CN117889854B - Flood control, rescue and disaster relief path planning method - Google Patents
Flood control, rescue and disaster relief path planning method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 65
- 239000003016 pheromone Substances 0.000 claims abstract description 80
- 230000008859 change Effects 0.000 claims abstract description 70
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 58
- 230000008569 process Effects 0.000 claims description 11
- 238000005457 optimization Methods 0.000 claims description 10
- 238000013507 mapping Methods 0.000 claims description 6
- 230000009466 transformation Effects 0.000 claims description 4
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 9
- 239000000463 material Substances 0.000 description 3
- 239000002689 soil Substances 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 239000003673 groundwater Substances 0.000 description 2
- 238000006424 Flood reaction Methods 0.000 description 1
- 206010019345 Heat stroke Diseases 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000018044 dehydration Effects 0.000 description 1
- 238000006297 dehydration reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000008014 freezing Effects 0.000 description 1
- 238000007710 freezing Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000000779 smoke Substances 0.000 description 1
- 230000007480 spreading Effects 0.000 description 1
- 238000010257 thawing Methods 0.000 description 1
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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Abstract
The invention relates to the technical field of disaster relief path planning, in particular to a flood control rescue and relief path planning method. According to the method, weather severe coefficients are obtained according to the integral change trend of weather change data of each path in a preset historical time period and the difference characteristics of rainfall time sequence between adjacent paths; obtaining a route rugged coefficient according to the gradient and the sharp turn number in each route, the fitting goodness and the difference of the route gradient between adjacent routes; predicting an initial water level change time sequence, and marking an early warning river according to a prediction result; further obtaining disaster relief risk coefficients of each path; obtaining an optimized pheromone volatilization coefficient; adjusting the initial pheromone updating formula to obtain an optimized pheromone updating formula; and optimally planning the travelable path. According to the invention, by considering the conditions of the path and the surrounding environment information, the suitable pheromone volatilization coefficient is adjusted, and the optimal planning effect on the disaster relief path is improved.
Description
Technical Field
The invention relates to the technical field of disaster relief path planning, in particular to a flood control rescue and relief path planning method.
Background
The flood control, rescue and disaster relief path planning can discover risks and decisions as soon as possible aiming at disasters such as flood, mountain floods and inland inundations, coordinate multi-party resources, respond quickly, accelerate disaster emergency response time and reduce personnel and property losses. When planning a disaster relief path, the weather change and the hydrologic water level condition are required to be monitored and early-warned in real time, and the disaster is effectively prevented from being enlarged by taking effective measures according to the efficient organization rescue work of actual conditions.
In the prior art, the conventional ant colony algorithm is adopted to perform path planning for flood control, rescue and disaster relief, but the aspects of information processing, decision making technology and the like are not combined with the path situation and surrounding environment information to perform planning, so that the planning capacity is low; and the fixed pheromone volatilization coefficient is used, so that the optimal path planning effect is poor.
Disclosure of Invention
In order to solve the technical problem that the optimal disaster relief path planning effect is poor due to inaccurate pheromone of an acquired path, the invention aims to provide a flood control rescue and relief path planning method, which adopts the following specific technical scheme:
The invention provides a flood control, rescue and disaster relief path planning method, which comprises the following steps:
Acquiring disaster relief path data of all drivable paths in the flood control, rescue and relief process, wherein the disaster relief path data comprises the gradient and sharp bend number of the paths; acquiring weather change data in a neighborhood range of each path and water level change data of each river in the neighborhood range at each time point in a preset historical time period, wherein the weather change data comprises: rainfall data, temperature data, and visibility;
Acquiring a rainfall time sequence of each path; obtaining a severe weather coefficient according to the overall change trend of the weather change data of each path and the difference characteristics of the rainfall time sequence between adjacent paths; obtaining the fitting goodness of each path and a straight line, and obtaining the path rugged coefficient of each path according to the disaster relief path data of each path, the fitting goodness and the gradient difference between adjacent paths; acquiring an initial water level change time sequence of each river, predicting the initial water level change time sequence, and marking out an early-warning river according to a prediction result;
Obtaining disaster relief risk coefficients of each path according to the meteorological severe coefficient, the path rugged coefficient and the number of early-warning rivers in a neighborhood range of each path; obtaining an optimized pheromone volatilization coefficient corresponding to each path according to the disaster relief risk coefficients of all paths; acquiring an initial pheromone updating formula when an ant colony algorithm is executed, and adjusting the initial pheromone updating formula according to the optimized pheromone volatilization coefficient to acquire the optimized pheromone updating formula;
And optimally planning the drivable path according to the optimizing pheromone updating formula.
Further, the method for acquiring the meteorological severe coefficient comprises the following steps:
Obtaining the meteorological severe coefficient according to an obtaining formula of the meteorological severe coefficient, taking a path rou i as an example, wherein the obtaining formula of the meteorological severe coefficient is as follows:
Wherein mpo i is the weather harshness coefficient of the path rou i; The mean value of the visibility acquired in the preset historical time period of the path rou i; The average value of the temperature data acquired in the preset historical time period of the path rou i; the tem sta is a preset reference value of the comfort temperature of the human body; The average value of rainfall collected in a preset historical time period of the path rou i; DTW i-1,i is the DTW distance of the path rainfall timing sequence of path rou i-1 and path rou i; DTW i,i+1 is the DTW distance of the path rainfall timing sequence of path rou i and path rou i+1; delta is a parameter adjusting factor.
Further, the method for acquiring the path bumpy coefficient comprises the following steps:
Obtaining the fitting goodness of fitting each path and the straight line by using a least square method;
The path bumpy coefficient is obtained according to an obtaining formula of the path bumpy coefficient, taking the path rou i as an example, the obtaining formula of the path bumpy coefficient is:
Where rrc i is the path bumpy coefficient of path rou i; stn i is the number of sharp turns of path rou i, slo i is the path slope of path rou i, slo i+1 is the path slope of path rou i+1; r 2 is the goodness of fit of the path rou i to a straight line.
Further, the method for acquiring the early warning river comprises the following steps:
predicting element values in the initial water level change time sequence through a gray prediction model to obtain a predicted water level change time sequence;
and acquiring a preset water level warning value of each river, and marking the river as an early-warning river if the element values in the initial water level change time sequence and the predicted water level change time sequence are larger than the preset water level warning value.
Further, the meteorological severity coefficient, the route rugged coefficient and the number of the early warning rivers are in positive correlation with the disaster relief risk coefficient.
Further, the method for obtaining the pheromone volatilization coefficient comprises the following steps:
and carrying out linear transformation mapping on the disaster relief risk coefficients of all paths to a preset interval range to obtain mapping values serving as pheromone volatilization coefficients of the corresponding paths.
Further, the method for obtaining the optimized pheromone updating formula comprises the following steps:
and replacing the initial pheromone volatilization coefficient in the initial pheromone updating formula with the optimization pheromone volatilization coefficient corresponding to each path to obtain the optimization pheromone updating formula.
Further, the method for acquiring the rainfall time sequence comprises the following steps:
and under the preset historical time period, acquiring the rainfall in the neighborhood range of each path at each time point, and sequencing the rainfall from left to right according to the acquisition order to acquire the rainfall time sequence of each path.
Further, the gray prediction model selects a gray first-order model.
Further, the preset interval range is [0.2,0.5].
The invention has the following beneficial effects:
The invention combines the path condition, surrounding weather information and water level change information, and improves the planning effect on the disaster relief path. According to the integral change trend of the weather change data of each path and the difference characteristics of the rainfall time sequence between adjacent paths, obtaining a weather severe coefficient and obtaining the influence degree of weather change around each path on rescue; acquiring the fitting goodness of each path, and acquiring the path bumpy coefficient of each path according to the disaster relief path data, the fitting goodness and the gradient difference between adjacent paths of each path, so as to avoid the risk in the running process of the vehicle; acquiring an initial water level change time sequence of each river, predicting the initial water level change time sequence, marking out early-warning rivers according to the prediction result, judging the rivers with dangerous situations in time, and avoiding rescue workers from going short of evacuation and affecting rescue efficiency; further obtaining disaster relief risk coefficients of each path; analyzing the risk of each path, finding out paths with relatively smaller risks, guaranteeing the safety of rescue workers and improving rescue efficiency. In order to avoid being influenced by a poor path, a larger pheromone volatilization coefficient is given to the path, and an optimized pheromone volatilization coefficient corresponding to each path is obtained according to disaster relief risk coefficients of all paths; acquiring an initial pheromone updating formula when an ant colony algorithm is executed, and adjusting the initial pheromone updating formula to obtain an optimized pheromone updating formula; and optimally planning the disaster relief path. According to the invention, by considering the conditions of the path and the surrounding environment information, the suitable pheromone volatilization coefficient is adaptively adjusted, so that the optimal planning effect on the disaster relief path is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for planning a flood control rescue and relief route according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a path and a path node marking method according to an embodiment of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following is a detailed description of a specific implementation, structure, characteristics and effects of a flood control rescue and disaster relief path planning method according to the invention with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a specific scheme of a flood control rescue and relief route planning method, which is specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a flow chart of a method for planning a flood control rescue and relief route according to an embodiment of the present invention is shown, where the method includes:
Step S1: acquiring disaster relief path data in all drivable paths in the flood control, rescue and relief process, wherein the disaster relief path data comprises the gradient and sharp bend number of the paths; the method comprises the steps of obtaining weather change data in a neighborhood range of each path and water level change data of each river in the neighborhood range at each time point in a preset historical time period, wherein the weather change data comprise: rainfall data, temperature data, and visibility.
In the embodiment of the invention, in order to timely perform flood control, rescue and relief work, a relief work path is planned so as to obtain an optimal path. Firstly, acquiring all coordinate information of a position of a disaster relief person and all coordinate information of a position of an emergency rescue destination by using a GPS global positioning system, and determining all travelable paths so as to carry out path planning processing subsequently. The information of the road can be used for helping rescue workers to plan a disaster relief route better, know various information in the disaster relief route and guarantee safety; marking path nodes and road information of a path between the position of the disaster relief personnel and the position of the rescue and relief destination, and obtaining the path nodes, the gradient of the path and the number of sharp bends in the path. As shown in fig. 2, a schematic diagram of a path and a path node marking method is provided. In the figure, points nod 1 and nod 9 represent the location of a disaster relief person and the location of a rescue and relief destination; the points nod 2 to nod 8 are nodes of a path between the position of the disaster relief personnel and the position of the rescue and relief destination; the links in the figure represent paths from rou 1 to rou 13 between the location of the rescue personnel and the location of the rescue and relief destination. In other embodiments of the present invention, the marking of the path node and the road information may be specifically set according to the implementation, which is not limited and described herein. The gradient of the path is the ratio of the elevation difference of the starting point and the end point of the path to the total path of the path, and the elevation difference is the difference between two level surfaces of two points; sharp bends are bends in which the radius of the plane curve in the path is below 50 meters.
When the rainfall exceeds the limit of the drainage system, the drainage system may fail, and flood may occur; the excessive rainfall can increase the generation and flow of flood, so that the water level of the river channel rapidly rises to cause flood disasters; meanwhile, rainfall can also influence geological conditions, so that landslide, debris flow and other disasters are caused, and further threat is brought to flood control, rescue and disaster relief. When the temperature is higher, the freezing and thawing processes of the soil and the groundwater are affected, when the temperature is higher, the groundwater can be frozen, when the temperature is higher, the soil becomes soft after the frozen soil is thawed, and the stability risk of a geographic structure is increased; meanwhile, the high-temperature weather has a certain relation to the health of people and the working efficiency, and the people are easy to generate dehydration or heatstroke under the high-temperature environment, so that the flood control, rescue and disaster relief process is influenced. Under the conditions of heavy rainfall and the like, the visibility can be reduced, and at the moment, rescue workers can difficultly enter disaster areas due to wet and slippery road surfaces, low visibility and the like, so that the flood control and disaster relief process is influenced. Therefore, weather change data in a neighborhood range of each path and water level change data of each river in the neighborhood range in each time point in a preset historical time period are obtained, wherein the weather change data comprise: rainfall data, temperature data, and visibility.
It should be noted that, in one embodiment of the present invention, the path neighborhood range is a neighborhood range in which each point on the path is used as a circle center, r is used as a radius to draw a circle, and the union region of all circles is used as the path, where the empirical value of r is 5 km; the interval between each time point and the next time point is 5min.
In one embodiment of the invention, in order to facilitate the processing of the acquired data, the acquired weather change data and water level change data are preprocessed to remove noise in the data, and the invention selects a moving average method to carry out denoising processing on the acquired data; in other embodiments of the present invention, other denoising methods may be selected by the practitioner; the specific moving average method is a technical means well known to those skilled in the art, and will not be described herein.
Step S2: acquiring a rainfall time sequence of each path; obtaining a weather severe coefficient according to the integral change trend of weather change data of each path and the difference characteristics of rainfall time sequence between adjacent paths; obtaining the fitting goodness of each path and a straight line, and obtaining the path rugged coefficient of each path according to the disaster relief path data, the fitting goodness and the gradient difference between adjacent paths of each path; and acquiring an initial water level change time sequence of each river, predicting the initial water level change time sequence, and marking out the early-warning river according to a prediction result.
Flood is caused by a large amount of rainfall, so that the rainfall can directly influence the flood control and disaster relief process. When the rainfall exceeds the limit of the drainage system, the drainage system may fail, resulting in the occurrence of a flood. The excessive rainfall can increase the generation and flow of flood, so that the river water level rapidly rises to cause flood disasters. Meanwhile, rainfall can also influence geological conditions, so that landslide, debris flow and other disasters are caused, and further threat is brought to flood control, rescue and disaster relief. So the rainfall of each path is analyzed to obtain the rainfall time sequence of each path.
Preferably, in one embodiment of the present invention, the method for acquiring a rainfall timing sequence includes:
And under the preset historical time period, acquiring the rainfall in the neighborhood range of each path at each time point, and sequencing the rainfall from left to right according to the acquisition order to acquire the rainfall time sequence of each path. In one embodiment of the invention, taking path rou i as an example, the obtained rainfall constitutes a rainfall timing sequence of the path Wherein n is the total number of times of collecting rainfall data in a preset historical time period; the rainfall data acquired for the first time in the neighborhood range of the path rou i; the rainfall data acquired for the nth acquisition within the path rou i neighborhood.
In order to better plan a rescue route, the vehicle is prevented from running under severe weather conditions, so that the safety risk and accidents are reduced; and carrying out integral analysis on the weather change, and obtaining a weather severe coefficient according to the integral change trend of the weather change data of each path and the difference characteristics of the rainfall time sequence between adjacent paths.
Preferably, in one embodiment of the present invention, the method for acquiring the weather severe coefficient includes:
Obtaining the meteorological severe coefficient according to an obtaining formula of the meteorological severe coefficient, taking a path rou i as an example, wherein the obtaining formula of the meteorological severe coefficient is as follows:
Wherein mpo i is the weather harshness coefficient of the path rou i; The mean value of the visibility acquired in the preset historical time period of the path rou i; The average value of the temperatures acquired in the preset historical time period of the path rou i; the tem sta is a preset reference value of the comfort temperature of the human body; The average value of rainfall collected in a preset historical time period of the path rou i; DTW i-1,i is the DTW distance of the path rainfall timing sequence of path rou i-1 and path rou i; DTW i,i+1 is the DTW distance of the path rainfall timing sequence of path rou i and path rou i+1; delta is a parameter adjusting factor, and the parameter value is 1.
In the acquisition formula of the meteorological severe coefficient, the lower the visibility of the path rou i is, the worse the meteorological environment is, and the path is not suitable for being used as a disaster relief and rescue path; The difference between the average value of the temperatures acquired in the preset historical time period of the path rou i and the preset reference value of the comfort temperature of the human body is shown, the larger the difference is, the more the state of the rescue personnel is affected, and the effect is caused on the rescue and relief work progress; The rainfall amount change trend between the path rou i and the adjacent path rou i-1、roui+1 is shown, and the greater the change trend is, the more likely the rainfall amount of the path rou i is in an abnormal state, the less suitable the path is as a rescue and relief disaster, and the greater the weather harshness coefficient is.
It should be noted that, in one embodiment of the present invention, the preset reference value of the comfort temperature of the human body is 22 ℃; in other embodiments of the present invention, the preset reference value and the size of the parameter adjustment factor may be specifically set according to specific situations, which are not limited and described herein.
It should be noted that, in other embodiments of the present invention, the positive-negative correlation may be constructed by other basic mathematical operations, and specific means are technical means well known to those skilled in the art, which are not described herein. The specific DTW method is a technical means well known to those skilled in the art, and will not be described herein.
If the gradient of the road is large, the transportation vehicle needs to increase power to ensure rapid transportation of materials, increase fuel consumption and operation cost, and even the road with high gradient can increase the risk of unexpected driving of the vehicle under the condition of wet or loose road surface; meanwhile, the rapid-bending road usually needs to slow down, so that the running time and distance of the vehicle are increased, the vehicle is easy to run away, and the running risk of the vehicle in the rescue and relief process is increased; in order to avoid the influence of more complicated paths on disaster relief efficiency, the fitting goodness of each path and a straight line is obtained, and the path rugged coefficient of each path is obtained according to the disaster relief path data of each path, the fitting goodness and the gradient difference between adjacent paths.
Preferably, in one embodiment of the present invention, the method for acquiring the path bumpy coefficient includes:
Obtaining the fitting goodness of fitting each path and the straight line by using a least square method;
The path bumpy coefficient is obtained according to an obtaining formula of the path bumpy coefficient, taking the path rou i as an example, the obtaining formula of the path bumpy coefficient is:
Where rrc i is the path bumpy coefficient of path rou i; stn i is the number of sharp turns of path rou i; slo i is the path grade of path rou i; slo i+1 is the path grade of path rou i+1; r 2 is the goodness of fit of the path to the straight line.
In the obtaining formula of the rugged coefficient of the path, the more the sharp bends of the path rou i are, the greater the risk of the vehicle running is; the greater the slope of path rou i, the greater the risk of accident for the vehicle to travel; the i slo i-sloi+1 indicates a gradient difference between the path rou i and the next path rou i+1, the larger the difference, the larger the unexpected risk of the vehicle running, the more the path deviates from the straight line if the goodness of fit of the path to the straight line is smaller, the more the path is rugged, and the larger the obtained path rugged coefficient is.
It should be noted that, in other embodiments of the present invention, the positive-negative correlation may be constructed by other basic mathematical operations, and specific means are technical means well known to those skilled in the art, which are not described herein. In the embodiment of the present invention, the specific least square method is a technical means well known to those skilled in the art, and will not be described herein.
When the river water level rises, the originally passable roads and bridges can be submerged, traffic is blocked, transportation of rescue workers and materials is hindered, and smoke rescue actions are performed; meanwhile, the rise of the river water level can cause the increase of disaster risks such as river bank breach, flood spreading and the like, so that rescue workers can face more dangerous environments, and the risk of rescue of the rescue workers is increased; if the river water level reaches the warning state and then early warning is carried out, the evacuation time is tension and disaster relief is difficult, so that water level change data at a future time point need to be analyzed, in order to prevent the water level of the river from threatening disaster relief personnel, not only a known initial water level change time sequence is analyzed, but also a predicted water level change data sequence is combined, and whether the river is in the early warning condition or not is judged, and marking is carried out. And acquiring an initial water level change time sequence of each river, predicting the initial water level change time sequence, and marking out the early-warning river according to a prediction result.
Preferably, in one embodiment of the present invention, the method for acquiring the early warning river includes:
And predicting element values in the initial water level change time sequence through a gray prediction model to obtain a predicted water level change data sequence. In order to prevent the water level of the river from threatening disaster relief personnel, a preset water level warning value of each river is obtained, and if element values in the initial water level change time sequence and the predicted water level change time sequence are larger than the preset water level warning value, the river is marked as an early warning river.
In one embodiment of the invention, taking the water level change data of the qth river str q as an example, the initial water level change time sequence isWherein n is the total number of times of collecting water level change data in a preset historical time period; the water level change data is collected for the first time in river str q; Is the water level change data collected at the nth time of river str q. When the gray prediction model is carried out, a gray first-order model is selected. Firstly, converting an initial water level change time sequence into an accumulation generation sequence, estimating model parameters of a selected gray first-order model by adopting a least square method, then predicting the future water level change data condition of a river by adopting a built gray prediction model, setting the length to be predicted as alpha, and taking an empirical value as 10; obtaining a predicted water level change time sequence The specific transformation process, the least square method and the gray level prediction model are all technical means well known to those skilled in the art, and are not described herein. In other embodiments of the present invention, the method for estimating the model parameters and the selection of the gray prediction model may be specifically set according to specific situations, which are not limited and described herein in detail.
It should be noted that, in one embodiment of the present invention, the preset water level warning value is recorded asThe magnitude of the preset warning value can be set specifically according to the specific condition of the river, and is not limited and described in detail herein.
Step S3: obtaining disaster relief risk coefficients of each path according to the meteorological severe coefficient, the path rugged coefficient and the number of early-warning rivers in the neighborhood range of each path; obtaining an optimized pheromone volatilization coefficient corresponding to each path according to disaster relief risk coefficients of all paths; and acquiring an initial pheromone updating formula when the ant colony algorithm is executed, and adjusting the initial pheromone updating formula according to the optimized pheromone volatilization coefficient to obtain the optimized pheromone updating formula.
By comprehensively considering a plurality of factors such as meteorological conditions, road conditions, surrounding environments and the like, rescue workers can be helped to better evaluate and predict the risk degree of rescue teams and materials on paths when disasters occur, rescue routes and schemes can be planned better, and rescue efficiency and success rate are improved. And obtaining disaster relief risk coefficients of each path according to the meteorological severe coefficient, the path rugged coefficient and the number of the early-warning rivers in the neighborhood range of each path.
Preferably, in one embodiment of the present invention, the weather severity coefficient, the road roughness coefficient, and the number of early warning rivers are all in positive correlation with the disaster relief risk coefficient. The greater the meteorological severe coefficient is, the greater the route rugged coefficient is, the greater the number of early-warning rivers in the neighborhood range is, and for rescue workers, the more unfavorable the route is, the greater the rescue risk coefficient is.
In one embodiment of the present invention, the disaster relief risk factor is formulated as:
prci＝rrci*mpoi*(β+μ)
wherein prc i is a disaster relief risk factor for path rou i; rrc i is the path bumpy coefficient of path rou i; mpo i is the weather harshness coefficient of the path rou i; beta is the number of marked rivers in the vicinity of the path rou i; mu is a parameter adjusting factor, the disaster relief risk factor is prevented from being 0, and the empirical value is 1.
In the formula of the disaster relief risk coefficient, when the rugged road condition of the path is larger, the road condition of the path is worse, and the risk of disaster relief personnel is larger; when the meteorological severe coefficient of the path is larger, the climate in the path field range is worse, and the risk of disaster relief personnel is larger; when marked rivers in the path field range are more, the rivers with water levels exceeding the warning lines are more, the risks of disaster relief personnel are more, and the acquired disaster relief risk coefficients are more; otherwise, the smaller the disaster relief risk coefficient is.
It should be noted that, in other embodiments of the present invention, the positive-negative correlation may be constructed by other basic mathematical operations, and specific means are technical means well known to those skilled in the art, which are not described herein.
The smaller the disaster relief risk coefficient of the path is, the safer and more reliable the path is, the smaller the corresponding pheromone volatilization coefficient is, and the route is selected as far as possible; the greater the disaster relief risk coefficient of the path is, the higher the risk coefficient of the path is, the more unfavorable the rescue is, and the greater the corresponding information volatilization coefficient is; therefore, the pheromone volatilization coefficient can be used as an important basis for guiding the rescue team to select the route. And obtaining the pheromone volatilization coefficient corresponding to each path according to the disaster relief risk coefficients of all paths.
Preferably, in one embodiment of the present invention, the method for obtaining the pheromone volatilization coefficient includes:
And mapping the disaster relief risk coefficients of all paths into a preset interval range through linear transformation to obtain mapping values serving as pheromone volatilization coefficients of the corresponding paths. The larger the disaster relief risk coefficient is, the less the corresponding path is suitable for being used as an optimal disaster relief path, and the smaller the content of the corresponding pheromone is, the larger the volatilization coefficient of the pheromone is. In one embodiment of the invention, the size of the preset interval range is [0.2,0.5].
In the conventional ant colony algorithm, each time the pheromone is updated and iterated, the volatilization coefficients of the corresponding pheromones are the same, and the larger the volatilization coefficient of the pheromones is, the more the pheromones volatilize, the less the pheromones remain. In the process of flood control, rescue and disaster relief, the environmental information around the paths is constantly changed, the volatilization degrees of the corresponding pheromones of different paths are also different, the paths are different, and the information volatilization coefficients are different. In order to obtain accurate road planning information, an initial pheromone updating formula when an ant colony algorithm is executed is obtained, and the initial pheromone updating formula is adjusted according to the optimized pheromone volatilization coefficient to obtain the optimized pheromone updating formula.
Preferably, in one embodiment of the present invention, the optimization pheromone update formula is expressed as:
And replacing the initial pheromone volatilization coefficient in the initial pheromone updating formula with the optimization pheromone volatilization coefficient corresponding to each path to obtain the optimization pheromone updating formula. In one embodiment of the invention, the optimization pheromone update formula is expressed as:
Wherein ρ is the optimized pheromone volatilization coefficient corresponding to each path; Is the pheromone left by ant k in iteration z by walking through path rou i to path rou v; in the embodiment of the invention, in order to better dynamically adjust the concentration of the pheromone, the adaptability is enhanced while the pheromone is updated, and the pheromone is selected The dynamic rule of (2) is a technical means well known to those skilled in the art, and is not described herein.
Step S4: and optimally planning the drivable path according to the optimizing pheromone updating formula.
The optimization pheromone updating formula is used for carrying out iterative updating on the pheromones, and the risk coefficient and the pheromone volatilization coefficient of each path can be calculated more accurately, so that an ant colony algorithm is adopted to obtain the optimal disaster relief path more rapidly to find the optimal path, the drivable path is optimally planned according to the optimization pheromone updating formula, and the optimal disaster relief path is sent to a disaster relief command center. The ant colony algorithm is a technical means well known to those skilled in the art, and will not be described herein.
In summary, the weather severe coefficient is obtained according to the integral change trend of weather change data of each path in a preset historical time period and the difference characteristics of rainfall time sequence between adjacent paths; obtaining the fitting goodness of each path and a straight line, and obtaining a path rugged coefficient according to the gradient and sharp turn number in each path and the difference of the fitting goodness and the path gradient between adjacent paths; acquiring an initial water level change time sequence of each river, predicting the initial water level change time sequence, and marking out an early-warning river according to a prediction result; further obtaining disaster relief risk coefficients of each path; obtaining a corresponding optimized pheromone volatilization coefficient; adjusting the initial pheromone updating formula to obtain an optimized pheromone updating formula; and optimally planning the travelable path. According to the invention, by considering the conditions of the path and the surrounding environment information, the suitable pheromone volatilization coefficient is adaptively adjusted, so that the optimal planning effect on the disaster relief path is improved.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
Claims (10)
1. A flood control, rescue and disaster relief path planning method, the method comprising:
Acquiring disaster relief path data of all drivable paths in the flood control, rescue and relief process, wherein the disaster relief path data comprises the gradient and sharp bend number of the paths; acquiring weather change data in a neighborhood range of each path and water level change data of each river in the neighborhood range at each time point in a preset historical time period, wherein the weather change data comprises: rainfall data, temperature data, and visibility;
Acquiring a rainfall time sequence of each path; obtaining a severe weather coefficient according to the overall change trend of the weather change data of each path and the difference characteristics of the rainfall time sequence between adjacent paths; obtaining the fitting goodness of each path and a straight line, and obtaining the path rugged coefficient of each path according to the disaster relief path data of each path, the fitting goodness and the gradient difference between adjacent paths; acquiring an initial water level change time sequence of each river, predicting the initial water level change time sequence, and marking out an early-warning river according to a prediction result;
Obtaining disaster relief risk coefficients of each path according to the meteorological severe coefficient, the path rugged coefficient and the number of early-warning rivers in a neighborhood range of each path; obtaining an optimized pheromone volatilization coefficient corresponding to each path according to the disaster relief risk coefficients of all paths; acquiring an initial pheromone updating formula when an ant colony algorithm is executed, and adjusting the initial pheromone updating formula according to the optimized pheromone volatilization coefficient to acquire the optimized pheromone updating formula;
And optimally planning the drivable path according to the optimizing pheromone updating formula.
2. The flood control, rescue and relief path planning method according to claim 1, wherein the method for acquiring the meteorological severe coefficient comprises the following steps:
Obtaining the meteorological severe coefficient according to an obtaining formula of the meteorological severe coefficient, taking a path rou i as an example, wherein the obtaining formula of the meteorological severe coefficient is as follows:
Wherein mpo i is the weather harshness coefficient of the path rou i; The mean value of the visibility acquired in the preset historical time period of the path rou i; The average value of the temperature data acquired in the preset historical time period of the path rou i; the tem sta is a preset reference value of the comfort temperature of the human body; The average value of rainfall collected in a preset historical time period of the path rou i; DTW i-1,i is the DTW distance of the path rainfall timing sequence of path rou i-1 and path rou i; DTW i,i+1 is the DTW distance of the path rainfall timing sequence of path rou i and path rou i+1; delta is a parameter adjusting factor.
3. The method for planning a flood control, rescue and relief work path according to claim 1, wherein the method for acquiring the rugged coefficient of the path comprises the following steps:
Obtaining the fitting goodness of fitting each path and the straight line by using a least square method;
The path bumpy coefficient is obtained according to an obtaining formula of the path bumpy coefficient, taking the path rou i as an example, the obtaining formula of the path bumpy coefficient is:
Where rrc i is the path bumpy coefficient of path roux; stn i is the number of sharp turns of path rou i, slo i is the path slope of path rou i, slo i+1 is the path slope of path rou i+1; r 2 is the goodness of fit of the path rou i to a straight line.
4. The method for planning a flood control, rescue and relief work path according to claim 1, wherein the method for acquiring the early warning river comprises the following steps:
predicting element values in the initial water level change time sequence through a gray prediction model to obtain a predicted water level change time sequence;
and acquiring a preset water level warning value of each river, and marking the river as an early-warning river if the element values in the initial water level change time sequence and the predicted water level change time sequence are larger than the preset water level warning value.
5. The method for planning a flood control, rescue and relief work path according to claim 1 wherein the meteorological severity coefficient, the route bumpy coefficient and the number of early warning rivers are in positive correlation with the relief work risk coefficient.
6. The method for planning a flood control, rescue and disaster relief path according to claim 1, wherein the method for acquiring the pheromone volatilization coefficient comprises the following steps:
and carrying out linear transformation mapping on the disaster relief risk coefficients of all paths to a preset interval range to obtain mapping values serving as pheromone volatilization coefficients of the corresponding paths.
7. The method for planning a flood control, rescue and relief work path according to claim 1, wherein the method for obtaining the optimized pheromone updating formula comprises the following steps:
and replacing the initial pheromone volatilization coefficient in the initial pheromone updating formula with the optimization pheromone volatilization coefficient corresponding to each path to obtain the optimization pheromone updating formula.
8. The method for planning a flood control, rescue and relief work path according to claim 1, wherein the method for acquiring the rainfall time sequence comprises the following steps:
and under the preset historical time period, acquiring the rainfall in the neighborhood range of each path at each time point, and sequencing the rainfall from left to right according to the acquisition order to acquire the rainfall time sequence of each path.
9. The method for planning a flood control, rescue and relief work path according to claim 4 wherein said gray predictive model is a gray first-order model.
10. The method for planning a flood control, rescue and relief work path according to claim 6 wherein said predetermined interval range is [0.2,0.5].
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| CN111427378A (en) * | 2020-04-10 | 2020-07-17 | 南宁师范大学 | Method for planning preferential rescue path of unmanned aerial vehicle in mountainous region |
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| CN111427378A (en) * | 2020-04-10 | 2020-07-17 | 南宁师范大学 | Method for planning preferential rescue path of unmanned aerial vehicle in mountainous region |
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