CN108510105A - A kind of forest fire sprawling prediction technique based on Markov model - Google Patents

A kind of forest fire sprawling prediction technique based on Markov model Download PDF

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CN108510105A
CN108510105A CN201810179014.2A CN201810179014A CN108510105A CN 108510105 A CN108510105 A CN 108510105A CN 201810179014 A CN201810179014 A CN 201810179014A CN 108510105 A CN108510105 A CN 108510105A
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fire
forest fire
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markov
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龙华
吕丹
吴睿
邵玉斌
杜庆治
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Kunming University of Science and Technology
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Abstract

The present invention relates to a kind of, and the forest fire based on Markov model spreads prediction technique, belongs to fire prediction technical field.Initially set up the forest fire Fundamental database in target forest zone；When forest fire occurs, the forest fire Fundamental database in target forest zone is recalled；Corresponding Markov forest fires are established with real-time weather environment spread prediction model by the forest fire Fundamental database in the target forest zone recalled；Prediction model is spread by established Markov forest fires, calculates the spreading trend of forest fire.The present invention is by introducing Markov model, mainly solve that traditional forest fire sprawling prediction technique is computationally intensive, calculates that the time is long, largely quantitative calculating initial value is needed for different fire hazard environments, so that forest fire damage control decision reacts slow phenomenon, to improve the rapidity and accuracy of forest fire sprawling prediction.

Description

A kind of forest fire sprawling prediction technique based on Markov model
Technical field
The present invention relates to a kind of, and the forest fire based on Markov model spreads prediction technique, belongs to fire prediction technology neck Domain.
Background technology
In recent decades, since worldwide population increases rapidly, process of industrialization is accelerated, and mankind's activity is to forest Aggravation is influenced, the anomalous variation of global climate is added, forest fire constantly occurs, and fast prediction forest fire spreading trend is compeled In the eyebrows and eyelashes.
Usually, although the computational methods based on fire dynamics are capable of the state in the Accurate Prediction scene of a fire, it is calculated Amount is big, and the calculating time is long, and largely quantitative calculating initial value is needed for different fire hazard environments, is unfavorable for damage by fire control The fast reaction of decision；Similarly, the various factor subjectivities based on the method for qualitative analysis given by analytic process are strong, with There are prodigious deviations for real process.
Invention content
The technical problem to be solved by the present invention is to the limitations and deficiency for the prior art, provide a kind of based on Markov moulds The forest fire of type spreads prediction technique, introduces Markov model, changes to traditional forest fire sprawling prediction technique Into solving that traditional forest fire sprawling prediction technique is computationally intensive, it is long to calculate the time, for different fire hazard environment needs Largely quantitative calculating initial value, so that forest fire damage control decision reacts slow phenomenon, to improve forest fire Spread the rapidity and accuracy of prediction.
The technical scheme is that：A kind of forest fire sprawling prediction technique based on Markov model, introduces Markov model is improved traditional forest fire sprawling prediction technique, specifically includes following 4 steps：
(1) the forest fire Fundamental database in target forest zone is established.
(2) when forest fire occurs, the forest fire Fundamental database in target forest zone is recalled.
(3) the forest fire Fundamental database in the target forest zone by recalling is corresponding with the foundation of real-time weather environment Markov forest fires spread prediction model.
(4) prediction model is spread by established Markov forest fires, calculates the spreading trend of forest fire.
Further, the Fundamental database described in step (1) refers to comprising the initiation required whole base of forest fire The database of plinth data, wherein including two parts：The three-dimensional framework database in forest zone and the basic database in forest zone.
Further, the three-dimensional framework database in the forest zone and the basic database in forest zone respectively refer to the three-dimensional in forest zone The data such as terrain data and vegetation, weather and fire occurred in the past.
Further, the purpose of the forest fire Fundamental database for recalling target forest zone described in step (2) be in order to The calculating described in the corresponding Markov forest fires sprawling prediction model of foundation and step (4) described in step (3) gets out of the wood The spreading trend of fire provides data.
Further, parameter that there are three the corresponding Markov forest fires sprawling prediction models of foundation described in step (3), S, PI and A, S are state set, i.e. the type of all combustibles in forest zone, such as herbaceous plant, shrub, arbor；PI is that priori is general The matrix of the probability composition of each combustible combustion when rate matrix, i.e. forest zone initialize；A is state-transition matrix, i.e., given The matrix of the probability composition of current combustible combustion in the case of previous combustible combustion.
Further, each combustible combustion when the type of all combustibles in the forest zone and forest zone initialize The matrix of probability composition is it is known that and is provided by the Fundamental database.
Further, the state set S of the type composition of all combustibles in the forest zone is：
S={ S1,S2,...,SN}
Wherein N is model state number, i.e. the type sum of all combustibles in forest zone, and can be retouched by Markov process It states.
Further, the matrix PI of the probability composition of each combustible combustion is when the initialization of the forest zone：
PI=[PIi]
Wherein PIi=P (Si), ∑ PIi=1,1≤i≤N, P (Si) it is combustible SiThe probability to burn when initialization.
Further, the state-transition matrix, i.e., it is described give it is current in the case of previous combustible combustion The probability calculation formula of combustible combustion is：
Wherein P (Si-1,Si) it is the front and back probability occurred of two combustible combustions, P (Si-1) it is combustible Si-1When initialization The probability of burning, λ are that forest fire spreads the factor, i.e. the factors such as wind speed, landform are influenced caused by forest fire.
Further, forest fire sprawling factor lambda can be improved to obtain by the Fire spreading model of Wang Zhengfei, count Calculating formula is：
Wherein R0For initial rate of propagation, KsFor fuel type correction factor, KwFor wind correction coefficient,For landform Waviness correction factor,For the gradient, ε is the other influences factor.
Further, forest fire sprawling factor lambda need to be repeated experiment and obtained by specific event of fire；And add Entering being capable of fast prediction forest fire spreading trend after forest fire sprawling factor lambda is calculated.
Present invention has the advantages that：Solve traditional forest fire sprawling prediction technique is computationally intensive, it is long to calculate the time, Largely quantitative calculating initial value is needed for different fire hazard environments, so that the reaction of forest fire damage control decision is slow The phenomenon that, to improve the rapidity and accuracy of forest fire sprawling prediction.
Description of the drawings
Fig. 1 is the flow diagram of the present invention；
Fig. 2 is the schematic diagram of step of the present invention (3).
Specific implementation mode
With reference to the accompanying drawings and detailed description, the invention will be further described.
Embodiment 1：As shown in Fig. 2, a kind of forest fire based on Markov model spreads prediction technique, Markov is introduced Model is improved traditional forest fire sprawling prediction technique, specifically includes following 4 steps：
(1) the forest fire Fundamental database in target forest zone is established.
(2) when forest fire occurs, the forest fire Fundamental database in target forest zone is recalled.
(3) the forest fire Fundamental database in the target forest zone by recalling is corresponding with the foundation of real-time weather environment Markov forest fires spread prediction model.
(4) prediction model is spread by established Markov forest fires, calculates the spreading trend of forest fire.
Further, the Fundamental database described in step (1) refers to comprising the initiation required whole base of forest fire The database of plinth data, wherein including two parts：The three-dimensional framework database in forest zone and the basic database in forest zone.
Further, the three-dimensional framework database in the forest zone and the basic database in forest zone respectively refer to the three-dimensional in forest zone The data such as terrain data and vegetation, weather and fire occurred in the past.
Further, the purpose of the forest fire Fundamental database for recalling target forest zone described in step (2) be in order to The calculating described in the corresponding Markov forest fires sprawling prediction model of foundation and step (4) described in step (3) gets out of the wood The spreading trend of fire provides data.
Further, parameter that there are three the corresponding Markov forest fires sprawling prediction models of foundation described in step (3), S, PI and A, S are state set, i.e. the type of all combustibles in forest zone, such as herbaceous plant, shrub, arbor；PI is that priori is general The matrix of the probability composition of each combustible combustion when rate matrix, i.e. forest zone initialize；A is state-transition matrix, i.e., given The matrix of the probability composition of current combustible combustion in the case of previous combustible combustion.
Further, each combustible combustion when the type of all combustibles in the forest zone and forest zone initialize The matrix of probability composition is it is known that and is provided by the Fundamental database.
Further, the state set S of the type composition of all combustibles in the forest zone is：
S={ S1,S2,...,SN}
Wherein N is model state number, i.e. the type sum of all combustibles in forest zone, and can be retouched by Markov process It states.
Further, the matrix PI of the probability composition of each combustible combustion is when the initialization of the forest zone：
PI=[PIi]
Wherein PIi=P (Si), ∑ PIi=1,1≤i≤N, P (Si) it is combustible SiThe probability to burn when initialization.
Further, the state-transition matrix, i.e., it is described give it is current in the case of previous combustible combustion The probability calculation formula of combustible combustion is：
Wherein P (Si-1,Si) it is the front and back probability occurred of two combustible combustions, P (Si-1) it is combustible Si-1When initialization The probability of burning, λ are that forest fire spreads the factor, i.e. the factors such as wind speed, landform are influenced caused by forest fire.
Further, forest fire sprawling factor lambda can be improved to obtain by the Fire spreading model of Wang Zhengfei, count Calculating formula is：
Wherein R0For initial rate of propagation, KsFor fuel type correction factor, KwFor wind correction coefficient,For landform Waviness correction factor,For the gradient, ε is the other influences factor.
Further, forest fire sprawling factor lambda need to be repeated experiment and obtained by specific event of fire；And add Entering being capable of fast prediction forest fire spreading trend after forest fire sprawling factor lambda is calculated.
Embodiment 2：As shown in Figure 1, a kind of forest fire based on Markov model spreads prediction technique, to traditional gloomy Woods fire spread prediction technique is improved.Initially set up the Fundamental database of the forest fire in target forest zone；Then occurring Corresponding Markov forest fires are established with real-time weather environment by Fundamental database when forest fire and spread prediction model, this There are three parameter, S, PI and A for model, and S is state set, i.e. the type of all combustibles in forest zone；PI is prior probability matrix, i.e., The matrix of the probability composition of each combustible combustion when forest zone initializes；A is state-transition matrix, i.e., given previous flammable The matrix of object probability composition of current combustible combustion in the case of burning；It is climing finally by established Markov forest fires Prolong the spreading trend that prediction model calculates forest fire.Compared with prior art, the present invention by introducing Markov model, it is main Solves computationally intensive traditional forest fire sprawling prediction technique, calculating time length, for different fire hazard environment needs Largely quantitative calculating initial value, so that forest fire damage control decision reacts slow phenomenon, to improve forest fire Spread the rapidity and accuracy of prediction.
The specific implementation mode of the present invention is explained in detail above in association with attached drawing, but the present invention is not limited to above-mentioned Embodiment within the knowledge of a person skilled in the art can also be before not departing from present inventive concept Put that various changes can be made.

Claims (10)

1. a kind of forest fire based on Markov model spreads prediction technique, it is characterised in that：
(1) the forest fire Fundamental database in target forest zone is established；
(2) when forest fire occurs, the forest fire Fundamental database in target forest zone is recalled；
(3) to establish corresponding Markov with real-time weather environment by the forest fire Fundamental database in the target forest zone recalled gloomy Woods fire spread prediction model；
(4) prediction model is spread by established Markov forest fires, calculates the spreading trend of forest fire.
2. the forest fire according to claim 1 based on Markov model spreads prediction technique, it is characterised in that：It is described The Fundamental database of step (1) refers to comprising the database for causing the required whole basic data of forest fire, wherein wrapping Containing two parts：The three-dimensional framework database in forest zone and the basic database in forest zone；
The three-dimensional framework database in the forest zone and the basic database in forest zone respectively refer to three dimensional topographic data and the plant in forest zone By, weather and data of fire occurred in the past.
3. the forest fire according to claim 1 based on Markov model spreads prediction technique, it is characterised in that：It is described The purpose of the forest fire Fundamental database for recalling target forest zone of step (2) is in order to corresponding to the foundation described in step (3) Markov forest fires sprawling prediction model and step (4) described in calculate forest fire spreading trend provide number According to.
4. the forest fire according to claim 1 based on Markov model spreads prediction technique, it is characterised in that：It is described There are three parameters for the corresponding Markov forest fires sprawling prediction model of foundation of step (3), and S, PI and A, S is state set, That is the type of all combustibles in forest zone；PI is prior probability matrix, i.e., the probability of each combustible combustion when forest zone initializes The matrix of composition；A is state-transition matrix, i.e., the probability of current combustible combustion in the case of given previous combustible combustion The matrix of composition.
5. the forest fire according to claim 4 based on Markov model spreads prediction technique, it is characterised in that：It is described All combustibles in forest zone type and forest zone initialize when each combustible combustion probability composition matrix be it is known that And it is provided by the Fundamental database.
6. the forest fire according to claim 4 based on Markov model spreads prediction technique, it is characterised in that：It is described All combustibles in forest zone type composition state set S be：
S={ S1,S2,...,SN}
Wherein, N is model state number, i.e. the type sum of all combustibles in forest zone, and can be described by Markov process.
7. the forest fire according to claim 4 based on Markov model spreads prediction technique, it is characterised in that：It is described Forest zone initialization when each combustible combustion probability composition matrix PI be：
PI=[PIi]
Wherein, PIi=P (Si), ∑ PIi=1,1≤i≤N, P (Si) it is combustible SiThe probability to burn when initialization.
8. the forest fire according to claim 4 based on Markov model spreads prediction technique, it is characterised in that：It is described State-transition matrix A, i.e., the described probability calculation for giving current combustible combustion in the case of previous combustible combustion Formula is：
Wherein, P (Si-1,Si) it is the front and back probability occurred of two combustible combustions, P (Si-1) it is combustible Si-1It burns when initialization Probability, λ is that forest fire spreads the factor, i.e. the factors such as wind speed, landform influence caused by forest fire.
9. the forest fire according to claim 8 based on Markov model spreads prediction technique, it is characterised in that：It is described Forest fire sprawling factor lambda can improve to obtain by the Fire spreading model of Wang Zhengfei, calculation formula is：
Wherein, R0For initial rate of propagation, KsFor fuel type correction factor, KwFor wind correction coefficient,For landform waviness Correction factor,For the gradient, ε is the other influences factor.
10. the forest fire according to claim 8 based on Markov model spreads prediction technique, it is characterised in that：Institute The forest fire sprawling factor lambda stated need to be repeated experiment and obtained by specific event of fire.
CN201810179014.2A 2018-03-05 2018-03-05 A kind of forest fire sprawling prediction technique based on Markov model Pending CN108510105A (en)

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Cited By (4)

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Publication number Priority date Publication date Assignee Title
CN109492314A (en) * 2018-11-19 2019-03-19 中国矿业大学 A kind of determination method of the horizontal best firebreak of compartment combustible
CN111476964A (en) * 2020-03-04 2020-07-31 宁波财经学院 Remote forest fire prevention monitoring system and method
CN111539634A (en) * 2020-04-26 2020-08-14 众安仕（北京）科技有限公司 Fire rescue aid decision scheme generation method
CN112985437A (en) * 2021-02-05 2021-06-18 国网吉林省电力有限公司长春供电公司 Path navigation method and device in disaster area scene

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109492314A (en) * 2018-11-19 2019-03-19 中国矿业大学 A kind of determination method of the horizontal best firebreak of compartment combustible
CN111476964A (en) * 2020-03-04 2020-07-31 宁波财经学院 Remote forest fire prevention monitoring system and method
CN111539634A (en) * 2020-04-26 2020-08-14 众安仕（北京）科技有限公司 Fire rescue aid decision scheme generation method
CN112985437A (en) * 2021-02-05 2021-06-18 国网吉林省电力有限公司长春供电公司 Path navigation method and device in disaster area scene

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Application publication date: 20180907