CN111091254A - Operation risk quantification method, operation risk evaluation method and device - Google Patents

Operation risk quantification method, operation risk evaluation method and device Download PDF

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CN111091254A
CN111091254A CN201811238049.5A CN201811238049A CN111091254A CN 111091254 A CN111091254 A CN 111091254A CN 201811238049 A CN201811238049 A CN 201811238049A CN 111091254 A CN111091254 A CN 111091254A
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赵新斌
张日权
王浩锋
刘玉坤
万健
汤银才
俞力玲
方方
万一楠
方斌
陈乾
张颖超
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East China Normal University
China Academy of Civil Aviation Science and Technology
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Abstract

The embodiment of the invention provides an operation risk quantification method, an operation risk evaluation method and an operation risk evaluation device, wherein the operation risk quantification method comprises the following steps: and acquiring QAR data, and obtaining an operation risk value according to the QAR data and a pre-established risk quantification model. By implementing the method and the device, the quantification of the operation risk is realized, so that a foundation is laid for evaluation and analysis of the operation risk, and the overall control and accurate supervision of the operation risk by a management department are facilitated.

Description

Operation risk quantification method, operation risk evaluation method and device
Technical Field
The invention relates to the technical field of risk evaluation, in particular to an operation risk quantification method, an operation risk evaluation method and an operation risk evaluation device.
Background
Comparing the number of common events, signs and accidents between airlines is the most common method for evaluating the performance of airlines at present. According to the general events, signs and accident occurrence quantity, the risk evaluation is only carried out on the company from the operation result, the comprehensive influence of the man-machine ring on the civil aircraft operation risk is ignored, the quantification of the operation risk cannot be realized, the operation risk cannot be evaluated and analyzed, and the overall grasp and the accurate supervision of the civil aviation management department on the risk of the airline company are not facilitated. Therefore, how to realize the quantification of the aviation operation risk becomes an urgent problem to be solved.
Disclosure of Invention
In view of this, the embodiment of the invention provides an operation risk quantification method, an operation risk evaluation method and an operation risk evaluation device, which are used for solving the problem that the operation risk cannot be quantified in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect of the present invention, an operational risk quantification method is provided, where the operational risk quantification method includes: QAR data is acquired; and obtaining an operation risk value according to the QAR data and a pre-established risk quantification model.
With reference to the first aspect, in a first implementation manner of the first aspect, obtaining an operational risk value according to the QAR data and a pre-established risk quantification model includes: determining an operation risk quantification index; selecting second QAR data for quantifying the operation risk from the QAR data according to the operation risk quantification index; and inputting the second QAR data into the risk quantification model to obtain the operation risk value.
With reference to the first aspect or the first embodiment of the first aspect, in a second embodiment of the first aspect, the risk quantification model is:
Figure BDA0001838662280000021
Figure BDA0001838662280000022
wherein R isTotal tDenotes the operational risk value on day t, RNon-warning tRisk value, m, representing day t non-alarm type monitoring items1Representing the mean risk, R, of non-alarm monitoring items during a history periodWarning tRisk value, m, representing day t warning-like monitoring items2A risk average, M, representing the alarm-like monitoring item in said one history periodtIndicates the flight number of the t day, q indicates the number of non-warning monitoring items, and wjRepresents the weight of the jth non-warning monitoring item to the operation risk, RijtThe ratio of the offset of the jth non-warning monitoring item of the ith flight on the tth day relative to a preset standard value to the maximum offset of the non-warning monitoring item of the whole industry relative to the preset standard value in the historical period is represented, p represents the number of warning monitoring items, w represents the number of warning monitoring itemslWeight, y, representing the ith alarm class monitoring item to operational riskiltThe number of occurrences of the l-th alert class monitoring item indicating the ith flight on the t-th day.
With reference to the second embodiment of the first aspect, in the third embodiment of the first aspect, the R is obtained by the following formulaijt：
Figure BDA0001838662280000023
Wherein x isijtValue, x, of the jth non-alert monitoring item representing the ith flight on the tth dayj0A preset standard value, x, representing the jth non-warning monitoring itemjAnd the maximum value of the jth non-warning type monitoring item in the historical period in the industry-wide industry is represented.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, or the third implementation manner of the first aspect, in the fourth implementation manner of the first aspect, after the obtaining of the QAR data, before obtaining the operational risk value according to the QAR data and a pre-established risk quantification model, the method further includes: and cleaning the QAR data.
In a second aspect of the present invention, an operation risk evaluation method is provided, where the operation risk evaluation method includes: according to the first aspect of the invention or the operation risk quantification method of any embodiment of the first aspect of the invention, an operation risk value of each object to be evaluated in one historical period is obtained; determining the mean value, the variance and the probability density function of the running risk of each object to be evaluated according to the running risk value of each object to be evaluated in a historical period; and determining a comprehensive risk evaluation index of each object to be evaluated according to the mean value, the variance and the probability density function of the operation risk of each object to be evaluated.
With reference to the second aspect, in the first embodiment of the second aspect, the probability density function is determined by a kernel density estimation method according to an operation risk value in a history period of each object to be evaluated.
With reference to the second aspect or the first embodiment of the second aspect, in the second embodiment of the second aspect, determining a risk comprehensive evaluation index of each object to be evaluated according to a mean, a variance, and a probability density function of an operational risk of each object to be evaluated includes: for each object to be evaluated, executing: determining n deviation lines according to the mean value and the variance of the motion risk, wherein n is an integer greater than or equal to 1; determining n deviation evaluation indexes according to the n deviation lines and the probability density function; and determining the comprehensive risk evaluation index according to each deviation evaluation index.
In a third aspect of the present invention, an operational risk quantifying apparatus is provided, including: the data acquisition module is used for acquiring QAR data; and the risk quantification module is used for obtaining an operation risk value according to the QAR data and a pre-established risk quantification model.
In a fourth aspect of the present invention, there is provided an operation risk evaluation device including: a risk value obtaining module, configured to obtain an operation risk value of each object to be evaluated in one history period according to the operation risk quantification method described in the first aspect of the present invention or any embodiment of the first aspect; the risk data determination module is used for determining the mean value, the variance and the probability density function of the operation risk of each object to be evaluated according to the operation risk value of each object to be evaluated in one historical period; and the risk evaluation index determining module is used for determining a risk comprehensive evaluation index of each object to be evaluated according to the mean value, the variance and the probability density function of the operation risk of each object to be evaluated.
In a fifth aspect of the present invention, a computer-readable storage medium is provided, and the computer-readable storage medium stores computer instructions for causing the computer to execute the operation risk quantifying method according to the first aspect or any embodiment of the first aspect of the present invention, or causing the computer to execute the operation risk evaluating method according to the second aspect or any embodiment of the second aspect of the present invention.
In a sixth aspect of the present invention, there is provided an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the operation risk quantification method according to the first aspect or any embodiment of the first aspect of the present invention, or to perform the operation risk assessment method according to any embodiment of the second aspect of the present invention.
Compared with the prior art, the technical scheme of the invention at least has the following advantages:
the embodiment of the invention provides an operation risk quantification method, an operation risk evaluation method and an operation risk evaluation device, wherein the operation risk quantification method comprises the following steps: the QAR data is acquired, the operation risk value is obtained according to the QAR data and the pre-established risk quantification model, and quantification of the operation risk is achieved, so that a foundation is laid for evaluation and analysis of the operation risk, and overall assurance and accurate supervision of the operation risk by a management department are facilitated.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of an operation risk quantifying method in an embodiment of the present invention;
FIG. 2 is a flow chart of another specific example of a method of risk quantification in an embodiment of the present invention;
FIG. 3 is a flowchart of a specific example of an operational risk assessment method according to an embodiment of the present invention;
FIG. 4 is a flowchart of another specific example of an operational risk assessment method in an embodiment of the present disclosure;
fig. 5 is a schematic block diagram of a specific example of the operation risk quantifying means in the embodiment of the present invention;
FIG. 6 is a schematic block diagram of a specific example of an operational risk assessment apparatus in an embodiment of the present invention;
fig. 7 is a schematic diagram of a specific example of an electronic device in the embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the technical features related to the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.
An embodiment of the present invention provides an operation risk quantification method, as shown in fig. 1, the operation risk quantification method includes:
step S1: QAR data is acquired;
step S2: and obtaining an operation risk value according to the QAR data and a pre-established risk quantification model.
Through the step S1 and the step S2, the operation risk quantification method provided by the embodiment of the present invention achieves quantification of the operation risk, thereby laying a foundation for evaluation and analysis of the operation risk, and facilitating overall assurance and accurate supervision of the operation risk by a management department.
In a preferred embodiment, as shown in fig. 2, the step S2 of obtaining the operational risk value according to the QAR data and the pre-established risk quantification model includes:
step S21: determining an operation risk quantification index; the operation risk quantitative index includes but is not limited to a Controlled Flight Impact (CFIT), a risk of rushing/deviating from a runway, a risk of runaway and the like.
Step S22: and selecting second QAR data for quantifying the operation risk from the QAR data according to the operation risk quantification index.
Specifically, different QAR data are used for describing different operation risk quantitative indexes, and since the operation risk quantitative indexes include many contents, the embodiments of the present invention cannot be exhaustive, and thus, typical events such as a controllable flight collision, a rush/run-out runway risk, and an out-of-control risk are still described, but the present invention is not limited thereto.
For controllable flight ground collision, the method adopts 'glideslope deviation, course deviation, 50 feet to ground descent rate large, approach speed small, landing configuration late selected, landing configuration not landed, landing gear late, ground elevation angle small, ground elevation angle large, landing gradient large, approach gradient large (200 feet to 50 feet) and GPWS terrain warning' in QAR data to depict; for the risk of rushing out of or deviating out of the runway, the 'take-off form warning, take-off interruption, large landing speed, large approach speed, course deviation, glide slope deviation, non-landing configuration landing and grounding distance' in the QAR data are adopted for depicting; for the out-of-control risk, a GPWS ground proximity warning alarm, a stall warning, a small approach speed, a course deviation, a glide slope deviation, an overlarge elevation angle, a non-landing configuration landing and a large descent rate in QAR data are adopted for depicting.
Step S23: and inputting the second QAR data into a risk quantification model to obtain an operation risk value.
Specifically, for the risk quantitative index determined in the step S21, the second QAR data selected in the step S22 for describing the risk quantitative index is input into a pre-established risk quantitative model, which in a preferred embodiment of the present invention is:
Figure BDA0001838662280000071
Figure BDA0001838662280000081
wherein R isTotal tDenotes the operational risk value on day t, RNon-warning tRisk value, m, representing day t non-alarm type monitoring items1Representing the mean risk, R, of non-alarm monitoring items during a history periodWarning tRisk value, m, representing day t warning-like monitoring items2Means of risk, M, representing alarm-like monitoring items in a historical periodtIndicates the flight number of the t day, q indicates the number of non-warning monitoring items, and wjRepresents the weight of the jth non-alarm class monitoring item to the operation risk,Rijtthe ratio of the offset of the jth non-warning monitoring item of the ith flight on the tth day relative to a preset standard value to the maximum offset of the non-warning monitoring item of the whole industry relative to the preset standard value in a historical period, p represents the number of the warning monitoring items, w represents the number of the warning monitoring itemslWeight, y, representing the ith alarm class monitoring item to operational riskiltThe number of occurrences of the l-th alert class monitoring item indicating the ith flight on the t-th day.
The QAR data is defined as a non-warning-type monitoring item when it is continuous data, and is defined as a warning-type monitoring item when it is discrete data.
The weight w of the jth non-warning monitoring item on the operation riskjAnd the weight w of the ith warning class monitoring item to the operation risklThe method and the device can be used for scoring according to professionals in the field of aviation, the professionals score the weights w of the non-warning monitoring items and the warning monitoring items on the operation risks according to self knowledge reserves and combination of rich experiences accumulated in the field, and the weight w of the jth non-warning monitoring item on the operation risks is determined according to the scoring of the professionalsjAnd the weight w of the ith warning class monitoring item to the operation riskl。
A ratio R of the offset of the jth non-warning monitoring item of the ith flight on the tth day relative to the preset standard value to the maximum offset of the non-warning monitoring item of the whole industry relative to the preset standard value in the historical periodijtThis can be obtained by the following formula:
Figure BDA0001838662280000091
wherein x isijtValue, x, of the jth non-alert monitoring item representing the ith flight on the tth dayj0A preset standard value, x, representing the jth non-warning monitoring itemjAnd the maximum value of the jth non-warning monitoring item in the historical period of the industry is shown. For each non-alarm type monitoring item, there will be oneAnd when the value of the non-warning monitoring item exceeds the standard value, the non-warning monitoring item is indicated to possibly have certain risk, and the standard value is set according to different models.
According to the embodiment of the invention, the QAR data corresponding to the determined operation risk quantitative index is input into the pre-established risk quantitative model, and the operation risk value of a certain model of an airline company in a certain day can be obtained, so that the operation risk is quantized, and a foundation is laid for evaluating and analyzing the operation risk.
In a preferred embodiment, as shown in fig. 2, after the step S1 of obtaining the QAR data, before the step S2 of obtaining the operational risk value according to the QAR data and the pre-established risk quantification model, the method further includes:
step S3: cleaning QAR data; the acquired QAR data is cleaned, so that distortion data in the QAR data are removed, and the data input into the risk quantification model are all available data.
The embodiment of the invention also provides an operation risk evaluation method, as shown in fig. 3, the operation risk evaluation method comprises the following steps:
step S4: obtaining an operation risk value of each object to be evaluated in a historical period according to the operation risk quantification method; the object to be evaluated can be an airline company, and for one airline company, the operation risk value of each model of the airline company in each day can be obtained through the operation risk quantification method embodiment, so that the operation risk value of the airline company in a historical period can be obtained.
Step S5: determining the mean value, the variance and the probability density function of the running risk of each object to be evaluated according to the running risk value of each object to be evaluated in a historical period; according to the operation risk value of each object to be evaluated in one history period obtained in step S4, the average value of the operation risk of each object to be evaluated in the history period, that is, the average daily operation risk value, can be easily obtained, and the variance of the operation risk can be easily obtained; according to the operation risk value of each object to be evaluated in one historical period, the probability density function of each object to be evaluated can be obtained through the kernel density estimation method.
Step S6: determining a comprehensive risk evaluation index of each object to be evaluated according to the mean value, the variance and the probability density function of the operation risk of each object to be evaluated; specifically, as shown in fig. 4, for each object to be evaluated, the following steps are performed:
step S61: and determining n deviation lines according to the mean value and the variance of the motion risk, wherein n is an integer greater than or equal to 1. Let the mean of the running risk be m and the variance be σ, then the deviation line be liM + i × σ, i is 1,2, …, n. In the embodiment of the present invention, if n is 3, 3 deviation lines can be determined, where l is each1＝m+1×σ,l2＝m+2×σ，l3＝m+3×σ。
Step S62, determining n deviation evaluation indexes according to the n deviation lines and the probability density function, specifically obtaining the α th deviation evaluation index z by utilizing the tail probability of the probability density functionα：
Figure BDA0001838662280000111
Where p (x) represents a probability density function.
Step S63: determining a comprehensive risk evaluation index according to each deviation evaluation index; in particular, z can be represented by the formula1+z2+z3+1, obtaining the comprehensive risk evaluation index z.
According to the operation risk evaluation method provided by the embodiment of the invention, the operation risks of each airline company can be ranked, specifically, the risk comprehensive evaluation indexes obtained by each airline company through the operation risk evaluation method are ranked from big to small, the operation risk of the airline company corresponding to the risk comprehensive evaluation index ranked in the front is relatively high, and the operation risk of the airline company corresponding to the risk comprehensive evaluation index ranked in the rear is relatively low, so that the performance evaluation of each airline company is realized.
An embodiment of the present invention further provides an operation risk quantification apparatus, as shown in fig. 5, the operation risk quantification apparatus includes: a data acquisition module 1 for acquiring QAR data, the details of which can be referred to the related description of step S1 in the above method embodiment; the risk quantification module 2 is configured to obtain an operational risk value according to the QAR data and a pre-established risk quantification model, and the details can be referred to the related description of step S2 in the above method embodiment.
Through the data acquisition module 1 and the risk quantification module 2, the operation risk quantification device provided by the embodiment of the invention realizes quantification of the operation risk, thereby laying a foundation for evaluation and analysis of the operation risk and being beneficial to overall grasp and accurate supervision of the operation risk by management departments.
An embodiment of the present invention further provides an operation risk evaluation device, as shown in fig. 6, the operation risk evaluation device includes: the risk value obtaining module 3 is configured to obtain an operation risk value in a history period of each object to be evaluated according to the operation risk quantification method provided in the embodiment of the present invention, and the details may refer to the related description of step S4 in the above method embodiment; the risk data determining module 4 is configured to determine a mean value, a variance, and a probability density function of the operation risk of each object to be evaluated according to the operation risk value of each object to be evaluated in one history period, and details may refer to the related description of step S5 in the foregoing method embodiment; the risk evaluation index determining module 5 is configured to determine a risk comprehensive evaluation index of each object to be evaluated according to the mean, the variance, and the probability density function of the operation risk of each object to be evaluated, and the details may be referred to the related description of step S6 in the above method embodiment.
For the description of the relevant details and effects of the operation risk evaluation device, reference may be made to the relevant contents of the above operation risk evaluation method embodiment, and details are not repeated here.
An embodiment of the present invention further provides an electronic device, as shown in fig. 7, the electronic device may include a processor 71 and a memory 72, where the processor 71 and the memory 72 may be connected by a bus or in another manner, and fig. 7 takes the connection by the bus as an example.
The processor 71 may be a Central Processing Unit (CPU). The Processor 71 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof.
The memory 72, as a non-transitory computer readable storage medium, may be used for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the operation risk quantification method or the operation risk evaluation method in the embodiment of the present invention (for example, the data acquisition module 1, the risk quantification module 2 shown in fig. 5, or the risk value acquisition module 3, the risk data determination module 4, and the risk evaluation index determination module 5 shown in fig. 6). The processor 71 executes various functional applications and data processing of the processor by executing the non-transitory software programs, instructions and modules stored in the memory 72, namely, implements the operation risk quantification method or the operation risk evaluation method in the above method embodiments.
The memory 72 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor 71, and the like. Further, the memory 72 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 72 may optionally include memory located remotely from the processor 71, and such remote memory may be connected to the processor 71 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 72 and, when executed by the processor 71, perform an operational risk quantification method as in the embodiment of fig. 1 or 2, or an operational risk assessment method as in the embodiment of fig. 3 or 4.
The details of the electronic device may be understood with reference to the corresponding descriptions and effects in the embodiments shown in fig. 1 to fig. 4, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims (12)

1. An operational risk quantification method, comprising:
QAR data is acquired;
and obtaining an operation risk value according to the QAR data and a pre-established risk quantification model.
2. The operational risk quantification method of claim 1 wherein obtaining an operational risk value from the QAR data and a pre-established risk quantification model comprises:
determining an operation risk quantification index;
selecting second QAR data for quantifying the operation risk from the QAR data according to the operation risk quantification index;
and inputting the second QAR data into the risk quantification model to obtain the operation risk value.
3. The operational risk quantification method according to claim 1 or 2, wherein the risk quantification model is:
Figure FDA0001838662270000011
wherein R isTotal tDenotes the operational risk value on day t, RNon-warning tRisk value, m, representing day t non-alarm type monitoring items1Representing the mean risk, R, of non-alarm monitoring items during a history periodWarning tRisk value, m, representing day t warning-like monitoring items2A risk average, M, representing the alarm-like monitoring item in said one history periodtIndicates the flight number of the t day, q indicates the number of non-warning monitoring items, and wjRepresents the weight of the jth non-warning monitoring item to the operation risk, RijtThe ratio of the offset of the jth non-warning monitoring item of the ith flight on the tth day relative to a preset standard value to the maximum offset of the non-warning monitoring item of the whole industry relative to the preset standard value in the historical period is represented, p represents the number of warning monitoring items, w represents the number of warning monitoring itemslWeight, y, representing the ith alarm class monitoring item to operational riskiltThe number of occurrences of the l-th alert class monitoring item indicating the ith flight on the t-th day.
4. The operational risk quantification method according to claim 3, wherein the R is obtained by the following formulaijt：
Figure FDA0001838662270000021
Wherein x isijtValue, x, of the jth non-alert monitoring item representing the ith flight on the tth dayj0A preset standard value, x, representing the jth non-warning monitoring itemjAnd the maximum value of the jth non-warning type monitoring item in the historical period in the industry-wide industry is represented.
5. The operational risk quantification method of any one of claims 1-4, wherein after the QAR data is acquired, and before the operational risk value is obtained from the QAR data and a pre-established risk quantification model, further comprising: and cleaning the QAR data.
6. An operational risk evaluation method, comprising:
obtaining an operational risk value of each object to be evaluated in a historical period according to the operational risk quantification method of any one of claims 1 to 5;
determining the mean value, the variance and the probability density function of the running risk of each object to be evaluated according to the running risk value of each object to be evaluated in a historical period;
and determining a comprehensive risk evaluation index of each object to be evaluated according to the mean value, the variance and the probability density function of the operation risk of each object to be evaluated.
7. The operational risk evaluation method according to claim 6, wherein the probability density function is determined by a kernel density estimation method according to the operational risk value of each of the objects to be evaluated in one history period.
8. The operational risk evaluation method according to claim 6 or 7, wherein determining a risk comprehensive evaluation index of each object to be evaluated according to the average, variance and probability density function of the operational risk of each object to be evaluated comprises: for each object to be evaluated, executing:
determining n deviation lines according to the mean value and the variance of the motion risk, wherein n is an integer greater than or equal to 1;
determining n deviation evaluation indexes according to the n deviation lines and the probability density function;
and determining the comprehensive risk evaluation index according to each deviation evaluation index.
9. An operational risk quantifying apparatus, comprising:
the data acquisition module is used for acquiring QAR data;
and the risk quantification module is used for obtaining an operation risk value according to the QAR data and a pre-established risk quantification model.
10. An operational risk assessment device, comprising:
a risk value obtaining module, configured to obtain an operation risk value of each object to be evaluated in one history period according to the operation risk quantification method according to any one of claims 1 to 5;
the risk data determination module is used for determining the mean value, the variance and the probability density function of the operation risk of each object to be evaluated according to the operation risk value of each object to be evaluated in one historical period;
and the risk evaluation index determining module is used for determining a risk comprehensive evaluation index of each object to be evaluated according to the mean value, the variance and the probability density function of the operation risk of each object to be evaluated.
11. A computer-readable storage medium storing computer instructions for causing a computer to execute the operational risk quantifying method according to any one of claims 1 to 5 or the operational risk evaluating method according to any one of claims 6 to 8.
12. An electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the operational risk quantification method according to any one of claims 1 to 5 or the operational risk assessment method according to any one of claims 6 to 8.
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