CN116244265B - Processing method and device for marine weather numerical forecasting product and electronic equipment - Google Patents
Processing method and device for marine weather numerical forecasting product and electronic equipment Download PDFInfo
- Publication number
- CN116244265B CN116244265B CN202310214711.8A CN202310214711A CN116244265B CN 116244265 B CN116244265 B CN 116244265B CN 202310214711 A CN202310214711 A CN 202310214711A CN 116244265 B CN116244265 B CN 116244265B
- Authority
- CN
- China
- Prior art keywords
- product
- numerical
- numerical forecasting
- user
- forecasting
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/17—Details of further file system functions
- G06F16/174—Redundancy elimination performed by the file system
- G06F16/1744—Redundancy elimination performed by the file system using compression, e.g. sparse files
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/12—Use of codes for handling textual entities
- G06F40/126—Character encoding
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention discloses a processing method, a device and electronic equipment of a marine weather numerical forecasting product, which effectively reduce the workload of subsequent data coding processing by preprocessing the marine weather numerical forecasting product according to the user requirements. The conversion from the adoption of floating point number matrix expression to the adoption of character string expression of the numerical forecasting product is realized by carrying out coding treatment on the numerical forecasting product after pretreatment, and a foundation is laid for the better compression effect of the subsequent compression treatment. And determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product, and selecting a compression algorithm with the best compression ratio. And compressing the target numerical forecast product by using an optimal compression algorithm, so that the storage space occupied by the file can be effectively reduced. Therefore, the bandwidth occupied by the numerical forecasting product in transmission is greatly reduced, and the communication cost of the numerical forecasting product is effectively reduced.
Description
Technical Field
The invention relates to the technical field of marine weather forecast, in particular to a processing method and device of a marine weather numerical forecast product and electronic equipment.
Background
The numerical forecasting is widely applied to the field of marine weather forecasting at present, and is a technical means for forecasting the change and development of future marine meteorological elements according to the current marine atmospheric state by using an atmospheric and marine mathematical model. In order to study different scientific problems, different numerical forecasting modes such as a sea wave mode, a storm tide mode, a circulation mode, an atmosphere mode and the like are established aiming at the subdivision field with emphasis. The output prediction result of the numerical prediction mode may be called a numerical prediction product, which is a time-varying result of a prediction element (such as sea surface wind, temperature, effective wave height, etc.), and is usually stored or expressed in an array.
With the continuous improvement of the ocean atmosphere forecasting requirement, the numerical forecasting products are greatly improved in time and space resolution, correspondingly, the storage space occupied by the files is also continuously increased, and the organization, transmission and use of the data are adversely affected by the oversized data files. This adverse effect can be particularly pronounced in situations where data transmission is limited, such as in weather navigation during ocean going of a ship. In the scene, two-way communication is needed between the ship and the command center, the ship gives out an expected route or position request, the command center gives out a numerical prediction product of the marine weather and transmits the numerical prediction product in a satellite communication mode, but the numerical prediction product is limited by communication bandwidth, and the marine weather numerical prediction product with larger data volume cannot be transmitted in a commercial scene because the occupied bandwidth is generated, and higher communication cost is generated.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a processing method and device for a marine weather numerical forecasting product and electronic equipment.
According to one aspect of the present invention, there is provided a method of processing a marine weather numerical forecast product, comprising: preprocessing a numerical forecasting product of the marine weather according to the requirement of a user, wherein the numerical forecasting product is expressed by adopting a floating point matrix; encoding the pretreated numerical forecasting product to obtain a target numerical forecasting product expressed by a character string; determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product; and compressing the target numerical forecast product by using the optimal compression algorithm to obtain a corresponding compressed file.
Preferably, the processing method of the marine weather numerical forecasting product further comprises the following steps: the user requirements are obtained, wherein the user requirements comprise communication bandwidth, forecast elements, spatial extent and resolution of the user request.
Preferably, the preprocessing of the numerical forecasting product of the marine weather according to the user demand includes: determining coverage space and storage space of a baseline product that is the same as the resolution requested by the user, wherein the baseline product is a standardized numerical forecast product; determining a coverage space of an external rectangle formed by the space range of the user request; determining a first coefficient between the user demand and the numerical forecast product based on the coverage space and storage space of the baseline product and the coverage space of the circumscribed rectangle; and preprocessing the numerical forecasting product of the marine weather according to a first coefficient between the user demand and the numerical forecasting product.
Preferably, the determining the first coefficient between the user demand and the numerical forecast product based on the coverage space and the storage space of the baseline product and the coverage space of the circumscribed rectangle includes: calculating a first coefficient P between the user demand and the numerical forecasting product based on the coverage space and the storage space of the baseline product and the coverage space of the external rectangle by the following formula t ：
Wherein a is a coefficient which takes a value according to the position of the user, M is a theoretical value of the communication bandwidth requested by the user, C b And A is the storage space of the baseline product, and C is the coverage space of the circumscribed rectangle.
Preferably, the preprocessing of the marine weather numerical forecasting product according to the first coefficient between the user demand and the numerical forecasting product includes: when P t When the value is not less than 1 after being rounded down, according to P t The value is divided into blocks to obtain a standardized single-element numerical forecasting product, wherein the standardized single-element numerical forecasting product is a numerical forecasting product containing a plurality of forecasting ageing values in a whole space range, and the number of the forecasting ageing values is equal to P t The values are the same; when P t And when the value is smaller than 1 after being rounded down, calculating a second coefficient between the communication bandwidth requested by the user and the storage space of the baseline product, and carrying out block processing on the numerical forecasting product according to the value of the second coefficient.
Preferably, the encoding processing is performed on the preprocessed numerical forecasting product to obtain a target numerical forecasting product expressed by a character string, including: acquiring the matrix shape of a floating point number matrix of the pretreated numerical forecasting product; converting the floating point number matrix into a one-dimensional matrix based on the matrix shape, and converting the one-dimensional matrix into a list; and determining the number of bits of the reserved decimal, and converting each numerical value in the list into a character string based on the number of bits to obtain a target numerical forecast product expressed by the character string.
Preferably, the processing method of the marine weather numerical forecasting product further comprises the following steps: reading header information of the compressed file, wherein the header information comprises an enumeration value of the optimal compression algorithm and configuration information of encoding processing; determining a corresponding decompression algorithm according to the enumeration value of the optimal compression algorithm; decompressing the compressed file by using the decompression algorithm to obtain a corresponding character string; and based on the configuration information, encoding the obtained character string to obtain a target numerical forecast product expressed by adopting a floating point number matrix.
According to another aspect of the present invention, there is provided a processing apparatus for marine weather numerical forecasting products, comprising: the preprocessing module is used for preprocessing a numerical forecasting product of the marine weather according to the requirement of a user, wherein the numerical forecasting product is expressed by adopting a floating point matrix; the coding module is used for coding the preprocessed numerical forecasting product to obtain a target numerical forecasting product expressed by a character string; the algorithm determining module is used for determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product; and the compression module is used for compressing the target numerical forecast product by utilizing the optimal compression algorithm to obtain a corresponding compressed file.
According to a further aspect of the present invention there is provided a computer readable storage medium storing a computer program for performing the method according to any one of the above aspects of the present invention.
According to still another aspect of the present invention, there is provided an electronic device including: a processor; a memory for storing the processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any of the above aspects of the present invention.
Therefore, the invention effectively reduces the workload of the subsequent data coding processing by preprocessing the numerical forecasting product of the marine weather according to the user demand. The conversion from the adoption of floating point number matrix expression to the adoption of character string expression of the numerical forecasting product is realized by carrying out coding treatment on the numerical forecasting product after pretreatment, and a foundation is laid for the better compression effect of the subsequent compression treatment. And determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product, and selecting a compression algorithm with the best compression ratio. And compressing the target numerical forecast product by using an optimal compression algorithm to obtain a corresponding compressed file, so that the storage space occupied by the file can be effectively reduced. Therefore, the bandwidth occupied by the numerical forecasting product in transmission is greatly reduced, and the communication cost of the numerical forecasting product is effectively reduced.
Drawings
Exemplary embodiments of the present invention may be more completely understood in consideration of the following drawings:
FIG. 1 is a flow chart of a method of processing a marine weather forecast product, according to an exemplary embodiment of the present invention;
FIG. 2 is a schematic diagram of a processing device for marine weather numerical forecasting products according to an exemplary embodiment of the present invention;
fig. 3 is a structure of an electronic device provided in an exemplary embodiment of the present invention.
Detailed Description
Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present invention and not all embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein.
It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
It will be appreciated by those of skill in the art that the terms "first," "second," etc. in embodiments of the present invention are used merely to distinguish between different steps, devices or modules, etc., and do not represent any particular technical meaning nor necessarily logical order between them.
It should also be understood that in embodiments of the present invention, "plurality" may refer to two or more, and "at least one" may refer to one, two or more.
It should also be appreciated that any component, data, or structure referred to in an embodiment of the invention may be generally understood as one or more without explicit limitation or the contrary in the context.
In addition, the term "and/or" in the present invention is merely an association relationship describing the association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In the present invention, the character "/" generally indicates that the front and rear related objects are an or relationship.
It should also be understood that the description of the embodiments of the present invention emphasizes the differences between the embodiments, and that the same or similar features may be referred to each other, and for brevity, will not be described in detail.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the techniques, methods, and apparatus should be considered part of the specification.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Embodiments of the invention are operational with numerous other general purpose or special purpose computing system environments or configurations with electronic devices, such as communications terminals, computer systems, servers, etc. Examples of well known communication terminals, computing systems, environments, and/or configurations that may be suitable for use with electronic devices, such as communication terminals, computer systems, servers, and the like, include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the foregoing, and the like.
Electronic devices such as communication terminals, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
Exemplary method
In the embodiment of the invention, the marine weather guarantee product for navigation is a regular grid product, and the marine weather numerical forecast product comprises a plurality of forecast elements such as effective wave height, maximum wave height, average wave period, average wave direction, sea surface wind and the like. In general, each forecasting element is a file, in which the forecasting results of the forecasting element are stored and organized in a matrix. Since the prediction of a plurality of future moments is included, the data is usually a three-dimensional array [ time, lat, lon ], that is, the prediction element is generally composed of a longitude, latitude and time 3-dimensional array, and the data volume of the prediction element increases rapidly along with the improvement of the spatial resolution and the time resolution. Taking the sea wave numerical forecasting product (effective wave height) as an example and taking the global numerical forecasting mode as an example, the spatial range of the sea wave numerical forecasting product comprises 180 latitude, 360 longitude and 180 degrees multiplied by 360 degrees, and if the spatial resolution is 0.1 degrees and the forecasting ageing is 120 hours, the array dimension is 777.6 thousands of effective wave height forecasting values. The above data is only a single element, and in the case of multiple elements, such as reconsidering the forecast aging (time resolution) and multiple forecast elements, the amount of data will be multiplied by a multiplier.
In the ocean vessel weather navigation scenario, data communication is generally performed with a shore base through satellites. When the ship sails in the ocean, the position of the ship is closely related to the communication transmission effect of the marine satellite, and if the ship sails in the ocean, the satellite communication effect is good on the whole in the northern hemisphere, and when the ship sails in the southern hemisphere is at high latitude, the satellite communication effect is greatly reduced. In ocean oceanographic marine meteorological guarantee work, the hydrological meteorological guarantee products need to be obtained from a shore base, and the variety of the products is guaranteed, such as a forecast graph, a grid numerical forecast product and the like. The product aimed by the invention is a hydrological lattice-point numerical forecasting product. Limited by satellite communication conditions, the method can occupy a long time when receiving a large data volume file in the ocean, and further influence other communication services on the ship, so that the data volume is reduced as much as possible and the communication time is shortened under the condition of ensuring the normal application of the marine weather navigation service through reasonable design.
FIG. 1 is a flow chart of a method for processing a marine weather forecast product, according to an exemplary embodiment of the present invention. The method for processing the marine weather numerical forecast product can be applied to a communication terminal, as shown in fig. 1, and comprises the following steps:
Step S101: and preprocessing a numerical forecasting product of the marine weather according to the user requirement, wherein the numerical forecasting product is expressed by adopting a floating point matrix.
Preferably, the processing method of the marine weather numerical forecasting product further comprises the following steps: the user requirements are obtained, wherein the user requirements comprise communication bandwidth, forecast elements, spatial extent and resolution of the user request.
Specifically, in ocean weather navigation, the communication condition of a single ship is affected by various conditions such as the communication facilities and the sea locations. In general, the calculation standard is 3/5 of the communication bandwidth of the ship receiving data, and the constraint condition is that the transmission is completed in a single file second.
Normally, marine meteorological elements for sailing support include wind, wave, current and the like, and in practical application, the elements are stored in different files and are distinguished by element identification in file names. Therefore, the prediction aging, the spatial region and the resolution in the single-element file need to be self-adaptively organized, and correspond to the three-dimensional array.
In order to better develop organization (or partitioning) of single element documents, standardized numerical forecasting products need to be predefined as baseline products, and experiments are developed. The following will take two experimental results for the same spatial range but two different resolutions as examples. Baseline product 1: the single element single forecast time effect, the geographical space is 5 degree multiplied by 5 degree, the resolution is 0.125 degree, after forecast field character conversion coding and compression treatment, the product is about 3.65-4.43kb interval. Baseline product 2: the single element single forecast time effect, the geographical space is 5 degree multiplied by 5 degree, the resolution is 0.25 degree, and the forecast field character conversion coding and compression treatment are carried out to the product within the interval of about 1.21-1.32 kb.
The preprocessing is finally to determine the transmitted standardized single-element numerical forecasting product (determining the whole space or baseline product combination and determining the single-time effect or multiple-time effect combination), so that the communication bandwidth, forecasting elements, space range and resolution of the user request are required to be acquired, and data support is provided for the subsequent preprocessing.
Preferably, the preprocessing of the numerical forecasting product of the marine weather according to the user demand includes: determining coverage space and storage space of a baseline product that is the same as the resolution requested by the user, wherein the baseline product is a standardized numerical forecast product; determining a coverage space of an external rectangle formed by the space range of the user request; determining a first coefficient between the user demand and the numerical forecast product based on the coverage space and storage space of the baseline product and the coverage space of the circumscribed rectangle; and preprocessing the numerical forecasting product of the marine weather according to a first coefficient between the user demand and the numerical forecasting product.
Specifically, the result of the adaptive processing is prioritized to directly cover the spatial range of the request, so that the storage space occupied by the baseline product with the same resolution is searched according to the resolution of the user request, and the coverage space of the baseline product is set as C b The storage space is A, the A value is the upper limit value of the experimental range and is rounded up, such as 4.4kb or 4.6kb to 5kb. Let the space range of the user request be the longitude and latitude of the left lower point and the right upper point, and respectively make rounding processing for the coordinates of the left lower point and the right upper point to form an external rectangle (Bounding Box), and let the coverage space of the external rectangle be C. Further, based on C b And A and C, determining a first coefficient between the user demand and the numerical forecasting product, and finally preprocessing the numerical forecasting product of the marine weather according to the first coefficient.
Preferably, the determining the first coefficient between the user demand and the numerical forecast product based on the coverage space and the storage space of the baseline product and the coverage space of the circumscribed rectangle includes: calculating a first coefficient P between the user demand and the numerical forecasting product based on the coverage space and the storage space of the baseline product and the coverage space of the external rectangle by the following formula t ：
Wherein a is a coefficient which takes a value according to the position of the user, M is a theoretical value of the communication bandwidth requested by the user, C b Is the coverage space of the baseline product, A is the storage space of the baseline product, and C is the And (5) circumscribing a rectangular coverage space.
Specifically, a first coefficient P between the user's demand and the numerical forecasting product is calculated as follows t And according to the calculated first coefficient, carrying out corresponding pretreatment (block treatment) on the numerical forecast product of the marine weather:
wherein a is a coefficient, and the range is [0.9-0.98 ] according to the position of the user]M is the theoretical value of the communication bandwidth requested by the user, C b And A is the storage space of the baseline product, and C is the coverage space of the circumscribed rectangle.
The value of a needs to be determined according to the communication position, for example, in the arctic region of high latitude, even if maritime satellite communication is used, the communication capability is still limited to be relatively large, so that the general value can be relatively close to the upper limit, such as about 0.98. In a region with good communication conditions, such as a pacific region of a mid-latitude, the value is about 0.9.
Preferably, the preprocessing of the marine weather numerical forecasting product according to the first coefficient between the user demand and the numerical forecasting product includes: when P t When the value is not less than 1 after being rounded down, according to P t The value is divided into blocks to obtain a standardized single-element numerical forecasting product, wherein the standardized single-element numerical forecasting product is a numerical forecasting product containing a plurality of forecasting ageing values in a whole space range, and the number of the forecasting ageing values is equal to P t The values are the same; when P t And when the value is smaller than 1 after being rounded down, calculating a second coefficient between the communication bandwidth requested by the user and the storage space of the baseline product, and carrying out block processing on the numerical forecasting product according to the value of the second coefficient.
Specifically, if P t The value is equal to or greater than 1 after being rounded down, and the user bandwidthNumerical forecasting products supporting direct transmission of requested spatial range (single element single aging, P t The values being simultaneously predictive ageing values which can be combined in a single element, e.g. P t And if the value is 3 downwards, the self-adaptive block processing result of the user is that the numerical forecasting product of the standardized single element is a numerical forecasting product containing 3 forecasting timeouts of the whole space range. Judging that the branching condition is finished); m is a theoretical value of the communication bandwidth of the user, such as 200K/s.
If P t When the value is rounded to 0, it indicates that the user bandwidth does not support the forecast product of directly sending the request space range, so the multi-file combination of sending the baseline product is converted (i.e. the user space range is formed by combining a plurality of baseline products, and the subsequent judgment can be combined if the user space range is aged). Then, a second coefficient of the user bandwidth and the size of the storage space of the baseline product is calculated and set as P b The method is calculated according to the following formula:
wherein a is a coefficient, and the range is between 0.9 and 0.98 according to the position of the user.
Calculated P by the method b Rounding downwards, and if the value is greater than or equal to 1, forecasting ageing in the single-element forecasting product is the value; if the value is 0, it indicates that the request bandwidth is smaller than the baseline forecast product, and the forecast product with the next level of spatial resolution (lower spatial resolution) is provided for the user, and the blocking mode is the same as the blocking mode and is not described in detail.
Combining the elements, the combination of baseline forecast products, all forecast aging values for one forecast, a series of standardized single element numerical forecast products (distinguished by file naming) will be formed, and these files will be used for subsequent encoding processes.
Step S102: and carrying out coding treatment on the pretreated numerical forecasting product to obtain a target numerical forecasting product expressed by a character string.
Preferably, the encoding processing is performed on the preprocessed numerical forecasting product to obtain a target numerical forecasting product expressed by a character string, including: acquiring the matrix shape of a floating point number matrix of the pretreated numerical forecasting product; converting the floating point number matrix into a one-dimensional matrix based on the matrix shape, and converting the one-dimensional matrix into a list; and determining the number of bits of the reserved decimal, and converting each numerical value in the list into a character string based on the number of bits to obtain a target numerical forecast product expressed by the character string.
Specifically, the result output by the numerical prediction mode is typically stored as floating point data, and includes at least 8 decimal places, but decimal places do not necessarily represent higher data accuracy, and noise may be mixed in. In marine vessel voyage security in the ocean, different decimal place retaining schemes (generally 1-3 places are reserved) are adopted for different forecasting elements. For the effective wave height element, 2-bit decimal is reserved generally to meet the requirement. The decimal place reservation can be cut off or rounded off.
The numerical forecasting product of the marine weather is the state change of the marine atmosphere in a future period calculated through power mode simulation, and the numerical forecasting product has a certain change rule. If the sea area is affected by the cyclone, the sea area without the influence of the weather system is always calm. Oceanography belongs to the field of geography, and also obeys the basic law of geography, namely anything is related to other things, but things which are close in space are more closely related. From this point of view, the element value at a certain spatial position can be expressed by the element value and the offset of the similar position:
y loc ＝y neighbourhood +delta
wherein y is loc For a value of an element at a certain location (which in a particular implementation can be understood as the effective wave height), y neighbourhood Is y and y loc The element values adjacent to each other at the positions, delta is the difference (also called offset) between the two.
Based on this idea, data compression can be performed, and only the offset representation is encoded except for the first position where the complete element value needs to be encoded. The adjacent concepts in the above equation can be further extended.
Numerical forecasting products (also called forecasting fields) are converted from floating point number representation to ASC code character string representation, so that the aim is to have better compression effect in subsequent compression processing. Assuming that the Huffman coding compression mode is selected, statistics is carried out on the numerical value of the forecast field to be compressed, and coding processing is carried out according to the frequency of the numerical value. Taking the effective wave height as an example, reserving a decimal place, and assuming that the range [0.1-14.0] of the effective wave height in the area can appear, the maximum value can be 140 kinds, 0.1,0.2,0.3-14.0, and after conversion treatment, the forecasting field is expressed by ASC code character strings, and only 63 kinds (the value can be converted into character combination) of single characters can appear, so that the higher appearance frequency is necessarily existed in the character strings in a numerical mode; in addition, if other compression algorithms such as LZ series algorithm or PPMD algorithm, whether it is "sliding window" coding of LZ type algorithm or the manner of using partial matching of PPMD to use prediction of subsequent output, a principle of partial similarity is used, which is consistent with the idea of expressing and converting into characters by using offset amount above, a better compression effect will be obtained.
The specific steps of the numerical forecasting product from floating point number expression to character string expression are as follows:
firstly, acquiring the shape of a matrix, wherein if the matrix is 100 rows and 100 columns, the shape of the matrix is recorded as 100 x 100;
a second step of determining and converting reserved decimal places (units) into characters and recording the output corresponding character values (the character values are used for the reduction processing, the character strings are corresponding to the digits at the floating point number);
thirdly, converting the multidimensional matrix into a one-dimensional matrix (a flat operation), namely converting the original matrix of 100 x 100 into a matrix of 10000 x 1, and then converting the matrix into a list;
fourth, traversing the list to complete the character conversion process of each numerical value in the list (the step realizes the conversion of the numerical value into a character string)
Take one data as an illustration:
let the current value be data i ，data pre Being the leading value of the current value in the list, if it is the first value in the list, data pre ＝0
(1) Let diff calculate the difference between the two, diff=data i -data pre
(2) Converting the result of (1) into an integer, specifically processing:
according to the value of the reserved decimal point number units, diff is multiplied by 10 units Rounding after rounding. int (round (diff 10) units ))
(3) Converting the result of (2) into binary, and specifically processing:
If the input decimal value is greater than or equal to 0, converting decimal into binary value and shifting left by one bit; if the input decimal value is negative, the encoding is reversed:
(4) and (3) carrying out the following treatment on the result of the step (3):
splitting the binary system of the last step from the right side, forming each 5 binary values into a block (part less than 5 bits is discarded) to form a block sequence, then arranging the block sequence in a reverse order, processing the block sequence block by block according to the arrangement order (excluding the last block), performing OR operation on the binary system and the binary system value 100000 block by block, directly supplementing 0 in the high order of the binary system value of the last block of the sequence, and forming the block sequence of each 6 bits of binary system values after the processing.
(5) And (3) carrying out the following treatment on the result of the step (4):
and converting the binary value of each block sequence into an integer according to the block sequence, converting the integer +63 into a corresponding ASC code value to form a corresponding character string sequence, and completing the processing process of converting single data into characters.
The above is a processing procedure of one data in the list, and after the other data are processed by adopting a similar method, the character string value (ASC code mode expression) after all the data in the list are converted is generated.
Step S103: and determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product.
Specifically, various compression algorithms need to be tested on ASC code character strings of numerical forecasting products, and the result with the best compression ratio is selected. Specifically, after the above processing, the prediction element field is converted into a character string expression, which inevitably has the condition of repeated ASC codes, so that the existing compression algorithm can be adopted to compress the character string, and the algorithm with the best compression ratio is selected as the final result, and the algorithm participating in set comparison comprises LZMA2, bzip2, deflate, ZStandard, brotli and PPMd. The smaller and better CR is defined as the compression ratio, the formula isM C To predict field size after compression using some algorithm, M ASC To forecast the string size of the element field. After comparing the compression ratios of different algorithms, the code using the compression algorithm is recorded and used for decompression operation.
Step S104: and compressing the target numerical forecast product by using the optimal compression algorithm to obtain a corresponding compressed file.
Specifically, an optimal compression algorithm is utilized to compress a target numerical forecast product, a series of compressed files meeting the requirements are generated, and the head of each compressed file records the following information: the first row records the position of the left lower point of the regular grid and the spatial resolution of latitude and longitude; the second row records the starting time and time step of the time dimension (the situation of a plurality of forecast moments occurs); a third row records the matrix shape; the fourth row records the enumeration value of the selected character string compression algorithm; and a fifth line, recording the compressed forecast field value.
Preferably, the processing method of the marine weather numerical forecasting product further comprises the following steps: reading header information of the compressed file, wherein the header information comprises an enumeration value of the optimal compression algorithm and configuration information of encoding processing; determining a corresponding decompression algorithm according to the enumeration value of the optimal compression algorithm; decompressing the compressed file by using the decompression algorithm to obtain a corresponding character string; and based on the configuration information, encoding the obtained character string to obtain a target numerical forecast product expressed by adopting a floating point number matrix.
Specifically, the specific steps for decoding the compressed file are as follows:
firstly, reading head information, namely reading the head information of a file to obtain basic configuration information of a forecast field, such as spatial resolution of lower left position, latitude and longitude, and enumeration values of time dimension, step length, matrix shape and character string compression algorithm;
step two, character string decompression processing, namely, reading the tail part of the file from the fifth row in a binary stream mode at one time, determining a character string compression algorithm by using a corresponding enumeration value, and obtaining an ASC codeword string by using a corresponding decompression algorithm;
And thirdly, restoring the character string codes to a forecast field matrix, wherein the method comprises the following steps of:
setting a variable Index as a global variable (default value is 0) for the character string Index;
(1) and loading the character string obtained in the second step, taking the first character of the character string through an Index (in the case of Index being 0), subtracting 63 from the ASC code value of the character to obtain a value of reserved decimal number (units), and increasing the Index value by 1.
(2) All decoded values are stored in a list (the list is initialized to null) and the Last value is set to Last (default value is 0). When the Index value is smaller than the string length, performing decoding processing of the single numerical value in a circulating way (namely (3) restoring the single numerical value);
(3) let restore single value as Result (initialized to 1), shift right operation bit as Shift (initialized to 0). The loop process operates as follows (unless jumped out): obtaining a character string of Index (1 is increased when one Index is obtained), subtracting 63 from the ASC code value of the character string to obtain a value B, if the value B is smaller than 31, jumping out of a loop, otherwise, adding the value B to Result after shifting left by 5 bits, and increasing the Shift value by 5; when the circulation condition is out, judging whether the binary last bit of the B is 0, if so, shifting the Result by 1 bit to the right, and if not, reversing the Result and shifting the Result by 1 bit to the right. The result of the above processing is the return value of (3).
(4) And (3) setting the Last value in (2) to the sum of Last values of the return values after the processing in (3), and storing the values in the list in (2).
(5) And (3) processing according to the steps (2) - (4) to obtain an integer list stored in the step (2), setting each numerical value as data, processing the data according to the following formula, multiplying the data by the minus units power of 10, and rounding according to the units bit number to obtain a restored floating point value, wherein the calculation formula is as follows.
round((data*10 -units ),units)
After all processing is completed, a floating point number list is obtained.
(6) And restoring the floating point number list to a floating point matrix according to the matrix shape in the header information.
In summary, according to the invention, the workload of the subsequent data encoding processing is effectively reduced by preprocessing the numerical forecast product of the marine weather according to the user requirements. The conversion from the adoption of floating point number matrix expression to the adoption of character string expression of the numerical forecasting product is realized by carrying out coding treatment on the numerical forecasting product after pretreatment, and a foundation is laid for the better compression effect of the subsequent compression treatment. And determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product, and selecting a compression algorithm with the best compression ratio. And compressing the target numerical forecast product by using an optimal compression algorithm to obtain a corresponding compressed file, so that the storage space occupied by the file can be effectively reduced. Therefore, the bandwidth occupied by the numerical forecasting product in transmission is greatly reduced, and the communication cost of the numerical forecasting product is effectively reduced.
The processing method of the marine weather numerical forecast product can be applied to the marine satellite transmission communication scene, and can be used for carrying out operations such as data blocking (according to standardized single-element products), generalization processing, encoding compression and the like by organizing and processing numerical forecast data, so that the data compression ratio is improved, the storage space occupied by files is reduced, and the marine weather navigation service of ships is served. The method can be applied to different offshore communication scenes, such as receiving the numerical forecast data by the ship terminal through commercial narrow-band satellite broadcast (the narrow-band satellite broadcast bandwidth is insufficient, if a compression technology is not adopted, the transmission time is longer), receiving the numerical forecast data by the commercial ship through the maritime satellite (the transmission time is reduced after file compression, the cost is reduced), decompressing and restoring the data through terminal software after receiving the data, and being applied to the maritime weather navigation service, so that the compression method has higher practical value.
Exemplary apparatus
Fig. 2 is a schematic structural view of a processing device 200 for marine weather numerical forecasting products according to an exemplary embodiment of the present invention. As shown in fig. 2, the apparatus includes: the preprocessing module 210 is configured to preprocess a numerical forecasting product of the marine weather according to a user requirement, where the numerical forecasting product is expressed by adopting a floating point matrix; the encoding module 220 is configured to encode the preprocessed numerical forecasting product to obtain a target numerical forecasting product expressed by a character string; the algorithm determining module 230 is configured to determine, according to the string size of the target numerical forecast product, an optimal compression algorithm matching the target numerical forecast product from a preset compression algorithm set; and the compression module 240 is configured to perform compression processing on the target numerical forecast product by using the optimal compression algorithm, so as to obtain a corresponding compressed file.
Preferably, the processing device 200 of the marine weather numerical forecast product further comprises: and the acquisition module is used for acquiring the user requirements, wherein the user requirements comprise communication bandwidth, forecast elements, spatial range and resolution requested by the user.
Preferably, the preprocessing module 210 is specifically configured to: determining coverage space and storage space of a baseline product that is the same as the resolution requested by the user, wherein the baseline product is a standardized numerical forecast product; determining a coverage space of an external rectangle formed by the space range of the user request; determining a first coefficient between the user demand and the numerical forecast product based on the coverage space and storage space of the baseline product and the coverage space of the circumscribed rectangle; and preprocessing the numerical forecasting product of the marine weather according to a first coefficient between the user demand and the numerical forecasting product.
Preferably, the determining the first coefficient between the user demand and the numerical forecast product based on the coverage space and the storage space of the baseline product and the coverage space of the circumscribed rectangle includes: calculating a first coefficient P between the user demand and the numerical forecasting product based on the coverage space and the storage space of the baseline product and the coverage space of the external rectangle by the following formula t ：
Wherein a is a coefficient which takes a value according to the position of the user, M is a theoretical value of the communication bandwidth requested by the user, C b And A is the storage space of the baseline product, and C is the coverage space of the circumscribed rectangle.
Preferably, the preprocessing of the marine weather numerical forecasting product according to the first coefficient between the user demand and the numerical forecasting product includes: when P t When the value is not less than 1 after being rounded down, according to P t The value is divided into blocks to obtain a standardized single-element numerical forecasting product, wherein the standardized single-element numerical forecasting product is a numerical forecasting product containing a plurality of forecasting ageing values in a whole space range, and the number of the forecasting ageing values is equal to P t The values are the same; when P t And when the value is smaller than 1 after being rounded down, calculating a second coefficient between the communication bandwidth requested by the user and the storage space of the baseline product, and carrying out block processing on the numerical forecasting product according to the value of the second coefficient.
Preferably, the encoding module 220 is specifically configured to: acquiring the matrix shape of a floating point number matrix of the pretreated numerical forecasting product; converting the floating point number matrix into a one-dimensional matrix based on the matrix shape, and converting the one-dimensional matrix into a list; and determining the number of bits of the reserved decimal, and converting each numerical value in the list into a character string based on the number of bits to obtain a target numerical forecast product expressed by the character string.
Preferably, the processing device 200 of the marine weather forecast product further comprises a decompression module for performing the following steps: reading header information of the compressed file, wherein the header information comprises an enumeration value of the optimal compression algorithm and configuration information of encoding processing; determining a corresponding decompression algorithm according to the enumeration value of the optimal compression algorithm; decompressing the compressed file by using the decompression algorithm to obtain a corresponding character string; and based on the configuration information, encoding the obtained character string to obtain a target numerical forecast product expressed by adopting a floating point number matrix.
The processing device of the marine weather numerical forecasting product according to the embodiment of the present invention corresponds to the processing method of the marine weather numerical forecasting product according to another embodiment of the present invention, and will not be described herein.
Exemplary electronic device
Fig. 3 is a structure of an electronic device provided in an exemplary embodiment of the present invention. As shown in fig. 3, the electronic device 30 includes one or more processors 31 and memory 32.
The processor 31 may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
Memory 32 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by the processor 31 to implement the methods of the software programs of the various embodiments of the present invention described above and/or other desired functions. In one example, the electronic device may further include: an input device 33 and an output device 34, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
In addition, the input device 33 may also include, for example, a keyboard, a mouse, and the like.
The output device 34 can output various information to the outside. The output device 34 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device that are relevant to the present invention are shown in fig. 3 for simplicity, components such as buses, input/output interfaces, etc. being omitted. In addition, the electronic device may include any other suitable components depending on the particular application.
Exemplary computer program product and computer readable storage Medium
In addition to the methods and apparatus described above, embodiments of the invention may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform steps in a method according to various embodiments of the invention described in the "exemplary methods" section of this specification.
The computer program product may write program code for performing operations of embodiments of the present invention in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the invention may also be a computer-readable storage medium, having stored thereon computer program instructions, which when executed by a processor, cause the processor to perform steps in a method according to various embodiments of the invention described in the "exemplary method" section of the description above.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present invention have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present invention are merely examples and not intended to be limiting, and these advantages, benefits, effects, etc. are not to be considered as essential to the various embodiments of the present invention. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, as the invention is not necessarily limited to practice with the above described specific details.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The block diagrams of the devices, systems, apparatuses, systems according to the present invention are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, systems, apparatuses, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
The method and system of the present invention may be implemented in a number of ways. For example, the methods and systems of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
It is also noted that in the systems, devices and methods of the present invention, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered as equivalent aspects of the present invention. The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the invention. Thus, the present invention is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the invention to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (6)
1. A method of processing a marine weather numerical forecast product, comprising:
preprocessing a numerical forecasting product of the marine weather according to the requirement of a user, wherein the numerical forecasting product is expressed by adopting a floating point matrix;
before preprocessing the numerical forecasting product of the marine weather according to the user requirement, the method further comprises the following steps: acquiring the user demand, wherein the user demand comprises a communication bandwidth, a forecast element, a spatial range and a resolution of a user request;
the preprocessing of the numerical forecasting product of the marine weather according to the user demand comprises the following steps:
determining coverage space and storage space of a baseline product that is the same as the resolution requested by the user, wherein the baseline product is a standardized numerical forecast product;
determining a coverage space of an external rectangle formed by the space range of the user request;
Determining a first coefficient between the user demand and the numerical forecast product based on the coverage space and storage space of the baseline product and the coverage space of the circumscribed rectangle;
preprocessing the numerical forecasting product of the marine weather according to a first coefficient between the user demand and the numerical forecasting product;
the determining a first coefficient between the user demand and the numerical forecast product based on the coverage space and the storage space of the baseline product and the coverage space of the circumscribed rectangle includes:
calculating a first coefficient P between the user demand and the numerical forecasting product based on the coverage space and the storage space of the baseline product and the coverage space of the external rectangle by the following formula t ：
Wherein a is a coefficient which takes a value according to the position of the user, M is a theoretical value of the communication bandwidth requested by the user, C b The coverage space of the baseline product is A, the storage space of the baseline product is A, and C is the coverage space of the external rectangle;
the preprocessing of the marine weather numerical forecasting product according to the first coefficient between the user demand and the numerical forecasting product comprises the following steps:
When P t When the value is not less than 1 after being rounded down, according to P t The value is divided into blocks to obtain a standardized single-element numerical forecasting product, wherein the standardized single-element numerical forecasting product is a numerical forecasting product containing a plurality of forecasting ageing values in a whole space range, and the number of the forecasting ageing values is equal to P t The values are the same;
when P t When the value is smaller than 1 after being rounded downwards, calculating a second coefficient between the communication bandwidth requested by the user and the storage space of the baseline product, and carrying out block processing on the numerical forecasting product according to the value of the second coefficient;
encoding the pretreated numerical forecasting product to obtain a target numerical forecasting product expressed by a character string;
determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product;
and compressing the target numerical forecast product by using the optimal compression algorithm to obtain a corresponding compressed file.
2. The method according to claim 1, wherein the encoding the preprocessed numerical forecast product to obtain the target numerical forecast product expressed by the character string comprises:
Acquiring the matrix shape of a floating point number matrix of the pretreated numerical forecasting product;
converting the floating point number matrix into a one-dimensional matrix based on the matrix shape, and converting the one-dimensional matrix into a list;
and determining the number of bits of the reserved decimal, and converting each numerical value in the list into a character string based on the number of bits to obtain a target numerical forecast product expressed by the character string.
3. The method as recited in claim 1, further comprising:
reading header information of the compressed file, wherein the header information comprises an enumeration value of the optimal compression algorithm and configuration information of encoding processing;
determining a corresponding decompression algorithm according to the enumeration value of the optimal compression algorithm;
decompressing the compressed file by using the decompression algorithm to obtain a corresponding character string;
and based on the configuration information, encoding the obtained character string to obtain a target numerical forecast product expressed by adopting a floating point number matrix.
4. A processing device for marine weather numerical forecast products, comprising:
the preprocessing module is used for preprocessing a numerical forecasting product of the marine weather according to the requirement of a user, wherein the numerical forecasting product is expressed by adopting a floating point matrix;
Before preprocessing the numerical forecasting product of the marine weather according to the user requirement, the method further comprises the following steps: acquiring the user demand, wherein the user demand comprises a communication bandwidth, a forecast element, a spatial range and a resolution of a user request;
the preprocessing of the numerical forecasting product of the marine weather according to the user demand comprises the following steps:
determining coverage space and storage space of a baseline product that is the same as the resolution requested by the user, wherein the baseline product is a standardized numerical forecast product;
determining a coverage space of an external rectangle formed by the space range of the user request;
determining a first coefficient between the user demand and the numerical forecast product based on the coverage space and storage space of the baseline product and the coverage space of the circumscribed rectangle;
preprocessing the numerical forecasting product of the marine weather according to a first coefficient between the user demand and the numerical forecasting product;
the determining a first coefficient between the user demand and the numerical forecast product based on the coverage space and the storage space of the baseline product and the coverage space of the circumscribed rectangle includes:
Calculating a first coefficient P between the user demand and the numerical forecasting product based on the coverage space and the storage space of the baseline product and the coverage space of the external rectangle by the following formula t ：
Wherein a is a coefficient which takes a value according to the position of the user, M is a theoretical value of the communication bandwidth requested by the user, C b The coverage space of the baseline product is A, the storage space of the baseline product is A, and C is the coverage space of the external rectangle;
the preprocessing of the marine weather numerical forecasting product according to the first coefficient between the user demand and the numerical forecasting product comprises the following steps:
when P t When the value is not less than 1 after being rounded down, according to P t The value is divided into blocks to obtain a standardized single-element numerical forecasting product, wherein the standardized single-element numerical forecasting product is a numerical forecasting product containing a plurality of forecasting ageing values in a whole space range, and the number of the forecasting ageing values is equal to that of the number of the forecasting ageing values in the whole space rangeP t The values are the same;
when P t When the value is smaller than 1 after being rounded downwards, calculating a second coefficient between the communication bandwidth requested by the user and the storage space of the baseline product, and carrying out block processing on the numerical forecasting product according to the value of the second coefficient;
The coding module is used for coding the preprocessed numerical forecasting product to obtain a target numerical forecasting product expressed by a character string;
the algorithm determining module is used for determining an optimal compression algorithm matched with the target numerical forecasting product from a preset compression algorithm set according to the character string size of the target numerical forecasting product;
and the compression module is used for compressing the target numerical forecast product by utilizing the optimal compression algorithm to obtain a corresponding compressed file.
5. A computer readable storage medium storing a computer program for performing the method of any one of the preceding claims 1-3.
6. An electronic device, the electronic device comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method of any of the preceding claims 1-3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310214711.8A CN116244265B (en) | 2023-03-07 | 2023-03-07 | Processing method and device for marine weather numerical forecasting product and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310214711.8A CN116244265B (en) | 2023-03-07 | 2023-03-07 | Processing method and device for marine weather numerical forecasting product and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116244265A CN116244265A (en) | 2023-06-09 |
| CN116244265B true CN116244265B (en) | 2023-08-18 |
Family
ID=86629343
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310214711.8A Active CN116244265B (en) | 2023-03-07 | 2023-03-07 | Processing method and device for marine weather numerical forecasting product and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116244265B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116955460B (en) * | 2023-09-21 | 2023-12-05 | 国家海洋环境预报中心 | Method and device for generating ocean forecast information service product |
| CN117082474B (en) * | 2023-10-17 | 2024-02-02 | 国家海洋局北海预报中心((国家海洋局青岛海洋预报台)(国家海洋局青岛海洋环境监测中心站)) | System for acquiring marine environment forecast data in real time by scientific investigation ship |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2017203773A (en) * | 2016-05-10 | 2017-11-16 | 株式会社メテオテック・ラボ | Sea weather forecasting providing method |
| CN108681449A (en) * | 2018-05-17 | 2018-10-19 | 北京航空航天大学 | Digital satellite load information compresses multiple connection source code artificial intelligence Writing method |
| CN109656712A (en) * | 2018-11-29 | 2019-04-19 | 中国辐射防护研究院 | A kind of method and system for extracting GRIB code data |
| CN109981111A (en) * | 2019-03-28 | 2019-07-05 | 杭州即得科技有限公司 | A kind of method, apparatus and storage electronic equipment of data compression coding |
| CN112069141A (en) * | 2020-08-25 | 2020-12-11 | 广东华风海洋信息系统服务有限公司 | Special compression method for meteorological forecast lattice point data |
| CN112468154A (en) * | 2019-09-06 | 2021-03-09 | 广东华风海洋信息系统服务有限公司 | Data compression method suitable for visualization of oceanographic weather |
| CN114187369A (en) * | 2021-11-26 | 2022-03-15 | 南京信息工程大学 | Weather forecast data compression method based on video compression technology |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ATE493676T1 (en) * | 2003-04-17 | 2011-01-15 | Secr Defence | CORRECTION OF TROPOSPHERE-INDUCED ERRORS IN GLOBAL POSITIONING SYSTEMS |
-
2023
- 2023-03-07 CN CN202310214711.8A patent/CN116244265B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2017203773A (en) * | 2016-05-10 | 2017-11-16 | 株式会社メテオテック・ラボ | Sea weather forecasting providing method |
| CN108681449A (en) * | 2018-05-17 | 2018-10-19 | 北京航空航天大学 | Digital satellite load information compresses multiple connection source code artificial intelligence Writing method |
| CN109656712A (en) * | 2018-11-29 | 2019-04-19 | 中国辐射防护研究院 | A kind of method and system for extracting GRIB code data |
| CN109981111A (en) * | 2019-03-28 | 2019-07-05 | 杭州即得科技有限公司 | A kind of method, apparatus and storage electronic equipment of data compression coding |
| CN112468154A (en) * | 2019-09-06 | 2021-03-09 | 广东华风海洋信息系统服务有限公司 | Data compression method suitable for visualization of oceanographic weather |
| CN112069141A (en) * | 2020-08-25 | 2020-12-11 | 广东华风海洋信息系统服务有限公司 | Special compression method for meteorological forecast lattice point data |
| CN114187369A (en) * | 2021-11-26 | 2022-03-15 | 南京信息工程大学 | Weather forecast data compression method based on video compression technology |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116244265A (en) | 2023-06-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116244265B (en) | Processing method and device for marine weather numerical forecasting product and electronic equipment | |
| US11754685B2 (en) | Point cloud compression using a space filling curve for level of detail generation | |
| US10911787B2 (en) | Hierarchical point cloud compression | |
| US10853973B2 (en) | Point cloud compression using fixed-point numbers | |
| US11409998B2 (en) | Trimming search space for nearest neighbor determinations in point cloud compression | |
| US11895307B2 (en) | Block-based predictive coding for point cloud compression | |
| CN110572655B (en) | Method and equipment for encoding and decoding point cloud attribute based on neighbor weight parameter selection and transmission | |
| US7693337B2 (en) | Multi-mode alpha image processing | |
| USRE42186E1 (en) | Data transform processing apparatus and method | |
| EP2441049A2 (en) | Method for encoding/decoding a 3d mesh model that comprises one or more components | |
| US5444488A (en) | Method and apparatus for coding digital data using vector quantizing techniques | |
| US7965206B2 (en) | Apparatus and method of lossless coding and decoding | |
| Chuang et al. | Adaptive grayscale image coding scheme based on dynamic multi-grouping absolute moment block truncation coding | |
| Hu et al. | Efficient greyscale image compression technique based on vector quantization | |
| CN115102934A (en) | Point cloud data decoding method, encoding method, device, equipment and storage medium | |
| CN116648915A (en) | Point cloud encoding and decoding method, encoder, decoder and computer storage medium | |
| Wang et al. | A novel low bit rate side match vector quantization algorithm based on structed state codebook | |
| WO2024074123A1 (en) | Method, apparatus, and medium for point cloud coding | |
| US20210165764A1 (en) | Storage system including encoder | |
| WO2023198168A1 (en) | Method, apparatus, and medium for point cloud coding | |
| CN116170595A (en) | Original image processing method and device, electronic equipment and storage medium | |
| CN116233389A (en) | Point cloud coding processing method, point cloud decoding processing method and related equipment | |
| CN115880379A (en) | Semantic scalable image coding method, system, device and storage medium | |
| CN115474041A (en) | Point cloud attribute prediction method and device and related equipment | |
| CN114842108A (en) | Probability grid map processing method and device and storage device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |