CN111444426A - Technology recommendation method based on technology library - Google Patents
Technology recommendation method based on technology library Download PDFInfo
- Publication number
- CN111444426A CN111444426A CN202010224427.5A CN202010224427A CN111444426A CN 111444426 A CN111444426 A CN 111444426A CN 202010224427 A CN202010224427 A CN 202010224427A CN 111444426 A CN111444426 A CN 111444426A
- Authority
- CN
- China
- Prior art keywords
- technical
- treatment
- library
- technology
- matched
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/90—Programming languages; Computing architectures; Database systems; Data warehousing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/70—Machine learning, data mining or chemometrics
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Human Resources & Organizations (AREA)
- Computing Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Data Mining & Analysis (AREA)
- Crystallography & Structural Chemistry (AREA)
- Chemical & Material Sciences (AREA)
- Software Systems (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- General Engineering & Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a technology recommendation method based on a technology library, which comprises the following steps: constructing a technical library, wherein the description of each repair type technical case in the technical library comprises a basic description, the basic description comprises a plurality of attributes of a treatment object, a treatment process, process key parameters and evaluation indexes after treatment, and the plurality of attributes of the treatment object comprise the name of the treatment object, the type of pollutants contained in the treatment object and the evaluation indexes before treatment; providing a plurality of attributes of a treatment object to be analyzed to a technical library; and preferentially matching pollutant types contained in the treatment object, and after the corresponding repair type technical cases are matched in the technical library according to the pollutant types contained in the treatment object, searching according to the name of the treatment object and the evaluation index before treatment. The technology recommendation method based on the technology library has accurate and efficient recommendation result, thereby providing very beneficial guidance for actual water body treatment work.
Description
Technical Field
The invention relates to the field of software, in particular to a technology recommendation method based on a technology library.
Background
The water body pollution mainly refers to the phenomenon that pollutants discharged by human activities enter a water body to cause water quality reduction and reduction or loss of utilization value. The water body pollution can cause the deterioration of the ecological environment, and seriously threatens the survival and development of human beings. At present, a plurality of technical achievements surrounding the control and treatment of water body pollution exist, and in order to enable the technical achievements to better serve the water environment treatment work, a technical library needs to be constructed urgently by utilizing the technical achievements, and technical guidance is provided for an actual water body treatment link by applying the technical library, so that the conversion of research achievements is promoted, the actual water body treatment efficiency is improved, and the actual water body treatment effect is improved.
Disclosure of Invention
An object of the present invention is to solve at least the above problems and/or disadvantages and to provide at least the advantages described hereinafter.
The invention aims to provide a technology recommendation method based on a technology library, which can automatically recommend restoration-type technical cases to a user, has accurate and efficient recommendation results, and provides very beneficial guidance for actual water body treatment work.
To achieve these objects and other advantages in accordance with the purpose of the invention, there is provided a technology recommendation method based on a technology library, including:
inputting a plurality of repair type technical cases in a technical library so as to construct the technical library, wherein the repair type technical cases are technical schemes for reducing pollutants in a treatment object, the description of each repair type technical case in the technical library comprises a basic description, the basic description comprises a plurality of attributes, a treatment process, process key parameters and evaluation indexes after treatment of the treatment object, and the plurality of attributes of the treatment object comprise the name of the treatment object, the type of pollutants contained in the treatment object and the evaluation indexes before treatment;
providing a plurality of attributes of an abatement object to be analyzed to the technical library, and performing matching retrieval in the technical library based on the provided plurality of attributes of the abatement object to be analyzed; in the matching retrieval process, preferentially matching the pollutant types contained in the treatment objects, and after the corresponding repairing type technical cases are matched in the technical library according to the pollutant types contained in the treatment objects, retrieving according to the names of the treatment objects and the evaluation indexes before treatment;
if the evaluation indexes before treatment cannot be matched, recommending a repair technical case matched according to the pollutant types contained in the treatment objects and the names of the treatment objects in the technical library; and if the names of the treatment objects and the evaluation indexes before treatment can be matched, recommending the repair technical cases matched according to the pollutant types contained in the treatment objects, the names of the treatment objects and the evaluation indexes before treatment in the technical library.
Preferably, the technology recommendation method based on the technology library further includes:
and establishing a technical set by taking each repair technical case as a core technology, and inputting an actual treatment scheme formed by treating the treatment object according to the matched repair technical case and a treated evaluation index obtained by treating the treatment object according to the matched repair technical case into the technical set corresponding to the matched repair technical case, so as to update the technical library.
Preferably, the technology recommendation method based on the technology library further includes: in the technical set, the process key parameters of an actual treatment scheme formed by treating the treatment object according to the matched repair type technical case are compared with the process key parameters of the matched repair type technical case, the treated evaluation indexes obtained by treating the treatment object according to the matched repair type technical case are compared with the treated evaluation indexes of the repair type technical case, the difference of the process key parameters and the difference of the treated evaluation indexes are determined, and the reasons for causing the difference of the process key parameters and the difference of the treated evaluation indexes are recorded in the technical set.
Preferably, in the technology recommendation method based on the technology library, when the matched repair-type technical case is recommended, a technology set constructed by using the matched repair-type technical case as a core technology is recommended.
Preferably, in the technology recommendation method based on the technology library,
the description of each repair type technical case in the technical library further comprises an evaluation description, the evaluation description comprises a technical evaluation grade and an economic benefit evaluation index, the technical evaluation grade comprises a technical contribution degree evaluation grade and a technical readiness degree evaluation grade, and the economic benefit evaluation index comprises technical implementation cost and technical income;
when matching retrieval is carried out in the technical library on the basis of the provided multiple attributes of the treatment object to be analyzed and the matched repair technical cases are recommended, the matched repair technical cases are sorted from high to low according to the technical readiness degree evaluation level;
the technical readiness evaluation level comprises 1-9 levels, ① basic principles are discovered sequentially from 1-9 levels, a technical scheme is formed ②, a small-scale test study is carried out ③, a pilot-scale test study is carried out ④, a process kit or the overall design of a product and a platform is formed ⑤, a ⑥ engineering demonstration or the product and the platform are formed, ⑦ is evaluated by a third party or is verified and approved by a user, ⑧ standardization is carried out, and ⑨ is popularized and applied.
Preferably, in the technology recommendation method based on the technology library,
and when the matched restoration-class technical case is recommended based on the provided multiple attributes of the treatment object to be analyzed, estimating the technical implementation cost and the technical profit of the treatment object to be analyzed according to the scale of the treatment object to be analyzed and the scale and the economic benefit evaluation index of the treatment object of the matched restoration-class technical case, and recommending the estimation result together with the matched restoration-class technical case.
Preferably, in the technology recommendation method based on the technology library, the evaluation level of the technology contribution degree includes original innovation, integrated innovation, introduced innovation and applied innovation.
Preferably, in the technology recommendation method based on the technology library, the evaluation index before treatment includes a COD value, an ammonia nitrogen content, a total nitrogen content, and a total pollutant content of the treatment object before treatment of the treatment object, and the evaluation index after treatment includes a COD removal rate, an ammonia nitrogen removal rate, a total nitrogen removal rate, and a total pollutant removal rate of the treatment object after treatment of the treatment object.
The invention at least comprises the following beneficial effects:
according to the invention, the technical library is constructed based on the restoration technical cases, the restoration technical cases are described by adopting specific basic description, the restoration technical cases are recommended according to a stepped matching retrieval strategy aiming at a treatment object in an actual scene, and the recommendation result is accurate and efficient, so that very beneficial guidance is provided for the actual water body treatment work, the conversion of research results is facilitated, the efficiency of actual water body treatment is improved, and the effect of water body treatment is improved.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
Fig. 1 is a flowchart of a technology library-based technology recommendation method according to an embodiment of the present invention.
Detailed Description
The present invention is further described in detail below with reference to the attached drawings so that those skilled in the art can implement the invention by referring to the description text.
As shown in fig. 1, the present invention provides a technology recommendation method based on a technology library, including:
inputting a plurality of repair type technical cases in a technical library so as to construct the technical library, wherein the repair type technical cases are technical schemes for reducing pollutants in a treatment object, the description of each repair type technical case in the technical library comprises a basic description, the basic description comprises a plurality of attributes, a treatment process, process key parameters and evaluation indexes after treatment of the treatment object, and the plurality of attributes of the treatment object comprise the name of the treatment object, the type of pollutants contained in the treatment object and the evaluation indexes before treatment.
In the process of constructing the technology library, the repair type technology case is used as a core element of the technology library. The restoration technology is a technical measure for reducing pollutants starting from the aspects of pollutant emission sources, conversion ways and final forms according to the formation process and the degradation principle of the pollutants. Mainly comprises emission reduction technologies of industrial sources, urban living sources and non-point sources. After the technical scheme is formed and feasibility demonstration is carried out, the process is often determined and optimized through a small test stage and a pilot test stage, key technical parameters of the process are analyzed, engineering demonstration is carried out on a site with a certain scale, and the applicability of the process and the stability of the treatment effect are further checked; design parameters of the technology are extracted in the actual application process, and the applicability and treatment effect of the technology are checked through application of different types of treatment objects, so that the technology process capable of being popularized and applied is formed. Treatment techniques often have a definite process and specific technical parameters can be used to reflect the characteristics of the process.
Providing a plurality of attributes of an abatement object to be analyzed to the technical library, and performing matching retrieval in the technical library based on the provided plurality of attributes of the abatement object to be analyzed; in the matching and searching process, the pollutant types contained in the treatment objects are preferentially matched, and after the corresponding repairing type technical cases are matched in the technical library according to the pollutant types contained in the treatment objects, the searching is carried out according to the names of the treatment objects and the evaluation indexes before treatment.
If the evaluation indexes before treatment cannot be matched, recommending a repair technical case matched according to the pollutant types contained in the treatment objects and the names of the treatment objects in the technical library; and if the names of the treatment objects and the evaluation indexes before treatment can be matched, recommending the repair technical cases matched according to the pollutant types contained in the treatment objects, the names of the treatment objects and the evaluation indexes before treatment in the technical library.
When a user desires to treat a treatment object in an actual scene, a plurality of attributes of the treatment object, including a name, a pollutant type, and an evaluation index before treatment, need to be investigated in advance, for example, the treatment object is a section of river, a chemical plant is near the river, and then the pollutant type and various evaluation indexes of the river can be determined based on the type of the chemical plant and the detection of the river. After obtaining this information, the user can perform a matching search in the technical library.
In the process of matching and searching, the types of pollutants are preferentially matched, and then the names of the treatment objects and the evaluation indexes before treatment are searched. This is because the same abatement method is intended to be selected for the same pollutant species, but the specific abatement process may also be different according to the abatement object, so the scope of the remediation-type technical case is narrowed first by the pollutant species, and then further narrowed by the name of the abatement object. If it is assumed that, for a treatment object in an actual scene, a repair type technical case can be found in which the evaluation index before treatment can also be matched, which means that the conditions of the treatment object in the actual scene and the treatment object in the repair type technical case are relatively close, then when the repair type technical case is applied, the workload for debugging the treatment process and the key process parameters will be relatively small, even only non-key parameters need to be adjusted, the actual treatment efficiency will be higher, and the treatment effect will be better. If the assessment indexes before treatment cannot be matched for the treatment object in an actual scene, at least a repair technical case with matched pollutant types and treatment object names can be provided for a user, the recommendation still has great guiding significance, and only due to different assessment indexes before treatment, some proper adjustments need to be made to the treatment process and key process parameters.
According to the invention, the technical library is constructed based on the restoration technical cases, the restoration technical cases are described by adopting specific basic description, the restoration technical cases are recommended according to a stepped matching retrieval strategy aiming at a treatment object in an actual scene, and the recommendation result is accurate and efficient, so that very beneficial guidance is provided for the actual water body treatment work, the conversion of research results is facilitated, the efficiency of actual water body treatment is improved, and the effect of water body treatment is improved.
In a preferred embodiment, the technology recommendation method based on the technology library further includes: and establishing a technical set by taking each repair technical case as a core technology, and inputting an actual treatment scheme formed by treating the treatment object according to the matched repair technical case and a treated evaluation index obtained by treating the treatment object according to the matched repair technical case into the technical set corresponding to the matched repair technical case, so as to update the technical library.
The user administers the administration object under the actual scene according to the repair technical case recommended by the system, the implementation details of the actual administration scheme may be different from the recommended repair technical case, and the obtained evaluation index after administration may also be slightly different. Therefore, a technical set is constructed by the actual treatment scheme and the restoration technical cases, the actual treatment scheme is used as a supplement of the restoration technical cases, more sufficient reference is provided for other users, and the guiding significance of the actual water body treatment is further improved.
In a preferred embodiment, the technology recommendation method based on the technology library further includes: in the technical set, the process key parameters of an actual treatment scheme formed by treating the treatment object according to the matched repair type technical case are compared with the process key parameters of the matched repair type technical case, the treated evaluation indexes obtained by treating the treatment object according to the matched repair type technical case are compared with the treated evaluation indexes of the repair type technical case, the difference of the process key parameters and the difference of the treated evaluation indexes are determined, and the reasons for causing the difference of the process key parameters and the difference of the treated evaluation indexes are recorded in the technical set.
And analyzing the difference between the process key parameters in the actual treatment scheme and the evaluation indexes after treatment, and analyzing the reasons possibly generated by the difference, recording the reasons in a technical set, and providing more sufficient reference for other users.
In a preferred embodiment, in the technology recommendation method based on the technology library, when the matched repair-class technical case is recommended, a technology set constructed by using the matched repair-class technical case as a core technology is recommended.
When a user carries out matching retrieval aiming at a treatment object of an actual scene, not only a standard repair technical case can be obtained, but also a technical set can be obtained, the technical set comprises various deformations of the standard repair technical case in the specific implementation process, and the user can make a more effective actual treatment scheme based on the actual situation of the user. The embodiment further improves the effect of technology recommendation to the user and can better meet the requirements of the user.
In a preferred embodiment, the technical recommendation method based on the technical library further comprises an evaluation description in the technical library, the evaluation description comprises a technical evaluation grade and an economic benefit evaluation index, the technical evaluation grade comprises a technical contribution evaluation grade and a technical readiness evaluation grade, and the economic benefit evaluation index comprises technical implementation cost and technical income, matching retrieval is carried out in the technical library based on a plurality of provided attributes of the treatment object to be analyzed, when the matched repair technical cases are recommended, the matched repair technical cases are ranked from high to low according to the technical readiness evaluation grade, wherein the technical readiness evaluation grade comprises 1-9 grades, the basic principle is found from 1-9 grades in sequence, ② forms a technical scheme, conduct bench test research, ④ conduct pilot test research, ⑤ forms an overall design of a process package or a product or a platform, ⑥ demonstrates engineering or forms a product or a platform, is evaluated by a third party or is approved by a user ⑦, and is approved by a 368678, and is popularized and obtained.
And aiming at each repair technical case, an evaluation description is also set, and the evaluation description comprises a technical evaluation grade and an economic benefit evaluation index. When recommending corresponding repair technical cases to a user, a plurality of repair technical cases for realizing matching may exist, and at this time, the repair technical cases are sorted from high to low according to the evaluation level of the technical readiness degree. In general, users expect to find a technology which can be put into use immediately, so that the treatment work on the actual water body can be quickly realized. Based on the setting of the embodiment, the technology with high readiness, namely, the technology which is more mature in the implementation level, is preferentially recommended to the user so as to meet the needs of the user. In addition, the technical contribution degree evaluation level and the economic benefit evaluation index are also very important reference bases, and a user can select a scheme with the corresponding technical contribution degree evaluation level and the economic benefit evaluation index according to actual conditions.
In a preferred embodiment, in the technology recommendation method based on the technology library, when performing matching search in the technology library based on the provided multiple attributes of the abatement object to be analyzed and recommending the matched remediation-class technical case, the technology implementation cost and the technology profit of the abatement object to be analyzed are estimated according to the scale of the abatement object to be analyzed and the scale and economic benefit evaluation indexes of the abatement object of the matched remediation-class technical case, and the estimation result is recommended together with the matched remediation-class technical case.
The embodiment also considers the scale of the treatment object provided by the user, and estimates the technical implementation cost and the technical profit of the actual treatment by combining the scale of the treatment object in the matched technical case of the repair class, for example, when the size of the lake is different, the technical implementation cost and the technical profit will be changed, and here, the simple estimation is performed only according to the scale of the treatment object, and the estimated estimation is used as an auxiliary reference when the user selects a certain technical case of the repair class.
In a preferred embodiment, in the technology recommendation method based on the technology library, the technology contribution evaluation level includes original innovation, integrated innovation, introduced innovation and applied innovation.
In a preferred embodiment, the pre-treatment evaluation index includes a COD value, an ammonia nitrogen content, a total nitrogen content, and a total pollutant content of the treatment object before the treatment of the treatment object, and the post-treatment evaluation index includes a COD removal rate, an ammonia nitrogen removal rate, a total nitrogen removal rate, and a total pollutant removal rate of the treatment object after the treatment of the treatment object.
While embodiments of the invention have been disclosed above, it is not intended to be limited to the uses set forth in the specification and examples. It can be applied to all kinds of fields suitable for the present invention. Additional modifications will readily occur to those skilled in the art. It is therefore intended that the invention not be limited to the exact details and illustrations described and illustrated herein, but fall within the scope of the appended claims and equivalents thereof.
Claims (8)
1. The technology recommendation method based on the technology library is characterized by comprising the following steps:
inputting a plurality of repair type technical cases in a technical library so as to construct the technical library, wherein the repair type technical cases are technical schemes for reducing pollutants in a treatment object, the description of each repair type technical case in the technical library comprises a basic description, the basic description comprises a plurality of attributes, a treatment process, process key parameters and evaluation indexes after treatment of the treatment object, and the plurality of attributes of the treatment object comprise the name of the treatment object, the type of pollutants contained in the treatment object and the evaluation indexes before treatment;
providing a plurality of attributes of an abatement object to be analyzed to the technical library, and performing matching retrieval in the technical library based on the provided plurality of attributes of the abatement object to be analyzed; in the matching retrieval process, preferentially matching the pollutant types contained in the treatment objects, and after the corresponding repairing type technical cases are matched in the technical library according to the pollutant types contained in the treatment objects, retrieving according to the names of the treatment objects and the evaluation indexes before treatment;
if the evaluation indexes before treatment cannot be matched, recommending a repair technical case matched according to the pollutant types contained in the treatment objects and the names of the treatment objects in the technical library; and if the names of the treatment objects and the evaluation indexes before treatment can be matched, recommending the repair technical cases matched according to the pollutant types contained in the treatment objects, the names of the treatment objects and the evaluation indexes before treatment in the technical library.
2. The technology library-based technology recommendation method of claim 1, further comprising:
and establishing a technical set by taking each repair technical case as a core technology, and inputting an actual treatment scheme formed by treating the treatment object according to the matched repair technical case and a treated evaluation index obtained by treating the treatment object according to the matched repair technical case into the technical set corresponding to the matched repair technical case, so as to update the technical library.
3. The technology library-based technology recommendation method of claim 2, further comprising: in the technical set, the process key parameters of an actual treatment scheme formed by treating the treatment object according to the matched repair type technical case are compared with the process key parameters of the matched repair type technical case, the treated evaluation indexes obtained by treating the treatment object according to the matched repair type technical case are compared with the treated evaluation indexes of the repair type technical case, the difference of the process key parameters and the difference of the treated evaluation indexes are determined, and the reasons for causing the difference of the process key parameters and the difference of the treated evaluation indexes are recorded in the technical set.
4. The technology-base-based technology recommendation method of claim 3, wherein when recommending the matched repair-class technical cases, a technology set constructed with the matched repair-class technical cases as core technologies is recommended at the same time.
5. The technology library-based technology recommendation method of claim 1,
the description of each repair type technical case in the technical library further comprises an evaluation description, the evaluation description comprises a technical evaluation grade and an economic benefit evaluation index, the technical evaluation grade comprises a technical contribution degree evaluation grade and a technical readiness degree evaluation grade, and the economic benefit evaluation index comprises technical implementation cost and technical income;
when matching retrieval is carried out in the technical library on the basis of the provided multiple attributes of the treatment object to be analyzed and the matched repair technical cases are recommended, the matched repair technical cases are sorted from high to low according to the technical readiness degree evaluation level;
the technical readiness evaluation level comprises 1-9 levels, ① basic principles are discovered sequentially from 1-9 levels, a technical scheme is formed ②, a small-scale test study is carried out ③, a pilot-scale test study is carried out ④, a process kit or the overall design of a product and a platform is formed ⑤, a ⑥ engineering demonstration or the product and the platform are formed, ⑦ is evaluated by a third party or is verified and approved by a user, ⑧ standardization is carried out, and ⑨ is popularized and applied.
6. The technology library-based technology recommendation method of claim 5,
and when the matched restoration-class technical case is recommended based on the provided multiple attributes of the treatment object to be analyzed, estimating the technical implementation cost and the technical profit of the treatment object to be analyzed according to the scale of the treatment object to be analyzed and the scale and the economic benefit evaluation index of the treatment object of the matched restoration-class technical case, and recommending the estimation result together with the matched restoration-class technical case.
7. The technology recommendation method based on the technology library of claim 5, wherein the technology contribution evaluation level comprises original innovation, integrated innovation, introduced innovation and applied innovation.
8. The technology library-based technology recommendation method of any one of claims 1 to 7, wherein the pre-treatment evaluation index comprises a COD value, an ammonia nitrogen content, a total nitrogen content and a total pollutant content of the treatment object before the treatment of the treatment object, and the post-treatment evaluation index comprises a COD removal rate, an ammonia nitrogen removal rate, a total nitrogen removal rate and a total pollutant removal rate of the treatment object after the treatment of the treatment object.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010224427.5A CN111444426A (en) | 2020-03-26 | 2020-03-26 | Technology recommendation method based on technology library |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010224427.5A CN111444426A (en) | 2020-03-26 | 2020-03-26 | Technology recommendation method based on technology library |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111444426A true CN111444426A (en) | 2020-07-24 |
Family
ID=71650881
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010224427.5A Pending CN111444426A (en) | 2020-03-26 | 2020-03-26 | Technology recommendation method based on technology library |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111444426A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104794528A (en) * | 2015-01-05 | 2015-07-22 | 胡宝清 | Rocky desertification governance model case library management system and rocky desertification governance model case library management method |
| CN105260598A (en) * | 2015-09-29 | 2016-01-20 | 中南大学 | Oral diagnosis and treatment decision support system and decision method |
| CN109166004A (en) * | 2018-08-03 | 2019-01-08 | 贵州大学 | The product customization method of case-based reasioning |
-
2020
- 2020-03-26 CN CN202010224427.5A patent/CN111444426A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104794528A (en) * | 2015-01-05 | 2015-07-22 | 胡宝清 | Rocky desertification governance model case library management system and rocky desertification governance model case library management method |
| CN105260598A (en) * | 2015-09-29 | 2016-01-20 | 中南大学 | Oral diagnosis and treatment decision support system and decision method |
| CN109166004A (en) * | 2018-08-03 | 2019-01-08 | 贵州大学 | The product customization method of case-based reasioning |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN1629838A (en) | Method, apparatus and system for processing, browsing and information extracting of electronic document | |
| Pisani et al. | Does it pay to be a multinational? A large‐sample, cross‐national replication assessing the multinationality–performance relationship | |
| Domshlak et al. | To max or not to max: Online learning for speeding up optimal planning | |
| King et al. | Projecting future concentrations of atmospheric CO 2 with global carbon cycle models: The importance of simulating historical changes | |
| CN103454390B (en) | A kind of method and device of measuring dissolved oxygen concentration | |
| Ahakwa et al. | Do natural resources and green technological innovation matter in addressing environmental degradation? Evidence from panel models robust to cross-sectional dependence and slope heterogeneity | |
| CN110209790A (en) | Question and answer matching process and device | |
| CN107368613A (en) | Short text sentiment analysis method and device | |
| CN102737042A (en) | Method and device for establishing question generation model, and question generation method and device | |
| Bukhari et al. | Consequence of FDI on CO2 emissions in case of Pakistan | |
| CN111709244A (en) | Deep learning method for identifying causal relationship of contradictory dispute events | |
| CN109492081A (en) | Text information search and information interacting method, device, equipment and storage medium | |
| Li et al. | Arima model-based web services trustworthiness evaluation and prediction | |
| CN108280127A (en) | A kind of similar news duplicate checking of magnanimity selects method, system and device | |
| CN111444426A (en) | Technology recommendation method based on technology library | |
| CN112052166B (en) | Test case generation method and device based on domination relationship | |
| Zhu et al. | A crowdsourcing quality control model for tasks distributed in parallel | |
| Whitacre et al. | Credit assignment in adaptive evolutionary algorithms | |
| Asgharbeygi et al. | Inductive revision of quantitative process models | |
| Keele et al. | Time spent in Federal Court: US forest service land management litigation 1989–2008 | |
| RU2007144174A (en) | OPTIMIZATION OF DECISIONS CONCERNING NUMEROUS OBJECTS, IN THE PRESENCE OF VARIOUS FUNDAMENTAL UNCERTAINTY | |
| CN109743203B (en) | Distributed service security combination system and method based on quantitative information flow | |
| CN112419113A (en) | Foundation learning effect analysis method | |
| Alur et al. | Relating average and discounted costs for quantitative analysis of timed systems | |
| Park et al. | Evolving stochastic dispatching rules for order acceptance and scheduling via genetic programming |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |