CN111160802B - Method and device for evaluating preset scheme - Google Patents
Method and device for evaluating preset scheme Download PDFInfo
- Publication number
- CN111160802B CN111160802B CN201911421178.2A CN201911421178A CN111160802B CN 111160802 B CN111160802 B CN 111160802B CN 201911421178 A CN201911421178 A CN 201911421178A CN 111160802 B CN111160802 B CN 111160802B
- Authority
- CN
- China
- Prior art keywords
- event
- scene
- preset
- content
- evaluated
- 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.)
- Active
Links
Images
Classifications
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Document Processing Apparatus (AREA)
Abstract
The application provides a preset scheme evaluation method and a preset scheme evaluation device, wherein the preset scheme evaluation method comprises the following steps: acquiring a preset scheme to be evaluated; carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated; acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content; and scoring the treatment content according to a preset assessment index, and determining whether the preset scheme to be assessed is adopted according to a scoring result. Therefore, the technical problem that the operability and the practicability of the corresponding preset scheme are not comprehensive enough when the event is analyzed manually in the prior art is solved, the rationality of the preset scheme can be evaluated quickly through verification of the rationality or the completeness of the preset scheme, and the operability and the practicability of the preset scheme are improved.
Description
Technical Field
The present application relates to the field of information processing technologies, and in particular, to a method and an apparatus for evaluating a preset scheme.
Background
In actual life, corresponding preset schemes need to be given for emergencies such as typhoons and earthquakes, in the related art, corresponding preset schemes are given manually based on experience, and the operability and the practicability of the preset schemes are not comprehensive enough.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, a first objective of the present application is to provide a method for evaluating a preset scheme, which solves the technical problem in the prior art that the operability and the practicability of the corresponding preset scheme are not comprehensive enough when an event is analyzed manually, and can quickly evaluate the rationality of the preset scheme by verifying the rationality or completeness of the preset scheme, thereby improving the operability and the practicability of the preset scheme.
A second object of the present application is to provide a preset scenario evaluation apparatus.
A third object of the present application is to provide an electronic device.
A fourth object of the present application is to propose a non-transitory computer-readable storage medium.
A fifth object of the present application is to propose a calculation program.
In order to achieve the above object, an embodiment of a first aspect of the present application provides a method for evaluating a preset scheme, including: acquiring a preset scheme to be evaluated; carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated; acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content; and scoring the treatment content according to a preset assessment index, and determining whether the preset scheme to be assessed is adopted according to a scoring result.
Optionally, the obtaining of the preset scheme to be evaluated includes:
acquiring a target event, and generating an event scene corresponding to the target event;
obtaining scene description information corresponding to the event scene;
and generating a scene label according to the scene description information, and generating a preset scheme to be evaluated according to the scene label.
Optionally, the obtaining of the scenario description information corresponding to the event scenario includes: acquiring scene description information corresponding to the event scene input by a user; and/or selecting a preset description template to process the event scene to generate scene description information corresponding to the event scene.
Optionally, the obtaining the contextual index includes:
and identifying the scene description information through a semantic identification algorithm or a rule matching algorithm to obtain the scene index.
Optionally, before the inputting the contextual index and the structural content to be evaluated into a target contextual coping model for processing and generating a treatment content, the method further includes:
analyzing historical event data based on a knowledge graph to obtain an incidence relation rule between event loss data and treatment content;
and selecting an event loss data source corresponding to a target event, a rule condition type and standardized treatment content according to the incidence relation rule between the event loss data and the treatment content to generate the target scenario coping model corresponding to the target event.
Optionally, after the scoring processing is performed on the treatment content according to a preset evaluation index, the method further includes:
and if the scoring result is less than or equal to a preset threshold value, adjusting the treatment content.
The preset scheme evaluation method of the embodiment of the application obtains a preset scheme to be evaluated; carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated; acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content; and scoring the treatment content according to a preset assessment index, and determining whether the preset scheme to be assessed is adopted according to a scoring result. Therefore, the technical problem that in the prior art, corresponding preset scheme operability and practicability are not comprehensive enough when the event is analyzed manually is solved, the rationality of the preset scheme can be evaluated quickly through verification of the rationality or completeness of the preset scheme, and therefore the operability and the practicability of the preset scheme are improved.
In order to achieve the above object, a second aspect of the present application provides a preset solution evaluating apparatus, including: the first acquisition module is used for acquiring a preset scheme to be evaluated; the first generation module is used for carrying out structural processing on the scheme to be evaluated to generate structural content to be evaluated; the second acquisition module is used for acquiring the scene indexes; the processing module is used for inputting the scene indexes and the to-be-evaluated structured content into a target scene response model for processing to generate disposal content; the scoring module is used for scoring the treatment content according to a preset evaluation index; and the determining module is used for determining whether the preset scheme to be evaluated is adopted according to the scoring result.
Optionally, the first obtaining module includes:
the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a target event and generating an event scene corresponding to the target event;
a second obtaining unit, configured to obtain scenario description information corresponding to the event scenario;
and the generating unit is used for generating a scene label according to the scene description information and generating a preset scheme to be evaluated according to the scene label.
Optionally, the second obtaining unit is specifically configured to:
acquiring scene description information corresponding to the event scene input by a user; and/or the presence of a gas in the atmosphere,
and selecting a preset description template to process the event scene to generate scene description information corresponding to the event scene.
Optionally, the second obtaining module is specifically configured to:
and identifying the scene description information through a semantic identification algorithm or a rule matching algorithm to obtain the scene index.
Optionally, the apparatus further comprises:
the third acquisition module is used for analyzing historical event data based on the knowledge graph and acquiring an incidence relation rule between the event loss data and the handling content;
and the second generation module is used for selecting an event loss data source corresponding to the target event, a rule condition type and treatment content according to the incidence relation rule between the event loss data and the treatment content to generate the target scenario coping model corresponding to the target event.
Optionally, the apparatus further comprises:
and the adjusting module is used for adjusting the handling content if the scoring result is less than or equal to a preset threshold value.
The preset scheme evaluation device of the embodiment of the application acquires a preset scheme to be evaluated; carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated; acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content; and scoring the treatment content according to a preset assessment index, and determining whether the preset scheme to be assessed is adopted according to a scoring result. Therefore, the technical problem that in the prior art, corresponding preset scheme operability and practicability are not comprehensive enough when the event is analyzed manually is solved, the rationality of the preset scheme can be evaluated quickly through verification of the rationality or completeness of the preset scheme, and therefore the operability and the practicability of the preset scheme are improved.
To achieve the above object, an embodiment of a third aspect of the present application provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the method for pre-set solution evaluation as described in the above embodiments of the first aspect.
To achieve the above object, a fourth aspect of the present application provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the preset scenario evaluation method according to the first aspect of the present application.
To achieve the above object, an embodiment of a fifth aspect of the present application provides a computer program product, wherein when instructions in the computer program product are executed by a processor, a preset scheme evaluation method is performed.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flow chart illustrating a method for evaluating a default scenario according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating another method for evaluating a default scenario provided in an embodiment of the present application;
FIG. 3 is a diagram illustrating a method for evaluating a default scenario according to an embodiment of the present disclosure;
FIG. 4 is a diagram illustrating another method for evaluating a default scenario provided in an embodiment of the present application;
FIG. 5 is a schematic structural diagram of an apparatus for evaluating a default scenario according to an embodiment of the present disclosure;
FIG. 6 is a schematic structural diagram of another preset solution evaluating apparatus provided in an embodiment of the present application;
FIG. 7 is a schematic structural diagram of another preset solution evaluating apparatus provided in the embodiment of the present application;
fig. 8 is a schematic structural diagram of another preset-scheme evaluation apparatus according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative and intended to explain the present application and should not be construed as limiting the present application.
A preset scenario evaluation method and apparatus according to an embodiment of the present application are described below with reference to the drawings.
Fig. 1 is a schematic flow chart of a method for evaluating a default scenario provided in an embodiment of the present application.
As shown in fig. 1, the preset recipe evaluating method includes the steps of:
Specifically, a preset scheme to be evaluated may be determined first, and the target event scenario may be evaluated in all directions, or a current preset scheme may be simulated first, and it is verified whether the current preset scheme satisfies the capability of dealing with the scenario, so as to evaluate the preset scheme.
That is, there are many ways to obtain the preset scheme to be evaluated, and as an example, the preset scheme to be evaluated selected by the user is directly received; as another example, a target event is acquired, an event scenario corresponding to the target event is generated, scenario description information corresponding to the event scenario is acquired, a scenario label is generated according to the scenario description information, and a preset scheme to be evaluated is generated according to the scenario label.
It can be understood that preset schemes corresponding to different events are different, and preset schemes corresponding to the same event at different stages of occurrence are also different, for example, preset schemes corresponding to two events of typhoon and earthquake are different, and preset schemes corresponding to typhoon before typhoon or typhoon with different wind levels in different areas and different time periods are also different, for example, for eight-level typhoon, the generated preset schemes are respectively evacuation of residents in a prediction range before how many hours before typhoon, and prediction schemes such as strengthening wind and rain prevention work at a preset place, or prediction schemes such as predicting the number of injured people, the number of trapped people, and the like during typhoon landing, and calling goods and materials are also used.
And 102, carrying out structural processing on the scheme to be evaluated to generate structural content to be evaluated.
And 103, acquiring the scene indexes, inputting the scene indexes and the structured content to be evaluated into a target scene coping model for processing, and generating the disposal content.
Specifically, after the scheme to be evaluated is obtained, structured processing is performed to generate structured content to be evaluated, such as time, place, specific occurrence content and the like, for example, when the scheme to be evaluated is a typhoon landing, the place a, the number of injured people N, the number of trapped people M and the like.
The handling content can be the content such as the number of rescue teams and rescue goods and materials.
It can be understood that there are many ways to obtain the contextual indexes, and as an example, the contextual indexes are obtained by identifying the contextual description information through a semantic identification algorithm or a rule matching algorithm; as another example, all contextual indicators involved in the preset scheme are associated according to the structured content to be evaluated.
And step 104, performing grading processing on the processing content according to a preset evaluation index, and determining whether a preset scheme to be evaluated is adopted or not according to a grading result.
Specifically, the preset evaluation index may be set as needed, and as a possible implementation manner, the evaluation index is produced through the to-be-evaluated structured content, and the method includes: association rules of the scenario indexes and the disposal contents, performability of disposal procedures, reasonability of disposal contents and the like.
Further, the processing content is graded according to preset evaluation indexes, whether a preset scheme to be evaluated is adopted or not is determined according to the grading result, as an example, different weights are set for different indexes, the scores obtained by each index are weighted and summed to obtain the grading result, and whether the preset scheme to be evaluated is adopted or not is further determined according to the comparison between the grading result and a preset threshold value.
It should be noted that, if the scoring result is less than or equal to the preset threshold, the handling content needs to be adjusted, so as to further improve the effectiveness of the handling content.
The method for evaluating the preset scheme of the embodiment of the application acquires the preset scheme to be evaluated; carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated; acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content; and grading the treatment content according to a preset evaluation index, and determining whether to adopt the preset scheme to be evaluated according to a grading result. Therefore, the technical problem that in the prior art, corresponding preset scheme operability and practicability are not comprehensive enough when the event is analyzed manually is solved, the rationality of the preset scheme can be evaluated quickly through verification of the rationality or completeness of the preset scheme, and therefore the operability and the practicability of the preset scheme are improved.
Fig. 2 is a schematic flow chart of another method for evaluating a default scenario provided in an embodiment of the present application.
As shown in fig. 2, the preset recipe evaluating method includes the steps of:
Specifically, different target events can be simulated according to the target event which actually occurs as the target event, each moment of the target event can be used as an event scenario, so that event scenarios corresponding to the target event can be generated, for example, a scenario of one hour of earthquake occurrence, a scenario of two hours of earthquake occurrence, and the like, scenario description information corresponding to the event scenarios is obtained, for example, a scenario description information location a corresponding to a scenario of one hour of earthquake occurrence has house collapse, a location B has earthquake sensation, a resident condition, a rescue condition, and the like, scenario labels such as locations, injuries, supplies, and the like are generated according to the scenario description information, and a preset scheme to be evaluated is generated according to the scenario labels.
The preset scheme to be evaluated is generated according to the scene tags, and it can be understood that the best matching preset scheme is obtained according to the characteristics of the preset scheme, including the application area of the preset scheme, the type of the preset scheme aiming at the event and the preset scheme tags.
The method includes acquiring scenario description information corresponding to an event scenario in a plurality of ways, and acquiring scenario description information corresponding to the event scenario input by a user as an example; as another example, a preset description template is selected to process an event scenario to generate scenario description information corresponding to the event scenario.
Specifically, after the scheme to be evaluated is obtained, structured processing is performed to generate structured content to be evaluated, such as time, place, specific occurrence content and the like, for example, when the scheme to be evaluated is a typhoon landing, the place a, the number of injured people N, the number of trapped people M and the like.
And step 203, identifying the scene description information through a semantic identification algorithm or a rule matching algorithm to obtain a scene index.
Specifically, a semantic recognition algorithm or a rule matching algorithm is mainly adopted to recognize scene description information to obtain scene indexes, and if part of contents in the scene description cannot be intelligently recognized or recognition results need to be adjusted, the scene indexes can be manually adjusted, so that the effectiveness and accuracy of subsequent processing are further improved.
And step 204, analyzing historical event data based on the knowledge graph, and acquiring an association relation rule between the event loss data and the handling content.
And step 205, selecting an event loss data source corresponding to the target event, a rule condition type and standardized handling content according to the incidence relation rule between the event loss data and the handling content to generate a target scenario coping model corresponding to the target event.
Specifically, historical target event professional data, industry experience and project experience can be analyzed by means of a knowledge graph technology, and standardized association relation rules of disaster loss data and disposal content data are obtained.
Further, as shown in fig. 3, 2) start to create a disaster scenario rule, and establish a normalized association relationship between disaster damage data and disposal content data, 3) define rule input conditions and select standardized disaster damage data sources, 4) select a rule condition type, which is mainly a description of disaster conditions, such as injury population >300, where >300 are rule condition types, 5) define rule output results and select standardized disposal content, and associate the conditions and the results, 6) complete creation of scenario rules for a certain type of target event according to steps of 2) -5), and 7) package 6) data by event type, each event type corresponds to one target scenario coping model, and thus, an event damage data source, a rule condition type, and standardized disposal content corresponding to a target event can be selected to generate a target scenario coping model corresponding to the target event.
And step 206, inputting the scene indexes and the structured content to be evaluated into the target scene coping model for processing, and generating the disposal content.
And step 207, scoring the treatment content according to a preset evaluation index, and determining whether a preset scheme to be evaluated is adopted according to a scoring result.
In step 208, if the scoring result is less than or equal to the preset threshold, the processing content is adjusted.
Specifically, the preset evaluation index may be set as needed, and as a possible implementation manner, the evaluation index is produced through the to-be-evaluated structured content, including: association rules of the scenario indexes and the disposal contents, performability of disposal procedures, reasonability of disposal contents and the like.
Further, the treatment content is scored according to preset evaluation indexes, whether a preset scheme to be evaluated is adopted or not is determined according to scoring results, as an example, different weights are set for different indexes, scores obtained by each index are weighted and summed to obtain a scoring result, and whether the preset scheme to be evaluated is adopted or not is further determined according to comparison of the scoring result and a preset threshold value.
It should be noted that, if the scoring result is less than or equal to the preset threshold, the handling content needs to be adjusted, so as to further improve the effectiveness of the handling content.
In order to make the above process more clear to those skilled in the art, the following example is detailed in conjunction with fig. 4:
specifically, the user may first determine a preset scheme to be evaluated, perform all-around evaluation on the preset scheme, or first simulate a target event scenario, verify whether the preset scheme currently owned satisfies the capability of coping with the scenario, and implement evaluation on the preset scheme.
For example, when the event scenario is XX years, X months, X days, X, and X occurs 7-level earthquake at the place Y, 30 people die, a large number of people are injured, and economic loss is serious, and according to the structured content of the preset scheme, the recommended preset scheme is as follows: the earthquake emergency preset scheme of the province Y and the I-level response starting are as follows: disaster areas, dead population, injured population, economic loss and the like, wherein the structured content of the preset scheme comprises the following contents: emergency response standard module, group build organizational structure module, emergency treatment module, recover module etc. after the calamity, wherein, emergency treatment module has contains many submodules, for example medical rescue module, buried pressure population search and rescue module, the sparse module in key spot, for example: the buried population search and rescue module comprises aiming disaster loss, disposal tasks, disposal contents, carrying equipment materials, rescue force, resource quantity, rescue force quantity and the like.
Further, treatment content is automatically recommended according to the contextual indexes and the preset scheme structured content, and evaluation indexes are generated according to the associated structured preset scheme content and contextual indexes, for example, relevant indexes of the rationality of the treatment content include: whether the carrying equipment is reasonable or not, whether the dispatching rescue team is reasonable or not and whether the rescue team capacity is reasonable or not are judged, scoring is carried out according to obtained scene indexes, scoring weights of different indexes are different, and finally the capacity of the preset scheme for dealing with the scene is evaluated according to scoring results.
Scene one: the user can determine the preset scheme to be evaluated first, and the comprehensive evaluation is carried out on the preset scheme.
1) Selecting a preset scheme to be evaluated;
2) Creating an event scenario, namely simulating different target events according to actually occurring target events (namely emergencies), wherein each moment of the target events can be used as an event scenario;
3) Inputting event and scene description information, wherein a user can completely self-define the input scene description information, and can also select a description template (the template defines the description format, the content of each field, commonly-used description sentences and commonly-used vocabularies) to quickly generate the scene description information based on the template;
4) Associating all scene indexes related to the preset scheme according to the structured content of the preset scheme;
5) According to the event situation information, the system can intelligently identify situation indexes (the situation indexes are used for structurally depicting the event situation), and the intelligent identification is mainly completed by adopting a semantic identification algorithm or a rule matching algorithm; if some contents in the description can not be intelligently identified or the identification result needs to be adjusted, the user can manually adjust the scene indexes;
6) Automatically recommending the disposal content according to the scene indexes and the preset scheme structured content (the automatic recommendation is mainly realized by matching the scene indexes), so that the disposal content aiming at the event scene is automatically matched;
7) Presetting content production evaluation indexes structured by a scheme, wherein the content production evaluation indexes comprise association rules of scene indexes and disposal contents, disposal flow performability, the rationality of the disposal contents and the like;
8) Judging the rationality of the treatment content generated in the step 6) by combining the evaluation index, for example, obtaining an evaluation result in a manual scoring mode, and feeding back unreasonable content in a commenting mode, so that the preset scheme content can be optimized in a targeted manner.
9) And evaluating the preset scheme by simulating a plurality of different event scenes, namely, repeating the processes from 2) to 8) for a plurality of times to finish the evaluation of the preset scheme.
Scene two: the user can simulate the target event scene firstly, verify whether the current preset scheme meets the capability of dealing with the event scene, and realize the evaluation of the preset scheme.
1) Creating an event scene, namely simulating different target events according to the actually occurring target events, wherein each moment of the target events can be used as an event scene;
2) Inputting event scene description information, wherein a user can completely self-define the input scene description information, and can also select a description template (the template defines the description format, the contents of each field, commonly-used description sentences and commonly-used vocabularies) to quickly generate the scene description information based on the template;
3) Inputting a scene label aiming at the current description scene information;
4) Automatically matching a preset scheme to be evaluated according to the scene label (according to the characteristics of the preset scheme, including the application area of the preset scheme, the preset scheme aiming at the event type and the preset scheme label, intelligently matching to obtain the best matched preset scheme), and if the automatically matched preset scheme does not meet the requirements of the user, manually adjusting the user to the preset scheme to be evaluated;
5) The subsequent operation steps are generally implemented in scenario one, and repeated description is not repeated.
Therefore, the disaster situation and the corresponding disposal content are modeled through the rule engine, the corresponding relation is established, different target events are simulated according to different depicted event situations, the situation triggers the preset scheme, the related disposal content is automatically matched through the rule preset scheme, the structural description of the disposal content serves as the evaluation content, the preset scheme evaluation model is established, the similarity calculation is carried out on the preset scheme content extracted based on the event portrait and the case content, the preset scheme evaluation work is completed, the user is helped to quickly evaluate the rationality of the preset scheme, and therefore the operability and the practicability of the preset scheme are improved.
The embodiment of the application also provides a preset scheme evaluation device.
Fig. 5 is a schematic structural diagram of a preset scenario evaluation apparatus according to an embodiment of the present application.
As shown in fig. 5, the preset-scenario evaluation apparatus includes: a first obtaining module 501, a first generating module 502, a second obtaining module 503, a processing module 504, a scoring module 505, and a determining module 506, wherein:
a first obtaining module 501, configured to obtain a preset scheme to be evaluated.
A first generating module 502, configured to perform a structuring process on the scheme to be evaluated to generate a structured content to be evaluated.
A second obtaining module 503, configured to obtain the contextual index.
The processing module 504 is configured to input the scenario indicator and the to-be-evaluated structured content into a target scenario handling model for processing, and generate a disposal content.
And a scoring module 505, configured to score the treatment content according to a preset evaluation index.
A determining module 506, configured to determine whether to adopt the preset scheme to be evaluated according to the scoring result.
In an embodiment of the present application, based on fig. 5, as shown in fig. 6, the first obtaining module 501 includes: the first acquiring unit 5011, the second acquiring unit 5012, and the generating unit 5013.
The first acquiring unit 5011 is configured to acquire a target event and generate an event scenario corresponding to the target event.
The second obtaining unit 5012 is configured to obtain context description information corresponding to the event context.
The generating unit 5013 is configured to generate a scenario label according to the scenario description information, and generate a preset scheme to be evaluated according to the scenario label.
In an embodiment of the present application, the second obtaining unit 5012 is specifically configured to: acquiring scene description information corresponding to the event scene input by a user; and/or selecting a preset description template to process the event situation to generate situation description information corresponding to the event situation.
In an embodiment of the present application, the second obtaining module 503 is specifically configured to: and identifying the scene description information through a semantic identification algorithm or a rule matching algorithm to obtain the scene index.
In an embodiment of the present application, on the basis of fig. 5, as shown in fig. 7, the apparatus may further include: a third obtaining module 507 and a second generating module 508.
And a third obtaining module 507, configured to analyze historical event data based on a knowledge graph, and obtain an association rule between event loss data and treatment content.
A second generating module 508, configured to select, according to the association relation rule between the event loss data and the treatment content, an event loss data source corresponding to the target event, a rule condition type, and the treatment content, and generate the target scenario coping model corresponding to the target event.
In an embodiment of the present application, on the basis shown in fig. 6, as shown in fig. 8, the apparatus may further include: an adjustment module 509.
An adjusting module 509, configured to adjust the handling content if the scoring result is less than or equal to a preset threshold.
It should be noted that the explanation of the embodiment of the preset scheme evaluation method is also applicable to the preset scheme evaluation device of the embodiment, and is not repeated herein.
The preset scheme evaluation device of the embodiment of the application acquires a preset scheme to be evaluated; carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated; acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content; and grading the treatment content according to a preset evaluation index, and determining whether to adopt the preset scheme to be evaluated according to a grading result. Therefore, the technical problem that in the prior art, corresponding preset scheme operability and practicability are not comprehensive enough when the event is analyzed manually is solved, the rationality of the preset scheme can be evaluated quickly through verification of the rationality or completeness of the preset scheme, and therefore the operability and the practicability of the preset scheme are improved.
In order to implement the foregoing embodiments, an embodiment of the present application further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to:
acquiring a preset scheme to be evaluated;
carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated;
acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content;
and scoring the treatment content according to a preset assessment index, and determining whether the preset scheme to be assessed is adopted according to a scoring result.
In order to implement the foregoing embodiments, the present application further proposes a non-transitory computer-readable storage medium, on which a computer program is stored, the program being executed by a processor to:
acquiring a preset scheme to be evaluated;
carrying out structuring processing on the scheme to be evaluated to generate structured content to be evaluated;
acquiring a scene index, inputting the scene index and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content;
and scoring the treatment content according to a preset assessment index, and determining whether the preset scheme to be assessed is adopted according to a scoring result.
A computer program product is disclosed in which instructions, when executed by a processor, perform a preset scenario evaluation method.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Further, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following technologies, which are well known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A method for evaluating a predetermined solution, comprising the steps of:
generating an event scenario corresponding to a target event according to the target event, and acquiring a preset scheme to be evaluated according to scenario description information corresponding to the event scenario, wherein the target event comprises a natural disaster event;
carrying out structural processing on the preset scheme to be evaluated to generate structural content to be evaluated, wherein the structural content to be evaluated comprises the occurrence time, the occurrence place and the occurrence content of the natural disaster event;
identifying the scene description information through a semantic identification algorithm or a rule matching algorithm to obtain scene indexes, inputting the scene indexes and the to-be-evaluated structured content into a target scene coping model for processing, and generating disposal content;
grading the processing content according to a preset evaluation index, and determining whether to adopt the preset scheme to be evaluated according to a grading result, wherein the preset evaluation index comprises a scene index and an association rule of the processing content, the performability of a processing flow and the reasonability of the processing content;
before the scenario indexes and the to-be-evaluated structured content are input into a target scenario coping model to be processed and processed to generate the treatment content, the method further comprises the following steps:
analyzing historical event data based on a knowledge graph to obtain an incidence relation rule between event loss data and handling content;
and selecting an event loss data source corresponding to a target event, a rule condition type and standardized treatment content according to the incidence relation rule between the event loss data and the treatment content to generate the target scenario coping model corresponding to the target event.
2. The method according to claim 1, wherein the generating an event scenario corresponding to the target event according to the target event and acquiring a preset scheme to be evaluated according to scenario description information corresponding to the event scenario includes:
acquiring a target event, and generating an event scene corresponding to the target event;
obtaining scene description information corresponding to the event scene;
and generating a scene label according to the scene description information, and generating a preset scheme to be evaluated according to the scene label.
3. The method of claim 2, wherein the obtaining of the context description information corresponding to the event context comprises:
acquiring scene description information corresponding to the event scene input by a user; and/or the presence of a gas in the gas,
and selecting a preset description template to process the event scene to generate scene description information corresponding to the event scene.
4. The method of claim 1, wherein after said scoring said treatment content according to a preset assessment index, further comprising:
and if the scoring result is less than or equal to a preset threshold value, adjusting the treatment content.
5. A preset-scenario evaluation apparatus, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for generating an event scene corresponding to a target event according to the target event and acquiring a preset scheme to be evaluated according to scene description information corresponding to the event scene, and the target event comprises a natural disaster event;
the first generation module is used for carrying out structural processing on the preset scheme to be evaluated to generate structural content to be evaluated, wherein the structural content to be evaluated comprises the occurrence time, the occurrence place and the occurrence content of the natural disaster event;
the second acquisition module is used for identifying the scene description information through a semantic identification algorithm or a rule matching algorithm to acquire scene indexes;
the third acquisition module is used for analyzing historical event data based on the knowledge graph and acquiring an incidence relation rule between event loss data and treatment content;
the second generation module is used for selecting an event loss data source, a rule condition type and treatment content corresponding to the target event according to the incidence relation rule between the event loss data and the treatment content to generate a target scenario coping model corresponding to the target event;
the processing module is used for inputting the scene indexes and the to-be-evaluated structured content into a target scene response model for processing to generate disposal content;
the scoring module is used for scoring the treatment content according to preset evaluation indexes, wherein the preset evaluation indexes comprise a contextual index and an association rule of the treatment content, the performability of a treatment process and the reasonability of the treatment content;
and the determining module is used for determining whether the preset scheme to be evaluated is adopted or not according to the scoring result.
6. The apparatus of claim 5, wherein the first obtaining module comprises:
the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a target event and generating an event scene corresponding to the target event;
a second obtaining unit, configured to obtain scenario description information corresponding to the event scenario;
and the generating unit is used for generating a scene label according to the scene description information and generating a preset scheme to be evaluated according to the scene label.
7. The apparatus of claim 6, wherein the second obtaining unit is specifically configured to:
acquiring scene description information corresponding to the event scene input by a user; and/or the presence of a gas in the gas,
and selecting a preset description template to process the event scene to generate scene description information corresponding to the event scene.
8. The apparatus of claim 5, further comprising:
and the adjusting module is used for adjusting the handling content if the scoring result is less than or equal to a preset threshold value.
9. An electronic device, comprising:
at least one processor; and a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the preset scenario evaluation method of any of the preceding claims 1-4.
10. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the preset scenario evaluation method according to any one of claims 1 to 4.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911421178.2A CN111160802B (en) | 2019-12-31 | 2019-12-31 | Method and device for evaluating preset scheme |
| PCT/CN2020/141794 WO2021136454A1 (en) | 2019-12-31 | 2020-12-30 | Preset solution evaluation method and apparatus |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911421178.2A CN111160802B (en) | 2019-12-31 | 2019-12-31 | Method and device for evaluating preset scheme |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111160802A CN111160802A (en) | 2020-05-15 |
| CN111160802B true CN111160802B (en) | 2023-02-28 |
Family
ID=70560636
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911421178.2A Active CN111160802B (en) | 2019-12-31 | 2019-12-31 | Method and device for evaluating preset scheme |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN111160802B (en) |
| WO (1) | WO2021136454A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111160802B (en) * | 2019-12-31 | 2023-02-28 | 清华大学 | Method and device for evaluating preset scheme |
| CN113077353B (en) * | 2021-04-22 | 2024-02-02 | 北京十一贝科技有限公司 | Method, device, electronic equipment and medium for generating nuclear insurance conclusion |
| CN113298383A (en) * | 2021-05-26 | 2021-08-24 | 凯美瑞德（苏州）信息科技股份有限公司 | Asset assessment method and device and electronic equipment |
| CN113822042B (en) * | 2021-08-10 | 2022-06-17 | 深圳市长亮科技股份有限公司 | Information processing method and device, storage medium and computing equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101840439A (en) * | 2010-05-25 | 2010-09-22 | 天津大学 | Emergency situation recommending method based on emergency incident and emergency response plan |
| CN106339971A (en) * | 2016-08-19 | 2017-01-18 | 贵州电网有限责任公司遵义供电局 | Emergency drilling management and assessment analysis system |
| CN110009475A (en) * | 2019-02-12 | 2019-07-12 | 平安科技（深圳）有限公司 | Risk checks method for monitoring, device, computer equipment and storage medium |
| CN110443571A (en) * | 2019-07-16 | 2019-11-12 | 阿里巴巴集团控股有限公司 | The method, device and equipment of knowledge based map progress resume assessment |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10671772B2 (en) * | 2015-09-04 | 2020-06-02 | Independent Energy Standards Corporation | Computer-implemented impact analysis of energy facilities |
| CN106682246A (en) * | 2015-11-05 | 2017-05-17 | 国家电网公司 | Graphical design platform for power grid emergency training schemes |
| CN106327402A (en) * | 2016-08-19 | 2017-01-11 | 贵州电网有限责任公司遵义供电局 | Emergency exercise management system |
| CN108121750B (en) * | 2016-11-30 | 2022-07-08 | 西门子公司 | Model processing method and device and machine readable medium |
| CN111160802B (en) * | 2019-12-31 | 2023-02-28 | 清华大学 | Method and device for evaluating preset scheme |
-
2019
- 2019-12-31 CN CN201911421178.2A patent/CN111160802B/en active Active
-
2020
- 2020-12-30 WO PCT/CN2020/141794 patent/WO2021136454A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101840439A (en) * | 2010-05-25 | 2010-09-22 | 天津大学 | Emergency situation recommending method based on emergency incident and emergency response plan |
| CN106339971A (en) * | 2016-08-19 | 2017-01-18 | 贵州电网有限责任公司遵义供电局 | Emergency drilling management and assessment analysis system |
| CN110009475A (en) * | 2019-02-12 | 2019-07-12 | 平安科技（深圳）有限公司 | Risk checks method for monitoring, device, computer equipment and storage medium |
| CN110443571A (en) * | 2019-07-16 | 2019-11-12 | 阿里巴巴集团控股有限公司 | The method, device and equipment of knowledge based map progress resume assessment |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2021136454A1 (en) | 2021-07-08 |
| CN111160802A (en) | 2020-05-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111160802B (en) | Method and device for evaluating preset scheme | |
| CN111145510B (en) | Alarm receiving processing method, device and equipment | |
| US20130218823A1 (en) | Method and system for analysing flight data recorded during a flight of an aircraft | |
| CN107256428B (en) | Data processing method, data processing device, storage equipment and network equipment | |
| KR102353545B1 (en) | Method and Apparatus for Recommending Disaster Response | |
| CN110674790B (en) | Abnormal scene processing method and system in video monitoring | |
| CN111160805A (en) | Emergency plan auxiliary information acquisition method, device and equipment | |
| CN104217216A (en) | Method and device for generating detection model, method and device for detecting target | |
| CN112036168A (en) | Event subject recognition model optimization method, device and equipment and readable storage medium | |
| EP3929800A1 (en) | Skill word evaluation method and device, electronic device, and computer readable medium | |
| CN115828112A (en) | Fault event response method and device, electronic equipment and storage medium | |
| Thomas et al. | Real-time prediction of severe influenza epidemics using Extreme Value Statistics | |
| CN116414990A (en) | Vehicle fault diagnosis and prevention method | |
| CN111813644A (en) | System performance evaluation method and device, electronic equipment and computer readable medium | |
| CN111860118A (en) | Human behavior analysis method based on artificial intelligence | |
| CN113807622A (en) | Event decision generation method and device, electronic equipment and storage medium | |
| CN110738077B (en) | Foreign matter detection method and device | |
| CN113435753A (en) | Enterprise risk judgment method, device, equipment and medium in high-risk industry | |
| CN117435999A (en) | Risk assessment method, apparatus, device and medium | |
| CN111611923B (en) | Emergency plan drilling evaluation method and device | |
| CN112069833A (en) | Log analysis method, log analysis device and electronic equipment | |
| CN110362828B (en) | Network information risk identification method and system | |
| CN112199805A (en) | Power transmission line hidden danger identification model evaluation method and device | |
| CN116542783A (en) | Risk assessment method, device, equipment and storage medium based on artificial intelligence | |
| CN113342978A (en) | City event processing method and device |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |