bidding product in terms of technical performance, price, service, etc.

[0085] In this embodiment, the visual report is a form of report that presents complex statistical data and analysis results in a graphical manner.

[0086] In this embodiment, the visualization tools include: bar charts, pie charts, topology charts, and heat maps.

[0087] The beneficial effects of the above technical solution are: building an evaluation index library through evaluation indicators obtained through application requirements, and obtaining scoring strategies for different scenarios based on machine learning technology in combination with scoring rules, and intelligently scoring target proposals, which can save time and effort, and is not easily affected by human factors. At the same time, the scoring strategy can be changed according to different scenarios, and there is no need to spend a lot of time to familiarize and learn new scoring rules in each bid evaluation process, and there will be no scoring errors and injustices, thereby improving the bid evaluation efficiency.

[0088] Embodiment 2:

[0089] Based on Example 1, the embodiment of the present invention constructs a module, including:

[0090] A first acquisition unit: acquires the evaluation purpose and evaluation object of the bid evaluation score sheet, and determines the application scenario of the bid evaluation score sheet according to the evaluation purpose and evaluation object;

[0091] A first determining unit: determining application requirements of the bid evaluation score sheet according to the application scenario;

[0092] Reading unit: reading basic information of the relevant scoring table from the database based on the API interface according to the application requirements;

[0093] Parsing unit: Determine the classification and attributes of the rating information by parsing the basic information and extracting the keywords, data types, and descriptions in the rating table;

[0094] The second acquisition unit is configured to acquire corresponding associated evaluation indicators according to the classification and attributes of the scoring information.

[0095] In this embodiment, the evaluation purpose of the bid evaluation score sheet may be to determine which bidders have reached the specified minimum standard and to evaluate the capability of each bidder.

[0096] In this embodiment, the evaluation object is usually an organization that is eligible to participate in a project or service in the bidding document, or an individual or company that has submitted a competitive application.

[0097] In this embodiment, the application scenarios of the bid evaluation score sheet may be: government procurement, engineering contracting, architectural design competition, and academic research funding.

[0098] In this embodiment, the API interface is an application programming interface that allows communication and data exchange between different software programs.

[0099] In this embodiment, the scoring database is a distributed database system specifically used to store and manage bid evaluation data. The scoring database can store various scoring information in the bid evaluation form.

[0100] In this embodiment, the scoring criteria are classified into: technical indicators, business indicators, interpersonal relationship indicators, and document indicators.

[0101] In this embodiment, the attributes of the scoring criteria are: comparability, objectivity, quantifiability and quantification.

[0102] The beneficial effects of the above technical solution are: determining the application requirements of the bid evaluation score sheet according to the evaluation purpose and evaluation object of the bid evaluation score sheet, reading the basic information of the relevant score sheet, obtaining the key content, and determining the corresponding evaluation indicators. The evaluation indicators of various projects can be unified to ensure that the evaluation standards of each project are consistent, avoiding errors caused by inconsistent evaluation standards, and at the same time, reducing standard differences caused by manually formulated evaluation standards.

[0103] Embodiment 3:

[0104] Based on Example 2, the embodiment of the present invention defines a module, including:

[0105] The third acquisition unit: searches for the corresponding bidding announcement on the bidding website using the relevant keywords of the bidding project, and acquires the relevant information of the bidding project according to the bidding announcement;

[0106] The second determination unit: determines the characteristics and needs of the bidding project according to the relevant information, and determines the corresponding scoring criteria;

[0107] A third determining unit: determining the weight of each evaluation item in the scoring process according to the scoring criteria;

[0108] Definition Unit: Define scoring rules based on industry standards and best practices according to the weight of each evaluation item.

[0109] In this embodiment, keywords related to the bidding project may be: bidding documents, bidding deadline, bid opening time, and public announcement of successful bidders.

[0110] In this embodiment, the tender notice is a notice for publicly soliciting potential bidders, and is used to invite bidders to participate in the bidding for a specific project.

[0111] In this embodiment, the relevant information of the bidding project includes:

[0112] Project Overview: includes project name, project number, project description, and project budget.

[0113] Procurement scope: includes the scope of items or services purchased, such as design, construction, and equipment.

[0114] Bidder qualification requirements: including the bidder's qualifications, such as registered capital, experience, and qualification level.

[0115] In this embodiment, the weight of the evaluation item refers to the importance of each evaluation item.

[0116] The beneficial effects of the above technical solution are: formulating corresponding scoring standards based on the characteristics and needs of the bidding project, determining the weight of each evaluation item, and defining scoring rules based on industry standards and best practices, which can ensure the reliability and fairness of the scoring rules and improve the accuracy and consistency of the evaluation results.

[0117] Embodiment 4:

[0118] Based on Example 3, the acquisition module of the embodiment of the present invention includes:

[0119] Preprocessing unit: obtain scene images, corresponding evaluation indicators and existing scoring labels under different scenes according to the third-party platform, and preprocess the evaluation indicator data and existing scoring label data;

[0120] Partitioning unit: divides the preprocessed data into feature columns and target columns;

[0121] Fourth acquisition unit: acquiring useful features based on the feature column and the target column according to the evaluation index library and the scoring rules, and performing model training through a convolutional neural network;

[0122] Evaluation unit: evaluates the precision and recall of the trained model to obtain the generalization performance of the model;

[0123] Intelligent scoring unit: Deploy the trained model to the actual scenario, obtain the automatic adjustment scoring strategy for different scenarios in real time, and perform intelligent scoring on the target proposals.

[0124] In this embodiment, the rating labels may be: excellent, good, or poor.

[0125] In this embodiment, the feature column includes: project information and project description.

[0126] In this embodiment, the target column includes: score.

[0127] In this embodiment, the useful features refer to the features of the evaluation index, such as the specific range of the index evaluation value.

[0128] In this embodiment, the generalization performance of the model refers to the performance of the model on new data, that is, the model's predictive ability for unseen data.

[0129] The beneficial effect of the above technical solution is: by preprocessing and dividing the scene pictures in different scenarios, the corresponding evaluation indicators and the data of the existing scoring labels, useful features are obtained to train the model, which can prevent the model from overfitting, ensure the performance of the model, improve the adaptability of the model to different evaluation scenarios, and ensure the accuracy of the evaluation results.

[0130] Embodiment 5:

[0131] Based on Example 4, the display module of the embodiment of the present invention includes:

[0132] The fifth acquisition unit: obtains the intelligent scoring process and results according to the scoring log, and obtains the corresponding data analysis tools according to the analysis purpose;

[0133] Import unit: import the intelligent scoring process and results into the data analysis tool, perform data analysis in different dimensions, and obtain scoring data based on the analysis results;

[0134] Creation unit: generating a visualization report from the scoring data, obtaining the purpose and audience of the report, selecting a corresponding visualization tool, and creating visualization elements;

[0135] A display unit displays the visualization report based on visualization elements.

[0136] In this embodiment, the scoring log is a tool for recording and tracking the process and results of scoring the project, including: the specific process and results, as well as the source, time, and rater of these scores.

[0137] In this embodiment, the data analysis tools may be: SQL and database management tools, machine learning tools, and big data platforms.

[0138] In this embodiment, data analysis of different dimensions refers to analyzing different aspects and dimensions of data, which may include time dimension, space dimension, category dimension, and attribute dimension.

[0139] In this embodiment, the visualization element refers to an image, a graphic, or a text element used in a visualization display. Different visualization elements may have different properties such as color, shape, and size.

[0140] The beneficial effects of the above technical solution are: importing the intelligent scoring process and results into the data analysis tool and performing data analysis in different dimensions, obtaining scoring data, and generating visual reports for display, which can better understand the scoring data and identify key data, and ensure the transparency of the scoring process and results.

[0141] Embodiment 6:

[0142] Based on Example 5, the embodiment of the present invention further includes:

[0143] Verification module: authenticates the identity of users who access the intelligent bid evaluation score sheet configuration management system, and protects the privacy and data security of users through a security authentication mechanism;

[0144] Authorization module: authorizes authenticated users and assigns role- and task-based permission levels;

[0145] Restriction module: restricts user access to specific resources and functions based on access control lists according to the permission levels;

[0146] Monitoring and Auditing Module: Real-time monitoring and auditing of access activities and behaviors, and identification of security vulnerabilities and abuse behaviors.

[0147] In this embodiment, the security authentication mechanism is a mechanism for ensuring the security of a system or application program, which can prevent unauthorized access, operation, and destruction.

[0148] In this embodiment, the roles may be: administrator, editor, viewer.

[0149] In this embodiment, the tasks may be: scoring, reviewing.

[0150] In this embodiment, the permission level refers to the control level of access rights to a computer system, network resources, or other systems. The permission level determines which files a user can access, which programs can be run, which settings can be changed, and which objects can be created.

[0151] In this embodiment, the access control list is a method for describing a group of objects (usually files or directories) and their access permissions, defining which users and groups can access the objects and the operations they can perform when accessing the objects.

[0152] The beneficial effects of the above technical solution are: identity authentication and authorization of users who access the intelligent bid evaluation score sheet configuration management system, and restriction of users' access to specific resources and functions, real-time monitoring of users' activities, timely identification of users' illegal operations and risky operations, protection of system security, and improvement of system reliability.

[0153] Embodiment 7:

[0154] Based on Example 6, the authorization module of this embodiment of the present invention includes:

[0155] Fourth determination unit: obtaining the position information of the user who has passed the identity authentication, and determining the position level of the user according to the position information;

[0156] Fifth determination unit: Determine the basic authority and highest authority of the user based on the position level and position structure;

[0157] The sixth determination unit: determines the user's operable authority scope according to the user's basic authority and highest authority;

[0158] Authorization unit: Authorize users based on the scope of their operational permissions.

[0159] In this embodiment, the user's position information includes: basic information, work unit, and work experience.

[0160] In this embodiment, the position level refers to the position grade of the user in the company, such as manager, engineer, sales representative, etc.

[0161] In this embodiment, the position structure refers to the hierarchical relationship and division of responsibilities between positions in an enterprise or organization.

[0162] In this embodiment, the basic permissions of a user refer to the minimum set of permissions that the user can access and execute when using software or a system, such as viewing permissions.

[0163] In this embodiment, the highest authority of a user refers to the highest authority level that the user has when using software or a system, allowing the user to perform more advanced operations, such as editing authority and management authority.

[0164] The beneficial effects of the above technical solution are: determining the user's basic authority and highest authority according to the user's position level, thereby determining the user's operational authority range and authorizing the user, which can avoid data leakage or malicious tampering and improve the reliability and security of the system.

[0165] Embodiment 8:

[0166] Based on Embodiment 7, the second determining unit in the embodiment of the present invention includes:

[0167] The first determination subunit: determine the project plan of the bidding project based on relevant information, and determine the project management parameters and project construction parameters based on the project plan;

[0168] The second determination subunit: determines the project process based on the project management parameters and the project construction parameters, and determines the construction label according to the project process;

[0169] A first acquisition subunit: acquiring construction data from a preset database according to the construction label, and determining a plurality of engineering factors according to the construction data;

[0170] The third determination subunit: obtaining the global non-transferable construction characteristics and local transferable construction characteristics of each engineering factor, and determining the project characteristics and project needs of the bidding project based on the global non-transferable construction characteristics and local transferable construction characteristics;

[0171] The second acquisition subunit: determines the project quality supervision rules according to the project characteristics and project needs, and obtains the supervision indicators corresponding to the project quality supervision rules;

[0172] Extension subunit: obtain multiple scoring project vectors according to the supervision indicators, and expand the project vector to be evaluated into an augmented vector;

[0173] Solving subunit: Establish a local weighted linear regression model based on the augmented vector, and use the stochastic gradient descent algorithm to solve the local weighted linear regression model to obtain the optimized solution;

[0174] The fourth determination subunit: obtains the scoring weight of each scoring project vector according to the optimization solution, and determines the scoring criteria based on the scoring weight of each project score and the project application attributes.

[0175] In this embodiment, the project plan of the bidding project includes: project overview, task allocation, resource management, progress tracking, and risk management.

[0176] In this embodiment, the project management parameters are various factors that need to be considered in the project management process, including scope, progress, cost, quality, and risk.

[0177] In this embodiment, the project construction parameters are various factors that need to be considered during the construction process, including personnel, materials, equipment, and time.

[0178] In this embodiment, the project process refers to dividing the entire project into multiple operational parts and managing and controlling them in an orderly manner, including: task name, responsible person, start time, end time, duration, etc.

[0179] In this embodiment, the construction label is a tool for identifying and managing various materials, equipment, tools, etc. at the construction site, including: item name or description, quantity or weight, production date or purchase date, storage location or usage location.

[0180] In this embodiment, construction data refers to various types of information generated during the construction process, such as project information, engineering progress, material information, and quality management.

[0181] In this embodiment, the multiple engineering factors refer to multiple factors that need to be considered and managed when carrying out an engineering project, such as: time factors, cost factors, technical factors, personnel factors, and environmental factors.

[0182] In this embodiment, the global non-transfer construction features refer to some common features in the process of project management. These features are not affected by specific construction stages or processes, but run through the entire project, such as:

[0183] Time factor: One of the characteristics of global non-transfer construction is the pressure of construction period, that is, the progress of construction period needs to be considered and controlled throughout the entire project to ensure that the project can proceed as planned.

[0184] Cost factor: The second feature of global non-transfer construction is cost control, that is, effective cost control is required throughout the entire project to achieve the goal of minimizing costs.

[0185] In this embodiment, the locally transferable construction features refer to the fact that certain specific construction features differ between different stages or processes during the project management process and can be improved through adjustment and management, such as:

[0186] Time factor: One of the characteristics of locally transferable construction is the time node, that is, different time nodes can be set as the criteria for evaluation and assessment in different construction stages.

[0187] Cost factor: The second feature of partially transferable construction is cost allocation, that is, the cost budget can be reallocated and adjusted between different construction stages or processes according to actual conditions.

[0188] Technical factors: The third feature of partially transferable construction is technical difficulties, that is, different technical difficulties will be encountered in different construction stages or processes, which need to be studied and solved in a targeted manner.

[0189] In this embodiment, the project quality supervision rules are a set of criteria and guidelines that guide the quality control and supervision work in the project management process to ensure that the project or product meets the expected quality requirements.

[0190] In this embodiment, the supervision index refers to the key index that needs to be paid attention to in the project quality management process, which is used to evaluate the quality status of the project, such as: defect rate, quality improvement, and process compliance.

[0191] In this embodiment, the scoring item vector is a tool for performing quantitative and qualitative analysis on each scoring item in the bidding document.

[0192] In this embodiment, the augmented vector represents each characteristic of the project in a numerical manner to facilitate quantitative comparison and scoring.

[0193] In this embodiment, stochastic gradient descent is an optimization algorithm in machine learning, which is used to solve the minimum value of the objective function. It is an iterative algorithm. In each iteration, the point is updated according to the gradient direction of the current point to converge to the minimum value of the objective function.

[0194] In this embodiment, the declared attributes refer to the description of the nature, characteristics, advantages, etc. of the project.

[0195] The beneficial effects of the above technical solution are: determining the project characteristics and project needs of the bidding project based on the global non-transferable construction characteristics and local transferable construction characteristics of each engineering factor can more accurately grasp the key needs of the bidding project and improve the success rate of project applications. At the same time, determining the scoring criteria based on the scoring weight of each project score and the project application attributes can ensure the fairness of the scoring criteria and avoid unfairness caused by subjective judgment.

[0196] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0197] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent bidding evaluation score sheet configuration management system, characterized in that: include: Construction module: determine the application requirements of the bid evaluation score sheet, obtain the basic information of the bid evaluation score sheet and the associated evaluation indicators according to the application requirements, and build an evaluation indicator library; Definition module: obtain relevant information of the bidding project, and define scoring rules based on the scoring criteria according to the relevant information; Acquisition module: obtains automatic adjustment scoring strategies for different scenarios based on the evaluation index library and scoring rules based on machine learning technology, and performs intelligent scoring on target proposals; Display module: Analyze the intelligent scoring process and results, obtain scoring data, generate visual reports, and display them through visualization tools.

2. The intelligent bidding evaluation score sheet configuration management system according to claim 1 is characterized in that: Building blocks, including: A first acquisition unit: acquires the evaluation purpose and evaluation object of the bid evaluation score sheet, and determines the application scenario of the bid evaluation score sheet according to the evaluation purpose and evaluation object; A first determining unit: determining application requirements of the bid evaluation score sheet according to the application scenario; Reading unit: reading basic information of the relevant scoring table from the database based on the API interface according to the application requirements; Parsing unit: Determine the classification and attributes of the rating information by parsing the basic information and extracting the keywords, data types, and descriptions in the rating table; The second acquisition unit is configured to acquire corresponding associated evaluation indicators according to the classification and attributes of the scoring information.

3. The intelligent bidding evaluation score sheet configuration management system according to claim 1 is characterized in that: Define the module, including: The third acquisition unit: searches for the corresponding bidding announcement on the bidding website using the relevant keywords of the bidding project, and acquires the relevant information of the bidding project according to the bidding announcement; The second determination unit: determines the characteristics and needs of the bidding project according to the relevant information, and determines the corresponding scoring criteria; A third determining unit: determining the weight of each evaluation item in the scoring process according to the scoring criteria; Definition Unit: Define scoring rules based on industry standards and best practices according to the weight of each evaluation item.

4. The intelligent bidding evaluation score sheet configuration management system according to claim 1 is characterized in that: Get modules, including: Preprocessing unit: obtain scene images, corresponding evaluation indicators and existing scoring labels under different scenes according to the third-party platform, and preprocess the evaluation indicator data and existing scoring label data; Partitioning unit: divides the preprocessed data into feature columns and target columns; Fourth acquisition unit: acquiring useful features based on the feature column and the target column according to the evaluation index library and the scoring rules, and performing model training through a convolutional neural network; Evaluation unit: evaluates the precision and recall of the trained model to obtain the generalization performance of the model; Intelligent scoring unit: Deploy the trained model to the actual scenario, obtain the automatic adjustment scoring strategy for different scenarios in real time, and perform intelligent scoring on the target proposals.

5. The intelligent bidding evaluation score sheet configuration management system according to claim 1 is characterized in that: Display module, including: The fifth acquisition unit: obtains the intelligent scoring process and results according to the scoring log, and obtains the corresponding data analysis tools according to the analysis purpose; Import unit: import the intelligent scoring process and results into the data analysis tool, perform data analysis in different dimensions, and obtain scoring data based on the analysis results; Creation unit: generating a visualization report from the scoring data, obtaining the purpose and audience of the report, selecting a corresponding visualization tool, and creating visualization elements; A display unit displays the visualization report based on visualization elements.

6. The intelligent bidding evaluation score sheet configuration management system according to claim 1 is characterized in that: Also includes: Verification module: authenticates the identity of users who access the intelligent bid evaluation score sheet configuration management system, and protects the privacy and data security of users through a security authentication mechanism; Authorization module: authorizes authenticated users and assigns role- and task-based permission levels; Restriction module: restricts user access to specific resources and functions based on access control lists according to the permission levels; Monitoring and Auditing Module: Real-time monitoring and auditing of access activities and behaviors, and identification of security vulnerabilities and abuse behaviors.

7. The intelligent bidding evaluation score sheet configuration management system according to claim 6 is characterized in that: Authorization modules, including: Fourth determination unit: obtaining the position information of the user who has passed the identity authentication, and determining the position level of the user according to the position information; Fifth determination unit: Determine the basic authority and highest authority of the user based on the position level and position structure; The sixth determination unit: determines the user's operable authority scope according to the user's basic authority and highest authority; Authorization unit: Authorize users based on the scope of their operational permissions.

8. The intelligent bidding evaluation score sheet configuration management system according to claim 3 is characterized in that: The second determining unit includes: The first determination subunit: determine the project plan of the bidding project based on relevant information, and determine the project management parameters and project construction parameters based on the project plan; The second determination subunit: determines the project process based on the project management parameters and the project construction parameters, and determines the construction label according to the project process; A first acquisition subunit: acquiring construction data from a preset database according to the construction label, and determining a plurality of engineering factors according to the construction data; The third determination subunit: obtaining the global non-transferable construction characteristics and local transferable construction characteristics of each engineering factor, and determining the project characteristics and project needs of the bidding project based on the global non-transferable construction characteristics and local transferable construction characteristics; The second acquisition subunit: determines the project quality supervision rules according to the project characteristics and project needs, and obtains the supervision indicators corresponding to the project quality supervision rules; Extension subunit: obtain multiple scoring project vectors according to the supervision indicators, and expand the project vector to be evaluated into an augmented vector; Solving subunit: Establish a local weighted linear regression model based on the augmented vector, and use the stochastic gradient descent algorithm to solve the local weighted linear regression model to obtain the optimized solution; The fourth determination subunit: obtains the scoring weight of each scoring project vector according to the optimization solution, and determines the scoring criteria based on the scoring weight of each project score and the project application attributes.

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