CN111553511A - Data analysis method and equipment for dust and sand process - Google Patents
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Abstract
The method comprises the steps of obtaining METAR messages of a target airport in a preset historical time period; preprocessing METAR messages and screening the dust messages to obtain at least two dust messages, and message key characteristics and conversion values of each dust message; analyzing the dust process of at least two dust messages based on message key characteristics and conversion values thereof to obtain the dust message corresponding to the METAR message in each dust process; and respectively extracting the key features of the dust process from the dust message corresponding to each dust process to obtain the key features and the feature values of the process corresponding to each dust process, so that the process key features and the feature values of each dust process are extracted while the historical METAR message is analyzed for big data, and the prediction of the dust weather of the airport can be efficiently and conveniently carried out on the process key features and the feature values of the subsequent historical dust process.
Description
Technical Field
The application relates to the field of computers, in particular to a data analysis method and equipment for a dust and sand process.
Background
In actual civil aviation operation, low-visibility weather is very common severe weather which affects operation, and the weather which can generate low visibility mainly comprises fog, haze, sand dust, volcanic ash and the like, wherein the sand dust weather frequently occurs in Xinjiang and North China; in international operations, most airports in the middle east are susceptible to influences, the visibility is affected by sand weather, and serious sand storms usually accompany strong winds and may directly damage aircraft engines and the like, so that the characteristic statistical analysis of the sand weather at the airports is extremely important.
Disclosure of Invention
The method and the device for analyzing the data of the dust and sand process analyze the dust and sand process and the dust and sand message corresponding to each historical dust and sand process and the process key feature and the feature value of the dust and sand message corresponding to each dust and sand process through data analysis of historical aviation routine weather report messages of the airport, realize big data analysis of the historical aviation routine weather report messages, and extract the process key feature and the feature value of each analyzed dust and sand process, so that the dust and sand weather of the airport can be predicted efficiently and conveniently in the following process.
According to an aspect of the present application, there is provided a data analysis method of a dust and sand process, wherein the method comprises:
acquiring an aviation routine weather report METAR message of a target airport in a preset historical time period;
preprocessing the METAR messages and screening the dust messages to obtain at least two dust messages, and message key characteristics and conversion values of each dust message;
analyzing the dust and sand process of the at least two dust and sand messages based on the message key characteristics and the conversion values thereof to obtain the dust and sand message corresponding to each dust and sand process corresponding to the METAR message;
and respectively extracting the key features of the dust and sand process from the dust and sand message corresponding to the dust and sand process each time to obtain the key features and the feature values of the process corresponding to the dust and sand process each time.
Further, in the above method, the preprocessing the meta message and screening the dust message to obtain at least two dust messages, and a message key feature and a conversion value of each dust message include:
extracting key features of the METAR message to obtain message key features and feature values corresponding to the METAR message;
according to a preset METAR message editing and sending rule, converting the characteristic value of the message key characteristic corresponding to the METAR message to obtain a conversion value of the message key characteristic corresponding to the METAR message;
and screening the METAR messages based on the key message characteristics and the conversion values thereof corresponding to the METAR messages to obtain at least two dust messages.
Further, in the above method, the screening, based on the message key features and the conversion values thereof corresponding to the meta message, of the meta message to obtain at least two dust messages includes:
judging whether the conversion values of the key features of the message corresponding to the METAR message meet a first preset condition and a second preset condition,
if so, determining the corresponding METAR message as a dust message when both the first preset condition and the second preset condition are met, so as to obtain at least two dust messages;
the first preset condition comprises that a conversion value of a message key feature corresponding to the METAR message contains relevant information for indicating a sand weather phenomenon;
the second preset condition comprises that the conversion value of the key features of the message corresponding to the METAR message is within a preset dominant visibility range.
Further, in the above method, the analyzing the dust and sand process of the at least two dust and sand messages based on the key feature of the message and the conversion value thereof to obtain the dust and sand message corresponding to each dust and sand process corresponding to the meta message includes:
respectively calculating the release time difference of each two adjacent dust messages;
and performing the following steps on the release time of each two adjacent dust messages to obtain the total number of the dust and sand processes corresponding to the METAR message and the dust and sand message corresponding to each dust and sand process:
judging whether the issuing time difference is larger than a preset time difference threshold value or not,
if not, recording two adjacent dust messages corresponding to the release time difference as the dust messages in the same dust process;
if so, recording two adjacent sand-dust messages corresponding to the release time difference as different sand-dust processes, recording a previous sand-dust message in the two adjacent sand-dust messages corresponding to the release time difference as a last sand-dust message in the current sand-dust process, and recording a next sand-dust message in the two adjacent sand-dust messages corresponding to the release time difference as a first sand-dust message in the next sand-dust process.
Further, in the above method, the key features of the message include release time, wind direction, wind speed, visibility dominance, and weather phenomenon, and the key features of the process include duration, dominance wind direction, minimum wind speed, maximum wind speed, average wind speed, and minimum visibility;
the method for extracting the key features of the dust process from the dust messages corresponding to the dust process at each time respectively to obtain the key features and the feature values of the process corresponding to the dust process at each time comprises the following steps:
calculating a characteristic value of the duration of each dust and sand process based on the release time corresponding to the first dust and sand message and the release time of the last dust and sand message in each dust and sand process respectively;
calculating a characteristic value of minimum visibility in each dust and sand process based on the conversion values of the corresponding dominant visibility of all the dust and sand messages in each dust and sand process;
respectively calculating a characteristic value of a dominant wind direction of each dust and sand process based on the wind direction turning values corresponding to all the dust and sand messages in each dust and sand process;
and respectively calculating the characteristic value of the minimum wind speed, the characteristic value of the maximum wind speed and the characteristic value of the average wind speed in each dust-proof process based on the conversion values of the wind speeds corresponding to all the dust messages in each dust-proof process.
Further, in the above method, the method further includes:
and storing the dust message, the process key characteristics and the characteristic values of the dust messages corresponding to each dust process in the total dust process number into a dust process database.
Further, in the above method, the method further includes:
acquiring a real-time METAR message of the target airport in the current time period;
analyzing the real-time METAR message based on the dust and sand process database to obtain dust and sand forecast information corresponding to the target airport, wherein the dust and sand forecast information comprises a predicted value of the process key feature.
According to another aspect of the present application, there is also provided a data analysis apparatus for a dust and sand process, wherein the apparatus comprises:
the acquiring device is used for acquiring an aviation routine weather report METAR message of a target airport in a preset historical time period;
the preprocessing device is used for preprocessing the METAR message and screening the dust message to obtain at least two dust messages, and the message key characteristics and the conversion values of each dust message;
a dust and sand process determining device, configured to perform dust and sand process analysis on the at least two dust and sand messages based on the message key features and the conversion values thereof, to obtain a dust and sand message corresponding to each dust and sand process corresponding to the meta message;
and the characteristic extraction device is used for respectively extracting the key characteristics of the dust and sand process from the dust and sand message corresponding to the dust and sand process each time to obtain the key characteristics of the process corresponding to the dust and sand process each time and the characteristic value of the key characteristics.
According to another aspect of the present application, there is also provided a computer readable medium having stored thereon computer readable instructions, which, when executed by a processor, cause the processor to implement the data analysis method of the dust and sand process as described above.
According to another aspect of the present application, there is also provided a data analysis apparatus for a dust and sand process, characterized in that the apparatus comprises:
one or more processors;
a computer-readable medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement a data analysis method as described above for the dust and sand process.
Compared with the prior art, the method comprises the steps of firstly obtaining the METAR message of the aviation routine weather report of the target airport in the preset historical time period; then preprocessing the METAR messages and screening the dust messages to obtain at least two dust messages, and message key characteristics and conversion values of each dust message; then, based on the message key features and the conversion values thereof, carrying out dust and sand process analysis on the at least two dust and sand messages to obtain the dust and sand message corresponding to each dust and sand process corresponding to the METAR message; and respectively extracting the key features of the dust and sand process from the dust and sand message corresponding to the dust and sand process each time to obtain the key features and the feature values of the process corresponding to the dust and sand process each time. According to the method and the device, the sand-dust process, the sand-dust messages corresponding to each historical sand-dust process and the process key features and the feature values of the sand-dust messages corresponding to each sand-dust process are analyzed through data analysis of the historical aviation routine weather report messages of the airport, the analyzed process key features and the analyzed feature values of each sand-dust process are extracted while the big data analysis of the historical aviation routine weather report messages is achieved, the process key features and the analyzed feature values of each sand-dust process are convenient to conduct the follow-up prediction of the sand-dust weather of the airport based on the process key features and the analyzed feature values of the historical sand-dust process, and the sand-dust weather of the airport can be efficiently and conveniently predicted.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 illustrates a flow diagram of a method of data analysis of a dust and sand process according to an aspect of the subject application;
FIG. 2 illustrates a schematic diagram of a data analysis facility for a dust and sand process according to one aspect of the subject application;
the same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (e.g., Central Processing Units (CPUs)), input/output interfaces, network interfaces, and memory.
The Memory may include volatile Memory in a computer readable medium, Random Access Memory (RAM), and/or nonvolatile Memory such as Read Only Memory (ROM) or flash Memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, Phase-Change RAM (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), flash Memory or other Memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, magnetic cassette tape, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transmyedia), such as modulated data signals and carrier waves.
As shown in fig. 1, an aspect of the present application provides a flow diagram of a data analysis method for a sand and dust process, which is applied to data analysis of a historical Aviation routine weather Report (metal) message and weather prediction of a sand and dust process. The method comprises a step S11, a step S12, a step S13 and a step S14, wherein the method specifically comprises the following steps:
and step S11, acquiring an aviation routine weather report METAR message of the target airport in a preset historical time period. Here, the preset historical event period includes, but is not limited to, any historical time period T. For example, the meta message and its listed data in a preset historical time period T of an airport (such as airport a) include, but are not limited to, airport four-character codes, the release time of the message, wind direction, wind speed, dominant visibility, runway visibility, weather phenomena, cloud height, temperature, dew point temperature, air pressure, and trend item/RM remark item.
Step S12, preprocessing the meta message and screening the dust message to obtain at least two dust messages, and the message key feature and the conversion value of each dust message, so as to realize the screening of the dust message and the extraction of the message key feature reflected by each dust message.
And step S13, analyzing the dust and sand process of the at least two dust and sand messages based on the key features of the messages and the conversion values thereof to obtain the dust and sand message corresponding to each dust and sand process corresponding to the METAR message.
And step S14, respectively extracting the key features of the dust process from the dust message corresponding to the dust process each time to obtain the key features and the feature values of the process corresponding to the dust process each time.
Through the steps S11 to S14, the present application analyzes the sand-dust process, the sand-dust message corresponding to each historical sand-dust process, and the process key feature and the feature value thereof reflected by the sand-dust message corresponding to each sand-dust process through data analysis of the historical aviation routine weather report message of the airport, so as to realize big data analysis of the historical aviation routine weather report message, and simultaneously extract the analyzed process key feature and the analyzed feature value of each sand-dust process, so that the process key feature and the analyzed feature value of each sand-dust process are convenient for the subsequent process key feature and the analyzed feature value thereof based on the historical sand-dust process, and the sand-dust weather of the airport can be efficiently and conveniently predicted.
For example, in step S11, a meta message 1, a meta message 2, a meta message 3, a meta message … …, a meta message (n-1), and a meta message n of the airport a in the preset historical time period T are obtained, where n is the number of all meta messages collected by the airport a in the preset historical time period T and is a positive integer greater than or equal to 2. In step S12, preprocessing and screening dust and sand messages on the meta message 1, the meta message 2, the meta message 3, … …, the meta message (n-1), and the meta message n of the airport a within a preset historical time period T to obtain at least two dust and sand messages, and message key features and conversion values of each of the dust and sand messages, wherein if there are m dust and sand messages screened from n meta messages, where m is a positive integer less than or equal to n, the dust and sand messages obtained by screening are respectively: the screening of the sanddust messages and the extraction of the message key features reflected by each sanddust message are realized by the sanddust message 1, the sanddust message 2, the sanddust message 3, the sanddust message … …, the sanddust message (m-1) and the sanddust message m, and the message key features reflected by each sanddust message and the conversion values thereof. In step S13, based on the key feature and the conversion value of each of the m dust messages, performing dust process analysis on the m dust messages to obtain the total number of dust processes contained in the METAR message, i.e., the total number ss _ num of the dust processes, and the dust messages corresponding to each dust process, such as the dust messages corresponding to the dust process event1 being the dust message 1, the dust message 2, the dust message 3, the dust message … …, the dust message 9, and the dust message 10, the dust messages corresponding to the dust process event2 being the dust message 11, the dust message 12, the dust message 13, … …, the dust message 22, and the dust message 23, the dust messages corresponding to the dust process event3 being the dust messages 24, the dust message 25, the dust messages 26, … …, the dust message 44, the dust message 45, the dust message … …, and the dust process event (m-13) corresponding to the dust process event (13-13, … …), Sand message (m-12), sand message (m-11), … …, sand message (m-1), and sand message m. In step S14, sand and dust process key feature extraction is performed on sand and dust messages corresponding to sand and dust process event1, sand and dust process event2, sand and dust process event3, sand and dust process event … …, sand and dust process event (r-1) and sand and dust process event (r), respectively, to obtain process key feature 1 and its feature value 1 corresponding to sand and dust process event1, process key feature 2 and its feature value 2 corresponding to sand and dust process event2, process key feature 3 and its feature value 3 corresponding to sand and dust process event3, … …, process key feature (r-1) and its feature value (r-1) corresponding to sand and dust process event (r) and its feature value r corresponding to sand and dust process event (r), where, the process key feature and its feature value corresponding to each sand and dust process not only achieves analysis of the sand and dust process, but also achieves extraction of the process key feature and its feature value of each sand and dust process, therefore, the process key characteristics and the characteristic values of the subsequent history-based dust and sand process can be used for efficiently and conveniently predicting the dust and sand weather of the airport.
Next, in the above embodiment of the present application, the step S12 is to perform preprocessing and screening on the meta message, and obtain at least two dust messages, and a message key feature and a conversion value of each dust message, including:
extracting key features of the METAR message to obtain message key features and feature values corresponding to the METAR message;
according to a preset METAR message compiling and sending rule, the characteristic value of the message key characteristic corresponding to the METAR message is converted, and the conversion value of the message key characteristic corresponding to the METAR message is obtained. Here, the preset compiling and reporting rule of the meta message includes, but is not limited to, performing numerical conversion or character conversion on a feature value corresponding to a key feature of the message when the feature value corresponding to the key feature of the message exceeds a preset feature value threshold value corresponding to the key feature of the message or the feature value includes a character string for indicating a weather phenomenon.
And screening the METAR messages based on the key message characteristics and the conversion values thereof corresponding to the METAR messages to obtain at least two dust messages.
For example, since the dust and sand process is analyzed in step S13, when the dust and sand message is counted and extracted in step S12, the message key features (i.e., message elements) that need to be extracted from the original meta message sorted data may include, but are not limited to, release time, wind direction and speed, dominant visibility, weather phenomenon, and the like, when the key features are extracted from the meta message, any feature extraction algorithm may be adopted, in a preferred embodiment of the present application, an algorithm of using _ cols as a parameter specified by read _ csv of pandas is used to perform key feature extraction on each meta message to obtain a message key feature and a feature value thereof corresponding to each meta message, for example, the feature value corresponding to the message is 800m and the like, which indicates visibility differently; and then, according to a preset compiling and sending rule of the METAR message, converting the characteristic value of the message key characteristic corresponding to the METAR message to obtain a conversion value of the message key characteristic corresponding to the METAR message, for example, converting the characteristic value used for indicating weather phenomena in the message key characteristic into a character string format, and converting the characteristic values of the release time, the wind direction and the wind speed, the dominant visibility and the like in the message key characteristic into numerical values for comparison. According to the preset compiling and sending rules of METAR messages, the following conversion preprocessing can be carried out: for example, in the conversion process of the CAVOK (vehicular visibility Okay, clear sky), the feature value of the key feature of the message, which is the dominant visibility: the CAVOK item is replaced by 10000 in a numerical mode, wherein CAVOK represents the decorating And Visibility isOK, the Visibility is larger than 9999m, namely the weather is good, low Visibility sand weather does not exist, namely the weather is clear, And therefore any numerical value larger than 9999 can be replaced, such as 10000, 12000, 15000 And other numerical values; for another example, when the feature value corresponding to the key feature of the message with the feature value of null data is null data, that is, when the feature value corresponding to the key feature of the message with the dominant visibility is null data, that is, the feature value corresponding to the key feature of the message with the dominant visibility is null value, the null value may be converted into an arbitrary numerical value of 10000 or more than 9999, and when the feature value corresponding to the key feature of the message with weather phenomenon is null value, the null value may be converted into "no wx" for representing no weather, so as to convert the key feature and the feature value of the message corresponding to each meta message, thereby obtaining the key feature and the conversion value of the message corresponding to each meta message, so as to subsequently screen the meta message based on the key feature and the conversion value of the message corresponding to each meta message obtained after the conversion processing.
In this embodiment, the screening of the dust and sand messages on the meta message in step S12 based on the key feature of the meta message and the conversion value thereof to obtain at least two dust and sand messages specifically includes:
judging whether the conversion values of the key features of the message corresponding to the METAR message meet a first preset condition and a second preset condition,
if so, determining the corresponding METAR message as a dust message when both the first preset condition and the second preset condition are met, so as to obtain at least two dust messages.
Here, the first preset condition includes that a conversion value of a message key feature corresponding to the METAR message includes related information for indicating a dust weather phenomenon; for example, the feature value corresponding to the key feature of the message including the weather phenomenon includes information indicating the weather phenomenon of sand dust, such as "SS" (sand storm), "SA" (sand raising), "DU" (dust raising), and "nowx". The second preset condition includes that a conversion value of a key feature of the message corresponding to the meta message is within a preset dominant visibility range, where the preset dominant visibility range includes but is not limited to a visibility threshold value which is less than or equal to a visibility threshold value, and the visibility threshold value may be any visibility value, such as any values of 800m, 1000m, 1500m, 500m, and the like.
For example, in a preferred embodiment of the present application, for each meta message, it is determined whether a conversion value of a message key feature corresponding to the meta message satisfies a first preset condition and a second preset condition, for example, whether the conversion value of the message key feature in the meta message includes: the method comprises the steps that information used for indicating sand weather phenomena such as SS (sand storm), SA (flying sand), DU (flying dust) and nowx is used, whether a conversion value of key features of a message in the METAR message is within a preset dominant visibility range or not is judged, and if the conversion value of the weather phenomena in the METAR message is SA (flying sand) and the conversion value of the dominant visibility is 300 (the conversion value 300 of the dominant visibility is within a preset visibility threshold range), the METAR message is considered to be the sand message; if the conversion value corresponding to the weather phenomenon in the METAR message does not relate to SS (sand storm), SA (sand raising), DU (dust raising), nowx and the like which are used for indicating the information of the sand weather phenomenon and/or the conversion value of the dominant visibility are not in the preset dominant visibility range, the METAR message is considered not to be the sand message, and the screening processing of the sand message on the METAR message through the first preset condition and the second preset condition is realized, so that the corresponding sand message, the message key feature corresponding to each sand message and the conversion value of the sand message are obtained.
Next to the foregoing embodiment of the present application, in step S13, based on the key features of the message and the conversion values thereof, the dust and sand process analysis is performed on the at least two dust and sand messages to obtain a total number of dust and sand processes corresponding to the meta message and a dust and sand message corresponding to each dust and sand process, and the method specifically includes:
respectively calculating the release time difference of each two adjacent dust messages;
and performing the following steps on the release time of each two adjacent dust messages to obtain the total number of the dust and sand processes corresponding to the METAR message and the dust and sand message corresponding to each dust and sand process:
and judging whether the issuing time difference is greater than a preset time difference threshold value, wherein the preset time difference threshold value can be any time value, and considering that the weather phenomenon fluctuates in a short time to cause judgment errors, in a preferred embodiment of the application, the preset time difference threshold value is preferably 6 h.
If not, recording two adjacent dust messages corresponding to the release time difference as the dust messages in the same dust process;
if so, recording two adjacent sand-dust messages corresponding to the release time difference as different sand-dust processes, recording a previous sand-dust message in the two adjacent sand-dust messages corresponding to the release time difference as a last sand-dust message in the current sand-dust process, and recording a next sand-dust message in the two adjacent sand-dust messages corresponding to the release time difference as a first sand-dust message in the next sand-dust process.
For example, each dust message has its corresponding release time t, the release time difference of each two adjacent dust messages in m dust messages is calculated, that is, the release time of the previous dust message in each two adjacent dust messages is subtracted by the release time of the next dust message to obtain the release time difference delta of each two adjacent dust messages, and then the following steps are performed on the release time of each two adjacent dust messages to obtain the total number of dust processes ss _ num corresponding to the meta message and the dust message corresponding to each dust process: for example, the release time difference between the dust message k and the dust message (k +1) is delta k, where k is a positive integer smaller than m, and it is determined whether the release time difference delta k is greater than a preset time difference threshold value: 6h, if not, the issuing time difference delta k is smaller than the preset time difference threshold value: recording a sand dust message k and a sand dust message (k +1) corresponding to the release time difference delta k as belonging to the same sand dust process after 6 h; if yes, the release time difference delta k is larger than the preset time difference threshold value: recording two adjacent sand-dust messages corresponding to the release time difference delta k, namely a sand-dust message k and a sand-dust message (k +1), as different sand-dust processes, recording the previous sand-dust message k in the two adjacent sand-dust messages corresponding to the release time difference delta k as the last sand-dust message in the current sand-dust process, recording the next sand-dust message (k +1) in the two adjacent sand-dust messages corresponding to the release time difference delta k as the first sand-dust message in the next sand-dust process, so as to determine the boundary lines of the different sand-dust processes, and accumulating the number of the sand-dust processes +1 when determining one sand-dust process, so as to obtain the total sand-dust process number ss _ num contained in the sand-dust messages 1, 2, 3, … …, 1 and m-1, the definition of the dust and sand process and the determination of the dust and sand message corresponding to the dust and sand process each time are realized through the distribution time difference of every two adjacent dust and sand messages.
Next, in the above embodiment of the present application, the key features of the message include release time, wind direction, wind speed, visibility dominance, and weather phenomenon, and the key features of the process include duration, dominance wind direction, minimum wind speed, maximum wind speed, average wind speed, and minimum visibility;
in step S14, the sand-dust process key feature extraction is performed on each sand-dust message corresponding to the sand-dust process, so as to obtain the process key feature and the feature value thereof corresponding to each sand-dust process, which specifically includes:
calculating a characteristic value of the duration of each dust and sand process based on the release time corresponding to the first dust and sand message and the release time of the last dust and sand message in each dust and sand process respectively;
calculating a characteristic value of minimum visibility in each dust and sand process based on the conversion values of the corresponding dominant visibility of all the dust and sand messages in each dust and sand process;
respectively calculating a characteristic value of a dominant wind direction of each dust and sand process based on the wind direction turning values corresponding to all the dust and sand messages in each dust and sand process;
and respectively calculating the characteristic value of the minimum wind speed, the characteristic value of the maximum wind speed and the characteristic value of the average wind speed in each dust-proof process based on the conversion values of the wind speeds corresponding to all the dust messages in each dust-proof process.
For example, when the key feature extraction of the dust and sand process is performed on each dust and sand process, the start time (i.e., the release time of the first dust and sand message) and the end time (i.e., the release time of the last dust and sand message) of each dust and sand process event are output, the duration of each dust and sand process and the feature value of the duration (i.e., the specific value of the duration) can be calculated, and the duration of the dust and sand process is used to represent the duration of the influence of the dust and sand process, so that the influence can be subsequently determined on the dust and sand process under the condition of the duration; because each sand-dust process event comprises more than one sand-dust message, the corresponding dominant visibility of the sand-dust process can reflect the severity of the sand-dust process, and in order to effectively reflect the severity of the sand-dust process each time, the minimum value of the conversion values of the corresponding dominant visibility of all the sand-dust messages in the sand-dust process each time is determined as the characteristic value of the minimum visibility of the event in the sand-dust process each time, so that the severity of the sand-dust process each time can be accurately reflected; different wind directions of the sand process events can reflect a weather system causing a sand storm, and when key features of the sand process are extracted, the feature value of the dominant wind direction of each sand process event is calculated respectively based on the wind direction turning values corresponding to all sand messages in each sand process event so as to determine the dominant wind direction of each sand process, so that the subsequent areas which can be influenced or swept by the sand process can be prepared and prevented in advance based on the dominant wind direction; in the sand and dust process, the influence on the swept area is larger when the wind speed is larger, when key characteristics of the sand and dust process are extracted in the sand and dust process, the characteristic value of the minimum wind speed, the characteristic value of the maximum wind speed and the characteristic value of the average wind speed of each sand and dust process event are calculated respectively based on the conversion values of the wind speeds corresponding to all sand and dust messages in each sand and dust process event, and the type of the sand and dust process can be conveniently analyzed in the follow-up weather through the average wind speed. By extracting and analyzing the key features of the dust process according to the dust message corresponding to the dust process, the process key features and the feature values of the dust process are obtained, and meanwhile, the duration, the severity, the influence area and the like of the dust process are reflected through the process key features and the feature values of the process key features, so that the forthcoming dust process can be predicted based on the historical process key features and the historical feature values of the dust process.
Next to the foregoing embodiments of the present application, an embodiment of the present application provides a method for analyzing data of a dust and sand process, further including: and storing the dust message, the process key characteristics and the characteristic values of the dust messages corresponding to each dust process in the total dust process number into a dust process database. For example, after the meta message of the airport a in the preset historical time period T is analyzed for the dust and sand process, and the analysis of the dust and sand process and the extraction of the process key features are performed based on the dust and sand message, each of the dust and sand process events 1, the dust and sand process event2, the dust and sand process events 3, … …, the dust and sand process event (r-1), and the dust and sand process event (r) in the total number of dust and sand processes ss _ num included in the meta message of the airport a in the preset historical time period T is stored in the dust and sand process database, wherein the process key features and feature values corresponding to each dust and sand process are denoted as ss _ wx, so that the following dust and sand process related data (such as the dust and sand process key information corresponding to the dust process) can be used for dust forecast, and a convenient and fast weather condition can be created for the following specific analysis, the specific analysis and prediction of the dust and sand process can be rapidly carried out aiming at the specific process.
Next to the foregoing embodiments of the present application, an embodiment of the present application provides a method for analyzing data of a dust and sand process, further including:
acquiring a real-time METAR message of the target airport in the current time period; here, the value of the current time period is any time interval.
Analyzing the real-time METAR message based on the dust and sand process database to obtain dust and sand forecast information corresponding to the target airport, wherein the dust and sand forecast information comprises a predicted value of the process key feature.
For example, in the prediction process of the actual sand weather, the real-time METAR message of the target airport in the current time period is firstly acquired, and combines the historical dust and sand process in the dust and sand process database, the key characteristics of the process, the characteristic values of the key characteristics and the like, carrying out dust process analysis on the real-time METAR message of the target airport in the current time period, obtaining the forecast information of the dust corresponding to the target airport, such as the forecast value of the lowest visibility, the forecast value of the duration, the forecast value of the main wind direction and the forecast value of the minimum wind degree of the forecast dust process, which are used for reflecting the influence duration, the possible influence area direction and the severity, etc. of the forecast dust process, therefore, in an actual application scene, the method can be used for instantly predicting and preventing the sand-dust weather which may appear in the target airport, so that the safety measures of the target airport in the sand-dust weather are ensured.
As shown in fig. 2, another aspect of the present application provides a schematic structural diagram of a data analysis apparatus for a dust and sand process, the apparatus includes an obtaining device 11, a preprocessing device 12, a dust and sand process determining device 13, and a feature extracting device 14, wherein,
the acquiring device 11 is used for acquiring an aviation routine weather report METAR message of a target airport in a preset historical time period. Here, the preset historical event period includes, but is not limited to, any historical time period T. For example, the meta message and its listed data in a preset historical time period T of an airport (such as airport a) include, but are not limited to, airport four-character codes, the release time of the message, wind direction, wind speed, dominant visibility, runway visibility, weather phenomena, cloud height, temperature, dew point temperature, air pressure, and trend item/RM remark item.
The preprocessing device 12 is configured to perform preprocessing and screening on the meta message, to obtain at least two dust messages, a message key feature of each dust message, and a conversion value thereof, and to implement screening of the dust messages and extraction of the message key feature reflected by each dust message.
A dust and sand process determining device 13, configured to perform dust and sand process analysis on the at least two dust and sand messages based on the message key features and the conversion values thereof, to obtain a dust and sand message corresponding to each dust and sand process corresponding to the meta message;
and the feature extraction device 14 is configured to perform sand-dust process key feature extraction on the sand-dust messages corresponding to each sand-dust process, respectively, to obtain a process key feature corresponding to each sand-dust process and a feature value thereof.
Through the acquiring device 11, the preprocessing device 12, the dust and sand process determining device 13 and the feature extracting device 14, data analysis is performed on historical aviation routine weather report messages of the airport to analyze the dust and sand processes, the dust and sand messages corresponding to each historical dust and sand process, and the process key features and feature values thereof reflected by the dust and sand messages corresponding to each dust and sand process, so that the process key features and feature values of each analyzed dust and sand process are extracted while the big data analysis on the historical aviation routine weather report messages is realized, and the process key features and feature values of each analyzed dust and sand process are convenient to predict the dust and sand weather of the airport efficiently and conveniently.
It should be noted that the content executed by the acquiring device 11, the preprocessing device 12, the dust and sand process determining device 13, and the feature extracting device 14 is the same as or corresponding to the content executed in the above step S11, step S12, step S13, and step S14, and for brevity, the description thereof is omitted.
According to another aspect of the present application, there is also provided a computer readable medium having stored thereon computer readable instructions, which, when executed by a processor, cause the processor to implement the data analysis method of the dust and sand process as described above.
According to another aspect of the present application, there is also provided a data analysis apparatus for a dust and sand process, the apparatus comprising:
one or more processors;
a computer-readable medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement a data analysis method as described above for the dust and sand process.
In summary, the method includes the steps that an aviation routine weather report METAR message of a target airport in a preset historical time period is obtained; then preprocessing the METAR messages and screening the dust messages to obtain at least two dust messages, and message key characteristics and conversion values of each dust message; then, based on the message key features and the conversion values thereof, carrying out dust and sand process analysis on the at least two dust and sand messages to obtain the dust and sand message corresponding to each dust and sand process corresponding to the METAR message; and respectively extracting the key features of the dust and sand process from the dust and sand message corresponding to the dust and sand process each time to obtain the key features and the feature values of the process corresponding to the dust and sand process each time. According to the method and the device, the sand-dust process, the sand-dust messages corresponding to each historical sand-dust process and the process key features and the feature values of the sand-dust messages corresponding to each sand-dust process are analyzed through data analysis of the historical aviation routine weather report messages of the airport, the analyzed process key features and the analyzed feature values of each sand-dust process are extracted while the big data analysis of the historical aviation routine weather report messages is achieved, the process key features and the analyzed feature values of each sand-dust process are convenient to conduct the follow-up prediction of the sand-dust weather of the airport based on the process key features and the analyzed feature values of the historical sand-dust process, and the sand-dust weather of the airport can be efficiently and conveniently predicted.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to at least two embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. At least two units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (10)
1. A method of data analysis of a dust and sand process, wherein the method comprises:
acquiring an aviation routine weather report METAR message of a target airport in a preset historical time period;
preprocessing the METAR messages and screening the dust messages to obtain at least two dust messages, and message key characteristics and conversion values of each dust message;
analyzing the dust and sand process of the at least two dust and sand messages based on the message key characteristics and the conversion values thereof to obtain the dust and sand message corresponding to each dust and sand process corresponding to the METAR message;
and respectively extracting the key features of the dust and sand process from the dust and sand message corresponding to the dust and sand process each time to obtain the key features and the feature values of the process corresponding to the dust and sand process each time.
2. The method according to claim 1, wherein the preprocessing and the screening of the meta message to obtain at least two dust messages and a message key feature and a conversion value thereof of each dust message comprise:
extracting key features of the METAR message to obtain message key features and feature values corresponding to the METAR message;
according to a preset METAR message editing and sending rule, converting the characteristic value of the message key characteristic corresponding to the METAR message to obtain a conversion value of the message key characteristic corresponding to the METAR message;
and screening the METAR messages based on the key message characteristics and the conversion values thereof corresponding to the METAR messages to obtain at least two dust messages.
3. The method according to claim 2, wherein the screening of the meta message for the dust-sand messages based on the message key features and the conversion values thereof corresponding to the meta message to obtain at least two dust-sand messages comprises:
judging whether the conversion values of the key features of the message corresponding to the METAR message meet a first preset condition and a second preset condition,
if so, determining the corresponding METAR message as a dust message when both the first preset condition and the second preset condition are met, so as to obtain at least two dust messages;
the first preset condition comprises that a conversion value of a message key feature corresponding to the METAR message contains relevant information for indicating a sand weather phenomenon;
the second preset condition comprises that the conversion value of the key features of the message corresponding to the METAR message is within a preset dominant visibility range.
4. The method according to claim 1, wherein the analyzing the at least two dust messages for the dust process based on the key feature of the message and the conversion value thereof to obtain the dust message corresponding to each dust process corresponding to the meta message comprises:
respectively calculating the release time difference of each two adjacent dust messages;
and performing the following steps on the release time of each two adjacent dust messages to obtain the total number of the dust and sand processes corresponding to the METAR message and the dust and sand message corresponding to each dust and sand process:
judging whether the issuing time difference is larger than a preset time difference threshold value or not,
if not, recording two adjacent dust messages corresponding to the release time difference as the dust messages in the same dust process;
if so, recording two adjacent sand-dust messages corresponding to the release time difference as different sand-dust processes, recording a previous sand-dust message in the two adjacent sand-dust messages corresponding to the release time difference as a last sand-dust message in the current sand-dust process, and recording a next sand-dust message in the two adjacent sand-dust messages corresponding to the release time difference as a first sand-dust message in the next sand-dust process.
5. The method of any one of claims 1 to 4, wherein the message key features include release time, wind direction, wind speed, prevailing visibility, and weather phenomenon, and the process key features include duration, prevailing wind direction, minimum wind speed, maximum wind speed, average wind speed, and minimum visibility;
the method for extracting the key features of the dust process from the dust messages corresponding to the dust process at each time respectively to obtain the key features and the feature values of the process corresponding to the dust process at each time comprises the following steps:
calculating a characteristic value of the duration of each dust and sand process based on the release time corresponding to the first dust and sand message and the release time of the last dust and sand message in each dust and sand process respectively;
calculating a characteristic value of minimum visibility in each dust and sand process based on the conversion values of the corresponding dominant visibility of all the dust and sand messages in each dust and sand process;
respectively calculating a characteristic value of a dominant wind direction of each dust and sand process based on the wind direction turning values corresponding to all the dust and sand messages in each dust and sand process;
and respectively calculating the characteristic value of the minimum wind speed, the characteristic value of the maximum wind speed and the characteristic value of the average wind speed in each dust-proof process based on the conversion values of the wind speeds corresponding to all the dust messages in each dust-proof process.
6. The method of claim 1, wherein the method further comprises:
and storing the dust message, the process key characteristics and the characteristic values of the dust messages corresponding to each dust process in the total dust process number into a dust process database.
7. The method of claim 6, wherein the method further comprises:
acquiring a real-time METAR message of the target airport in the current time period;
analyzing the real-time METAR message based on the dust and sand process database to obtain dust and sand forecast information corresponding to the target airport, wherein the dust and sand forecast information comprises a predicted value of the process key feature.
8. A data analysis apparatus for a dust and sand process, wherein the apparatus comprises:
the acquiring device is used for acquiring an aviation routine weather report METAR message of a target airport in a preset historical time period;
the preprocessing device is used for preprocessing the METAR message and screening the dust message to obtain at least two dust messages, and the message key characteristics and the conversion values of each dust message;
a dust and sand process determining device, configured to perform dust and sand process analysis on the at least two dust and sand messages based on the message key features and the conversion values thereof, to obtain a dust and sand message corresponding to each dust and sand process corresponding to the meta message;
and the characteristic extraction device is used for respectively extracting the key characteristics of the dust and sand process from the dust and sand message corresponding to the dust and sand process each time to obtain the key characteristics of the process corresponding to the dust and sand process each time and the characteristic value of the key characteristics.
9. A computer readable medium having computer readable instructions stored thereon, which when executed by a processor, cause the processor to implement the method of any one of claims 1 to 7.
10. A data analysis apparatus for a dust and sand process, the apparatus comprising:
one or more processors;
a computer-readable medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
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