CN114418293A - Artificial intelligence bid evaluation method, system and equipment based on big data analysis - Google Patents

Abstract

The invention provides an artificial intelligence bid evaluation method, system and equipment based on big data analysis, which are used for calling bid evaluation data information from a bid inviting file and extracting a bid evaluation model and a bid evaluation rule in the bid evaluation data information; bidding sub-modules in the obtained bidding documents according to the bidding keyword labels; judging whether the bidding sub-modules in the bidding document are matched with the bidding keyword tags in the bidding document; if the bidding documents are matched with the bidding documents, starting a scoring program to score the bidding sub-modules in the bidding documents; and outputting the total score of the bid evaluation. Automatic scoring and bid evaluation are realized, and comprehensive calculation scoring is performed in combination with expert scoring. In order to ensure the scoring accuracy, a large amount of repeated examination of each score is required, a large amount of scoring time is consumed, the manual intervention degree is large, each expert has different understanding on a certain project, and if some projects cannot be scored uniformly, the scoring of each expert lacks the standard, and the objectivity of scoring work is influenced.

Description

An artificial intelligence bid evaluation method, system and equipment based on big data analysis

technical field

The invention relates to the technical field of bidding, in particular to an artificial intelligence bid evaluation method, system and equipment based on big data analysis.

Background technique

At present, the bidding method has been applied in many industries, which can involve procurement bidding, construction bidding and so on. In each bidding process, the bidding announcement needs to be issued first, and the bidding company prepares the bidding documents based on the bidding documents, and bids according to the specified time. Then open the bid, call the bid and evaluate the bid process, and finally announce the winning company.

In the process of bid evaluation, an expert group is usually assigned first, and the experts evaluate each bidding document. If the bidding volume is large, it will take a lot of time to evaluate the bids individually, and the bid evaluation work cannot be guaranteed. objectivity.

In the process of scoring, experts need to calculate a large number of scoring items for bidding documents, and then weight according to the scores to calculate the results of each bidding document. In order to ensure the accuracy of the scoring, there are a large number of repeated checks for each score, which will consume a lot of time for bid evaluation, and the degree of manual intervention is large. Each expert has a different understanding of a certain item. If some items fail to unify the scoring rules , resulting in the lack of standards for each expert's score, which affects the objectivity of the bid evaluation work.

SUMMARY OF THE INVENTION

The present invention provides an artificial intelligence bid evaluation method based on big data analysis. The method conducts comprehensive evaluation and evaluation of bids according to a preset scoring method and combined with the evaluation of experts, so as to meet the requirements of bid evaluation.

AI bid evaluation methods include:

S101, retrieve bid evaluation data information from the bidding documents, and extract bid evaluation models and bid evaluation rules in the bid evaluation data information;

S102, bidding for submodules in obtaining bidding documents according to the bidding keyword tag;

S103, judging whether the bidding sub-module in the bidding document matches the bidding keyword label in the bidding document;

If there is a match, start the scoring process to score the bidding sub-modules in the bidding documents;

Output the total score of the bid evaluation.

Preferably, a bidding keyword tag is set in the bidding document; the bidding keyword tag is a rule set based on the bidding conditions required by the bidder in the bidding document.

Preferably, if the bidding sub-module in the bidding document fails to match the bidding keyword tag in the bidding document, the bidding document lacks the bidding keyword tag in the bidding document, and the bidding document is determined to be rejected.

Preferably, in the bid evaluation data information, multiple bid evaluation sub-modules are set, and each bid evaluation sub-module is set with a bid evaluation mark; the bid evaluation mark is set according to the bidding keyword tag.

Preferably, a bid evaluation weight coefficient is set for each bid evaluation sub-module, the bid evaluation weight coefficient is combined with the bid evaluation sub-module to obtain the current bid evaluation item score, and the bid evaluation item scores are added to obtain the bid evaluation score of the bidding document.

计算每个评标子模块评标权重系数；Preferably, by

Calculate the bid evaluation weight coefficient of each bid evaluation sub-module;

P is the importance of the bid evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag involved in the bid evaluation sub-module.

Preferably, a bid evaluation terminal is configured for each bid evaluation expert;

Obtain the evaluation expert's score for each bidding sub-module through the evaluation terminal;

The evaluation weight coefficient of the bid evaluation sub-module and the score of the bidding sub-module are calculated to obtain the score of each expert, and then the weighted average score of all evaluations is obtained to obtain the score of each bidding document.

Preferably, the score for each bid is calculated as follows;

DN=(XA1,XA2,XA3,XA4,XA5)

A1, A2, A3, A4, and A5 respectively represent different bidding sub-modules;

D1, D2, D3, and DN represent the scores of each expert, respectively.

The present invention also provides an artificial intelligence bid evaluation system based on big data analysis, comprising: a bidding document acquisition module, an identification setting module, a bid matching scoring module, an output module and a database;

The bidding document obtaining module is used to obtain the bidding document according to the preset format, and store the obtained bidding document in the database;

The identification setting module is used to set the bidding keyword label in the bidding document, set the bidding sub-module in the bidding document, set multiple bid evaluation sub-modules in the bid evaluation data information, and set the bid evaluation mark for each bid evaluation sub-module ;

The bidding matching scoring module is used to judge whether the bidding sub-module in the bidding document matches the bidding keyword tag in the bidding document; if it matches, start the scoring procedure to score the bidding sub-module in the bidding document;

The output module is used to output the total score of the bid evaluation.

The present invention also provides a device for implementing an artificial intelligence bid evaluation method based on big data analysis, including:

Memory for storing computer programs and artificial intelligence bid evaluation methods based on big data analysis;

A processor for executing the computer program and the artificial intelligence bid evaluation method based on big data analysis, so as to realize the steps of the artificial intelligence bid evaluation method based on big data analysis.

As can be seen from the above technical solutions, the present invention has the following advantages:

The artificial intelligence bid evaluation method and system based on big data analysis provided by the present invention realizes automatic scoring and bid evaluation, and performs comprehensive calculation and scoring in combination with expert scoring.

The present invention can screen the bids first, make matching judgment for the bid documents that do not meet the required bidding requirements, and eliminate those that do not meet the requirements, and then carry out subsequent bid evaluation.

During the bid evaluation process, the system can automatically calculate the bid evaluation score process, which can avoid the problem of missed evaluation and wrong evaluation in the manual calculation score.

Therefore, the bid evaluation work can be simplified, and the efficiency and accuracy of the bid evaluation can be improved. It avoids a large number of repeated inspections of each score, which consumes a lot of bid evaluation time, and the present invention can improve the efficiency of bid evaluation and the accuracy of bid evaluation.

The artificial intelligence bid evaluation method and system based on big data analysis provided by the present invention reduces the degree of manual intervention to a large extent, can be scored according to a unified model, realizes unified scoring rules, reduces the lack of standards for each expert's scoring, and affects bid evaluation work question of objectivity.

Description of drawings

In order to illustrate the technical solutions of the present invention more clearly, the accompanying drawings required in the description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, which are not relevant to ordinary skills in the art. As far as personnel are concerned, other drawings can also be obtained from these drawings on the premise of no creative work.

Figure 1 is a flowchart of an artificial intelligence bid evaluation method based on big data analysis;

Figure 2 is a schematic diagram of an artificial intelligence bid evaluation system based on big data analysis.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

A kind of artificial intelligence bid evaluation method based on big data analysis provided by the present invention, as shown in Figure 1, the method includes:

S101, retrieve bid evaluation data information from the bidding documents, and extract bid evaluation models and bid evaluation rules in the bid evaluation data information;

In the present invention, the bidding documents may include, but are not limited to, power material procurement bidding, or power construction project bidding items. In the bidding documents, there are bidding requirements, qualification requirements for bidders, capital requirements, and qualification requirements for bidders. Bid evaluation rules.

The bidding keyword tag is set in the bidding document; the bidding keyword tag is a rule set based on the bidding conditions required by the bidder in the bidding document. For example, bidding keywords may include, but are not limited to, bidding price, technical capability, R&D capability, corporate financial information, corporate reputation, corporate performance, and after-sales service.

Bidding keyword tags can be set and highlighted in the bidding documents in terms of bid price, technical capability, R&D capability, corporate financial information, corporate reputation, corporate performance, and after-sales service.

In the bid evaluation data information, multiple bid evaluation sub-modules are set, and a bid evaluation mark is set for each bid evaluation sub-module. The bid evaluation logo is set according to the bidding keyword label.

A bid evaluation weight coefficient is set for each bid evaluation sub-module, the bid evaluation weight coefficient is combined with the bid evaluation sub-module to obtain the current bid evaluation item score, and the bid evaluation item scores are added to obtain the bid evaluation score of the bidding document.

In the present invention, each bid evaluation item may correspond to at least one kind of bidding item information, and the bidding item information is set with a corresponding score.

S102, bidding for submodules in obtaining bidding documents according to the bidding keyword tag;

S103, judging whether the bidding sub-module in the bidding document matches the bidding keyword label in the bidding document;

S104, if there is a match, start the scoring program to score the bidding sub-modules in the bidding document;

S105, output the total score of the bid evaluation.

If the bidding sub-module in the bidding document fails to match the bidding keyword tag in the bidding document, the bidding document lacks the bidding keyword tag in the bidding document, and the bidding document is determined to be rejected.

In the present invention, a preset number of bidding keyword tags are set in the bidding document according to the bidding requirements, and the bidding keyword tags represent the requirements of the tenderer for the bidding enterprise. The bidders need to meet the corresponding requirements. For example, the bidding enterprise needs to meet the requirements of bidding price, technical ability, research and development ability, enterprise financial information, enterprise reputation, enterprise performance, and after-sales service. Then the bidder needs to explain each of the above items when bidding.

In the present invention, the above requirements are set as bidding keyword tags, that is, how many bidding keyword tags are set for how many items are required. When making bidding documents, the bidder needs to fill in the corresponding items according to the requirements of the bidder. For example, the bidder has set requirements for bidding price, technical ability, research and development ability, corporate financial information, corporate reputation, corporate performance, after-sales service, etc. . Then, the bidder needs to provide one-to-one corresponding enterprise information and bidding information to the above requirements, and form a bidding sub-module.

The present invention can match the bidding sub-module with the bidding keyword tag in the bidding document. If the bidding sub-module completely matches the bidding keyword label in the bidding documents, it means that the bidders all correspond to the requirements of the bidding documents.

If the bidding sub-module does not fully cover the bidding keyword tags of the bidding document, it means that there is a missing bid in the bidding document, and the system judges the bidding document as an invalid bid.

Further, in the bid evaluation method involved in the present invention, first

计算每个评标子模块评标权重系数；pass

Calculate the bid evaluation weight coefficient of each bid evaluation sub-module;

P is the importance of the bid evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag involved in the bid evaluation sub-module.

For example, the technical ability of the enterprise can be used as a keyword tag for bidding. Specifically, the sub-items include production capacity, R&D capacity, test capacity, equipment status and so on.

Similarly, corporate financial information specifically involves the company's asset information, liability information, profit information and so on.

In the present invention, a bid evaluation terminal is configured for each bid evaluation expert;

Obtain the evaluation expert's score for each bidding sub-module through the evaluation terminal;

The evaluation weight coefficient of the bid evaluation sub-module and the score of the bidding sub-module are calculated to obtain the score of each expert, and then the weighted average score of all evaluations is obtained to obtain the score of each bidding document.

The score for each bid is calculated as follows;

DN=(XA1,XA2,XA3,XA4,XA5)

A1, A2, A3, A4, and A5 respectively represent different bidding sub-modules;

D1, D2, D3, and DN represent the scores of each expert, respectively.

Based on the above method, the present invention also provides an artificial intelligence bid evaluation system based on big data analysis, as shown in FIG. 2 , including: a bidding document acquisition module, an identification setting module, a bid matching scoring module, an output module and a database;

The bidding document obtaining module is used to obtain the bidding document according to the preset format, and store the obtained bidding document in the database;

The identification setting module is used to set the bidding keyword label in the bidding document, set the bidding sub-module in the bidding document, set multiple bid evaluation sub-modules in the bid evaluation data information, and set the bid evaluation mark for each bid evaluation sub-module ;

The bidding matching scoring module is used to judge whether the bidding sub-module in the bidding document matches the bidding keyword tag in the bidding document; if it matches, start the scoring procedure to score the bidding sub-module in the bidding document;

The output module is used to output the total score of the bid evaluation.

A device for implementing an artificial intelligence bid evaluation method based on big data analysis, comprising: a memory for storing a computer program and an artificial intelligence bid evaluation method based on big data analysis; a processor for executing the computer program and a large data analysis-based bid evaluation method; Artificial intelligence bid evaluation method based on data analysis to realize the steps of artificial intelligence bid evaluation method based on big data analysis.

Among them, the artificial intelligence bid evaluation method based on big data analysis provided by the present invention mainly involves artificial intelligence computer vision technology and artificial intelligence cloud service in cloud technology. Specifically, artificial intelligence processing is realized by using computer vision technology and artificial intelligence cloud service. Bid evaluation process data can improve the accuracy of artificial intelligence processing bidding.

Among them, artificial intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. . In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, reasoning and decision-making.

The artificial intelligence technology involved in the present invention is a comprehensive subject, involving a wide range of fields, including both hardware-level technology and software-level technology. The basic technologies of artificial intelligence generally include technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation/interaction systems, and mechatronics. Artificial intelligence software technology mainly includes computer vision technology, speech processing technology, natural language processing technology, and machine learning/deep learning. Among them, computer vision technology (Computer Vision, CV) computer vision is a science that studies how to make machines "see". Further, it refers to the use of cameras and computers instead of human eyes to identify, track and measure objects. Vision, and further do graphics processing, so that computer processing becomes more suitable for human eyes to observe or transmit images to instruments for detection. As a scientific discipline, computer vision studies related theories and technologies, trying to build artificial intelligence systems that can obtain information from images or multidimensional data. Computer vision technology usually includes image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content/behavior recognition, 3D object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping It also includes common biometric identification technologies such as face recognition and fingerprint recognition.

In the present invention, the artificial intelligence bid evaluation method based on big data analysis can be used on terminal equipment, and the terminal equipment can refer to the equipment used to provide artificial intelligence services. Bidding and bid evaluation function services provided by the intelligent platform.

The device may also provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and basic cloud computing services such as artificial intelligence platforms. The device may be a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto.

Those skilled in the art can understand that various aspects of the artificial intelligence bid evaluation method, system and device based on big data analysis can be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure can be embodied in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, which may be collectively referred to herein as implementations "circuit", "module" or "system".

The above description of the disclosed embodiments enables any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. An artificial intelligence bid evaluation method based on big data analysis is characterized by comprising the following steps:

s101, calling bid evaluation data information from the bid inviting file, and extracting bid evaluation models and bid evaluation rules in the bid evaluation data information;

s102, obtaining a bidding submodule in a bidding document according to the bidding keyword label;

s103, judging whether the bidding sub-module in the bidding document is matched with the bidding keyword tag in the bidding document;

s104, if the bidding documents are matched with the bidding documents, starting a grading program, and grading the bidding sub-modules in the bidding documents;

and S105, outputting the total score of the evaluation targets.

2. The artificial intelligence bid evaluation method based on big data analysis according to claim 1,

setting a bidding keyword label in a bidding document; the bid keyword tag is a rule that is set based on a bid condition required by the bidder in the bid document.

3. The artificial intelligence bid evaluation method based on big data analysis according to claim 1,

and if the bidding submodule in the bidding document is not matched with the bidding keyword label in the bidding document, judging that the bidding document is wasted if the bidding submodule lacks the bidding keyword label in the bidding document.

4. The artificial intelligence bid evaluation method based on big data analysis according to claim 1,

setting a plurality of bid evaluation sub-modules in the bid evaluation data information, and setting bid evaluation identifications for each bid evaluation sub-module; and the bid evaluation mark is set according to the bid inviting keyword label.

5. The artificial intelligence bid evaluation method based on big data analysis according to claim 4,

and setting a bid evaluation weight coefficient for each bid evaluation submodule, combining the bid evaluation weight coefficient with the bid evaluation submodule to obtain the current bid evaluation item score, and summing the bid evaluation item scores to obtain the bid evaluation score of the bid document.

6. The artificial intelligence bid evaluation method based on big data analysis according to claim 5,

by passing

Calculating a bid evaluation weight coefficient of each bid evaluation submodule;

p is the importance of the evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag related in the evaluation sub-module.

7. The artificial intelligence bid evaluation method based on big data analysis according to claim 6, wherein a bid evaluation terminal is configured for each bid evaluation expert;

obtaining the grade of each bidding submodule by the bid evaluation expert through the bid evaluation terminal;

and calculating based on the evaluation weighting coefficient of the evaluation submodule and the score of the bidding submodule to obtain the score of each expert, and then carrying out weighted average scoring on all the evaluations to obtain the score of each bidding document.

8. The artificial intelligence bid evaluation method based on big data analysis according to claim 7, wherein the score of each bid document is calculated by;

DN＝(XA1，XA2，XA3，XA4，XA5)

a1, A2, A3, A4 and A5 respectively represent different bidding submodules;

d1, D2, D3, DN each represent the score of each expert.

9. An artificial intelligence bid evaluation system for realizing big data analysis is characterized by comprising: the system comprises a bidding document acquisition module, an identification setting module, a bidding matching scoring module, an output module and a database;

the bidding document acquisition module is used for acquiring bidding documents according to a preset format and storing the acquired bidding documents into a database;

the identification setting module is used for setting a bidding keyword label in a bidding document, setting a bidding sub-module in the bidding document, setting a plurality of bid evaluation sub-modules in the bid evaluation data information, and setting a bid evaluation identification for each bid evaluation sub-module;

the bid matching scoring module is used for judging whether a bid submodule in the bid file is matched with a bid calling keyword label in the bid file; if the bidding documents are matched with the bidding documents, starting a scoring program to score the bidding sub-modules in the bidding documents;

the output module is used for outputting the total score of the bid evaluation.

10. The device for realizing the artificial intelligence bid evaluation method based on big data analysis is characterized by comprising the following steps:

the storage is used for storing a computer program and an artificial intelligence evaluation method based on big data analysis;

a processor for executing the computer program and the artificial intelligence bid evaluation method based on big data analysis to realize the steps of the artificial intelligence bid evaluation method based on big data analysis according to any one of claims 1 to 8.

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