CN110458482A - A kind of Evaluation of Fire Protection ability construction method based on big data - Google Patents
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Abstract
A kind of Evaluation of Fire Protection ability construction method based on big data, the following steps are included: the relevant historical business datum of S1, acquisition fire-fighting service unit and fire-fighting duty station, and history reason of fire in region is counted as unit of the moon, obtain event of fire sample；S2, fire indication is tentatively chosen from event of fire sample；S3, branch mailbox is carried out to fire indication；Capacity index is surveyed in S4, the low prevention of screening；S5, setting index marking rule；S6, setting index weights；S7, it establishes Evaluation of Fire Protection model and model is verified；It is proved to be successful rear output model.The present invention is screened by the branch mailbox to a large amount of fire datas and to fire correlative factor, determine each correlative factor weight, construct the computation model of Evaluation of Fire Protection score, the ability of Evaluation of Fire Protection can be provided for the Fire Escape in city, and the risk that fire can occurs to urban area carries out assessment and hidden fire-fighting danger is and guided to check work.
Description
Technical field
The present invention relates to municipal public safety technical field more particularly to a kind of Evaluation of Fire Protection energy based on big data
Power construction method.
Background technique
Fire-fighting work is the important component of national economy and social development, is the important leverage built a harmonious society.
The identification and elimination of hidden fire-fighting danger are that the important topic of urban fire control safety and the Ministry of Public Security construct social security against fire " fire prevention
The important component of " four abilities " that wall " engineering is proposed.
Security against fire Risk Comprehensive Evaluation refers to based on statistics, the set of factors of analyzing influence region security against fire,
Such as build property, age, sundries stacking situation；Then the grade and weight for evaluating their influence degrees carry out analysis meter again
It calculates；The fire-fighting to entire assessment object is made in the interaction for investigating each system component by the method for system engineering again
Security performance evaluation；It is main to use the subjective assessment based on fire-fighting business personnel currently in hidden fire-fighting danger ranking process, or
Based on the safety evaluation marking system that fire-fighting business reference manual is established, subitem score is equal to multiplied by subitem by evaluation total score
The mode of weight assesses the total fire safety performance of assessment object.
For current safety evaluation, sub-indicator determine dependent on business personnel offset the identification of anti-risk source with
And the subjective logics such as hierarchical structure of each factor analysis；The establishment method of index weights depends on mean allocation, business people
Member's formulation, AHP analytic hierarchy process (AHP) etc..It is more subjective with the setting of sub-indicator weight currently for sub-indicator selection, vulnerable to
Business personnel's experience and horizontal influence, objectivity are insufficient；Not to generated mass data in the construction of current smart city
To reasonable application, lacking one can be used for lateral comparison, standardized evaluation criterion.Especially facing numerous and jumbled fire
How correlative factor screens and extracts the index item being most suitable for for assessing fire-fighting risk and set specific weight, now
There are no the methods of a set of mature and reliable.
Summary of the invention
(1) goal of the invention
To solve technical problem present in background technique, the present invention proposes a kind of Evaluation of Fire Protection based on big data
Ability construction method, the present invention are screened by the branch mailbox to a large amount of fire datas and to fire correlative factor, are determined
Each correlative factor weight constructs the computation model of Evaluation of Fire Protection score, can provide fire-fighting for the Fire Escape in city
The ability of safety evaluation, and the risk that fire can occurs to urban area assess and instructs urban fire control hidden troubles removing with this
Work.
(2) technical solution
The present invention provides a kind of Evaluation of Fire Protection ability construction method based on big data, comprising the following steps:
S1: selection area A；By obtaining the relevant historical business datum of fire-fighting service unit and fire-fighting duty station,
And history reason of fire in the A of region is counted as unit of the moon, obtain B event of fire sample in the A of region；Again by B
B event of fire sample is divided into C high risk exemplar and D according to the frequency that fire occurs by each sample in event of fire sample
A low-risk sample, and select R sample in B event of fire sample as model training collection and Z sample as detection
Collection；Wherein, the sum of the quantity of C and the quantity of D are the quantity of B；The quantity that the sum of quantity and the quantity of Z of R are B；
S2: again analyzing R sample, obtains the fire cause of each event of fire and the development of fire and disposed
Journey, and specific relevant regulations description in fire codes is combined, obtain the E security against fire variables for causing fire to occur；
S3: handling the E security against fire variable for causing fire to occur, obtain discrete variable, qualitative variable and
Continuous variable；Wherein, direct branch mailbox is taken to discrete variable and qualitative variable and card side's branch mailbox is used to continuous variable branch mailbox
Method carries out branch mailbox, obtains F the first evaluation indexes；
S4: the information value IV of each evaluation index in F the first evaluation indexes is calculated based on comentropy, then gets rid of information
It is worth the evaluation index that IV value is less than given threshold, obtains that high j the second evaluation index of the degree of correlation occurs with fire；Wherein,
O.01 the threshold value of information value IV is set as；The index for being i for specific branch mailbox number, the circular of information value IV
It is as follows:
S5: sorting according to the fire high risk sample size in each case, the index i for being m for branch mailbox sum, when the index
When the attribute of i is in the branch mailbox of ranking jth name, then the score of index i is qi；Wherein
qi≤100；
S7: giving a mark one by one to R sample in the A of region, obtains R scoring Xij；The scoring square of R sample is constructed again
Battle array；
S8: to the matrix scoring X of column each in rating matrixijIt is converted into standardized numeric ratings Yij；YijCalculating it is public
Formula are as follows:
Wherein, max (Xi) indicate the top score of this index；min(Xi) indicate the minimum score of this index；
S9: according to the calculation formula of comentropy, the comentropy E of each criterionization scoring is calculatedj；EjCalculating it is public
Formula are as follows:
Wherein,If pij=0, then it defines
S10: the weight of each index is normalized to obtain each index weights Wj；WjCalculation formula are as follows:
S11: fire-fighting risk assessment is carried out with index i each in the A of region, obtains the evaluation score Q of each index ii, wherein Qi's
Calculation formula are as follows:
S12: score Q is evaluated to detection according to S2-S11 further according to Z sample in detection collectioniIt is verified；It verifies into
The computation model of output safety evaluation score Qi after function.
Preferably, after selected to region A in S1, fire scene in the A of region is carried out falling figure in conjunction with GIS map,
And statistics division is carried out to region A as unit of grid.
Preferably, the security against fire variable for causing fire to occur in S2 includes but is not limited to annual family income, house person
Whether quantity home-use electricity, home-use gas volume, fire occurrence time, the building age, has Fire lift, fire fighting device to make
With the time limit, flow of the people, per-capita housing, water bolt quantity, combustibles closeness, apart from fire-fighting and rescue point distance, it is whether high-rise,
Fire fighting device deployment density, fire fighting device whether diversification, fire-fighting publicity put up density, strong and weak electricity line condition, ventilation situation,
Whether climatic condition matches independent conveying pump, whether with individually power supply electricity generation system and building spacing.
Preferably, in S3 card side's branch mailbox method comprising the following specific steps
S31, corresponding card side's threshold value is obtained according to freedom degree and significance；
S32, the continuity numerical variable example discrete to need are ranked up, and each example belongs to a section；
S33, each pair of adjacent instances section chi-square value X is calculated2；X2Calculation formula are as follows:
Wherein, AijIndicate that the example quantity of fire occurs for i-th of section jth class index；
EijIndicate AijExpected frequency；
S34, the smallest a pair of of the section of chi-square value is merged；
S35, S33 and S34 is repeated until minimum X2 value is more than given threshold, then the branch mailbox for completing continuous variable works.
Above-mentioned technical proposal of the invention has following beneficial technical effect:
The present invention by the way that passing fire behavior fire alarm analysis of cases, objective quantification is screened to fire correlative factor,
It determines the various evaluation index scoring criterions and index weights for causing fire occurrence factor, constructs Evaluation of Fire Protection score Qi's
Computation model, the risk that fire occurs to region whereby carry out assessment and instruct urban fire control hidden troubles removing to work with this；Pass through
Safety evaluation score QiComputation model score building, can assist to some that there are the buildings of severe compromise
It is checked in advance, fire is strangled in cradle, ensure municipal public safety, the present invention is fire-fighting weakness ring in investigation area
Section extends efficient help with hidden fire-fighting danger identification, has very valuable directive significance；
In addition, the present invention is to carry out building peace to security against fire grade in unit based on a large amount of history fire alarm fire data
Full evaluation score QiComputation model, this be a kind of pair of big data system application effective utilization, us can be helped deeper to manage
Solve the moving law of this complication system of urban fire control safety；The present invention is based on fire-fighting index of the entropy assessment to required assessment to do
Right assessment, previous right assessment are mostly some analytic hierarchy process (AHP)s, expert graded, these methods have it is more it is subjective because
Element, and entropy assessment, with respect to those subjective weighting methods, the higher objectivity of precision is more preferable, can preferably explain acquired results.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the Evaluation of Fire Protection ability construction method based on big data proposed by the present invention.
Specific embodiment
In order to make the objectives, technical solutions and advantages of the present invention clearer, With reference to embodiment and join
According to attached drawing, the present invention is described in more detail.It should be understood that these descriptions are merely illustrative, and it is not intended to limit this hair
Bright range.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid this is unnecessarily obscured
The concept of invention.
As shown in Figure 1, a kind of Evaluation of Fire Protection ability construction method based on big data proposed by the present invention, including with
Lower step:
S1: selection area A；By obtaining the relevant historical business datum of fire-fighting service unit and fire-fighting duty station,
And history reason of fire in the A of region is counted as unit of the moon, obtain B event of fire sample in the A of region；
B event of fire sample is divided into C according to the frequency that fire occurs by each sample in B event of fire sample again
A high risk exemplar and D low-risk sample, and select R sample in B event of fire sample as model training collection and Z
A sample is as detection collection；Wherein, the sum of the quantity of C and the quantity of D are the quantity of B；The sum of quantity and the quantity of Z of R are B's
Quantity；
S2: again analyzing B event of fire sample, obtain each event of fire fire cause and fire development with
Disposal process, and specific relevant regulations description in fire codes is combined, it obtains the security against fire that E cause fire to occur and becomes
Amount；
S3: handling the E security against fire variable for causing fire to occur, obtain discrete variable, qualitative variable and
Continuous variable；Wherein, direct branch mailbox is taken to discrete variable and qualitative variable and card side's branch mailbox is used to continuous variable branch mailbox
Method carries out branch mailbox, obtains F the first evaluation indexes；
S4: the information value IV of each evaluation index in F the first evaluation indexes is calculated based on comentropy, then gets rid of information
It is worth the evaluation index that IV value is less than given threshold, obtains that high j the second evaluation index of the degree of correlation occurs with fire；It needs
Bright, information value IV represents single index to the predictive ability of Fires Occurred；
Wherein, O.01 information value IV threshold value is set as；The index for being i for specific branch mailbox number, information value IV
Circular it is as follows:
S5: sorting according to the fire high risk sample size in each case, the index i for being m for branch mailbox sum, when the index
When the attribute of i is in the branch mailbox of ranking jth name, then the score of index i is qi；Wherein
qi≤100；It is given a mark using 100 points of systems to obtaining index i；
S7: giving a mark one by one to R sample in the A of region, obtains R scoring Xij；The scoring square of R sample is constructed again
Battle array；
S8: standardized numeric ratings Y is converted into the matrix scoring Xij of column each in rating matrixij；YijCalculating
Formula are as follows:
Wherein, max (Xi) indicate the top score of this index；min(Xi) indicate the minimum score of this index；
S9: according to the calculation formula of comentropy, the comentropy E of each criterionization scoring is calculatedj；EjCalculating it is public
Formula are as follows:
Wherein,If pij=0, then it defines
S10: the weight of each index is normalized to obtain each index weights Wj；WjCalculation formula are as follows:
It should be noted that this method is to rely on entropy assessment to the determination of specific targets weight: basic according to information theory
The explanation of principle, information are a measurements of system order degree, and entropy is a measurement of the unordered degree of system；If index
Comentropy is smaller, and the information content which provides is bigger, and effect should be bigger played in overall merit, and weight should just be got over
It is high；
S11: fire-fighting risk assessment is carried out with index i each in the A of region, obtains the evaluation score Q of each index ii, wherein Qi's
Calculation formula are as follows:
S12: score Q is evaluated to detection according to S2-S11 further according to Z sample in detection collectioniIt is verified；It verifies into
Output safety evaluates score Q after functioniComputation model.
The present invention by the way that passing fire behavior fire alarm analysis of cases, objective quantification is screened to fire correlative factor,
It determines the various evaluation index scoring criterions and index weights for causing fire occurrence factor, constructs Evaluation of Fire Protection score Qi's
Computation model, the risk that fire occurs to region whereby carry out assessment and instruct urban fire control hidden troubles removing to work with this；Pass through
Safety evaluation score QiComputation model score building, can assist to some that there are the buildings of severe compromise
It is checked in advance, fire is strangled in cradle, ensure municipal public safety, the present invention is fire-fighting weakness ring in investigation area
Section extends efficient help with hidden fire-fighting danger identification, has very valuable directive significance.
In an alternative embodiment, after selected to region A in S1, fire in the A of region is occurred in conjunction with GIS map
Place carries out falling figure, and carries out statistics division to region A as unit of grid；Wherein, region division granularity can be according to analysis
Need to adjust, including but not limited to building, grid, street and region etc..
In an alternative embodiment, the security against fire variable for causing fire to occur in S2 includes but is not limited to family year
Whether income house person quantity, home-use electricity, home-use gas volume, fire occurrence time, the building age, has fire-fighting electric
Ladder, fire fighting device service life, flow of the people, per-capita housing, water bolt quantity, combustibles closeness, apart from fire-fighting and rescue point
Distance, whether high level, fire fighting device deployment density, fire fighting device whether diversification, fire-fighting publicity put up density, power electric line
Whether situation ventilation situation, climatic condition, matches independent conveying pump, whether with individually power supply electricity generation system and building spacing.
In an alternative embodiment, in S3 card side's branch mailbox method comprising the following specific steps
S31, corresponding card side's threshold value is obtained according to freedom degree and significance；
S32, the continuity numerical variable example discrete to need are ranked up, and each example belongs to a section；
S33, each pair of adjacent instances section chi-square value X2 is calculated；X2Calculation formula are as follows:
Wherein, AijIndicate that the example quantity of fire occurs for i-th of section jth class index；
EijIndicate AijExpected frequency；
S34, the smallest a pair of of the section of chi-square value is merged；
S35, S33 and S34 is repeated until minimum X2 value is more than given threshold, then the branch mailbox for completing continuous variable works.
In an alternative embodiment, comprising the following steps: the test sample of selection is obtained by safety evaluation respectively
Divide QiComputation model score, scoring is divided after being converted into hundred-mark system:
When sample score is not less than 60 points, then being denoted as the region with the sample factor, there is high risk fire occurs；
When sample score no more than 60 points and is not less than 50 timesharing, then being denoted as the region with the sample factor has apoplexy
Fire occurs for danger；
When sample score is not more than 50 timesharing, then being denoted as the region with the sample factor, there is low-risk fire occurs；
Through being checked according to actual sample, safety evaluation score QiComputation model precision ratio reach 95.0%, reach higher level.
It should be understood that above-mentioned specific embodiment of the invention is used only for exemplary illustration or explains of the invention
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (4)
1. a kind of Evaluation of Fire Protection ability construction method based on big data, which comprises the following steps:
S1: selection area A；By acquisition fire-fighting service unit and the relevant historical business datum of fire-fighting duty station, and with
The moon is that unit counts history reason of fire in the A of region, obtains B event of fire sample in the A of region；Again by B fire
B event of fire sample is divided into C high risk exemplar according to the frequency that fire occurs for each sample in event sample and D low
Risk sample, and select R sample in B event of fire sample as model training collection and Z sample as detection collection；Its
In, the sum of quantity of quantity of C and D is the quantity of B；The quantity that the sum of quantity and the quantity of Z of R are B；
S2: again analyzing R sample, obtains the fire cause of each event of fire and the development and disposal process of fire, and
It is described in conjunction with relevant regulations specific in fire codes, obtains the E security against fire variables for causing fire to occur；
S3: handling the E security against fire variable for causing fire to occur, and obtains discrete variable, qualitative variable and continuous
Variable；Wherein, to discrete variable and qualitative variable take direct branch mailbox and to continuous variable branch mailbox using card side's branch mailbox method into
Row branch mailbox obtains F the first evaluation indexes；
S4: the information value IV of each evaluation index in F the first evaluation indexes is calculated based on comentropy, then gets rid of information value
IV value is less than the evaluation index of given threshold, obtains that high j the second evaluation index of the degree of correlation occurs with fire；Wherein, information
O.01 the threshold value of value IV is set as；The index for being i for specific branch mailbox number, the circular of information value IV is such as
Under:
S5: sorting according to the fire high risk sample size in each case, the index i for being m for branch mailbox sum, when index i's
When attribute is in the branch mailbox of ranking jth name, then the score of index i is qi；Wherein
S7: giving a mark one by one to R sample in the A of region, obtains R scoring Xij；The rating matrix of R sample is constructed again；
S8: to the matrix scoring X of column each in rating matrixijIt is converted into standardized numeric ratings Yij；YijCalculation formula
Are as follows:
Wherein, max (Xi) indicate the top score of this index；min(Xi) indicate the minimum score of this index；
S9: according to the calculation formula of comentropy, the comentropy E of each criterionization scoring is calculatedj；EjCalculation formula are as follows:
Wherein,If pij=0, then it defines
S10: the weight of each index is normalized to obtain each index weights Wj；WjCalculation formula are as follows:
S11: fire-fighting risk assessment is carried out with index i each in the A of region, obtains the evaluation score Q of each index ii, wherein QiCalculating
Formula are as follows:
S12: score Q is evaluated to detection according to S2-S11 further according to Z sample in detection collectioniIt is verified；It is proved to be successful rear defeated
The computation model of safety evaluation score Qi out.
2. a kind of Evaluation of Fire Protection ability construction method based on big data according to claim 1, which is characterized in that
After selecting region A in S1, fire scene in the A of region is carried out falling figure in conjunction with GIS map, and right as unit of grid
Region A carries out statistics division.
3. a kind of Evaluation of Fire Protection ability construction method based on big data according to claim 1, which is characterized in that
Cause in S2 fire occur security against fire variable include but is not limited to annual family income, house person quantity, home-use electricity,
Whether home-use gas volume fire occurrence time, the building age, has Fire lift, fire fighting device service life, flow of the people, people
Equal living space, water bolt quantity, combustibles closeness, apart from fire-fighting and rescue point distance, whether high-rise, fire fighting device deployment is close
Degree, fire fighting device whether diversification, fire-fighting publicity put up density, strong and weak electricity line condition, ventilation situation, climatic condition, whether
With independent conveying pump, whether with individually power supply electricity generation system and building spacing.
4. a kind of Evaluation of Fire Protection ability construction method based on big data according to claim 1, which is characterized in that
Branch mailbox method in card side's in S3 comprising the following specific steps
S31, corresponding card side's threshold value is obtained according to freedom degree and significance；
S32, the continuity numerical variable example discrete to need are ranked up, and each example belongs to a section；
S33, each pair of adjacent instances section chi-square value X is calculated2；X2Calculation formula are as follows:
Wherein, AijIndicate that the example quantity of fire occurs for i-th of section jth class index；EijTable
Show AijExpected frequency；
S34, the smallest a pair of of the section of chi-square value is merged；
S35, S33 and S34 is repeated until minimum X2 value is more than given threshold, then the branch mailbox for completing continuous variable works.
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| CN114019942A (en) * | 2021-11-04 | 2022-02-08 | 哈尔滨工业大学 | Industrial robot system security threat evaluation method based on time-sharing frequency |
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| CN115471993B (en) * | 2022-07-06 | 2023-09-26 | 江苏科技大学 | Fire alarm management level evaluation method and system based on IMODE hierarchical evolutionary algorithm |
| CN115271659A (en) * | 2022-07-28 | 2022-11-01 | 南京戴尔塔智能制造研究院有限公司 | Urban fire hazard early warning method and system based on video analysis |
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| CN116720727A (en) * | 2023-01-12 | 2023-09-08 | 艾利特控股集团有限公司 | Clothing production workshop safety monitoring and early warning method and system |
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| CN117495113B (en) * | 2024-01-02 | 2024-05-28 | 海纳云物联科技有限公司 | Building fire safety assessment method, equipment and medium |
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Application publication date: 20191115 |