CN105894706A - Forest fire prediction method and system - Google Patents
Forest fire prediction method and system Download PDFInfo
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- CN105894706A CN105894706A CN201610283727.4A CN201610283727A CN105894706A CN 105894706 A CN105894706 A CN 105894706A CN 201610283727 A CN201610283727 A CN 201610283727A CN 105894706 A CN105894706 A CN 105894706A
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- 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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Abstract
The invention discloses a forest fire prediction method and system, and the method and system collect the temperature data, humidity data, rainfall data, wind speed data and ground combustible moisture content data of a forest in real time, calculate a triangular fuzzy number of fire, judge the level of the fire, and achieves the dynamic prediction of forest fire. Meanwhile, the method and system also can input the triangular fuzzy numbers of season parameters, time parameters, population density parameters, road density parameters, population activity parameters, historical fire parameters and ground combustible type parameters, and bring environment factors and human factors into a fire prediction calculation model, and further improves the accuracy of fire prediction.
Description
Technical field
The present invention relates to field of forest fire prevention, particularly relate to a kind of forest fire Forecasting Methodology and system thereof.
Background technology
Forest is that the mankind depend on for existence and the indispensable resource of social development.Owing to some in social activities of the mankind is out of control and the reason such as abnormal natural cause, forest fire happens occasionally, and human life's property and ecological environment are caused huge harm.The reasons such as China is due to vast in territory, and with a varied topography, weather is various, and Forest Types is different with distribution, and Levels of Social Economic Development differs, and the density of population is big and skewness, national awareness of the importance of fire prevention weakness, forest fire protection task is the severeest all the time.
One important content of forest fire protection work is fire alarm, and the possibility i.e. forest fire occurred is made a prediction and reminds forest fire protection department to adjust the focus of work and counter-measure in time.In current existing all kinds of Forecasting Model of Forest Fires, the time and the number of times that generally use Related Mathematical Models that forest fire in long term the last period occurs carry out statistical analysis, are predicted for the most possible forest fire frequency.This class model is only to predict in following certain time period it may happen that the number of times of fire theoretically, also Fire response forecast model it is, it is not real-time fire prediction model, according to the real time information in forest environment the possibility that forest fire occurs can not be made a prediction and alarm is provided.
Summary of the invention
The technical problem to be solved in the present invention is that the possibility that forest fire occurs can not be made a prediction according to the real time information in forest environment and provide alarm by Forecasting Model of Forest Fire of the prior art.
For solving above-mentioned technical problem, the technical solution used in the present invention is:
A kind of forest fire Forecasting Methodology, comprises the steps:
(1), gathering or input the fire parameter of forest to be predicted, described fire parameter at least includes temperature parameter and humidity parameter；Each fire parameter uses Triangular Fuzzy Number, and (a, b c) represent, a, b, c are respectively lower limit, probable value and higher limit, wherein, 0≤a ＜ c≤1,0≤a≤b, b≤c≤1；
(2), according to equation below calculate forest fire Triangular Fuzzy Number,
Wherein, (ai, bi, ci) represent the Triangular Fuzzy Number of each fire parameter,
OepratorWith the operation rule of oeprator ⊙ it is:
(a1, b1, c1)⊙(a2, b2, c2)=(a1/a2, b1/b2, c1/c2)；
(3), fire alarm is made according to fire Triangular Fuzzy Number.
Concrete, the value mode of the Triangular Fuzzy Number of described temperature parameter is: design temperature lower limit and temperature upper limit are respectively P1Degree Celsius and Q1Degree Celsius, measuring and obtaining current forest temperature is R1Degree Celsius, the probable value of the Triangular Fuzzy Number calculating temperature parameter is b1=(R1-P1)/(Q1-P1), it is determined that b1Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of temperature parameter1=(a1, b1, c1), wherein a1、c1Respectively equal to aforementioned b1Affiliated interval endpoint value；
The value mode of the Triangular Fuzzy Number of described 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, it is determined that b2Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of humidity parameter2=(a2, b2, c2), wherein a2、c2Respectively equal to aforementioned b2Affiliated interval endpoint value.
Further, described fire parameter also includes wind speed parameter and rainfall parameter, and the value mode of the Triangular Fuzzy Number of wind speed parameter is: the wind speed setting upper limit is P3Thousand ms/h, the wind speed measuring the current forest of acquisition is Q3Thousand ms/h, the probable value b of the Triangular Fuzzy Number of wind speed parameter3=Q3/P3, it is determined that b3Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of wind speed parameter3=(a3, b3, c3), wherein a3、c3Respectively equal to aforementioned b3Affiliated interval endpoint value.
The value mode of the Triangular Fuzzy Number of rainfall parameter is: set the rainfall upper limit of in the past twenty four hours as P4Milliliter, in the twenty four hours of the measurement current forest of acquisition, rainfall is Q4Milliliter, the probable value b of the Triangular Fuzzy Number of rainfall parameter4=Q4/P4, it is determined that b4Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of wind speed parameter4=(a4, b4, c4), wherein a4、c4Respectively equal to aforementioned b4Affiliated interval endpoint value.
Further, described fire parameter also includes that described fire parameter also includes density of population parameter；The value mode of the Triangular Fuzzy Number of density of population parameter is: set the density of population upper limit as P5, the density of population of the current wood land of statistical calculation is Q5, the probable value b of the Triangular Fuzzy Number of density of population parameter5=Q5/P5If, b5> 1, then make b5=1.Judge b5Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of density of population parameter5=(a5, b5, c5), wherein a5、c5Respectively equal to aforementioned b5Affiliated interval endpoint value.
Further, described fire parameter also includes that ground fuel degenerates extent index；The value mode of the Triangular Fuzzy Number of ground fuel corruption extent index is: the moisture content measuring ground fuel is P6, the probable value b of the Triangular Fuzzy Number of ground fuel corruption extent index6=1-P6.Judge b6Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of ground fuel corruption extent index6=(a6, b6, c6), wherein a6、c6Respectively equal to aforementioned b6Affiliated interval endpoint value.
Further, described fire parameter also includes parameter in season, time parameter, roading density parameter, one or more in population activity parameter, history fire parameter and ground fuel species parameter.
Further, the concrete mode of described 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 interval in [0.875,1] five numerical intervals, fire size class is identified as basic, normal, high, dangerous or extremely dangerous according to interval residing for b, makes corresponding fire alarm according to different fire size class.
Present invention also offers a kind of pre-examining system of forest fire, including:
Collecting unit, is distributed in each collection point planned in advance of forest, at least collecting temperature value and humidity value；
Input block, is used for inputting fire parameter；
CPU, receive data and the fire parameter of input block that collecting unit gathers, set up the Triangular Fuzzy Number of fire parameter according to the value mode of the Triangular Fuzzy Number of the fire parameter described in claim 2 to 5, calculate the Triangular Fuzzy Number of fire according to the fire formula described in claim 1；
Alarm unit, sends alarm of fire, by central processing unit controls.
Further, described collecting unit also gathers wind speed, rainfall and ground fuel moisture content.
Further, collection data are transferred to CPU by internet by described collecting unit, and collecting unit uses rechargeable battery to power, and battery uses the charging of solar energy conversion equipment.
Beneficial effect: (1) the invention provides a kind of forest fire Forecasting Methodology and system thereof, the method and system can the temperature data of Real-time Collection forest, humidity data, rainfall product data, air speed data and ground fuel moisture content data, and calculate the Triangular Fuzzy Number of fire, achieve the dynamic prediction of forest fire, improve the accuracy of fire prediction.(2) present invention provides forest fire Forecasting Methodology and system thereof it is also conceivable to parameter in season, time parameter, density of population parameter, roading density parameter, one or more in population activity parameter, history fire parameter and ground fuel species parameter, environmental factor and human factor are added in Forecasting Model of Forest Fire, further increases the accuracy of fire prediction.
Accompanying drawing explanation
Fig. 1 is that system architecture diagram is predicted in forest fire of the present invention.
Wherein: 1, collecting unit；2, input block；3, CPU；4, alarm unit.
Detailed description of the invention
With detailed description of the invention, the present invention is described in further detail below in conjunction with the accompanying drawings.
Embodiment 1
As it is shown in figure 1, the pre-examining system of the forest fire of the present embodiment includes:
Collecting unit 1, is distributed in each collection point planned in advance of forest, collecting temperature value, humidity value, wind speed and rainfall；Collection data are transferred to CPU 3 by internet by collecting unit 1, and collecting unit 1 uses rechargeable battery to power, and battery uses the charging of solar energy conversion equipment；
Input block 2, is used for inputting fire parameter；
CPU 3, receives data and the fire parameter of input block 2 that collecting unit 1 gathers；
Alarm unit 4, sends alarm of fire, is controlled by CPU 3.
The temperature value R that CPU 3 is transmitted according to collecting unit 11, rh value P2, air speed value P3, rainfall value P in 24 hours4With ground fuel sweat rate P5Calculating the Triangular Fuzzy Number of fire, calculation procedure is as follows:
(1) probable value of the Triangular Fuzzy Number calculating temperature parameter is b1=(R1-P1)/(Q1-P1), wherein P1And Q1For default temperature upper limit and lowest temperature.Judge b1Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of temperature parameter1=(a1, b1, c1), wherein a1、c1Respectively equal to aforementioned b1Affiliated interval endpoint value；
(2) the probable value b of the Triangular Fuzzy Number of humidity parameter is calculated2=P2, wherein 0≤P2≤1.Judge b2Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of humidity parameter2=(a2, b2, c2), wherein a2、c2Respectively equal to aforementioned b2Affiliated interval endpoint value.
(3) the probable value b of the Triangular Fuzzy Number of calculation of wind speed parameter3=Q3/P3, wherein P3For default upper wind velocity limit value.Judge b3Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of wind speed parameter3=(a3, b3, c3), wherein a3、c3Respectively equal to aforementioned b3Affiliated interval endpoint value.
(4) the probable value b of the Triangular Fuzzy Number of rainfall parameter is calculated4=Q4/P4, wherein P4For the default forest 24 hourly rainfall depth upper limit.Judge b4Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of wind speed parameter4=(a4, b4, c4), wherein a4、c4Respectively equal to aforementioned b4Affiliated interval endpoint value.
(5) the probable value b of the Triangular Fuzzy Number of ground fuel corruption degree is calculated5=1-P5.Judge b5Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of ground fuel corruption extent index5=(a5, b5, c5), wherein a5、c5Respectively equal to aforementioned b5Affiliated interval endpoint value.
(6) Triangular Fuzzy Number of forest fire is calculated according to equation below,
Wherein, (ai, bi, ci) represent the Triangular Fuzzy Number of each fire parameter,
OepratorWith the operation rule of oeprator ⊙ it is:
(a1, b1, c1)⊙(a2, b2, c2)=(a1/a2, b1/b2, c1/c2)；
In order to improve the degree of accuracy of fire prediction further, include environmental factor and human factor in fire prediction model, the pre-examining system of forest fire of the present embodiment can also input parameter in season by input block 2, time parameter, density of population parameter, roading density parameter, population activity parameter, history fire parameter and Triangular Fuzzy Number S of ground fuel species parameteri=(ai, bi, ci), the aggregation of data that CPU 3 is transmitted according to collecting unit 1 and input block 2 calculates fire Triangular Fuzzy Number.
CPU 3 judge fire Triangular Fuzzy Number T=(a, b, probable value b c) belongs to [0,0.125), [0.125,0.375), [0.375,0.625), [0.625,0.875), [0.875,1] which interval in five numerical intervals, is identified as basic, normal, high, dangerous or extremely dangerous according to interval residing for b by fire size class, and CPU 3 controls alarm unit 4 according to different fire size class and makes corresponding fire alarm.
Although in specification being illustrated embodiments of the present invention, but these embodiments are intended only as prompting, should not limit protection scope of the present invention.Carry out various omission without departing from the spirit and scope of the present invention, replace and change should be included in protection scope of the present invention.
Claims (10)
1. a forest fire Forecasting Methodology, it is characterised in that comprise the steps:
(1), gathering or input the fire parameter of forest to be predicted, described fire parameter at least includes temperature parameter and humidity parameter；Each fire parameter uses Triangular Fuzzy Number, and (a, b c) represent, a, b, c are respectively lower limit, probable value and higher limit, wherein, 0≤a ＜ c≤1,0≤a≤b, b≤c≤1；
(2), according to equation below calculate forest fire Triangular Fuzzy Number,
Wherein, (ai, bi, ci) represent the Triangular Fuzzy Number of each fire parameter,
OepratorWith the operation rule of oeprator ⊙ it is:
(a1, b1, c1)⊙(a2, b2, c2)=(a1/a2, b1/b2, c1/c2)；
(3), fire alarm is made according to fire Triangular Fuzzy Number.
Forest fire Forecasting Methodology the most according to claim 1, it is characterised in that
The value mode of the Triangular Fuzzy Number of described temperature parameter is: design temperature lower limit and temperature upper limit are respectively P1Degree Celsius and Q1Degree Celsius, measuring and obtaining current forest temperature is R1Degree Celsius, calculate the probable value b of the Triangular Fuzzy Number of temperature parameter1=(R1-P1)/(Q1-P1), it is determined that b1Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of temperature parameter1=(a1, b1, c1), wherein a1、c1Respectively equal to aforementioned b1Affiliated interval endpoint value；
The value mode of the Triangular Fuzzy Number of described 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, it is determined that b2Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of humidity parameter2=(a2, b2, c2), wherein a2、c2Respectively equal to aforementioned b2Affiliated interval endpoint value.
Forest fire Forecasting Methodology the most according to claim 2, it is characterised in that described fire parameter also includes wind speed parameter 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, the wind speed measuring the current forest of acquisition is Q3Thousand ms/h, the probable value b of the Triangular Fuzzy Number of wind speed parameter3=Q3/P3If, b3> 1, then make b3=1.Judge b3Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of wind speed parameter3=(a3, b3, c3),
Wherein a3、c3Respectively equal to aforementioned b3Affiliated interval endpoint value；
The value mode of the Triangular Fuzzy Number of rainfall parameter is: set the rainfall upper limit of in the past twenty four hours as P4Milliliter, in the twenty four hours of the measurement current forest of acquisition, rainfall is Q4Milliliter, the probable value b of the Triangular Fuzzy Number of rainfall parameter4=Q4/P4, it is determined that b4Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of wind speed parameter4=(a4, b4, c4), wherein a4、c4Respectively equal to aforementioned b4Affiliated interval endpoint value.
Forest fire Forecasting Methodology the most according to claim 3, it is characterised in that also include that ground fuel degenerates extent index；
The value mode of the Triangular Fuzzy Number of ground fuel corruption extent index is: the moisture content measuring ground fuel is P5, the probable value b of the Triangular Fuzzy Number of ground fuel corruption extent index5=1-P5.Judge b5Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of ground fuel corruption extent index5=(a5, b5, c5), wherein a5、c5Respectively equal to aforementioned b5Affiliated interval endpoint value.
Forest fire Forecasting Methodology the most according to claim 4, it is characterised in that described fire parameter also includes density of population parameter；
The value mode of the Triangular Fuzzy Number of density of population parameter is: set the density of population upper limit as P6, the density of population of the current wood land of statistical calculation is Q6, the probable value b of the Triangular Fuzzy Number of density of population parameter6=Q6/P6If, b6> 1, then make b6=1.Judge b6Belong to [0,0.25), [0.25,0.5), [0.5,0.75), which interval in [0.75,1] four numerical intervals, Triangular Fuzzy Number S of density of population parameter6=(a6, b6, c6), wherein a6、c6Respectively equal to aforementioned b6Affiliated interval endpoint value.
Forest fire Forecasting Methodology the most according to claim 5, it is characterised in that described fire parameter also includes parameter in season, time parameter, roading density parameter, one or more in population activity parameter, history fire parameter and ground fuel species parameter.
Forest fire Forecasting Methodology the most according to claim 6, it is characterized in that, the concrete mode of described fire alarm is: judge that the probable value b of fire Triangular Fuzzy Number belongs to [0,0.125), [0.125,0.375), [0.375,0.625), [0.625,0.875), [0.875,1] which interval in five numerical intervals, is identified as fire size class basic, normal, high, dangerous or extremely dangerous according to interval residing for b, makes corresponding fire alarm according to different fire size class.
8. the pre-examining system of forest fire, it is characterised in that including:
Collecting unit (1), is distributed in each collection point planned in advance of forest, at least collecting temperature value and humidity value；
Input block (2), is used for inputting fire parameter；
CPU (3), receive data and the fire parameter of input block (2) that collecting unit (1) gathers, set up the Triangular Fuzzy Number of fire parameter according to the value mode of the Triangular Fuzzy Number of the fire parameter described in claim 2 to 5, calculate the Triangular Fuzzy Number of fire according to the fire formula described in claim 1；
Alarm unit (4), sends alarm of fire, is controlled by CPU (3).
The pre-examining system of forest fire the most according to claim 8, it is characterised in that described collecting unit (1) also gathers wind speed, rainfall and ground fuel moisture content.
The pre-examining system of forest fire the most according to claim 8 or claim 9, it is characterized in that, collection data are transferred to CPU (3) by internet by described collecting unit (1), collecting unit (1) uses rechargeable battery to power, and battery uses the charging of solar energy conversion equipment.
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