CN105956151A - Plan-based assistant decision-making method, tailing pond monitoring method and system - Google Patents
Plan-based assistant decision-making method, tailing pond monitoring method and system Download PDFInfo
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Abstract
The first purpose of the invention is to provide a plan-based assistant decision-making method. The plan-based assistant decision-making method comprises the following steps of: step A, establishing a case database; step B, inputting emergency events; step C, judging whether the emergency events belong to a plan database, if yes, then directly calling and processing, or else, going to the next step; step D, calculating the similarity of each attribute in the emergency events; and step E, calculating the total similarity of the emergency events, comparing the total similarity of the emergency events with a set threshold, and taking corresponding measures. The second purpose of the invention is to disclose a tailing pond monitoring method, which comprises an on-line monitoring system and the above-mentioned plan-based assistant decision-making method. The third purpose of the invention is to provide a tailing pond monitoring system. The method and monitoring system provided by the invention rationally use information in a case database, and perform assistant decision making on abnormalities occurring in the tailing pond and accident treatment, which can guarantee the safe operation of the tailing pond, and reduce the disaster loss of the tailing pond to the greatest extent.
Description
Technical field
The present invention relates to Tailings Dam on-line monitoring and contingency management technical field, be specifically related to a kind of auxiliary based on prediction scheme
Decision method, Tailings Dam monitoring method and system.
Background technology
Tailings Dam is one of critical facility of Mine Safety in Production, and at present, most domestic Tailings Dam is already installed on line
Monitoring system.Tailings Dam on-line monitoring technique, by development for many years, has defined the on-line monitoring scheme of complete set, existing
Tailings Dam on-line monitoring system main purpose be to realize collection and the displaying of data, consequently facilitating auxiliary monitoring Tailings Dam run
State.
Emergency preplan is the important component part of emergency system, is the important evidence of Emergency decision, and current emergency preplan is big
Part exists in the form of text, and the level of informatization is low, and the digitized research of emergency preplan in the last few years and application have obtained necessarily
Development.
There is following defect in the monitoring of Tailings Dam: how when Tailings Dam monitoring notes abnormalities, joins with emergency preplan now
Dynamic, ensure the safe operation of Tailings Dam；How when accident occurs, aid decision and emergency disposal, at utmost lower mine tailing
Storehouse casualty loss.
In sum, being badly in need of one in industry assists existing on-line monitoring system to obtain data and conjunction the most accurately
The solution that exception and the accident of Tailings Dam appearance are processed by reason is to solve problems of the prior art.
Summary of the invention
The first object of the present invention is to provide a kind of aid decision-making method based on prediction scheme, comprises the following steps:
Step A: set up case database；
Step B, emergency event input；
Step C, to step B input emergency event be analyzed identify and obtain each attribute of emergency event description or
Measure；If emergency event belongs to case (i.e. emergency event and the case phase in case database in case database
With), then directly invoke prediction scheme scheme and carry out aid decision support；If the case that emergency event is not belonging in case database is (i.e.
Emergency event differs with the case in case database), then carry out next step；
The respective similarity of each attribute in step D, calculating emergency event；
Step E, total similarity of calculating emergency event, compare the threshold value of total similarity of emergency event with setting
Relatively, if total similarity of emergency event is more than or equal to the threshold value set, then directly invokes emergency planning method and carry out aid decision support；
If total similarity of emergency event is less than the threshold value set, then make inferences based on prediction scheme.
In above technical scheme preferably, the attribute of described emergency event includes event title, type, position, grade, shadow
The degree of sound, business reasons, time and place.
In above technical scheme preferably, in described step D the computational methods of similarity include the first computational methods and
The second computational methods, the first computational methods described specifically: for the Euclidean distance side of Numeric Attributes code requirement
Method, specially expression formula 1):
Wherein, f1(x y) is the similarity of a certain attribute；X is a certain attribute event value, and y is that a certain attribute case takes
Value；Max and min be respectively a certain attribute all prediction scheme property values in maximum and minima；
Described the second computational methods are specifically: use degree of overlapping metering method for character attibute, specifically use expression formula
2):
Wherein: f2(x y) is the similarity of a certain attribute；X is a certain attribute event value, and y is that a certain attribute case takes
Value.
In above technical scheme preferably, in described step E, total similarity of emergency event passes through the Boolean Model of extension
Obtain, the expression formula of the Boolean Model of extension such as expression formula 3):
Wherein: d is source case, qandFor retrieval type logical AND, sim (qand, it is d) that emergency event is the most similar to prediction scheme
Degree, total similarity ∈ [0,1], it is closer to 1 and shows that prediction scheme coupling is the best；xmThe similarity of m-th attribute, а in expression eventm
Represent the importance degree of m-th attribute；P represents the degree that between project, logical relation is strict, and value is 1 the most loose, and value is infinite greatly
The tightest.
In above technical scheme preferably, the threshold value that total similarity of described emergency event sets is as 0.9；
The described concrete grammar that makes inferences based on prediction scheme is: first by respective for each attribute of emergency event of calculating
Similarity is ranked up, then using case method maximum for the similarity of attribute as adaptive case method, finally by local
Replacement and parameter adjustment reach the adaptation of case.
The aid decision-making method based on prediction scheme that the present invention uses, has following technical effect that (1) Appropriate application case library
In information, exception and accident treatment that Tailings Dam occur carry out aid decision, ensure the safe operation of Tailings Dam, maximum
Degree lowers Tailings Dam casualty loss；(2) Boolean Model that extends obtains the similarity of attribute in emergency event, convenience of calculation and
Precision is high；(3) emergency event attribute use event title, type, position, grade, influence degree and specifically describe into
Line description and tolerance, improve fact retrieval, adaptive precision；(4) method of reasoning generation case is simplified, and is prone to behaviour
Make, improve precision event being judged and processing further.
The second object of the present invention is open a kind of Tailings Dam monitoring method, is included in line monitoring system and with described
Above-mentioned based on prediction scheme the aid decision-making method that on-line monitoring system is used in combination, specifically includes following steps:
The first step, Tailings Dam on-line monitoring system online monitoring data；
Second step, the online data obtaining the first step are analyzed, it is judged that whether data exceed setting value, if it has not,
Then continue monitoring；
If it has, then obtain alarm level and report to the police, the aid decision-making method based on prediction scheme described in use simultaneously
Event is processed.
In order to reach superior technique effect, before applying aid decision-making method based on prediction scheme that event is processed also
Including emergency monitoring process, described emergency monitoring process specifically:
Data by emergent monitoring system on-line monitoring Tailings Dam；The data obtained are analyzed；Judge that data are
No beyond setting value, if it has not, then cancel warning；
If it has, then obtain alarm level and report to the police, the aid decision-making method based on prediction scheme described in use simultaneously
Event is processed.
In above technical scheme preferably, the condition that described emergency monitoring process starts is:
When power interruptions or communication disruption occurs in on-line monitoring system, starting emergency power supply, emergency power supply controls simultaneously
Emergency communication system starts local radio communication module, sends data from trend centre data subsystem after startup；
Or, after starting emergency monitoring when the alert levels in second step is higher than the alarm threshold value set, automatically encrypt
All kinds of Monitoring Data monitoring frequencies, support artificial setpoint frequency simultaneously；Monitoring Data realizes local and remote backed up in synchronization；
Or, when starting when reporting to the police, on-line monitoring system selects photographic head nearby, and specifies it according to monitored object feature
Monitoring orientation, carries out key monitoring.
In order to reach superior technique effect, while the data of on-line monitoring system on-line monitoring Tailings Dam, also include people
The work data to monitoring Tailings Dam, are analyzed for the data being monitored on-line monitoring system.
The Tailings Dam monitoring method of the application present invention, organically combines on-line monitoring with emergent aid decision, and the most pre-
Case starts method and flow process, and exception and accident that Tailings Dam occur rationally process, and ensure the safe operation of Tailings Dam,
At utmost lower Tailings Dam casualty loss；Emergency monitoring process and the artificial data to monitoring Tailings Dam, improve further
Monitoring and the precision to event handling.
The third object of the present invention is to provide a kind of Tailings Dam monitoring system, including online data perception and transport layer,
Data management analysis and issue layer, pre-alarm management level and program management and aid decision layer；
Described online data perception and transport layer are by Tailings Dam displacement, saturation, reservoir level, Gan Tan, rainfall, seepage flow
Amount and video surveillance obtain the real-time running state data of Tailings Dam；
The data received are carried out storing, manage, analyze and issuing by described data management analysis and issue layer, and coordinate
Data stream is called control by each subsystem；
Described pre-alarm management level are according to the data received and Safety of Tailings Dam monitoring and warning, centre data subsystem
Automatically data analysis, judgement are carried out, it is achieved classifying alarm；
Described program management and aid decision layer are used for formulating system response level mechanism, it is achieved alarm plan links；Will
The emergency preplan editted is expressed as computer can be with the form identified, behaviour part message structure of going forward side by side；Set up for prediction scheme
Digitized emergency plan model, realizes orderly management to contingency management work.
The Tailings Dam monitoring system of the application present invention, has the effect that (1) is based on technology of Internet of things, intelligent sensing skill
Art, communication and multimedia information technology, database technology etc. realize sensor data acquisition, graphical representation, forewarning management etc.
Problem；(2) system is monitored data analysis automatically, and when monitoring result exceedes the warning value of default, system is reported automatically
Alert prompting；Pre-alarm system can judge alert event rank according to alarm mechanism, and simultaneity factor supports the contrast of artificial Monitoring Data
Analyze；(3) alert event grade judges, alert event in retrieval prediction scheme, calls or generate new emergency preplan, application after coupling
In emergent aid decision；(4) when alert event rank reaches emergency monitoring grade, system start-up emergency monitoring.
In addition to objects, features and advantages described above, the present invention also has other objects, features and advantages.
Below with reference to figure, the present invention is further detailed explanation.
Accompanying drawing explanation
The accompanying drawing of the part constituting the application is used for providing a further understanding of the present invention, and the present invention's is schematic real
Execute example and illustrate for explaining the present invention, being not intended that inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the structural representation of the Tailings Dam monitoring method of the preferred embodiment of the present invention 1；
Fig. 2 is the structural representation of aid decision-making method based on prediction scheme in Fig. 1.
Detailed description of the invention
Below in conjunction with accompanying drawing, embodiments of the invention are described in detail, but the present invention can limit according to claim
Multitude of different ways that is fixed and that cover is implemented.
Embodiment 1:
Seeing Fig. 1, a kind of Tailings Dam monitoring system, including online data perception and transport layer, data management analysis and send out
Layer of cloth, pre-alarm management level and program management and aid decision layer.
Described online data perception and transport layer are by Tailings Dam displacement, saturation, reservoir level, Gan Tan, rainfall, seepage flow
Amount and video surveillance obtain the real-time running state information of Tailings Dam, and send data to data management analysis and issue
Layer.
The data received are carried out storing, manage, analyze and issuing by described data management analysis and issue layer, and coordinate
Data stream is called control by each subsystem.
Described pre-alarm management level are according to the data received and Safety of Tailings Dam monitoring and warning, centre data subsystem
Automatically data analysis, judgement are carried out, it is achieved classifying alarm.
Described program management and aid decision layer are used for formulating system response level mechanism, it is achieved alarm plan links；Will
The emergency preplan editted is expressed as computer can be with the form identified, behaviour part message structure of going forward side by side；Set up for prediction scheme
Digitized emergency plan model, realizes orderly management to contingency management work.
The method that the Tailings Dam monitoring system of Application Example carries out on-line monitoring, Details as Follows:
The first step, Tailings Dam on-line monitoring system online monitoring data；The most also include personal monitoring's data, be used for
The data being monitored on-line monitoring system are analyzed.
Second step, the online data obtaining the first step are analyzed, it is judged that whether beyond setting value, (i.e. data are data
No transfinite), if it has not, then continue monitoring；
If it has, then obtain alarm level and report to the police, use aid decision-making method based on prediction scheme to event simultaneously
Process, or: enable emergent monitoring system and Tailings Dam be monitored, specifically:
Data by emergent monitoring system on-line monitoring Tailings Dam；The data obtained are analyzed；Judge that data are
No beyond setting value, if it has not, then cancel warning；
If it has, then obtain alarm level and carry out secondary warning, use aid decision-making method pair based on prediction scheme simultaneously
Event processes.
Apply aid decision-making method based on prediction scheme before event is processed, also to include emergency monitoring process, described should
Suddenly monitoring process is specifically: by the data of emergent monitoring system on-line monitoring Tailings Dam；The data obtained are analyzed；Sentence
Whether disconnected data are beyond setting value, if it has not, then cancel warning；If it has, then obtain alarm level and report to the police, make simultaneously
With described aid decision-making method based on prediction scheme, event is processed.
The condition that described emergency monitoring process starts is: when power interruptions or communication disruption occurs in on-line monitoring system,
Starting emergency power supply, emergency power supply controls emergency communication system and starts local radio communication module, after startup in trend simultaneously
Heart data subsystem sends data；Or, after the alert levels in second step is higher than the alarm threshold value set, start emergent prison
Survey, more automatically encrypt all kinds of Monitoring Data monitoring frequencies, support artificial setpoint frequency simultaneously；Monitoring Data realizes local and remote
Backed up in synchronization；Or, when starting when reporting to the police, on-line monitoring system selects photographic head nearby, and specifies according to monitored object feature
It monitors orientation, carries out key monitoring.
Use aid decision-making method based on prediction scheme that event is processed, herein aid decision-making method based on prediction scheme tool
Body is as follows:
Step A: set up case database, described case database mainly stores event attribute information, solution information
With evaluation of result information, case database by attribute list, event type table, event class table, influence degree table, coverage with
And reason table composition.The step setting up case database includes: case database design, data base organization, database development, than
As case database includes five cases (case 1, case 2, case 3, case 4 and case 5), refer to table 2 and table 3.
Step B, emergency event input, and this illustrates as a example by 2 emergency events, and event 1 is total phase of emergency event
Be more than or equal to the event of threshold value like degree, event 2 is total similarity event less than threshold value of emergency event.
Step C, the emergency event inputting step B are analyzed identifying and obtaining the description (attribute of its internal attribute
Including event title, type, position, grade, influence degree, business reasons, time and place etc.) in actual application, attribute
Description be referred to table 1 below:
The descriptive statistics table of the attribute of table 1 event
(whether emergency event belongs to the judgement of case database for the case that is not admitted in prediction scheme storehouse because of event 1 and event 2
Mode is: if each attribute description of emergency event is the most identical with each attribute description of the case in case database, then sentence
Determine the case that emergency event belongs in case database；Otherwise, emergency event is not belonging to the case in case database), therefore,
Enter next step.
Step D, calculate each attributes similarity of emergency event, the computational methods of similarity include the first computational methods and
The second computational methods, the first computational methods described specifically: for the Euclidean distance side of Numeric Attributes code requirement
Method, specially expression formula 1):
Wherein, f1(x y) is the similarity of a certain attribute；X is a certain attribute event value, and y is that a certain attribute case takes
Value；Max and min be respectively a certain attribute all prediction scheme property values in maximum and minima；
Described the second computational methods are specifically: use degree of overlapping metering method for character attibute, specifically use expression formula
2):
Wherein: f2(x y) is the similarity of a certain attribute；X is a certain attribute event value, and y is that a certain attribute case takes
Value.
In event 1, the similarity of each attribute refers to table 2, and in event 2, the similarity of each attribute refers to table 3.
Step E, according to extension Boolean Model total similarity of emergency event is calculated, refer to table 2 and table 3, institute
The Boolean Model stating extension specifically uses expression formula 3) obtain total similarity in emergency event, the Boolean Model of described extension is concrete
Use expression formula 3):
Wherein: d is source case, qandFor retrieval type logical AND, sim (qand, it is d) that emergency event is the most similar to prediction scheme
Degree, total similarity ∈ [0,1], it is closer to 1 and shows that prediction scheme coupling is the best；xmThe similarity of m-th attribute, а in expression eventm
Represent the importance degree of m-th attribute；P represents the degree that between project, logical relation is strict, value 2.
The similarity of table 2 each attribute of event 1 and total similarity statistical table
The similarity of table 3 each attribute of event 2 and total similarity statistical table
From table 2 and table 3, a is the relative Link Importance of each attribute that experience draws, event type, position are similar to event
Degree coupling impact is relatively small, and importance degree is relatively low；Similarity weights coupling is affected big, then by position, grade, influence degree
Its importance degree is high.
For event 1, it is more than, with total similarity of case 1, the threshold value set, then directly invokes case 1 side in prediction scheme storehouse
Method carries out aid decision support.
For event 2, because its total similarity with all cases is respectively less than the threshold value set, then: (1) by table 3 each
Individual attributes similarity is ranked up；(2) using case method maximum for attributes similarity as adaptive case method, table 3 takes
Case 1 event type, case 2 event class, case 1 position, case 1 business reasons, case 4 coverage, case 1 are impacted
(in each case, the similarity of attribute is identical, takes one, as in case 2 and case 4, the similarity of event class is equal for number
It being 1, then the event class taking the event class of case 2 and case 4 is the most permissible) corresponding local prediction scheme is as each independent attribute
Adaptation method；(3) reached the adaptation of case by Part Substitution and parameter adjustment, this process belongs to the mistake that a personal-machine is mutual
Journey, when all prediction scheme result of calculations that system provides are unable to reach adaptive effect, can carry out decision scheme discussion, artificially adjust
Partial approach and parameter.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.All within the spirit and principles in the present invention, that is made any repaiies
Change, equivalent, improvement etc., should be included within the scope of the present invention.
Claims (10)
1. an aid decision-making method based on prediction scheme, it is characterised in that comprise the following steps:
Step A: set up case database；
Step B, emergency event input；
Step C, the emergency event inputting step B are analyzed identifying and obtaining description or the tolerance of each attribute of emergency event
Method；If emergency event is identical with the case in case database, then directly invokes prediction scheme scheme and carry out aid decision support；If
Emergency event differs with the case in case database, then carry out next step；
The respective similarity of each attribute in step D, calculating emergency event；
Step E, the total similarity calculating emergency event also judge, it is judged that specifically: by total similarity of emergency event with
The threshold value set compares, if total similarity of emergency event is more than or equal to the threshold value set, then directly invokes emergency planning method
Carry out aid decision support；If total similarity of emergency event is less than the threshold value set, then make inferences based on prediction scheme, described base
The concrete grammar made inferences in prediction scheme is: first the emergency event the calculated respective similarity of each attribute arranged
Sequence, then using case method maximum for the similarity of attribute as adaptive case method, adjust finally by Part Substitution and parameter
The whole adaptation reaching case.
Aid decision-making method based on prediction scheme the most according to claim 1, it is characterised in that the attribute of described emergency event
Including event title, type, position, grade, influence degree, business reasons, time and place.
Aid decision-making method based on prediction scheme the most according to claim 1, it is characterised in that similarity in described step D
Computational methods include the first computational methods and the second computational methods, the first computational methods described specifically: for number
The Euclidean distance method of value type attribute code requirement, specially expression formula 1):
Wherein, f1(x y) is the similarity of a certain attribute；X is a certain attribute event value, and y is a certain attribute case value；max
It is maximum and minima in all prediction scheme property values of a certain attribute respectively with min；
Described the second computational methods are specifically: use degree of overlapping metering method for character attibute, concrete use expression formula 2):
Wherein: f2(x y) is the similarity of a certain attribute；X is a certain attribute event value, and y is a certain attribute case value.
Aid decision-making method based on prediction scheme the most according to claim 1, it is characterised in that answer urgent thing in described step E
Total similarity of part is obtained by the Boolean Model of extension, the expression formula of the Boolean Model of extension such as expression formula 3):
Wherein: d is source case, qandFor retrieval type logical AND, sim (qand, d) it is total similarity of emergency event and prediction scheme, always
Similarity ∈ [0,1], is closer to 1 and shows that prediction scheme coupling is the best；xmThe similarity of m-th attribute, а in expression eventmRepresent the
The importance degree of m attribute；P represents the degree that between project, logical relation is strict, and value is 1 the most loose, and value is infinite the tightest.
Aid decision-making method based on prediction scheme the most according to claim 1, it is characterised in that total phase of described emergency event
Seemingly spend the threshold value set as 0.9.
6. a Tailings Dam monitoring method, it is characterised in that be included in line monitoring system and join with described on-line monitoring system
Close the aid decision-making method based on prediction scheme as described in claim 1-5 any one used, specifically include following steps:
The first step, Tailings Dam on-line monitoring system online monitoring data；
Second step, the online data obtaining the first step are analyzed, it is judged that whether data are beyond setting value, if it has not, then continue
Continuous monitoring；
If it has, then obtain alarm level and report to the police, use described aid decision-making method based on prediction scheme to event simultaneously
Process.
Tailings Dam monitoring method the most according to claim 6, it is characterised in that: apply aid decision-making method based on prediction scheme
Also include emergency monitoring process before event is processed, described emergency monitoring process specifically:
Data by emergent monitoring system on-line monitoring Tailings Dam；The data obtained are analyzed；Judge whether data surpass
Go out setting value, if it has not, then cancel warning；
If it has, then obtain alarm level and report to the police, use described aid decision-making method based on prediction scheme to event simultaneously
Process.
Tailings Dam monitoring method the most according to claim 7, it is characterised in that: the condition that described emergency monitoring process starts
It is:
When power interruptions or communication disruption occurs in on-line monitoring system, starting emergency power supply, emergency power supply controls emergent simultaneously
Communication system starts local radio communication module, sends data from trend centre data subsystem after startup；
Or, after the alert levels in second step is higher than the alarm threshold value set, starts emergency monitoring, then encryption be all kinds of automatically
Monitoring Data monitoring frequency, supports artificial setpoint frequency simultaneously；Monitoring Data realizes local and remote backed up in synchronization；
Or, when starting when reporting to the police, on-line monitoring system selects photographic head nearby, and specifies it to monitor according to monitored object feature
Orientation, carries out key monitoring.
Tailings Dam monitoring method the most according to claim 6, it is characterised in that: on-line monitoring system on-line monitoring Tailings Dam
Data while also include manually data to monitoring Tailings Dam, carry out for the data that on-line monitoring system is monitored
Analyze.
10. Tailings Dam monitoring system, it is characterised in that include online data perception and transport layer, data management analysis and
Issue layer, pre-alarm management level and program management and aid decision layer；
Described online data perception and transport layer by Tailings Dam displacement, saturation, reservoir level, Gan Tan, rainfall, seepage discharge with
And video surveillance obtains the real-time running state data of Tailings Dam；
The data received are carried out storing, manage, analyze and issuing by described data management analysis and issue layer, and coordinate each son
Data stream is called control by system；
Described pre-alarm management level are automatic according to the data received and Safety of Tailings Dam monitoring and warning, centre data subsystem
Carry out data analysis, judgement, it is achieved classifying alarm；
Described program management and aid decision layer are used for formulating system response level mechanism, it is achieved alarm plan links；Will editor
Good emergency preplan is expressed as computer can be with the form identified, behaviour part message structure of going forward side by side；Numeral is set up for prediction scheme
Change prediction scheme, contingency management work is realized orderly management.
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| CN109149644A (en) * | 2018-09-29 | 2019-01-04 | 南京工程学院 | A kind of integrated strategy of on-line matching of light storage based on big data analysis and cooperative optimization method |
| CN110426994A (en) * | 2019-07-03 | 2019-11-08 | 浙江天澈科技有限公司 | A kind of chemical plant safety on line supervisory systems |
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| CN112232660A (en) * | 2020-10-15 | 2021-01-15 | 应急管理部天津消防研究所 | Method for evaluating and improving fire extinguishing and emergency evacuation plan |
| CN112633661A (en) * | 2020-12-17 | 2021-04-09 | 中铁第四勘察设计院集团有限公司 | BIM-based emergency dispatching command method, system, computer equipment and readable medium |
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| CN109149644B (en) * | 2018-09-29 | 2020-06-09 | 南京工程学院 | Light-storage integrated online strategy matching and collaborative optimization method based on big data analysis |
| CN111737409A (en) * | 2019-03-25 | 2020-10-02 | 株式会社东芝 | Support system and storage medium |
| CN110426994A (en) * | 2019-07-03 | 2019-11-08 | 浙江天澈科技有限公司 | A kind of chemical plant safety on line supervisory systems |
| CN110426994B (en) * | 2019-07-03 | 2020-07-31 | 浙江天澈科技有限公司 | Online safety supervisory systems of chemical plant |
| CN112232660A (en) * | 2020-10-15 | 2021-01-15 | 应急管理部天津消防研究所 | Method for evaluating and improving fire extinguishing and emergency evacuation plan |
| CN112633661A (en) * | 2020-12-17 | 2021-04-09 | 中铁第四勘察设计院集团有限公司 | BIM-based emergency dispatching command method, system, computer equipment and readable medium |
| CN113222361A (en) * | 2021-04-25 | 2021-08-06 | 北京中交华安科技有限公司 | Emergency rescue scheme generation method for emergency |
| CN113469583A (en) * | 2021-09-02 | 2021-10-01 | 中国电力科学研究院有限公司 | Power grid accident plan recommendation method, system, equipment and storage medium |
| CN115330268A (en) * | 2022-10-12 | 2022-11-11 | 华北科技学院(中国煤矿安全技术培训中心) | Comprehensive emergency command method and system for dealing with mine disaster |
| CN115330268B (en) * | 2022-10-12 | 2023-12-29 | 华北科技学院(中国煤矿安全技术培训中心) | Comprehensive emergency command method and system for coping with mine disasters |
| CN117350288A (en) * | 2023-12-01 | 2024-01-05 | 浙商银行股份有限公司 | Case matching-based network security operation auxiliary decision-making method, system and device |
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