CN109146754B - Rescue organization system and method based on improved ant colony algorithm - Google Patents
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Abstract
The invention provides a rescue organization system and a rescue organization method based on an improved ant colony algorithm, wherein the system comprises the following steps: the system comprises an application interface module, a sensor information acquisition module, a comprehensive analysis module, a rescue goods and materials management module and a network transmission module, wherein the comprehensive analysis module analyzes and processes current rescue information acquired by the application interface module and sensing information acquired by the sensor information acquisition module, and plans a proposed rescue route of ants between a rescue point and a rescue site by adopting an ant colony algorithm; the rescue goods and materials management module allocates rescue goods and materials and obtains current use information of the rescue goods and materials; the network transmission module synchronously stores the current rescue information, the perception information, the formulated rescue route and the current use information of the rescue goods and materials to the cloud. The invention can coordinate the material scheduling of a plurality of rescue points and rescue sites, improve the allocation speed of rescue materials, reduce the waste of human resources and ensure that the rescue scheme can be effectively executed.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a rescue organization system and a rescue organization method based on an improved ant colony algorithm.
Background
When dealing with large-scale natural disasters, rapidly organizing public personnel for emergency evacuation is an important way for reducing casualties. At present, aiming at emergency evacuation of personnel in public places, direct allocation of each participating department by a dispatching center is mainly relied on.
However, the organization method needs to consume more manpower, and when a plurality of rescue units participate, timely information sharing cannot be realized among the rescue units, so that the waste of rescue resources and manpower is caused, and the effective execution of a rescue scheme is influenced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a rescue organization system and a rescue organization method based on an improved ant colony algorithm.
In a first aspect, an embodiment of the present invention provides a rescue organization system based on an improved ant colony algorithm, including: the system comprises an application interface module, a sensor information acquisition module, a comprehensive analysis module, a rescue goods and materials management module and a network transmission module; wherein:
the application interface module is used for receiving current rescue information sent by rescuers;
the sensor information acquisition module is used for acquiring perception information acquired by sensors arranged on a rescue site;
the comprehensive analysis module is used for analyzing and processing the current rescue information and the perception information and planning a proposed rescue route of ants between a rescue point and a rescue site by adopting an ant colony algorithm;
the rescue goods and materials management module is used for allocating rescue goods and obtaining the current use information of the rescue goods and materials;
the network transmission module is used for synchronously storing the current rescue information, the perception information, the proposed rescue route and the current use information of the rescue goods and materials to a cloud.
Optionally, the rescue goods management module is further configured to: when the rescue goods and materials are damaged or in shortage, the rescue goods and materials are allocated again according to the current use condition of the rescue goods and materials at the rescue point.
Optionally, the current rescue information comprises: rescue place, current time, number of people participating in rescue, estimated number of people to be rescued and rescue goods and materials put into use;
the perception information includes: the method comprises the following steps of (1) carrying out on-site environment temperature, on-site air quality, on-site people flow condition, on-site rescue condition and evacuation path people flow distribution condition;
the current usage information includes: the type of the rescue goods and materials put into use, the quantity of each type of rescue goods and materials put into use, the distribution condition of the rescue goods and materials put into use, the type of the rescue goods and materials not put into use and the quantity of each type of rescue goods and materials not put into use;
the rescue goods and materials comprise: transportation equipment, excavating equipment, medical equipment, food, medicines and drinking water.
Optionally, the comprehensive analysis module is specifically configured to:
determining all rescue points and rescue sites needing to allocate materials according to the current rescue information and the perception information;
setting the rescue point as an initial node of the ant in the improved ant colony algorithm, setting the rescue site needing allocating materials as a target node of the ant, starting the ant with a corresponding amount of materials from the initial node, and when the ant reaches the target node, defaulting that the ant puts part or all of the materials in the corresponding amount into the target node;
drawing a rescue map according to the position information of the starting node and the target node; marking the current material storage quantity of each initial node and the material demand quantity of each target node on a rescue map;
and planning the path of the ants on the rescue map by adopting an ant colony algorithm to obtain a proposed rescue route.
Optionally, the ants comprise: water source and food ants, medical ants, digging ants; the water source and food ants are as follows: ants carrying water sources and foods; the medical ants refer to: ants carrying medical equipment and/or medical personnel; the digging ants refer to: carrying the excavating equipment and/or ants of the excavating technician.
Optionally, planning a path of the ant on the rescue map by using an ant colony algorithm to obtain a proposed rescue route, including:
assuming that the kth ant is currently located at the fth starting node position, the probability of an ant traveling to z target nodes is calculated as follows:
β＝γ+θ
wherein k is 1,2,3, …, and N represents the total number of ants; f is 1,2,3, …, M denotes the total number of start nodes; f is 1,2,3, …, Q represents the total number of target nodes;
denotes the probability, τ, of an ant numbered k from node f to node zfz(t) represents the pheromone concentration on the path from node f to node z, ηfz(t) represents the visibility between node f to node z,
the point that each ant can select is shown, and the point that the kth ant walks will be at
Alpha represents the influence factor of pheromone concentration, and is usually [0.3,0.7 ]]The interval value is taken, beta represents an influence factor of visibility, gamma represents the material demand quantity of the target node z, and theta represents the visibility; wherein, whenever one ant passes through a path from the node f to the node z, pheromones of the corresponding path are increased, and the pheromones are set to be gradually decreased according to time.
In a second aspect, the embodiment of the invention provides a rescue organization method based on an improved ant colony algorithm, which applies the rescue organization system based on the improved ant colony algorithm in any one of the first aspects to execute the organization of rescue tasks.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a rescue organization system and a rescue organization method based on an improved ant colony algorithm, which comprises the following steps: the system of application interface module, inductor information acquisition module, comprehensive analysis module, rescue goods and materials management module, network transmission module realizes the organization of rescue task, wherein: the application interface module receives current rescue information sent by rescuers; the sensor information acquisition module acquires sensing information acquired by sensors arranged on a rescue site; the comprehensive analysis module analyzes and processes the current rescue information and the perception information, and plans a proposed rescue route of ants between rescue points and rescue sites by adopting an ant colony algorithm; the rescue goods and materials management module allocates rescue goods and materials and obtains current use information of the rescue goods and materials; and the network transmission module synchronously stores the current rescue information, the perception information, the proposed rescue route and the current use information of the rescue goods and materials to a cloud. Therefore, the material scheduling of a plurality of rescue points and rescue sites can be coordinated, so that each unit participating in rescue can realize information sharing, the speed of allocating rescue materials is increased, the waste of human resources is reduced, and the rescue scheme can be effectively executed.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
fig. 1 is a schematic block diagram of a rescue organization system based on an improved ant colony algorithm.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
Along with the development of artificial intelligence, artificial intelligence algorithms are also gradually being put into people evacuation activities. The system formed by the artificial intelligence algorithm aggregation grasps various data through the sensing layer, transmits the data to the intelligent computing layer through the network layer, utilizes the algorithm to carry out computation, summarization and analysis, carries out interaction with users through the front-end interface, provides protection tools, fresh water food and the like for the users through external equipment, and achieves the purposes of increasing the survival probability of the personnel in the disaster site and helping the personnel to successfully escape.
The embodiment of the invention provides a rescue organization system based on an improved ant colony algorithm, which is just an organization for realizing rescue tasks by applying an artificial intelligence algorithm. Fig. 1 is a schematic block diagram of a rescue organization system based on an improved ant colony algorithm, and fig. 1 includes: the system comprises an application interface module 10, a sensor information acquisition module 20, a comprehensive analysis module 30, a rescue goods management module 40 and a network transmission module 50. Wherein: and the application interface module 10 is used for receiving the current rescue information sent by rescuers. The sensor information acquisition module 20 is used for acquiring sensing information acquired by sensors arranged on a rescue site; and the comprehensive analysis module 30 is used for analyzing and processing the current rescue information and the perception information, and planning a proposed rescue route of the ants between the rescue points and the rescue site by adopting an ant colony algorithm. And the rescue goods and materials management module 40 is used for allocating rescue goods and acquiring the current use information of the rescue goods and materials. And the network transmission module 50 is used for synchronously storing the current rescue information, the perception information, the formulated rescue route and the current use information of the rescue goods and materials to the cloud.
In an alternative embodiment, rescue material management module 40 is further configured to: when the rescue goods and materials are damaged or in shortage, the rescue goods and materials are allocated again according to the current use condition of the rescue goods and materials at the rescue point.
In an alternative embodiment, the comprehensive analysis module 30 is specifically configured to: determining all rescue points and rescue sites needing to allocate materials according to the current rescue information and the perception information; setting the rescue point as an initial node of an ant in an improved ant colony algorithm, setting a rescue site needing allocation of materials as a target node of the ant, starting the ant with a corresponding amount of materials from the initial node, and when the ant reaches the target node, defaulting that the ant puts part or all of the materials in the corresponding amount into the target node; drawing a rescue map according to the position information of the starting node and the target node; marking the current material storage quantity of each initial node and the material demand quantity of each target node on a rescue map; and planning the path of the ants on the rescue map by adopting an ant colony algorithm to obtain a proposed rescue route.
In an optional implementation manner, the network transmission module 50 may adopt an SDN-based network for transmission, so that data in the application interface module 10, the sensor information acquisition module 20, the comprehensive analysis module 30, and the rescue material management module 40 are synchronized in real time to each unit participating in rescue in the cloud, and the data stored in the cloud can be queried through the cloud, so as to obtain the latest rescue situation.
Taking the case that any ant on any starting node reaches the target node, the ant colony algorithm planning ant path on the rescue map is described in detail.
Specifically, assuming that the kth ant is currently located at the fth starting node position, the calculation formula of the probability of the ant traveling to z target nodes is as follows:
β＝γ+θ
wherein k is 1,2,3, …, and N represents the total number of ants; f is 1,2,3, …, M denotes the total number of start nodes; f is 1,2,3, …, Q represents the total number of target nodes;
denotes the probability, τ, of an ant numbered k from node f to node zfz(t) represents the pheromone concentration on the path from node f to node z, ηfz(t) represents the visibility between node f to node z,
the point that each ant can select is shown, and the point that the kth ant walks will be at
Alpha represents the influence factor of pheromone concentration, and is usually [0.3,0.7 ]]Interval value, beta represents visibility influence factor, and gamma represents object of target node zThe quantity of the resource demand, theta represents visibility; wherein, whenever one ant passes through a path from the node f to the node z, pheromones of the corresponding path are increased, and the pheromones are set to be gradually decreased according to time. Further, t represents the current time, and at the next time (t +1), the information rule on the rescue map satisfies the following formula:
pheromone addition rule:
τfz(t+1)＝Pfzτfz(t)+Δτfz(t，t+n)
wherein: delta taufz(t, t +1) represents the amount of pheromone that increases between node f and node z from time t to t +1,
represents pheromone, P, released by ant k at time t +1fzIndicates the residual ratio after volatilization of the pheromone, Delta taufz(t, t + n) represents the amount of pheromone that increases between f and z as time increases from t to t + n, and n represents the time of increase.
In this embodiment, the current rescue information includes: rescue place, current time, number of people participating in rescue, estimated number of people to be rescued and rescue goods and materials put into use; the perception information includes: the method comprises the following steps of on-site environment temperature, on-site air quality, on-site people flow condition, on-site rescue condition and evacuation path people flow distribution condition. The current usage information includes: the type of the rescue goods and materials put into use, the quantity of each rescue goods and materials put into use, the distribution condition of the rescue goods and materials put into use, the type of the rescue goods and materials not put into use, and the quantity of each rescue goods and materials not put into use. The rescue goods and materials include: transportation equipment, excavating equipment, medical equipment, food, medicines and drinking water. The ants comprise: water source and food ants, medical ants, digging ants; water source and food ants refer to: ants carrying water sources and foods; the medical ant means: ants carrying medical equipment and/or medical personnel; digging ants means: carrying the excavating equipment and/or ants of the excavating technician.
In addition, the embodiment of the invention provides a rescue organization method based on the improved ant colony algorithm, which is used for executing the organization of rescue tasks by applying the rescue organization system based on the improved ant colony algorithm.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (5)
1. A rescue organization system based on an improved ant colony algorithm is characterized by comprising: the system comprises an application interface module, a sensor information acquisition module, a comprehensive analysis module, a rescue goods and materials management module and a network transmission module; wherein:
the application interface module is used for receiving current rescue information sent by rescuers;
the sensor information acquisition module is used for acquiring perception information acquired by sensors arranged on a rescue site;
the comprehensive analysis module is used for analyzing and processing the current rescue information and the perception information and planning a proposed rescue route of ants between a rescue point and a rescue site by adopting an ant colony algorithm;
the rescue goods and materials management module is used for allocating rescue goods and obtaining the current use information of the rescue goods and materials;
the network transmission module is used for synchronously storing the current rescue information, the perception information, the proposed rescue route and the current use information of the rescue goods and materials to a cloud end;
the comprehensive analysis module is specifically used for:
determining all rescue points and rescue sites needing to allocate materials according to the current rescue information and the perception information;
setting the rescue point as an initial node of the ant in the improved ant colony algorithm, setting the rescue site needing allocating materials as a target node of the ant, starting the ant with a corresponding amount of materials from the initial node, and when the ant reaches the target node, defaulting that the ant puts part or all of the materials in the corresponding amount into the target node;
drawing a rescue map according to the position information of the starting node and the target node; marking the current material storage quantity of each initial node and the material demand quantity of each target node on a rescue map;
planning paths of ants on the rescue map by adopting an ant colony algorithm to obtain a proposed rescue route;
the method for planning the paths of ants on the rescue map by adopting the ant colony algorithm to obtain a proposed rescue route comprises the following steps:
assuming that the kth ant is currently located at the fth starting node position, the probability of an ant traveling to z target nodes is calculated as follows:
β＝γ+θ
wherein k is 1,2,3, …, and N represents the total number of ants; f is 1,2,3, …, M denotes the total number of start nodes; f is 1,2,3, …, Q represents the total number of target nodes;
denotes the probability, τ, of an ant numbered k from node f to node zfz(t) represents the pheromone concentration on the path from node f to node z, ηfz(t) represents the visibility between node f to node z,
the point that each ant can select is shown, and the point that the kth ant walks will be at
Alpha represents the influence factor of pheromone concentration and is in the range of 0.3,0.7]The interval value is taken, beta represents an influence factor of visibility, gamma represents the material demand quantity of the target node z, and theta represents the visibility; wherein, whenever one ant passes through a path from the node f to the node z, pheromones of the corresponding path are increased, and the pheromones are set to be gradually decreased according to time.
2. The improved ant colony algorithm-based rescue organization system according to claim 1, wherein the rescue material management module is further configured to: when the rescue goods and materials are damaged or in shortage, the rescue goods and materials are allocated again according to the current use condition of the rescue goods and materials at the rescue point.
3. The improved ant colony algorithm based rescue organization system according to claim 1, wherein the current rescue information comprises: rescue place, current time, number of people participating in rescue, estimated number of people to be rescued and rescue goods and materials put into use;
the perception information includes: the method comprises the following steps of (1) carrying out on-site environment temperature, on-site air quality, on-site people flow condition, on-site rescue condition and evacuation path people flow distribution condition;
the current usage information includes: the type of the rescue goods and materials put into use, the quantity of each type of rescue goods and materials put into use, the distribution condition of the rescue goods and materials put into use, the type of the rescue goods and materials not put into use and the quantity of each type of rescue goods and materials not put into use;
the rescue goods and materials comprise: transportation equipment, excavating equipment, medical equipment, food, medicines and drinking water.
4. The improved ant colony algorithm based rescue organization system according to claim 1, wherein the ants comprise: water source and food ants, medical ants, digging ants; the water source and food ants are as follows: ants carrying water sources and foods; the medical ants refer to: ants carrying medical equipment and/or medical personnel; the digging ants refer to: carrying the excavating equipment and/or ants of the excavating technician.
5. A rescue organization method based on the improved ant colony algorithm is characterized in that the rescue organization system based on the improved ant colony algorithm of any one of claims 1-4 is applied to execute the organization of rescue tasks.
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| CN111026008B (en) * | 2019-12-16 | 2021-12-24 | 上海宏力达信息技术股份有限公司 | Intelligent switch first-aid repair method and system based on ant colony algorithm |
| CN111428851B (en) * | 2020-03-30 | 2022-10-28 | 南方科技大学 | Rescue plan determination method, rescue plan determination device, server and storage medium |
| CN111444300B (en) * | 2020-04-07 | 2022-09-02 | 南方科技大学 | Layout method, device, server and storage medium for emergency rescue station |
| CN113053055A (en) * | 2021-03-08 | 2021-06-29 | 东北大学 | Integrated control system and method based on emergency evacuation decision optimization and intelligent induction |
| CN115619064B (en) * | 2022-12-16 | 2023-07-11 | 南方科技大学 | Rescue plan making method, device, equipment and storage medium |
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