CN114298392A - Fire wire longitude and latitude prediction algorithm for forest fire - Google Patents
Fire wire longitude and latitude prediction algorithm for forest fire Download PDFInfo
- Publication number
- CN114298392A CN114298392A CN202111591444.3A CN202111591444A CN114298392A CN 114298392 A CN114298392 A CN 114298392A CN 202111591444 A CN202111591444 A CN 202111591444A CN 114298392 A CN114298392 A CN 114298392A
- Authority
- CN
- China
- Prior art keywords
- longitude
- coordinates
- fire
- latitude
- latitude coordinates
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
- Y02A40/28—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture specially adapted for farming
Abstract
The invention discloses a fire wire longitude and latitude prediction algorithm facing forest fire, which is used for acquiring longitude and latitude coordinates of a boundary point of a fire wire at the current t moment and calculating the longitude and latitude coordinates of a fire center point; according to the burning speed of flame in forest fire of 0.1-0.7 m/s, and each boundary point expands outwards along the normal direction, the coordinates of the boundary points at the t +1 moment and the t +5 moment are roughly estimated; finally, respectively extracting longitude coordinates and latitude coordinates of three moments; based on the longitude coordinates and the latitude coordinates of the boundary points of the live wire at the three moments, predicting the longitude coordinates and the latitude coordinates of the boundary points of the live wire at the moments t +5, t +10 and t +30 by adopting a linear regression live wire prediction model; and the longitude coordinates and the latitude coordinates of the predicted time are in one-to-one correspondence to obtain the actual longitude and latitude coordinates of the predicted result. The invention can help the staff to predict the real-time fire condition. Through the real-time rapid analysis to the forest condition of a fire, can carry out effective processing to the conflagration, reduce the loss of lives and property that the conflagration brought.
Description
Technical Field
The invention relates to a fire wire longitude and latitude prediction algorithm for forest fire.
Background
Forest fires are the most dangerous enemies and the most feared disasters of forests, and can have the most serious and devastating consequences for forests. Forest fires not only burn pieces of forest to damage animals in the forest, but also cause soil impoverishment to destroy the conservation of forest water sources, and even cause the ecological environment to lose balance seriously. Therefore, the fire needs to be accurately predicted, and the real-time condition and the combustion range of the fire need to be known, so that the fire can be effectively controlled.
In statistics, Linear Regression (Linear Regression) is a Regression analysis that models the relationship between one or more independent and dependent variables using a least squares function called a Linear Regression equation. Such a function is a linear combination of one or more model parameters called regression coefficients. The case of only one independent variable is called simple regression, and the case of more than one independent variable is called multiple regression.
In linear regression, data is modeled using a linear prediction function, and unknown model parameters are also estimated from the data. These models are called linear models. The most common linear regression modeling is that the conditional mean of y given the value of X is an affine function of X.
In the prior art, the trend of fire development cannot be predicted in time after a fire occurs in a forest, so that the fire is not convenient to control in time, and the loss is reduced. Therefore, a fire wire longitude and latitude prediction algorithm facing to forest fires is urgently needed to solve the problem in the prior art.
In order to solve the technical problems, a new technical scheme is especially provided.
Disclosure of Invention
The invention aims to provide a fire wire longitude and latitude prediction algorithm for forest fire so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a fire wire longitude and latitude prediction algorithm for forest fire comprises the following steps:
s1, acquiring longitude and latitude coordinates of the boundary point of the fire wire at the current t moment, and calculating the longitude and latitude coordinates of the fire center point; according to the burning speed of flame in forest fire of 0.1-0.7 m/s, and each boundary point expands outwards along the normal direction, the coordinates of the boundary points at the t +1 moment and the t +2 moment are roughly estimated; finally, respectively extracting longitude coordinates and latitude coordinates of three moments;
s2, respectively predicting the longitude coordinates and the latitude coordinates of the boundary points of the live wire at the moments t +5, t +10 and t +30 by adopting a linear regression live wire prediction model based on the longitude coordinates and the latitude coordinates of the boundary points of the live wire at the three moments;
and S3, corresponding the longitude coordinates and the latitude coordinates of the predicted time one by one to obtain the actual longitude and latitude coordinates of the predicted result.
Preferably, the steps S1 to S3 are mainly used for predicting longitude and latitude coordinate points of 5 minutes, 10 minutes and 30 minutes in the future.
Compared with the prior art, the invention has the beneficial effects that: the provided algorithm can help the staff to predict the real-time fire condition. Through the real-time rapid analysis to the forest condition of a fire, can carry out effective processing to the conflagration, reduce the loss of lives and property that the conflagration brought.
Drawings
FIG. 1 is a flow chart of the fire boundary point longitude and latitude coordinate prediction method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to the attached drawings of the specification, the invention provides a technical scheme that: a fire wire longitude and latitude prediction algorithm for forest fire comprises the following steps:
s1, acquiring longitude and latitude coordinates of the boundary point of the fire wire at the current t moment, and calculating the longitude and latitude coordinates of the fire center point; according to the burning speed of flame in forest fire of 0.1-0.7 m/s, and each boundary point expands outwards along the normal direction, the coordinates of the boundary points at the t +1 moment and the t +2 moment are roughly estimated; finally, respectively extracting longitude coordinates and latitude coordinates of three moments;
s2, based on the longitude coordinates and the latitude coordinates of the fire wire boundary points at the three moments, predicting the longitude coordinates and the latitude coordinates of the fire wire boundary points at t +5, t +10 and t +30 moments by adopting a linear regression fire wire prediction model;
and S3, corresponding the longitude coordinates and the latitude coordinates of the predicted time one by one to obtain the actual longitude and latitude coordinates of the predicted result.
Preferably, the steps S1 to S3 are mainly used for predicting longitude and latitude coordinate points of 5 minutes, 10 minutes and 30 minutes in the future.
When the method is used, the algorithm provided by the invention can help the staff to predict the real-time fire condition. Through the real-time rapid analysis to the forest condition of a fire, can carry out effective processing to the conflagration, reduce the loss of lives and property that the conflagration brought.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (2)
1. A fire wire longitude and latitude prediction algorithm for forest fire is characterized by comprising the following steps:
s1, acquiring longitude and latitude coordinates of the boundary point of the fire wire at the current t moment, and calculating the longitude and latitude coordinates of the fire center point; according to the burning speed of flame in forest fire of 0.1-0.7 m/s, and each boundary point expands outwards along the normal direction, the coordinates of the boundary points at the t +1 moment and the t +2 moment are roughly estimated; finally, respectively extracting longitude coordinates and latitude coordinates of three moments;
s2, based on the longitude coordinates and the latitude coordinates of the fire wire boundary points at the three moments, predicting the longitude coordinates and the latitude coordinates of the fire wire boundary points at t +5, t +10 and t +30 moments by adopting a linear regression fire wire prediction model;
and S3, corresponding the longitude coordinates and the latitude coordinates of the predicted time one by one to obtain the actual longitude and latitude coordinates of the predicted result.
2. The fire line longitude and latitude prediction algorithm for forest fires according to claim 1, characterized in that: the steps S1 to S3 are mainly used for predicting longitude and latitude coordinate points of 5 minutes, 10 minutes and 30 minutes in the future.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111591444.3A CN114298392B (en) | 2021-12-23 | 2021-12-23 | Fire wire longitude and latitude prediction method for forest fire |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111591444.3A CN114298392B (en) | 2021-12-23 | 2021-12-23 | Fire wire longitude and latitude prediction method for forest fire |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114298392A true CN114298392A (en) | 2022-04-08 |
| CN114298392B CN114298392B (en) | 2023-05-12 |
Family
ID=80970009
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111591444.3A Active CN114298392B (en) | 2021-12-23 | 2021-12-23 | Fire wire longitude and latitude prediction method for forest fire |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114298392B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110007901A1 (en) * | 2008-12-26 | 2011-01-13 | Yoichi Ikeda | Communication device |
| CN102221309A (en) * | 2011-05-20 | 2011-10-19 | 陕西中天火箭技术有限责任公司 | Rocket and antiaircraft gun operation control and safety monitoring system and operation monitoring method |
| CN106991681A (en) * | 2017-04-11 | 2017-07-28 | 福州大学 | A kind of fire boundary vector information extract real-time and method for visualizing and system |
| CN108717582A (en) * | 2018-04-17 | 2018-10-30 | 平安科技（深圳）有限公司 | Forest fire prediction technique, device, computer equipment and storage medium |
| CN110389353A (en) * | 2019-08-21 | 2019-10-29 | 深圳云感物联网科技有限公司 | A kind of forest fire point precise positioning method and system |
| CN112308292A (en) * | 2020-10-10 | 2021-02-02 | 广东工业大学 | Method for drawing fire risk grade distribution map |
-
2021
- 2021-12-23 CN CN202111591444.3A patent/CN114298392B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110007901A1 (en) * | 2008-12-26 | 2011-01-13 | Yoichi Ikeda | Communication device |
| CN102221309A (en) * | 2011-05-20 | 2011-10-19 | 陕西中天火箭技术有限责任公司 | Rocket and antiaircraft gun operation control and safety monitoring system and operation monitoring method |
| CN106991681A (en) * | 2017-04-11 | 2017-07-28 | 福州大学 | A kind of fire boundary vector information extract real-time and method for visualizing and system |
| CN108717582A (en) * | 2018-04-17 | 2018-10-30 | 平安科技（深圳）有限公司 | Forest fire prediction technique, device, computer equipment and storage medium |
| CN110389353A (en) * | 2019-08-21 | 2019-10-29 | 深圳云感物联网科技有限公司 | A kind of forest fire point precise positioning method and system |
| CN112308292A (en) * | 2020-10-10 | 2021-02-02 | 广东工业大学 | Method for drawing fire risk grade distribution map |
Non-Patent Citations (3)
| Title |
|---|
| FUHU DENG等: "Leveraging Image Visual Features in Content-Based Recommender System", 《SCIENTIFIC PROGRAMMING》 * |
| 刘柯珍等: "基于卫星监测热点的林火分布及发生预报模型", 《林业工程学报》 * |
| 李晓炜: "森林气象火险指数的区域适应性及其概率模型", 《网页在线公开：IR.IGSNRR.AC.CN/HANDLE/311030/22058》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114298392B (en) | 2023-05-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR101960504B1 (en) | Apparatus and method for epidemic spread prediction modeling | |
| Maclean et al. | Climate change causes rapid changes in the distribution and site abundance of birds in winter | |
| AU2014343231B2 (en) | Cyber defense | |
| KR101769880B1 (en) | Method of simulating fire drill simulation of nuclear power plant and apparatus performing the same | |
| Penman et al. | Influence of fuels, weather and the built environment on the exposure of property to wildfire | |
| Helm et al. | Continuing decline of a keystone tree species in the K ruger N ational P ark, S outh A frica | |
| Podur et al. | A simulation model of the growth and suppression of large forest fires in Ontario | |
| Payne et al. | Disproportionate climate-induced range loss forecast for the most threatened African antelopes | |
| Price et al. | The spatial domain of wildfire risk and response in the Wildland Urban Interface in Sydney, Australia | |
| Cook et al. | Towards a framework for quantifying the population-level consequences of anthropogenic pressures on the environment: the case of seabirds and windfarms | |
| CN113111518A (en) | Fire simulation processing method based on Internet of things | |
| CN110782147A (en) | Fuzzy Petri network-based oil spill disaster chain risk analysis method | |
| Song et al. | Three types of power-law distribution of forest fires in Japan | |
| Wei et al. | Comparing contingency fire containment strategies using simulated random scenarios | |
| CN115985056A (en) | Combustible gas real-time monitoring and early warning method and system, storage medium and electronic equipment | |
| CN116363513A (en) | Tropical forest post-disaster repair detection system based on data analysis | |
| CN114298392A (en) | Fire wire longitude and latitude prediction algorithm for forest fire | |
| Ramachandran | Probabilistic approach to fire risk evaluation | |
| Miller | The hidden consequences of fire suppression | |
| Scott et al. | Emerging concepts in wildfire risk assessment and management | |
| CN111539093B (en) | High-temperature flue gas distribution linkage CA model for personnel evacuation simulation | |
| CN111062616A (en) | Factory production environment evaluation system and method based on big data | |
| Medina-Ramos et al. | Global Temperature Anomaly by Volterra-Laguerre Model from CO2 Emission, Solar Irradiance, Population, and the Oceans Heat Content | |
| CN117455244A (en) | Method, device and equipment for evaluating effect of preventing and treating wild fire by artificially influencing precipitation | |
| Taleb et al. | The Development of Scenarios for Serious Game: A Case for Fire Evacuation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |