CN112016849A - College management laboratory security risk assessment method based on cloud model - Google Patents

College management laboratory security risk assessment method based on cloud model Download PDF

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CN112016849A
CN112016849A CN202010956721.5A CN202010956721A CN112016849A CN 112016849 A CN112016849 A CN 112016849A CN 202010956721 A CN202010956721 A CN 202010956721A CN 112016849 A CN112016849 A CN 112016849A
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张海军
闫琼
闫学伟
李征
刘全威
张国辉
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Zhengzhou University of Aeronautics
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Abstract

The invention discloses a cloud model-based college management laboratory security risk assessment method, which comprises the following steps: calculating the weight of a secondary index in a management laboratory safety risk evaluation index system of colleges and universities relative to a target layer based on an analytic hierarchy process; partitioning a preset laboratory safety risk comment set by adopting a golden section method to obtain a standard evaluation cloud model; obtaining a scoring result of an expert on the secondary evaluation indexes, and calculating a first cloud model digital characteristic of each secondary evaluation index according to the scoring result; calculating a second cloud model digital characteristic of the safety risk assessment of the management laboratory of colleges and universities according to the first cloud model digital characteristic and the weight of the secondary index relative to the target layer; and inputting the digital characteristics of the second cloud model and the preset cloud drop number into the forward cloud generator to generate a security risk assessment result of the university management laboratory, which comprises the standard evaluation cloud model and the assessment scatter. By adopting the invention, the laboratory safety risk assessment result can be visually presented.

Description

College management laboratory security risk assessment method based on cloud model
Technical Field
The invention relates to the field of risk assessment, in particular to a cloud model-based security risk assessment method for a college management laboratory.
Background
The number of laboratories in colleges and universities in China is continuously increasing along with the development of higher education, the asset value of instruments and equipment reaches unprecedented scale, and the safety management of laboratories is increasingly complex. The laboratory is the main place for practicing teaching and scientific research in colleges and universities, and the safety of teachers and students is guaranteed to be placed at the first place. In recent years, to ensure the realization of safety teaching, education competent departments at different levels always carry forward the idea of 'life is supreme and safe first', and colleges and universities also actively make up a relevant safety regulation and regulation system, establish the principle of 'who is responsible for and responsible for, who uses and is responsible for', practically strengthen the responsibility system of the laboratory safety main body, and regularly develop the laboratory safety self-investigation activities. The laboratory safety work effect is obvious on the whole, but some laboratory safety accidents occur occasionally in colleges and universities, and great threats are brought to the personal safety of teachers and students.
At present, laboratory safety risk assessment of colleges and universities is still in a starting stage, mainly based on qualitative self-check, the assessment results cannot be quantized, the controllability of laboratory safety is low, and a scientific and normative safety assessment system is not formed. In 5 months in 2019, the education department issues an opinion on strengthening the safety work of laboratories in colleges and universities (teaching technical letters [ 2019 ] 36), clearly requires a safety risk assessment system to be established for the laboratories, and gradually establishes a laboratory safety quantitative assessment work mechanism. The scientific management of laboratory safety is further strengthened, a laboratory safety assessment model is established, the laboratory safety is quantitatively assessed regularly, management departments can be helped to find related potential safety hazards in time, rectification early warning is provided for laboratories unqualified in assessment, and the laboratory safety assessment model is prevented from suffering in the bud, and has important significance for reducing asset loss of colleges and universities, guaranteeing personal safety of teachers and students and improving the laboratory safety management level of colleges and universities.
At present, research contents in laboratory safety management mainly focus on the management status quo of laboratory safety, countermeasure suggestion, construction of a supervision management mechanism and the like, and research on laboratory safety evaluation is just started. Although some scholars respectively establish a laboratory fire risk evaluation model and a chemical safety evaluation method and provide a certain theoretical basis for laboratory safety evaluation, no scholars currently carry out special risk evaluation research on the laboratories of the university channels and the like. In addition, most evaluation results in the existing established laboratory safety risk assessment model are described in language, for example, high risk, medium risk and the like, and visual expression cannot be performed. Therefore, a method for visually acquiring the laboratory security risk assessment result is needed.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a cloud model-based college management laboratory security risk assessment method, which gives play to the conversion advantage of a cloud model between qualitative evaluation and quantitative representation, not only fully considers the randomness and the fuzziness of expert decision information, but also can visually present the laboratory security risk assessment result.
Based on the above, the invention provides a cloud model-based security risk assessment method for a management laboratory of colleges and universities, which comprises the following steps:
calculating the weight of a secondary index in a management laboratory safety risk evaluation index system of the colleges and universities relative to a target layer based on an analytic hierarchy process, wherein the management laboratory safety risk evaluation index system of the colleges and universities is established by adopting a Delphi method;
partitioning a preset laboratory safety risk comment set by adopting a golden section method to obtain a standard evaluation cloud model;
obtaining a scoring result of an expert on the secondary evaluation indexes, and calculating a first cloud model digital characteristic of each secondary evaluation index according to the scoring result;
calculating a second cloud model digital characteristic of the safety risk assessment of the management laboratory of colleges and universities according to the first cloud model digital characteristic and the weight of the secondary index relative to a target layer;
and inputting the digital characteristics of the second cloud model and the preset cloud drop number into the forward cloud generator to generate a security risk assessment result of the university management laboratory, which comprises the standard evaluation cloud model and the assessment scatter.
Wherein, the calculating of the weight of the secondary indexes in the management laboratory safety risk evaluation index system of colleges and universities relative to the target layer based on the analytic hierarchy process comprises the following steps:
establishing a judgment matrix of the criterion layer relative to the target layer and the secondary index relative to the criterion layer according to a scaling method;
acquiring the weight of each criterion layer and the weight of each secondary index relative to the criterion layer according to a preset formula;
acquiring the maximum characteristic value of the judgment matrix, carrying out consistency check on the judgment matrix, and judging whether to adjust the matrix according to a consistency check result;
and calculating the combined weight value of each secondary index relative to the laboratory safety risk evaluation according to the weight of each criterion layer and the weight of each secondary index relative to the criterion layer.
Wherein, the obtaining of the weight of each criterion layer and the weight of each secondary index relative to the criterion layer according to a preset formula comprises:
Figure BDA0002678885930000021
Figure BDA0002678885930000022
wherein alpha isijRepresents an element, W 'in the judgment matrix'iIs the weighted value corresponding to the ith index.
The step of obtaining the maximum eigenvalue of the judgment matrix and carrying out consistency check on the judgment matrix comprises the following steps:
Figure BDA0002678885930000031
Figure BDA0002678885930000032
wherein, A is a judgment matrix, W' is a weight vector corresponding to the judgment matrix, and R.I. is a random consistency index, and the value of the random consistency index is related to the order number n of the judgment matrix.
The obtaining of the scoring result of the expert on the secondary evaluation indexes and the calculating of the first cloud model digital characteristics of each secondary evaluation index according to the scoring result comprise:
Figure BDA0002678885930000033
Figure BDA0002678885930000034
Figure BDA0002678885930000035
Figure BDA0002678885930000036
wherein, in the standard evaluation cloud model, the XipRepresenting the scoring result of the ith secondary index by the P-th expert, the ExiCloud expectation representing the ith secondary index, the EniEntropy representing the ith secondary index, said HeiRepresenting the superentropy of the ith secondary index, and k is the number of experts.
Calculating a second cloud model digital characteristic of the safety risk assessment of the management laboratory of colleges and universities according to the first cloud model digital characteristic and the weight of the secondary index relative to a target layer;
Figure BDA0002678885930000037
Figure BDA0002678885930000041
Figure BDA0002678885930000042
wherein q is the total number of the secondary indexes, wiThe combined weight of the ith secondary index relative to the target layer.
Wherein the preset laboratory safety risk comment sets comprise high, medium, low and low.
Wherein, the colleges and universities' management laboratory safety risk evaluation index system includes: the system comprises a target layer, a criterion layer and a measure layer, wherein the elements of the target layer are an organization system, a safety system, safety education, basic safety and safety facilities, and the elements of the criterion layer are a management laboratory safety risk evaluation index system of colleges and universities.
Wherein the elements of the measure layer, namely the secondary indexes, comprise: responsibility systems, financial guarantees, safety archives, system construction, operating rules, solar systems, electrical safety, water safety, personal protection, instrument safety, other safety, activity development, safety examinations, safety cultures, fire extinguishing devices, emergency devices, and ventilation devices.
In the scoring result of the expert on the secondary evaluation index, the scoring interval is [0, 1], 0 represents the highest risk, and 1 represents no risk.
Compared with the prior art, the invention has the following beneficial effects:
aiming at the problem of the safety risk assessment of the management laboratory in colleges and universities, firstly, a laboratory safety risk assessment index system including an organization system, a safety system, basic safety, safety education and safety facilities is established, then, a laboratory safety risk assessment model is established based on an analytic hierarchy process and a cloud model, and finally, an assessment result is obtained according to the cloud model. The assessment method provided by the invention has the advantages of clear calculation principle, simpler calculation process and feasible scheme, and the assessment result can be visually presented, thereby providing a new idea for the safety risk assessment of laboratories of colleges and universities.
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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, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a cloud model-based college management laboratory security risk assessment method according to an embodiment of the present invention;
FIG. 2 is a flow chart of calculating weights of secondary indexes relative to a target layer in a management laboratory security risk assessment index system of colleges and universities based on an analytic hierarchy process according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a criteria evaluation cloud model provided by an embodiment of the invention;
FIG. 4 is a schematic diagram of a forward cloud generator provided by an embodiment of the present invention;
fig. 5 is a schematic diagram of the results of the security risk assessment in the university administration laboratory according to the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Fig. 1 is a flowchart of a cloud model-based college management laboratory security risk assessment method provided in an embodiment of the present invention, including:
s101, calculating the weight of a secondary index in a college manageability laboratory safety risk evaluation index system relative to a target layer based on an analytic hierarchy process, wherein the college manageability laboratory safety risk evaluation index system is established by adopting a Delphi method;
the college management laboratory safety risk evaluation index system comprises: the system comprises a target layer, a criterion layer and a measure layer, wherein the elements of the target layer are an organization system, a safety system, safety education, basic safety and safety facilities, and the elements of the criterion layer are a management laboratory safety risk evaluation index system of colleges and universities. The elements of the measure layer, namely the secondary indexes, comprise: responsibility systems, financial guarantees, safety archives, system construction, operating rules, solar systems, electrical safety, water safety, personal protection, instrument safety, other safety, activity development, safety examinations, safety cultures, fire extinguishing devices, emergency devices, and ventilation devices.
Fig. 2 is a flowchart for calculating the weight of a secondary index relative to a target layer in a management laboratory security risk evaluation index system of colleges and universities based on an analytic hierarchy process, which is provided by the embodiment of the present invention, and includes:
s201, establishing a judgment matrix of a criterion layer relative to a target layer and a judgment matrix of a secondary index relative to the criterion layer according to a scaling method;
and according to a safety risk evaluation index system of the management laboratory in colleges and universities, sequentially constructing a judgment matrix of the criterion layer relative to the target layer and a judgment matrix of the secondary index relative to the criterion layer by adopting a 1-9 scale method.
Figure BDA0002678885930000061
S202, acquiring the weight of each criterion layer and the weight of each secondary index relative to the criterion layer according to a preset formula; the obtaining of the weight of each criterion layer and the weight of each secondary index relative to the criterion layer according to a preset formula comprises:
Figure BDA0002678885930000062
Figure BDA0002678885930000063
wherein alpha isijRepresents an element, W 'in the judgment matrix'iIs the weight value, m, corresponding to the ith indexiIs an intermediate value.
S203, acquiring the maximum characteristic value of the judgment matrix, carrying out consistency check on the judgment matrix, and judging whether to adjust the matrix according to a consistency check result;
wherein, the maximum eigenvalue of each judgment matrix is checked for consistency, C.R. is less than or equal to 0.1, otherwise, the matrix needs to be adjusted:
obtaining the maximum eigenvalue of the judgment matrix and carrying out consistency check on the judgment matrix comprises the following steps:
Figure BDA0002678885930000064
Figure BDA0002678885930000065
wherein, A is a judgment matrix, W' is a weight vector corresponding to the judgment matrix, and R.I. is a random consistency index, and the value of the random consistency index is related to the order number n of the judgment matrix.
The random consistency index values are given in the following table:
order n R.I. Order of the scale R.I.
1 0.00 6 1.24
2 0.00 7 1.36
3 0.58 8 1.41
4 0.89 9 1.45
5 1.12 10 1.49
And S204, calculating the combined weight value of each secondary index relative to the laboratory safety risk evaluation according to the weight of each criterion layer and the weight of each secondary index relative to the criterion layer.
The combined weight value of each secondary index relative to the laboratory safety risk evaluation can be calculated by multiplying the standard layer weight by the corresponding secondary index layer weight.
S102, partitioning a preset laboratory safety risk comment set by adopting a golden section method to obtain a standard evaluation cloud model;
taking the set as a comment set, partitioning the laboratory safety risk comment set by adopting a golden section method, and drawing a standard evaluation cloud model, please refer to fig. 3.
S103, obtaining a grading result of an expert on the secondary evaluation indexes, and calculating a first cloud model digital characteristic of each secondary evaluation index according to the grading result;
and inviting a plurality of experts, scoring each secondary evaluation index, wherein in the scoring result of the experts on the secondary evaluation index, the scoring interval is [0, 1], 0 represents the highest risk, and 1 represents no risk.
The obtaining of the scoring result of the expert on the secondary evaluation indexes and the calculating of the first cloud model digital characteristics of each secondary evaluation index according to the scoring result comprise:
Figure BDA0002678885930000071
Figure BDA0002678885930000072
Figure BDA0002678885930000073
Figure BDA0002678885930000081
wherein, in the standard evaluation cloud model, the XipRepresenting the scoring result of the ith secondary index by the P-th expert, the ExiCloud expectation representing the ith secondary index, the EniEntropy representing the ith secondary index, said HeiRepresenting the superentropy of the ith secondary index, and k is the number of experts.
S104, calculating a second cloud model digital characteristic of the safety risk assessment of the university management laboratory according to the first cloud model digital characteristic and the weight of the secondary index relative to the target layer;
calculating a second cloud model digital characteristic of the safety risk assessment of the management laboratory of colleges and universities according to the first cloud model digital characteristic and the weight of the secondary index relative to the target layer:
Figure BDA0002678885930000082
Figure BDA0002678885930000083
Figure BDA0002678885930000084
q is the total number of secondary indexes, wiThe combined weight of the ith secondary index relative to the target layer.
And S105, inputting the digital characteristics of the second cloud model and the preset cloud drop number into the forward cloud generator, and generating a security risk assessment result of the university management laboratory, which comprises the standard evaluation cloud model and the assessment scatter.
Fig. 4 is a schematic diagram of a forward cloud generator according to an embodiment of the present invention, where the forward cloud generator is used to input a second cloud model digital feature for comprehensive evaluation in MATLAB, and the number of generated cloud drops can be set to be 1000, so as to obtain a visual assessment result of the security risk of the university management laboratory, as shown in fig. 5.
In another embodiment, taking the experiment center a as an example, the experiment center a includes a plurality of laboratories, and the experiment consumables do not relate to chemicals, biological products, and the like, and belong to a typical tube-through experiment center. In the past, the laboratory center regularly carries out safety self-check on the laboratory, mainly takes qualitative description as a main part, and cannot visually display the self-check result. Taking the experimental center as an example, the safety risk of the experimental center is comprehensively evaluated.
(1) And determining the evaluation index weight. The inviting expert constructs judgment matrixes of the criterion layer relative to the target layer and each secondary index relative to the criterion layer according to a 1-9 scale method, the maximum eigenvalue and the corresponding weight vector of each judgment matrix are sequentially solved, consistency check is carried out, and the result is shown in the following table:
G-E judgment matrix and calculation result
Figure BDA0002678885930000091
E-U judgment matrix and calculation result
Figure BDA0002678885930000092
E-U judgment matrix and calculation result
Figure BDA0002678885930000093
E-U judgment matrix and calculation result
Figure BDA0002678885930000094
E-U judgment matrix and calculation result
Figure BDA0002678885930000095
E-U judgment matrix and calculation result
Figure BDA0002678885930000096
And calculating the result according to the table to obtain the combined weight W of the secondary index relative to the target layer.
W＝[0.040 0.020 0.020 0.032 0.083 0.036 0.233 0.096 0.028 0.047 0.047 0.017 0.057 0.031 0.117 0.045 0.051]T
Drawing a standard evaluation cloud model, and setting V as a comment set:
V＝{v1，v2，v3，v4，v5hi, medium, low
And partitioning the laboratory safety risk comment set by adopting a golden section method, and drawing a standard evaluation cloud model, which is shown in figure 3.
And inviting five experts to score each secondary evaluation index, wherein the scoring interval is [0, 1], 0 represents the highest risk, 1 represents no risk, and the obtained scoring result is shown in the following table.
Figure BDA0002678885930000101
Respectively calculating the digital features of the cloud model of each secondary index according to the scoring result to guarantee the expenses (u)2) For example.
Figure BDA0002678885930000102
Figure BDA0002678885930000103
Figure BDA0002678885930000104
Figure BDA0002678885930000105
Similarly, the cloud model numerical characteristics of the other secondary indexes can be obtained as shown in the following table:
index (I) Cloud model digital features Index (I) Cloud model digital features
u1 (0.8720，0.0331，0.0050) u10 (0.9280，0.0281，0.0135)
u2 (0.7500，0.0451，0.0204) u11 (0.9100，0.0301，0.0067)
u3 (0.8160，0.0261，0.0142) u12 (0.7940，0.0391，0.0100)
u4 (0.8840，0.0261，0.0071) u13 (0.8920，0.0271，0.0061)
u5 (0.8700，0.0301，0.0199) u14 (0.8460，0.0261，0.0071)
u6 (0.9640，0.0140，0.0057) u15 (0.9540，0.0261，0.0071)
u7 (0.9040，0.0291，0.0092) u16 (0.9220，0.0180，0.0067)
u8 (0.9420，0.0231，0.0118) u17 (0.7860，0.0191，0.0041)
u9 (0.8580，0.0130，0.0071)
And calculating the cloud model digital characteristics of the laboratory safety risk comprehensive assessment.
ExGeneral assembly＝0.872×0.04+0.75×0.02+...+0.786×0.051＝0.8966
Figure BDA0002678885930000111
Figure BDA0002678885930000112
By applying the forward cloud generator, cloud digital features (0.8966, 0.0271, 0.0095) of comprehensive evaluation are input into the MATLAB, the number of generated cloud drops is set to be 1000, and a visualized safety risk evaluation result of the experiment center is obtained, as shown in FIG. 4, it can be seen that the safety risk evaluation level of the experiment center is low risk.
Compared with the prior art, the invention has the following beneficial effects:
aiming at the problem of the safety risk assessment of the management laboratory in colleges and universities, firstly, a laboratory safety risk assessment index system including an organization system, a safety system, basic safety, safety education and safety facilities is established, then, a laboratory safety risk assessment model is established based on an analytic hierarchy process and a cloud model, and finally, an assessment result is obtained according to the cloud model. The assessment method provided by the invention has the advantages of clear calculation principle, simpler calculation process and feasible scheme, and the assessment result can be visually presented, thereby providing a new idea for the safety risk assessment of laboratories of colleges and universities.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and substitutions can be made without departing from the technical principle of the present invention, and these modifications and substitutions should also be regarded as the protection scope of the present invention.

Claims (10)

1. A college management laboratory security risk assessment method based on a cloud model is characterized by comprising the following steps:
calculating the weight of a secondary index in a management laboratory safety risk evaluation index system of the colleges and universities relative to a target layer based on an analytic hierarchy process, wherein the management laboratory safety risk evaluation index system of the colleges and universities is established by adopting a Delphi method;
partitioning a preset laboratory safety risk comment set by adopting a golden section method to obtain a standard evaluation cloud model;
obtaining a scoring result of an expert on the secondary evaluation indexes, and calculating a first cloud model digital characteristic of each secondary evaluation index according to the scoring result;
calculating a second cloud model digital characteristic of the safety risk assessment of the management laboratory of colleges and universities according to the first cloud model digital characteristic and the weight of the secondary index relative to a target layer;
and inputting the digital characteristics of the second cloud model and the preset cloud drop number into the forward cloud generator to generate a security risk assessment result of the university management laboratory, which comprises the standard evaluation cloud model and the assessment scatter.
2. The cloud model-based college through-the-pipe laboratory security risk assessment method according to claim 1, wherein the calculating of the weight of the secondary index in the college through-the-pipe laboratory security risk assessment index system relative to the target layer based on the analytic hierarchy process comprises:
establishing a judgment matrix of the criterion layer relative to the target layer and the secondary index relative to the criterion layer according to a scaling method;
acquiring the weight of each criterion layer and the weight of each secondary index relative to the criterion layer according to a preset formula;
acquiring the maximum characteristic value of the judgment matrix, carrying out consistency check on the judgment matrix, and judging whether to adjust the matrix according to a consistency check result;
and calculating the combined weight value of each secondary index relative to the laboratory safety risk evaluation according to the weight of each criterion layer and the weight of each secondary index relative to the criterion layer.
3. The cloud model-based method for assessing the security risk of the managerial laboratory in colleges and universities, according to claim 2, wherein the obtaining of the weights of the criterion layers and the weights of the secondary indexes relative to the criterion layers according to a preset formula comprises:
Figure 727307DEST_PATH_IMAGE001
Figure 972343DEST_PATH_IMAGE002
wherein，αijRepresents an element in the decision matrix and,
Figure 955343DEST_PATH_IMAGE003
is the weighted value corresponding to the ith index.
4. The cloud model-based trans-tubular laboratory security risk assessment method for colleges and universities according to claim 3, wherein obtaining the maximum eigenvalue of the judgment matrix and performing consistency check on the judgment matrix comprises:
Figure 429180DEST_PATH_IMAGE004
Figure 837028DEST_PATH_IMAGE005
wherein A is a judgment matrix, W，And R.I. is a random consistency index, and the value of the random consistency index is related to the order n of the judgment matrix.
5. The cloud-model-based method for assessing the security risk of the managerial laboratory of colleges and universities according to claim 1, wherein the obtaining of the scoring result of the expert on the secondary evaluation indexes and the calculating of the first cloud model digital characteristics of each secondary evaluation index according to the scoring result comprise:
Figure 862753DEST_PATH_IMAGE006
Figure 473994DEST_PATH_IMAGE007
Figure 790DEST_PATH_IMAGE008
Figure 138510DEST_PATH_IMAGE009
wherein, in the standard evaluation cloud model, the XipRepresenting the scoring result of the ith secondary index by the P-th expert, the ExiCloud expectation representing the ith secondary index, the EniEntropy representing the ith secondary index, said HeiRepresenting the superentropy of the ith secondary index, and k is the number of experts.
6. The cloud model-based college through laboratory security risk assessment method according to claim 5, wherein a second cloud model digital feature of college through laboratory security risk assessment is calculated according to the first cloud model digital feature and the weight of the secondary index relative to the target layer;
Figure 476082DEST_PATH_IMAGE010
Figure 964832DEST_PATH_IMAGE011
Figure 170686DEST_PATH_IMAGE012
wherein q is the total number of the secondary indexes, wiThe combined weight of the ith secondary index relative to the target layer.
7. The cloud model-based college and university management laboratory security risk assessment method of claim 1, wherein the preset laboratory security risk score set comprises high, medium, low, and low.
8. The cloud model-based college and university management laboratory security risk assessment method according to claim 1, wherein the college management laboratory security risk assessment index system comprises: the system comprises a target layer, a criterion layer and a measure layer, wherein the elements of the target layer are an organization system, a safety system, safety education, basic safety and safety facilities, and the elements of the criterion layer are a management laboratory safety risk evaluation index system of colleges and universities.
9. The cloud model-based college-through laboratory security risk assessment method according to claim 8, wherein the elements of the measure layer, i.e. the secondary indicators, comprise: responsibility systems, financial guarantees, safety archives, system construction, operating rules, solar systems, electrical safety, water safety, personal protection, instrument safety, other safety, activity development, safety examinations, safety cultures, fire extinguishing devices, emergency devices, and ventilation devices.
10. The cloud model-based college-through laboratory security risk assessment method for colleges and universities according to claim 1, wherein in the scoring result of the expert on the secondary evaluation index, the scoring interval is [0, 1], 0 represents the highest risk, and 1 represents no risk.
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* Cited by examiner, † Cited by third party
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CN113610349A (en) * 2021-07-08 2021-11-05 北京工业大学 Chemical laboratory risk early warning method based on discrete Hopfield neural network
CN113610349B (en) * 2021-07-08 2023-10-20 北京工业大学 Chemistry laboratory risk early warning method based on discrete Hopfield neural network

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