CN116386299A - Meteorological early warning method and related device - Google Patents
Meteorological early warning method and related device Download PDFInfo
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Abstract
The application discloses a weather early warning method and a related device, comprising the following steps: determining disaster coefficients according to weather information by acquiring the weather information of a target area; generating an early warning report and determining a disaster type when the disaster coefficient reaches an early warning condition, wherein the disaster type comprises a first type and a second type; when the disaster type is the first type, matching a corresponding early warning strategy to realize disaster early warning; when the disaster type is the second type, determining a target disaster and generating a first early warning strategy to be combined with the first early warning strategy to realize early warning; the disaster type is determined according to the weather information, and the early warning strategies are matched according to different disaster types so as to achieve the targeted early warning effect aiming at different weather disasters.
Description
Technical Field
The application relates to the field of weather, in particular to a weather early warning method and a related device.
Background
With the improvement of living standard and the progress of science and technology, people have increasingly focused on the surrounding environment. However, in order to provide a good external activity place for people, the air quality is detected at a fixed place, but some existing environment detection devices can detect various harmful substances in the air, but cannot further use the monitoring data, which is not beneficial for the environmental monitoring department to early warn the area where environmental pollution is likely to occur. At present, the weather service industry in China mainly uses public weather service, and the monitoring of local weather disasters and the timely disaster-resistant self-rescue guidance for road traffic operation are relatively few.
Therefore, how to reasonably and timely early warn road traffic according to current weather information becomes a technical problem to be solved urgently.
Disclosure of Invention
In order to reasonably and timely early warn road traffic according to current weather information, the application provides a weather early warning method and a related device.
In a first aspect, the weather early warning method provided by the application adopts the following technical scheme:
a weather early warning method comprising:
acquiring meteorological information of a target area, and determining a hazard coefficient in the meteorological information;
when the hazard coefficient reaches a preset early warning condition, generating an early warning report according to current weather information, and determining a disaster type in the early warning report, wherein the disaster type is a first type or a second type;
when the disaster type is the first type, matching a corresponding early warning strategy according to the disaster type, and carrying out early warning according to the early warning strategy;
when the disaster type is the second type, determining a target disaster in the current weather information;
generating a first early warning strategy according to the target disaster and carrying out early warning according to the first early warning strategy.
Optionally, the step of acquiring weather information of the target area and determining a hazard coefficient in the weather information includes:
acquiring meteorological information of a target area, and acquiring basic data of each meteorological module in the meteorological information;
determining the risk coefficient of each meteorological module according to the basic data of each meteorological module and the preset hazard influence conditions;
and generating a risk coefficient table in the weather information according to the risk coefficient of each weather module.
Optionally, before the step of determining the risk coefficient of each meteorological module according to the basic data of each meteorological module and the preset hazard influence condition, the method further includes:
acquiring a use requirement, and determining a risk factor in the use requirement;
determining a dangerous condition corresponding to each monitoring attribute according to the dangerous factors and the current monitoring attribute;
and generating a preset hazard condition according to the hazard condition corresponding to each monitoring attribute.
Optionally, the step of generating an early warning report according to the current weather information, and determining a disaster type in the early warning report, where the disaster type is a first type or a second type, includes:
obtaining an abnormal coefficient in the current weather information;
determining an abnormal weather item according to the abnormal coefficient;
when the abnormal weather item meets the classification condition, generating a second early warning report and judging that the abnormal weather item is of a second type;
and when the abnormal weather item does not meet the classification condition, generating a first early warning report and judging that the abnormal weather item is of a first type.
Optionally, the step of generating a second early warning report and determining that the abnormal weather item is of the second type when the abnormal weather item meets the classification condition includes:
acquiring the number of items corresponding to the abnormal weather items, and judging the abnormal weather type according to the number of the items and a preset threshold;
when the number of the abnormal weather items is larger than the preset threshold value, judging that the abnormal weather items are of a second type;
and acquiring the project details of the abnormal weather project, and establishing a second abnormal early warning report with the number larger than one according to the project details.
Optionally, the step of matching the corresponding early warning policy according to the disaster type and performing early warning according to the early warning policy includes:
acquiring a weather strategy set, and matching in the weather strategy set according to the disaster type to acquire a matching result;
acquiring an early warning strategy from the matching result, and judging whether the early warning strategy meets implementation conditions or not;
if yes, early warning is carried out according to the early warning strategy.
Optionally, the step of determining the first disaster in the current weather information includes:
acquiring a weight value of each disaster type from the current weather information;
determining a target disaster according to the weight value of each disaster type and a preset ordering rule;
carrying out validity judgment on the target disaster;
and when the validity is determined, the target disaster is taken as a first disaster.
In a second aspect, the present application provides a weather pre-warning device, the weather pre-warning device comprising:
the hazard coefficient acquisition module is used for acquiring weather information of a target area and determining hazard coefficients in the weather information;
the disaster type determining module is used for generating an early warning report according to current weather information when the hazard coefficient reaches a preset early warning condition, and determining a disaster type in the early warning report, wherein the disaster type is a first type or a second type;
the first type module is used for matching a corresponding early warning strategy according to the disaster type when the disaster type is the first type, and carrying out early warning according to the early warning strategy;
the second type module is used for determining a target disaster in the current weather information when the disaster type is a second type;
and the strategy early warning module is used for generating a first early warning strategy according to the target disaster and carrying out early warning according to the first early warning strategy.
In a third aspect, the present application provides a computer device, the device comprising: a memory, a processor which, when executing the computer instructions stored by the memory, performs the method as claimed in any one of the preceding claims.
In a fourth aspect, the present application provides a computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform a method as described above.
In summary, the present application includes the following beneficial technical effects:
according to the method, the disaster coefficient is determined according to the meteorological information by acquiring the meteorological information of the target area; generating an early warning report and determining a disaster type when the disaster coefficient reaches an early warning condition, wherein the disaster type comprises a first type and a second type; when the disaster type is the first type, matching a corresponding early warning strategy to realize disaster early warning; when the disaster type is the second type, determining a target disaster and generating a first early warning strategy to be combined with the first early warning strategy to realize early warning; the disaster type is determined according to the weather information, and the early warning strategies are matched according to different disaster types so as to achieve the targeted early warning effect aiming at different weather disasters.
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FIG. 1 is a schematic diagram of a computer device in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of the weather early warning method of the present invention;
FIG. 3 is a flow chart of a second embodiment of the weather early warning method of the present invention;
FIG. 4 is a block diagram of a first embodiment of the weather warning device of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail by means of the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
Referring to fig. 1, fig. 1 is a schematic diagram of a computer device structure of a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the computer device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the architecture shown in fig. 1 is not limiting of a computer device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a weather warning program may be included in the memory 1005 as one type of storage medium.
In the computer device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the computer device of the present invention may be provided in the computer device, where the computer device invokes the weather early warning program stored in the memory 1005 through the processor 1001, and executes the weather early warning method provided by the embodiment of the present invention.
The embodiment of the invention provides a weather early warning method, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the weather early warning method.
In this embodiment, the weather early warning method includes the following steps:
step S10: and acquiring weather information of the target area, and determining a hazard coefficient in the weather information.
In the present embodiment, weather (weather) refers to a specific state of the atmosphere in a region that is closer to the ground surface in a short time. The weather phenomenon refers to various natural phenomena occurring in the atmosphere, namely, the comprehensive manifestation of the spatial distribution of various meteorological elements (such as air temperature, air pressure, humidity, wind, cloud, fog, rain, flash, snow, frost, thunder, hail, haze, etc.) in the atmosphere in a certain moment. The weather process is the time-dependent change of weather phenomenon in a certain area. Various weather systems have certain spatial scales and time scales, and the systems of various scales are mutually interwoven and interacted. Many combinations of weather systems constitute a wide range of weather conditions, constituting a hemispherical or even global atmospheric circulation. Weather systems are always in the process of continuous new generation, development and extinction, and have their corresponding weather phenomenon distribution in different stages of development.
It can be understood that the weather information is weather information, and the weather information of the target area is obtained through the preset sensing device, and the setting of the target area is set according to the actual use requirement and the functional parameters of the preset sensing device.
It should be noted that the preset sensors include, but are not limited to: atmospheric pressure sensors, air particle size sensors, air temperature sensors, and the like.
In a specific implementation, determining the hazard coefficient in the weather information refers to comparing a specific information value in the weather information with a standard range to generate the hazard coefficient, wherein the value of the hazard coefficient is an absolute value of a ratio of actual weather information to the standard range.
Step S20: when the hazard coefficient reaches a preset early warning condition, an early warning report is generated according to the current weather information, and the disaster type is determined in the early warning report, wherein the disaster type is the first type or the second type.
In this embodiment, the first type refers to a type that is single by disaster, for example: judging that only one disaster exists currently by acquiring a dangerous coefficient, including but not limited to ice disaster, heavy rain or debris flow and the like; meanwhile, the second type refers to that more than 1 disaster exists through judging weather information, and the second type belongs to the nature of composite disasters.
It can be understood that the early warning report refers to a determination result generated according to weather information, and the determination result can obtain the current disaster grade, the disaster specific information and the future disaster prediction in the early warning report. In order to improve the rationality of the early warning report, a prompt strategy can be added in the early warning report, for example, corresponding precautionary measures can be matched according to different disaster types, a flood prevention means is added when heavy rain comes, a key road transportation junction is docked, and key information is sent to a preset destination address so as to reduce loss of people and property.
Further, in order to improve accuracy of disaster type determination, the step of generating an early warning report according to current weather information, and determining a disaster type in the early warning report, wherein the disaster type is a first type or a second type, includes: obtaining an abnormal coefficient in the current weather information; determining an abnormal weather item according to the abnormal coefficient; when the abnormal weather item meets the classification condition, generating a second early warning report and judging that the abnormal weather item is of a second type; and when the abnormal weather item does not meet the classification condition, generating a first early warning report and judging that the abnormal weather item is of a first type.
The method includes generating an early warning report according to current weather information, wherein the early warning report is
In a specific implementation, the step of generating a second early warning report and determining that the abnormal weather item is of the second type when the abnormal weather item meets the classification condition includes: acquiring the number of items corresponding to the abnormal weather items, and judging the abnormal weather type according to the number of the items and a preset threshold; when the number of the abnormal weather items is larger than the preset threshold value, judging that the abnormal weather items are of a second type; and acquiring the project details of the abnormal weather project, and establishing a second abnormal early warning report with the number larger than one according to the project details.
It is understood that, in this embodiment, the obtaining the number of items corresponding to the abnormal weather item refers to determining the number of items simultaneously after determining the specific number by determining the specific number of items to which the abnormal weather belongs.
It should be noted that, in the present embodiment, the generation setting of the anomaly coefficient is set according to specific use requirements, and the setting of the preset threshold corresponding to the difference in resistance to extreme weather in each scene is different.
Step S30: when the disaster type is the first type, matching a corresponding early warning strategy according to the disaster type, and carrying out early warning according to the early warning strategy.
It can be appreciated that the early warning strategy includes: the method comprises the steps of early warning content, early warning port setting, early warning mode and early warning reminding mode.
It should be noted that the disaster types are different, and the corresponding influence areas and severity are also different.
Further, in order to reasonably perform disaster early warning, the steps of matching corresponding early warning strategies according to the disaster types and performing early warning according to the early warning strategies comprise the steps of obtaining a weather strategy set, and matching in the weather strategy set according to the disaster types to obtain a matching result; acquiring an early warning strategy from the matching result, and judging whether the early warning strategy meets implementation conditions or not; if yes, early warning is carried out according to the early warning strategy.
The weather policy set refers to a policy set related to a weather policy generated in advance.
It can be understood that the implementation condition refers to comparing the local early warning capability, matching the hardware and the implementation capability, if the local device can support early warning, the implementation condition is considered to be met, and if the local device cannot meet the implementation condition, the maximum early warning capability of the local device is obtained, the early warning policy is adjusted according to the maximum early warning capability, and the adjusted early warning policy is implemented.
Step S40: and when the disaster type is the second type, determining the target disaster in the current weather information.
Further, in order to accurately acquire the target disaster, the step of determining the first disaster in the current weather information includes: acquiring a weight value of each disaster type from the current weather information; determining a target disaster according to the weight value of each disaster type and a preset ordering rule; carrying out validity judgment on the target disaster; and when the validity is determined, the target disaster is taken as a first disaster.
The implementation of validity judgment refers to whether the target disaster is valid or not, wherein the validity judgment of the target disaster mainly judges the valid duration of the target disaster according to the current weather information corresponding to the target disaster, and if the valid duration of the target disaster is smaller than a preset valid duration, the target disaster can be judged to be invalid.
Step S50: generating a first early warning strategy according to the target disaster and carrying out early warning according to the first early warning strategy.
According to the embodiment, the disaster coefficient is determined according to the meteorological information by acquiring the meteorological information of the target area; generating an early warning report and determining a disaster type when the disaster coefficient reaches an early warning condition, wherein the disaster type comprises a first type and a second type; when the disaster type is the first type, matching a corresponding early warning strategy to realize disaster early warning; when the disaster type is the second type, determining a target disaster and generating a first early warning strategy to be combined with the first early warning strategy to realize early warning; the disaster type is determined according to the weather information, and the early warning strategies are matched according to different disaster types so as to achieve the targeted early warning effect aiming at different weather disasters.
Referring to fig. 3, a flow chart of a second embodiment of the weather early warning method of the present invention is shown.
Based on the above first embodiment, the step S10 of the weather early warning method of this embodiment further includes:
step S101: and acquiring weather information of the target area, and acquiring basic data of each weather module in the weather information.
It can be understood that the early warning information of the current road traffic weather disasters is all from a weather bureau early warning information platform, the weather bureau obtains data and then obtains a conclusion through algorithm analysis, after obtaining a budget result, early warning contents are informed to the masses in the form of media such as short messages, microblogs, micro-messages, broadcasting, newspapers and the like, and a traffic management department distributes the information to each guidance screen for guiding traffic after obtaining the early warning information. The whole process has the following problems: first, predict inaccurately, the early warning information of meteorological bureau is to prediction on a large scale, predicts inaccurately to the concrete place of concrete time, leads to the guide reliability to the traffic road not high. Secondly, the information is not timely released, and the traffic management department receives the early warning information and then releases the traffic guidance screens, so that the information is not timely released, and the optimal early warning time is easily missed.
It should be noted that the dynamic factors of weather mainly refer to wind and turbulence, which play a decisive role in the diffusion and dilution of pollutants in the atmosphere. Turbulence: the irregular movement of the atmosphere is also called atmospheric turbulence. The atmosphere moves up, down, left and right in addition to the horizontal movement. The meteorological thermodynamic factor mainly refers to temperature layer junction, stability and the like. And (3) temperature layer junction: the temperature profile with height becomes a temperature layer junction. It affects the flow condition of the atmosphere in the vertical direction, and the temperature layer junction is different due to the different ground structures. In the convection zone, the temperature generally decreases with increasing altitude, and the air temperature decreases by about 0.65 ℃ every 100m above altitude. The phenomenon that the air temperature increases with the increase of altitude is called reverse temperature. The atmosphere with the reverse temperature is a strongly stabilized atmosphere. Atmospheric stability: refers to the temperature level of the whole layer of air, and is a thermodynamic property of the atmosphere to accelerate, contain or not affect the movement of the air mass in which the air moves vertically.
Step S102: and determining the risk coefficient of each meteorological module according to the basic data of each meteorological module and the preset hazard influence condition.
Further, in order to improve accuracy of the monitoring attribute, before the step of determining the risk coefficient of each meteorological module according to the basic data of each meteorological module and the preset hazard influence condition, the method further includes: acquiring a use requirement, and determining a risk factor in the use requirement; determining a dangerous condition corresponding to each monitoring attribute according to the dangerous factors and the current monitoring attribute; and generating a preset hazard condition according to the hazard condition corresponding to each monitoring attribute.
Step S103: and generating a risk coefficient table in the weather information according to the risk coefficient of each weather module.
According to the embodiment, the basic data of each meteorological module are acquired in the meteorological information by acquiring the meteorological information of the target area; determining the risk coefficient of each meteorological module according to the basic data of each meteorological module and the preset hazard influence conditions; generating a risk coefficient table in the weather information according to the risk coefficient of each weather module; the corresponding danger coefficient is generated according to the basic data and the hazard influence conditions, so that the technical effect of reasonably generating the danger coefficient is realized, and the accuracy of weather early warning is further improved.
In addition, the embodiment of the invention also provides a computer readable storage medium, wherein the storage medium is stored with a program for weather early warning, and the program for weather early warning realizes the steps of the method for weather early warning when being executed by a processor.
Referring to fig. 4, fig. 4 is a block diagram illustrating a first embodiment of a weather early warning device according to the present invention.
As shown in fig. 4, the weather early warning device provided by the embodiment of the invention includes:
the hazard coefficient acquisition module 10 is used for acquiring weather information of a target area, and determining hazard coefficients in the weather information;
the disaster type determining module 20 is configured to generate an early warning report according to current weather information when the hazard coefficient reaches a preset early warning condition, and determine a disaster type in the early warning report, where the disaster type is a first type or a second type;
the first type module 30 is configured to match a corresponding early warning policy according to the disaster type when the disaster type is the first type, and perform early warning according to the early warning policy;
a second type module 40 for determining a target disaster in the current weather information when the disaster type is a second type;
the policy early warning module 50 is configured to generate a first early warning policy according to the target disaster and perform early warning according to the first early warning policy.
It should be understood that the foregoing is illustrative only and is not limiting, and that in specific applications, those skilled in the art may set the invention as desired, and the invention is not limited thereto.
According to the embodiment, the disaster coefficient is determined according to the meteorological information by acquiring the meteorological information of the target area; generating an early warning report and determining a disaster type when the disaster coefficient reaches an early warning condition, wherein the disaster type comprises a first type and a second type; when the disaster type is the first type, matching a corresponding early warning strategy to realize disaster early warning; when the disaster type is the second type, determining a target disaster and generating a first early warning strategy to be combined with the first early warning strategy to realize early warning; the disaster type is determined according to the weather information, and the early warning strategies are matched according to different disaster types so as to achieve the targeted early warning effect aiming at different weather disasters.
In an embodiment, the hazard coefficient obtaining module 10 is further configured to obtain weather information of the target area, where the weather information is used to obtain basic data of each weather module; determining the risk coefficient of each meteorological module according to the basic data of each meteorological module and the preset hazard influence conditions; and generating a risk coefficient table in the weather information according to the risk coefficient of each weather module.
In an embodiment, the hazard coefficient obtaining module 10 is further configured to obtain a usage requirement, and determine a hazard factor in the usage requirement; determining a dangerous condition corresponding to each monitoring attribute according to the dangerous factors and the current monitoring attribute; and generating a preset hazard condition according to the hazard condition corresponding to each monitoring attribute.
In an embodiment, the disaster type determining module 20 is further configured to obtain an anomaly coefficient in the current weather information; determining an abnormal weather item according to the abnormal coefficient; when the abnormal weather item meets the classification condition, generating a second early warning report and judging that the abnormal weather item is of a second type; and when the abnormal weather item does not meet the classification condition, generating a first early warning report and judging that the abnormal weather item is of a first type.
In an embodiment, the disaster type determining module 20 is further configured to obtain a number of items corresponding to the abnormal weather item, and determine the abnormal weather type according to the number of items in combination with a preset threshold; when the number of the abnormal weather items is larger than the preset threshold value, judging that the abnormal weather items are of a second type; and acquiring the project details of the abnormal weather project, and establishing a second abnormal early warning report with the number larger than one according to the project details.
In an embodiment, the first type module 30 is further configured to obtain a weather policy set, and perform matching in the weather policy set according to the disaster type to obtain a matching result; acquiring an early warning strategy from the matching result, and judging whether the early warning strategy meets implementation conditions or not; if yes, early warning is carried out according to the early warning strategy.
In an embodiment, the second type module 40 is further configured to obtain a weight value of each disaster type from the current weather information; determining a target disaster according to the weight value of each disaster type and a preset ordering rule; carrying out validity judgment on the target disaster; and when the validity is determined, the target disaster is taken as a first disaster.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in the embodiment can be referred to the method for weather early warning provided by any embodiment of the present invention, and are not described herein.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory)/RAM, magnetic disk, optical disk) and including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A weather early warning method, comprising:
acquiring meteorological information of a target area, and determining a hazard coefficient in the meteorological information;
when the hazard coefficient reaches a preset early warning condition, generating an early warning report according to current weather information, and determining a disaster type in the early warning report, wherein the disaster type is a first type or a second type;
when the disaster type is the first type, matching a corresponding early warning strategy according to the disaster type, and carrying out early warning according to the early warning strategy;
when the disaster type is the second type, determining a target disaster in the current weather information;
generating a first early warning strategy according to the target disaster and carrying out early warning according to the first early warning strategy.
2. The weather pre-warning method as claimed in claim 1, wherein the step of acquiring weather information of the target area and determining a hazard coefficient in the weather information comprises:
acquiring meteorological information of a target area, and acquiring basic data of each meteorological module in the meteorological information;
determining the risk coefficient of each meteorological module according to the basic data of each meteorological module and the preset hazard influence conditions;
and generating a risk coefficient table in the weather information according to the risk coefficient of each weather module.
3. The weather pre-warning method according to claim 2, wherein before the step of determining the risk factor of each weather module according to the basic data of each weather module in combination with a preset hazard influence condition, further comprises:
acquiring a use requirement, and determining a risk factor in the use requirement;
determining a dangerous condition corresponding to each monitoring attribute according to the dangerous factors and the current monitoring attribute;
and generating a preset hazard condition according to the hazard condition corresponding to each monitoring attribute.
4. The method of claim 1, wherein the step of generating an early warning report from current weather information, determining a disaster type in the early warning report, the disaster type being either a first type or a second type, comprises:
obtaining an abnormal coefficient in the current weather information;
determining an abnormal weather item according to the abnormal coefficient;
when the abnormal weather item meets the classification condition, generating a second early warning report and judging that the abnormal weather item is of a second type;
and when the abnormal weather item does not meet the classification condition, generating a first early warning report and judging that the abnormal weather item is of a first type.
5. The weather warning method as claimed in claim 4, wherein the step of generating a second warning report and determining that the abnormal weather item is of a second type when the abnormal weather item satisfies a classification condition comprises:
acquiring the number of items corresponding to the abnormal weather items, and judging the abnormal weather type according to the number of the items and a preset threshold;
when the number of the abnormal weather items is larger than the preset threshold value, judging that the abnormal weather items are of a second type;
and acquiring the project details of the abnormal weather project, and establishing a second abnormal early warning report with the number larger than one according to the project details.
6. The weather early warning method according to claim 1, wherein the step of matching the corresponding early warning policy according to the disaster type and performing early warning according to the early warning policy comprises:
acquiring a weather strategy set, and matching in the weather strategy set according to the disaster type to acquire a matching result;
acquiring an early warning strategy from the matching result, and judging whether the early warning strategy meets implementation conditions or not;
if yes, early warning is carried out according to the early warning strategy.
7. The weather pre-warning method of claim 1, wherein the step of determining the first hazard in the current weather information comprises:
acquiring a weight value of each disaster type from the current weather information;
determining a target disaster according to the weight value of each disaster type and a preset ordering rule;
carrying out validity judgment on the target disaster;
and when the validity is determined, the target disaster is taken as a first disaster.
8. A weather early warning device, characterized in that the weather early warning device includes:
the hazard coefficient acquisition module is used for acquiring weather information of a target area and determining hazard coefficients in the weather information;
the disaster type determining module is used for generating an early warning report according to current weather information when the hazard coefficient reaches a preset early warning condition, and determining a disaster type in the early warning report, wherein the disaster type is a first type or a second type;
the first type module is used for matching a corresponding early warning strategy according to the disaster type when the disaster type is the first type, and carrying out early warning according to the early warning strategy;
the second type module is used for determining a target disaster in the current weather information when the disaster type is a second type;
and the strategy early warning module is used for generating a first early warning strategy according to the target disaster and carrying out early warning according to the first early warning strategy.
9. A computer device, the device comprising: a memory, a processor which, when executing the computer instructions stored by the memory, performs the method of any one of claims 1 to 7.
10. A computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the method of any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116894107A (en) * | 2023-07-20 | 2023-10-17 | 中国长江电力股份有限公司 | Hydropower station disastrous weather archive storage system |
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| CN116894107A (en) * | 2023-07-20 | 2023-10-17 | 中国长江电力股份有限公司 | Hydropower station disastrous weather archive storage system |
| CN116894107B (en) * | 2023-07-20 | 2024-01-02 | 中国长江电力股份有限公司 | Hydropower station disastrous weather archive storage system |
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