CN105894706B - A kind of forest fire prediction technique and its system - Google Patents
A kind of forest fire prediction technique and its system Download PDFInfo
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- CN105894706B CN105894706B CN201610283727.4A CN201610283727A CN105894706B CN 105894706 B CN105894706 B CN 105894706B CN 201610283727 A CN201610283727 A CN 201610283727A CN 105894706 B CN105894706 B CN 105894706B
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/005—Fire alarms; Alarms responsive to explosion for forest fires, e.g. detecting fires spread over a large or outdoors area
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
Abstract
The invention discloses a kind of forest fire prediction technique and its systems, this method and system acquire temperature data, humidity data, rainfall product data, air speed data and the ground fuel moisture content data of forest in real time, and calculate the Triangular Fuzzy Number of fire, judge fire size class, realizes the dynamic prediction of forest fire.Simultaneously, this method and system can also input season parameter, time parameter, density of population parameter, roading density parameter, the Triangular Fuzzy Number of population activity parameter, history fire parameter and ground fuel species parameter, environmental factor and human factor are included in fire prediction computation model, further improve the accuracy of fire prediction.
Description
Technical field
The present invention relates to field of forest fire prevention more particularly to a kind of forest fire prediction techniques and its system.
Background technique
Forest is that the mankind depend on for existence and the indispensable resource of social development.Since the mankind are certain in social activities
Reasons, the forest fires such as out of control and abnormal natural cause happen occasionally, and cause to human life's property and ecological environment huge
Harm.China is with a varied topography due to vast in territory, weather multiplicity, Forest Types and different, the Levels of Social Economic Development of distribution
Different, the density of population is big and is unevenly distributed, the reasons such as national awareness of the importance of fire prevention weakness, and forest fire protection task is very all the time
It is severe.
A possibility that one important content of forest fire protection work is fire alarm, i.e., forest fire occurs is made a prediction
And forest fire protection department is reminded to adjust the focus of work and counter-measure in time.In current existing all kinds of Forecasting Model of Forest Fire
In, it generallys use Related Mathematical Models and statistical is carried out to the time of forest fire generation and number in longer term the last period
Analysis is predicted for possible forest fire frequency in the future.The class model is only theoretically predicted following a certain
The number of fire may occur in period, also as Fire response prediction model, be not real-time fire prediction model, not
A possibility that forest fire capable of being occurred according to the real time information in forest environment, makes a prediction and provides alarm.
Summary of the invention
The technical problem to be solved by the present invention is to Forecasting Model of Forest Fire in the prior art cannot be according to forest environment
In real time information a possibility that forest fire is occurred make a prediction and alarm be provided.
In order to solve the above technical problems, the technical solution adopted by the present invention are as follows:
A kind of forest fire prediction technique, includes the following steps:
(1), acquire or input the fire parameter of forest to be predicted, the fire parameter include at least temperature parameter and
Humidity parameter；Each fire parameter using Triangular Fuzzy Number (a, b, c) indicate, a, b, c be respectively lower limit value, probable value and on
Limit value, wherein 0≤a < c≤1,0≤a≤b, b≤c≤1；
(2), the Triangular Fuzzy Number of forest fire is calculated according to following formula,
Wherein, (ai, bi, ci) indicate the Triangular Fuzzy Number of each fire parameter,
OepratorOperation rule with oeprator ⊙ is:
(a1, b1, c1)⊙(a2, b2, c2)=(a1/a2, b1/b2, c1/c2)；
(3), fire alarm is made according to fire Triangular Fuzzy Number.
Specifically, the value mode of the Triangular Fuzzy Number of the temperature parameter is: set temperature lower limit and temperature upper limit point
It Wei not P1Degree Celsius and Q1Degree Celsius, it is R that measurement, which obtains current forest temperature,1Degree Celsius, calculate the Triangular Fuzzy Number of temperature parameter
Probable value be b1=(R1-P1)/(Q1-P1), determine b1Belong to [0,0.25), [0.25,0.5), [0.5,0.75), [0.75,1]
Which section in four numerical intervals, the Triangular Fuzzy Number S of temperature parameter1=(a1, b1, c1), wherein a1、c1Before respectively equal to
State b1The endpoint value in affiliated section；
The value mode of the Triangular Fuzzy Number of the humidity parameter is: measuring current forest relative humidity is P2, 0≤P2≤
1, calculate the probable value b of the Triangular Fuzzy Number of humidity parameter2=P2, determine b2Belong to [0,0.25), [0.25,0.5), [0.5,
0.75), which section in [0.75,1] four numerical intervals, the Triangular Fuzzy Number S of humidity parameter2=(a2, b2, c2), wherein
a2、c2Respectively equal to aforementioned b2The endpoint value in affiliated section.
Further, the fire parameter further includes wind speed parameter and rainfall parameter, the Triangular Fuzzy Number of wind speed parameter
Value mode be: the wind speed setting upper limit be P3Thousand ms/h, the wind speed that measurement obtains current forest is Q3Thousand ms/h, wind
The probable value b of the Triangular Fuzzy Number of fast parameter3=Q3/P3, determine b3Belong to [0,0.25), [0.25,0.5), [0.5,0.75),
Which section in [0.75,1] four numerical intervals, the Triangular Fuzzy Number S of wind speed parameter3=(a3, b3, c3), wherein a3、c3Point
It Deng Yu not aforementioned b3The endpoint value in affiliated section.
The value mode of the Triangular Fuzzy Number of rainfall parameter is: the rainfall upper limit for the twenty four hours of setting over is P4
Milliliter, it is Q that measurement, which obtains rainfall in the twenty four hours of current forest,4Milliliter, the Triangular Fuzzy Number of rainfall parameter can
It can value b4=Q4/P4, determine b4Belong to [0,0.25), [0.25,0.5), [0.5,0.75), in [0.75,1] four numerical intervals
Which section, the Triangular Fuzzy Number S of wind speed parameter4=(a4, b4, c4), wherein a4、c4Respectively equal to aforementioned b4Affiliated section
Endpoint value.
Further, it further includes density of population parameter that the fire parameter, which further includes the fire parameter,；Density of population ginseng
The value mode of several Triangular Fuzzy Numbers is: setting the density of population upper limit as P5, the population of the current wood land of statistical calculation is close
Degree is Q5, the probable value b of the Triangular Fuzzy Number of density of population parameter5=Q5/P5If b5> 1, then enable b5=1.Determine b5Belong to
[0,0.25), [0.25,0.5), [0.5,0.75), which section in [0.75,1] four numerical intervals, density of population parameter
Triangular Fuzzy Number S5=(a5, b5, c5), wherein a5、c5Respectively equal to aforementioned b5The endpoint value in affiliated section.
Further, the fire parameter further includes ground fuel corruption extent index；Ground fuel degenerates degree
The value mode of the Triangular Fuzzy Number of parameter is: the moisture content for measuring ground fuel is P6, ground fuel corruption degree ginseng
The probable value b of several Triangular Fuzzy Numbers6=1-P6.Determine b6Belong to [0,0.25), [0.25,0.5), [0.5,0.75), [0.75,
1] which section in four numerical intervals, ground fuel degenerate the Triangular Fuzzy Number S of extent index6=(a6, b6, c6),
Middle a6、c6Respectively equal to aforementioned b6The endpoint value in affiliated section.
Further, the fire parameter further includes season parameter, time parameter, roading density parameter, population activity ginseng
One of number, history fire parameter and ground fuel species parameter are a variety of.
Further, the concrete mode of the fire alarm is: judge the probable value b of fire Triangular Fuzzy Number belong to [0,
0.125), [0.125,0.375), [0.375,0.625), [0.625,0.875), which in [0.875,1] five numerical intervals
A section, fire size class is identified as according to section locating for b it is basic, normal, high, dangerous or extremely dangerous, according to different fire
Calamity grade makes corresponding fire alarm.
The present invention also provides a kind of forest fire forecasting systems, comprising:
Acquisition unit is distributed in each collection point of forest planned in advance, at least collecting temperature value and humidity value；
Input unit, for inputting fire parameter；
Central processing unit receives the data of acquisition unit acquisition and the fire parameter of input unit；Fire parameter is at least
Including temperature parameter and humidity parameter, each fire parameter is indicated using Triangular Fuzzy Number (a, b, c), under a, b, c are respectively
Limit value, probable value and upper limit value, wherein 0≤a < c≤1,0≤a≤b, b≤c≤1；
The Triangular Fuzzy Number of forest fire is calculated according to following formula,
Wherein, (ai, bi, ci) indicate the Triangular Fuzzy Number of each fire parameter,
OepratorOperation rule with oeprator ⊙ is:
(a1, b1, c1)⊙(a2, b2, c2)=(a1/a2, b1/b2, c1/c2)；
The value mode of the Triangular Fuzzy Number of temperature parameter is: set temperature lower limit and temperature upper limit are respectively P1Degree Celsius
And Q1Degree Celsius, it is R that measurement, which obtains current forest temperature,1Degree Celsius, calculate the probable value b of the Triangular Fuzzy Number of temperature parameter1=
(R1-P1)/(Q1-P1), determine b1Belong to [0,0.25), [0.25,0.5), [0.5,0.75), in [0.75,1] four numerical intervals
Which section, the Triangular Fuzzy Number S of temperature parameter1=(a1, b1, c1), wherein a1、c1Respectively equal to aforementioned b1Affiliated section
Endpoint value；
The value mode of the Triangular Fuzzy Number of humidity parameter is: measuring current forest relative humidity is P2, 0≤P2≤ 1, meter
Calculate the probable value b of the Triangular Fuzzy Number of humidity parameter2=P2, determine b2Belong to [0,0.25), [0.25,0.5), [0.5,0.75),
Which section in [0.75,1] four numerical intervals, the Triangular Fuzzy Number S of humidity parameter2=(a2, b2, c2), wherein a2、c2Point
It Deng Yu not aforementioned b2The endpoint value in affiliated section；
Alarm unit issues alarm of fire, by central processing unit controls.
Further, the acquisition unit also acquires wind speed, rainfall and ground fuel moisture content.
Further, the acquisition unit is transferred to central processing unit, acquisition unit for data are acquired by internet
It is powered using rechargeable battery, battery is charged using solar energy conversion equipment.
The utility model has the advantages that (1), the present invention provides a kind of forest fire prediction technique and its system, this method and system can
Temperature data, humidity data, rainfall product data, air speed data and the ground fuel moisture content data of acquisition forest in real time, and
The Triangular Fuzzy Number for calculating fire realizes the dynamic prediction of forest fire, improves the accuracy of fire prediction.(2) originally
The forest fire prediction technique provided is provided and its system is also conceivable to season parameter, time parameter, density of population parameter, road
Direction density parameter, one of population activity parameter, history fire parameter and ground fuel species parameter or a variety of, by environment
Factor and human factor joined in Forecasting Model of Forest Fire, further improve the accuracy of fire prediction.
Detailed description of the invention
Fig. 1 is forest fire forecasting system structural block diagram of the present invention.
Wherein: 1, acquisition unit；2, input unit；3, central processing unit；4, alarm unit.
Specific embodiment
Invention is further described in detail with reference to the accompanying drawings and detailed description.
Embodiment 1
As shown in Figure 1, the forest fire forecasting system of the present embodiment includes:
Acquisition unit 1 is distributed in each collection point of forest planned in advance, collecting temperature value, humidity value, wind speed and drop
Rainfall；Acquisition unit 1 will acquire data by internet and be transferred to central processing unit 3, and acquisition unit 1 uses rechargeable battery
Power supply, battery are charged using solar energy conversion equipment；
Input unit 2, for inputting fire parameter；
Central processing unit 3 receives the fire parameter of data and input unit 2 that acquisition unit 1 acquires；
Alarm unit 4 issues alarm of fire, is controlled by central processing unit 3.
The temperature value R that central processing unit 3 is transmitted according to acquisition unit 11, rh value P2, air speed value P3, 24 hours
Interior rainfall magnitude P4With ground fuel sweat rate P5The Triangular Fuzzy Number of fire is calculated, steps are as follows for calculating:
(1) probable value for calculating the Triangular Fuzzy Number of temperature parameter is b1=(R1-P1)/(Q1-P1), wherein P1And Q1It is pre-
If temperature upper limit and lowest temperature.Determine b1Belong to [0,0.25), [0.25,0.5), [0.5,0.75), [0.75,1] four
Which section in numerical intervals, the Triangular Fuzzy Number S of temperature parameter1=(a1, b1, c1), wherein a1、c1Respectively equal to aforementioned b1
The endpoint value in affiliated section；
(2) the probable value b of the Triangular Fuzzy Number of humidity parameter is calculated2=P2, wherein 0≤P2≤1.Determine b2Belong to [0,
0.25), [0.25,0.5), [and 0.5,0.75), which section in [0.75,1] four numerical intervals, the Triangle Module of humidity parameter
Paste number S2=(a2, b2, c2), wherein a2、c2Respectively equal to aforementioned b2The endpoint value in affiliated section.
(3) the probable value b of the Triangular Fuzzy Number of calculation of wind speed parameter3=Q3/P3, wherein P3For preset upper wind velocity limit value.
Determine b3Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which section in [0.75,1] four numerical intervals, wind
The Triangular Fuzzy Number S of fast parameter3=(a3, b3, c3), wherein a3、c3Respectively equal to aforementioned b3The endpoint value in affiliated section.
(4) the probable value b of the Triangular Fuzzy Number of rainfall parameter is calculated4=Q4/P4, wherein P4It is small for preset forest 24
When the rainfall upper limit.Determine b4Belong to [0,0.25), [0.25,0.5), [0.5,0.75), in [0.75,1] four numerical intervals
Which section, the Triangular Fuzzy Number S of wind speed parameter4=(a4, b4, c4), wherein a4、c4Respectively equal to aforementioned b4Affiliated section
Endpoint value.
(5) the probable value b of the Triangular Fuzzy Number of ground fuel corruption degree is calculated5=1-P5.Determine b5Belong to [0,
0.25), [0.25,0.5), [and 0.5,0.75), which section in [0.75,1] four numerical intervals, ground fuel degenerates journey
Spend the Triangular Fuzzy Number S of parameter5=(a5, b5, c5), wherein a5、c5Respectively equal to aforementioned b5The endpoint value in affiliated section.
(6) Triangular Fuzzy Number of forest fire is calculated according to following formula,
Wherein, (ai, bi, ci) indicate the Triangular Fuzzy Number of each fire parameter,
OepratorOperation rule with oeprator ⊙ is:
(a1, b1, c1)⊙(a2, b2, c2)=(a1/a2, b1/b2, c1/c2)；
In order to further increase the accuracy of fire prediction, environmental factor and human factor are included in fire prediction model,
The forest fire forecasting system of the present embodiment can also input season parameter, time parameter, density of population ginseng by input unit 2
Number, roading density parameter, the Triangular Fuzzy Number S of population activity parameter, history fire parameter and ground fuel species parameteri=
(ai, bi, ci), central processing unit 3 calculates fire triangle according to the aggregation of data that acquisition unit 1 and input unit 2 transmit and obscures
Number.
Central processing unit 3 judge the probable value b of fire Triangular Fuzzy Number T=(a, b, c) belong to [0,0.125),
[0.125,0.375), [0.375,0.625), [0.625,0.875), which section in [0.875,1] five numerical intervals,
Fire size class is identified as according to section locating for b basic, normal, high, dangerous or extremely dangerous, central processing unit 3 is not according to
Same fire size class control alarm unit 4 makes corresponding fire alarm.
Although embodiments of the present invention are illustrated in specification, these embodiments are intended only as prompting,
It should not limit protection scope of the present invention.It is equal that various omission, substitution, and alteration are carried out without departing from the spirit and scope of the present invention
It should be included within the scope of the present invention.
Claims (9)
1. a kind of forest fire prediction technique, it is characterised in that include the following steps:
(1), the fire parameter of forest to be predicted is acquired or inputs, the fire parameter includes at least temperature parameter and humidity
Parameter；Each fire parameter indicates that a, b, c are respectively lower limit value, probable value and the upper limit using Triangular Fuzzy Number (a, b, c)
Value, wherein 0≤a < c≤1,0≤a≤b, b≤c≤1；
(2), the Triangular Fuzzy Number of forest fire is calculated according to following formula,
Wherein, (ai, bi, ci) indicate the Triangular Fuzzy Number of each fire parameter,
OepratorOperation rule with oeprator ⊙ is:
(a1, b1, c1)⊙(a2, b2, c2)=(a1/a2, b1/b2, c1/c2)；
(3), fire alarm is made according to fire Triangular Fuzzy Number；
The value mode of the Triangular Fuzzy Number of the temperature parameter is: set temperature lower limit and temperature upper limit are respectively P1Degree Celsius
And Q1Degree Celsius, it is R that measurement, which obtains current forest temperature,1Degree Celsius, calculate the probable value b of the Triangular Fuzzy Number of temperature parameter1=
(R1-P1)/(Q1-P1), determine b1Belong to [0,0.25), [0.25,0.5), [0.5,0.75), in [0.75,1] four numerical intervals
Which section, the Triangular Fuzzy Number S of temperature parameter1=(a1, b1, c1), wherein a1、c1Respectively equal to aforementioned b1Affiliated section
Endpoint value；
The value mode of the Triangular Fuzzy Number of the humidity parameter is: measuring current forest relative humidity is P2, 0≤P2≤ 1, meter
Calculate the probable value b of the Triangular Fuzzy Number of humidity parameter2=P2, determine b2Belong to [0,0.25), [0.25,0.5), [0.5,0.75),
Which section in [0.75,1] four numerical intervals, the Triangular Fuzzy Number S of humidity parameter2=(a2, b2, c2), wherein a2、c2Point
It Deng Yu not aforementioned b2The endpoint value in affiliated section.
2. forest fire prediction technique according to claim 1, which is characterized in that the fire parameter further includes wind speed ginseng
Several and rainfall parameter；
The value mode of the Triangular Fuzzy Number of wind speed parameter is: the wind speed setting upper limit is P3Thousand ms/h, measurement obtains current gloomy
The wind speed of woods is Q3Thousand ms/h, the probable value b of the Triangular Fuzzy Number of wind speed parameter3=Q3/P3If b3> 1, then enable b3=1；
Determine b3Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which section in [0.75,1] four numerical intervals, wind
The Triangular Fuzzy Number S of fast parameter3=(a3, b3, c3), wherein a3、c3Respectively equal to aforementioned b3The endpoint value in affiliated section；
The value mode of the Triangular Fuzzy Number of rainfall parameter is: the rainfall upper limit for the twenty four hours of setting over is P4Milliliter,
It is Q that measurement, which obtains rainfall in the twenty four hours of current forest,4Milliliter, the probable value b of the Triangular Fuzzy Number of rainfall parameter4
=Q4/P4, determine b4Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which of [0.75,1] four numerical intervals
Section, the Triangular Fuzzy Number S of wind speed parameter4=(a4, b4, c4), wherein a4、c4Respectively equal to aforementioned b4The endpoint in affiliated section
Value.
3. forest fire prediction technique according to claim 2, which is characterized in that further include ground fuel corruption degree
Parameter；
The value mode of the Triangular Fuzzy Number of ground fuel corruption extent index is: the moisture content for measuring ground fuel is P5,
Ground fuel degenerates the probable value b of the Triangular Fuzzy Number of extent index5=1-P5；Determine b5Belong to [0,0.25), [0.25,
0.5), [0.5,0.75), which section in [0.75,1] four numerical intervals, ground fuel degenerates the triangle of extent index
Fuzzy number S5=(a5, b5, c5), wherein a5、c5Respectively equal to aforementioned b5The endpoint value in affiliated section.
4. forest fire prediction technique according to claim 3, which is characterized in that the fire parameter further includes that population is close
Spend parameter；
The value mode of the Triangular Fuzzy Number of density of population parameter is: setting the density of population upper limit as P6, the current forest of statistical calculation
The density of population in region is Q6, the probable value b of the Triangular Fuzzy Number of density of population parameter6=Q6/P6If b6> 1, then enable b6=
1；Determine b6Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which section in [0.75,1] four numerical intervals,
The Triangular Fuzzy Number S of density of population parameter6=(a6, b6, c6), wherein a6、c6Respectively equal to aforementioned b6The endpoint value in affiliated section.
5. forest fire prediction technique according to claim 4, which is characterized in that the fire parameter further includes season ginseng
It counts, time parameter, roading density parameter, one in population activity parameter, history fire parameter and ground fuel species parameter
Kind is a variety of.
6. forest fire prediction technique according to claim 5, which is characterized in that the concrete mode of the fire alarm
Be: judge the probable value b of fire Triangular Fuzzy Number belong to [0,0.125), [0.125,0.375), [0.375,0.625),
[0.625,0.875), which section in [0.875,1] five numerical intervals is distinguished fire size class according to section locating for b true
It is set to basic, normal, high, dangerous or extremely dangerous, makes corresponding fire alarm according to different fire size class.
7. a kind of forest fire forecasting system characterized by comprising
Acquisition unit (1) is distributed in each collection point of forest planned in advance, at least collecting temperature value and humidity value；
Input unit (2), for inputting fire parameter；
Central processing unit (3) receives the data of acquisition unit (1) acquisition and the fire parameter of input unit (2), according to right
It is required that the value mode of the Triangular Fuzzy Number of 2 to 4 any fire parameters establishes the Triangular Fuzzy Number of fire parameter, foundation
Fire formula described in claim 1 calculates the Triangular Fuzzy Number of fire；
Alarm unit (4) issues alarm of fire, is controlled by central processing unit (3).
8. forest fire forecasting system according to claim 7, which is characterized in that the acquisition unit (1) also acquires wind
Speed, rainfall and ground fuel moisture content.
9. forest fire forecasting system according to claim 7 or 8, which is characterized in that the acquisition unit (1) passes through mutual
Acquisition data are transferred to central processing unit (3) by networking, and acquisition unit (1) is powered using rechargeable battery, and battery is using too
Positive energy conversion equipment charging.
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| CN109612573B (en) * | 2018-12-06 | 2021-01-12 | 南京林业大学 | Crown fire and ground fire detection method based on noise spectrum analysis |
| CN110176119A (en) * | 2019-05-31 | 2019-08-27 | 重庆文理学院 | Fire-fighting real-time monitoring system |
| CN111008730B (en) * | 2019-11-07 | 2023-08-11 | 长安大学 | Crowd concentration prediction model construction method and device based on urban space structure |
| CN112543426A (en) * | 2020-11-30 | 2021-03-23 | 超越科技股份有限公司 | Method, device and system for monitoring water content of environmental combustible in real time |
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Application publication date: 20160824 Assignee: Nanjing Ruixi Technology Co., Ltd. Assignor: Nanjing Forestry University Contract record no.: X2019320000001 Denomination of invention: Forest fire prediction method and system Granted publication date: 20190104 License type: Common License Record date: 20190804 Application publication date: 20160824 Assignee: Nanjing Yunfeng Electronic Technology Co., Ltd. Assignor: Nanjing Forestry University Contract record no.: X2019320000002 Denomination of invention: Forest fire prediction method and system Granted publication date: 20190104 License type: Common License Record date: 20190805 |