A tide level data mutation point calibration method and a storage medium

Abstract

This invention relates to a method and storage medium for calibrating abrupt change points in tidal data. The method includes: acquiring tidal data within a preset time period; calculating the absolute value of the change between any two adjacent tidal data points; removing threshold values ​​from all calculated absolute values ​​to obtain the remaining absolute values; using the maximum value among the remaining absolute values ​​as the basis for determining the abrupt change points in all tidal data; interpolating the abrupt change points; sorting the interpolated tidal data according to time sequence, and then performing a fitting calculation based on a selected order to obtain the fitted tidal data. This method allows for the retrieval and calibration of abrupt change point data in tidal data, effectively reducing the workload of tidal data compilers and improving work efficiency.

Description

Technical Field

[0001] This application relates to the field of hydrological data compilation technology, specifically to a method for calibrating abrupt changes in tide level data and a storage medium. Background Technology

[0002] Hydrological data compilation is a crucial foundation for economic and social development and construction, playing an irreplaceable role in ensuring flood control, water supply, and ecological security, as well as in water conservancy projects, water resource management and protection, and ecological restoration. Tide level data compilation is a part of hydrological data compilation; however, in actual measurement work, telemetry-received tide level data is discrete. This fragmented data is not only difficult to process, but also makes it difficult to pinpoint its inherent patterns in data analysis. Furthermore, due to environmental challenges, tide level monitoring is difficult, and tide level monitoring data obtained from telemetry stations exhibits varying degrees of gaps and abrupt changes, affecting the completeness and validity of the data. Traditional compilation methods first identify key points of tide level change, then perform static analysis to determine the tide level curve after the identification process, which cannot guarantee data accuracy and is inefficient.

[0003] Existing methods for handling abrupt changes in tidal data include tidal level interpolation and historical similarity interpolation. The correlational tidal level interpolation method requires interpolating missing values ​​based on concurrent measured data and trends from the current station and neighboring stations (or upstream and downstream stations). The historical similarity interpolation method requires combining historical data from the current station and neighboring stations (or upstream and downstream stations) with historically similar processes to interpolate missing values. Both methods consume significant time and effort from staff, impacting work efficiency.

[0004] Using the relevant tide level interpolation method or the historical similarity process interpolation method requires a large number of data points for calculation, which places high demands on data acquisition and processing, and is subject to certain errors. Summary of the Invention

[0005] In view of the above problems, this application provides a method and storage medium for calibrating abrupt changes in tide level data, which solves the problem that existing tide level interpolation methods or historical similar process interpolation methods require a lot of time and effort from staff and affect work efficiency.

[0006] To achieve the above objectives, the inventors provide a method for calibrating abrupt changes in tide level data, comprising:

[0007] Obtain tide level data within a preset time period;

[0008] Calculate the absolute value of the change between any two adjacent tide levels;

[0009] Perform a boundary value removal operation on the absolute values ​​of all calculated change values ​​to obtain the absolute values ​​of the remaining change values;

[0010] The maximum value among the absolute values ​​of the remaining changes is used as the basis for the change, and the abrupt change data points in all tide level data are obtained.

[0011] Data interpolation is performed on mutation data points;

[0012] The interpolated tidal data are sorted chronologically, and then fitted according to the selected order to obtain the fitted tidal data.

[0013] In some embodiments, obtaining tide data within a preset time period specifically includes the following steps:

[0014] When tide data is received, tide data that is not within the preset range is intercepted, and tide data that was not intercepted within the preset time period is obtained.

[0015] In some embodiments, after intercepting the tide level data that is not within the preset range, the method further includes the following steps:

[0016] Once the intercepted tide data is manually verified and corrected, the corrected tide data will be added to the tide data that was not intercepted within the preset time period.

[0017] In some embodiments, the boundary value removal operation specifically includes the following steps:

[0018] The average of the absolute values ​​of all calculated changes is then multiplied by a preset factor to serve as the boundary value.

[0019] Remove the absolute values ​​of changes that exceed the limit.

[0020] In some embodiments, performing a boundary value removal operation on the absolute values ​​of all calculated change values ​​to obtain the absolute values ​​of the remaining change values ​​specifically includes the following steps:

[0021] Perform a boundary value removal operation on the absolute values ​​of all calculated change values, and then perform another boundary value removal operation on the absolute values ​​of the remaining change values ​​until all the absolute values ​​of the remaining change values ​​are within the boundary values.

[0022] In some embodiments, obtaining abrupt change data points from all tide level data specifically includes the following steps:

[0023] Loop through all the tide data and group the data, first putting the first tide data into the first group;

[0024] Then, when grouping the tide data sequentially, the change value between the tide data to be grouped and the tide data after the previous group is calculated.

[0025] If the absolute value of the calculated change is less than the value on which the change is based, the tide data that needs to be grouped will be assigned to the group containing the tide data after the previous group.

[0026] If the absolute value of the calculated change is greater than the value on which the change is based, a new group is created, and the tide data that needs to be grouped is added to the new group.

[0027] Tide level data in groups with fewer than a preset number of data points are considered as abrupt change data points.

[0028] In some embodiments, after obtaining the fitted and calculated tide level data, the method further includes the following steps:

[0029] The R-squared value is calculated for the fitted tide level data and the sorted tide level data.

[0030] If the R-squared value is less than the preset value, the order is changed and the fitting calculation is performed again. Then, the R-squared value is calculated again with the refitted tide data and the sorted tide data until the R-squared value meets the preset value, and the final fitted tide data is obtained.

[0031] In some embodiments, the following steps are also included:

[0032] When the order is changed from small to large to reach the preset order, if the R-squared value calculated from the refitted tide data and the sorted tide data does not meet the preset value, then the tide data obtained by fitting and calculating according to the preset order is retained.

[0033] In some embodiments, obtaining tide data within a preset time period specifically includes the following steps:

[0034] When the preset time point is reached, the tide level data for the preset time period of the previous day is obtained.

[0035] Another technical solution is also provided: a storage medium storing a computer program, which, when run by a processor, executes the steps in the above-described method for calibrating abrupt changes in tide level data.

[0036] Unlike existing technologies, the above technical solution, when calibrating abrupt changes in tidal data, acquires tidal data within a preset time period, then calculates the absolute value of the change between every two adjacent tidal data points. A boundary value removal operation is performed on all absolute values ​​of change to obtain the remaining absolute values. The maximum value among these remaining absolute values ​​is then used as the basis value for change. Abrupt change data is then acquired based on this basis value, and data interpolation is performed on the abrupt changes. The interpolated tidal data is then sorted chronologically, and a fitting calculation is performed based on the selected endpoint to obtain the fitted tidal data. This allows for the retrieval and calibration of abrupt change data in tidal data, effectively reducing the workload of tidal data compilers and improving work efficiency.

[0037] The above description of the invention is merely an overview of the technical solution of this application. In order to enable those skilled in the art to better understand the technical solution of this application and to implement it based on the description and drawings, and to make the above-mentioned objectives and other objectives, features and advantages of this application easier to understand, the following description is provided in conjunction with the specific embodiments and drawings of this application. Attached Figure Description

[0038] The accompanying drawings are only used to illustrate the principles, implementation methods, applications, features, and effects of specific embodiments of this application and other related content, and should not be considered as limitations on this application.

[0039] In the accompanying drawings of the instruction manual:

[0040] Figure 1 This is a flowchart illustrating a specific implementation of the tide level data mutation point calibration method.

[0041] Figure 2 This is a flowchart illustrating the boundary value removal operation described in a specific implementation.

[0042] Figure 3 This is a schematic diagram of another process for calibrating the tidal data mutation point as described in the specific implementation method;

[0043] Figure 4 This is a schematic diagram of another process for calibrating the tidal data mutation point as described in the specific implementation method;

[0044] Figure 5 This is a schematic diagram of the structure of the storage medium described in a specific embodiment.

[0045] The reference numerals used in the above figures are explained as follows:

[0046] 510. Storage medium,

[0047] 520. Processor. Detailed Implementation

[0048] To illustrate the possible application scenarios, technical principles, implementable specific solutions, and achievable objectives and effects of this application in detail, the following description, in conjunction with the listed specific embodiments and accompanying drawings, provides a detailed explanation. The embodiments described herein are merely illustrative of the technical solutions of this application and are therefore intended to limit the scope of protection of this application.

[0049] In this document, the term "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The term "embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment, nor does it specifically limit its independence or connection with other embodiments. In principle, in this application, as long as there are no technical contradictions or conflicts, the technical features mentioned in each embodiment can be combined in any way to form corresponding implementable technical solutions.

[0050] Unless otherwise defined, the technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the use of related terms herein is merely for the purpose of describing particular embodiments and is not intended to limit this application.

[0051] In the description of this application, the term "and / or" is used to describe the logical relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A exists, B exists, and A and B exist simultaneously. Additionally, the character " / " in this document generally indicates that the preceding and following objects have an "or" logical relationship.

[0052] In this application, terms such as “first” and “second” are used only to distinguish one entity or operation from another, and do not necessarily require or imply any actual quantity, hierarchy or order relationship between these entities or operations.

[0053] Unless otherwise specified, the use of terms such as “comprising,” “including,” “having,” or other similar expressions in this application is intended to cover non-exclusive inclusion, which does not exclude the presence of additional elements in a process, method, or product that includes the stated elements, such that a process, method, or product that includes a list of elements may include not only those defined elements but also other elements not expressly listed, or elements inherent to such a process, method, or product.

[0054] Similar to the understanding in the Examination Guidelines, in this application, expressions such as "greater than," "less than," and "exceeding" are understood to exclude the stated number; expressions such as "above," "below," and "within" are understood to include the stated number. Furthermore, in the description of the embodiments in this application, "multiple" means two or more (including two), and similar expressions related to "multiple" are also understood in this way, such as "multiple groups" and "multiple times," unless otherwise explicitly specified.

[0055] In the description of the embodiments of this application, the space-related expressions used, such as "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "vertical," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential," indicate the orientation or positional relationship based on the orientation or positional relationship shown in the specific embodiments or drawings. They are only for the purpose of describing the specific embodiments of this application or for the reader's understanding, and do not indicate or imply that the device or component referred to must have a specific position, a specific orientation, or be constructed or operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0056] Unless otherwise expressly specified or limited, the terms "installation," "connection," "linking," "fixing," and "setting," as used in the description of the embodiments of this application, should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral setting; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two components or the interaction between two components. For those skilled in the art to which this application pertains, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0057] The fitting algorithm comes from the MathNet.Numerics assembly of the C# mathematical library. It extracts the set of data sources (x,y) and abstracts them into scattered points distributed on the x and y coordinate axes. Then, according to the fitting algorithm, it fits a smooth curve (or straight line).

[0058] Please see Figure 1 This embodiment provides a method for calibrating abrupt changes in tide level data, including:

[0059] Step S110: Obtain tide data within a preset time period;

[0060] Step S120: Calculate the absolute value of the change between every two adjacent tide level data; if there are abrupt change points in the data (i.e., data points that change too much due to the influence of typhoons, instrument malfunctions, etc.), calculate the difference between the tide level data of two adjacent points. Since the data is not a fixed interval of 6 minutes, calculate the minute growth value k (i.e., the change value). Assuming that the time interval between the two data points A and B is 10 minutes, then k = (BA) / 10.

[0061] Step S130: Perform a boundary value removal operation on the absolute values ​​of all calculated change values ​​to obtain the absolute values ​​of the remaining change values;

[0062] Step S140: Take the maximum value among the absolute values ​​of the remaining changes as the basis value for change, and obtain the abrupt change data points in all tide level data;

[0063] Step S150: Perform data interpolation on the mutation data points;

[0064] Step S160: Sort the tide data after data interpolation according to time sequence;

[0065] Step S170: Perform fitting calculations based on the selected order to obtain the fitted tidal level data.

[0066] When it is necessary to calibrate abrupt changes in tidal data, tidal data within a preset time period is acquired, and the absolute value of the change between every two adjacent tidal data points is calculated. Boundary value removal is performed on all absolute values ​​of change to obtain the remaining absolute values. The maximum value among these remaining absolute values ​​is then used as the basis value for the change. Abrupt change data is then retrieved from all tidal data based on this basis value. Data interpolation is performed on the abrupt changes, and the interpolated tidal data is sorted chronologically. After processing, a fitting calculation is performed based on the selected endpoint to obtain the fitted tidal data. This method allows for the retrieval and calibration of abrupt change data in tidal data, effectively reducing the workload of tidal data compilation personnel and improving work efficiency.

[0067] In some embodiments, obtaining tide data within a preset time period specifically includes the following steps:

[0068] When tide data is received, tide data that is not within the preset range is intercepted, and tide data that was not intercepted within the preset time period is obtained.

[0069] Different rules are set for the extreme values ​​and characteristic values ​​of the tide level data collected from each station (e.g., water level data should be between the highest and lowest water levels, and rainfall data should be within the range of the maximum rainfall in 5 minutes). If the data is not within the range, the corresponding tide level data is intercepted. Finally, the tide level data for the preset time period is obtained.

[0070] In some embodiments, after intercepting the tide level data that is not within the preset range, the method further includes the following steps:

[0071] Once the intercepted tide data is manually verified and corrected, the corrected tide data will be added to the tide data that was not intercepted within the preset time period.

[0072] Intercepted tide data needs to be manually verified. Staff log into the relevant system page to check if there is any intercepted data. If there is intercepted data, it needs to be processed first. The intercepted data can be corrected or confirmed to be correct. After the intercepted tide data is verified and corrected, the corrected tide data is added back to the tide data for the preset time period.

[0073] Please see Figure 2 In some embodiments, by performing a boundary value removal operation on the absolute value of the calculated change value, the obtained change basis value can effectively and accurately find the data mutation point. The specific boundary value removal operation includes the following steps:

[0074] Step S210: Calculate the average of the absolute values ​​of all the calculated changes, and multiply the average by a preset factor as the limit value;

[0075] Step S220: Remove the absolute values ​​of changes that exceed the limit values.

[0076] The absolute values ​​of changes exceeding the threshold are removed, ensuring that the final change basis value can effectively and accurately locate data abrupt change points. A higher preset multiplier requires more interpolation points and increases the number of points far below the threshold; a minimum of 3 times is recommended, as 2 times may result in a straight line. Preferably, the preset multiplier is 5. Further, a more effective change basis value can be obtained by removing the threshold values ​​from the absolute values ​​of all calculated changes, specifically including the following steps:

[0077] Perform a boundary value removal operation on the absolute values ​​of all calculated change values, and then perform another boundary value removal operation on the absolute values ​​of the remaining change values ​​until all the absolute values ​​of the remaining change values ​​are within the boundary values.

[0078] By performing multiple boundary value removal operations until the absolute values ​​of the remaining changes are all within the corresponding boundary values, the maximum value among the absolute values ​​of the remaining changes is used as the basis for the change. This can more effectively find data mutation points and reduce errors.

[0079] In some embodiments, obtaining abrupt change data points from all tide level data specifically includes the following steps:

[0080] Loop through all the tide data and group the data, first putting the first tide data into the first group;

[0081] Then, when grouping the tide data sequentially, the change value between the tide data to be grouped and the tide data after the previous group is calculated.

[0082] If the absolute value of the calculated change is less than the value on which the change is based, the tide data that needs to be grouped will be assigned to the group containing the tide data after the previous group.

[0083] If the absolute value of the calculated change is greater than the value on which the change is based, a new group is created, and the tide data that needs to be grouped is added to the new group.

[0084] Tide level data in groups with fewer than a preset number of data points are considered as abrupt change data points.

[0085] When searching for abrupt changes in tidal data using a change-based value, the data is grouped by iterating through all tidal levels. First, the first tidal level data is placed in the first group. Then, the change value is calculated between the data and the last data in each group (e.g., calculating the change value between the second and first tidal levels). If the absolute value of the change value between the second and first tidal levels is less than the change-based value, the second tidal level data is grouped with the first tidal level data and placed in the second group. If the absolute value of the change value between the second and first tidal levels is greater than the change-based value, the grouping is re-established, and the second tidal level data is placed in the re-established group. This process continues until all tidal level data is grouped. Since abrupt changes are relatively few, groups with a large amount of data are considered normal data, while groups with a small amount of data are considered abrupt changes. Therefore, data points in groups with a large amount of data are considered normal data points, while abrupt changes are interpolated using linear interpolation.

[0086] Please see Figure 3 In some embodiments, after obtaining the fitted and calculated tide level data, the following steps are further included:

[0087] Step S310: Calculate the R-squared value of the fitted tide data and the sorted tide data;

[0088] Step S320: Determine whether the average value of R meets the preset value;

[0089] If the R-squared value meets the preset value, then proceed to step S330: obtain the final fitted tidal level data.

[0090] If the R-squared value is less than the preset value, then proceed to step S340: change the order, then return to step S170, refit and calculate, and then calculate the R-squared value of the refitted tide data and the sorted tide data until the R-squared value meets the preset value, and obtain the final fitted tide data.

[0091] The R-squared value is a number between 0 and 1, showing the correspondence between the estimated value of a trend line and the actual data. A trend line is considered most reliable when its R-squared value is close to or close to 1. Tide level data is sorted chronologically, then a specific order is selected for fitting calculations. The R-squared value is then calculated for both the fitted and processed tide level data. The closer the R-squared value is to 1, the better the fit between the line and the data points. (Assuming a certain location requires an R-squared value of 99.8%), if the R-squared value does not meet 99.8%, the order is changed and the fitting calculation continues until a suitable R-squared value is obtained.

[0092] In some embodiments, the following steps are also included:

[0093] When the order is changed from small to large to reach the preset order, if the R-squared value calculated from the refitted tide data and the sorted tide data does not meet the preset value, then the tide data obtained by fitting and calculating according to the preset order is retained.

[0094] Depending on specific requirements, such as defining the calculation order as 5-21 in a certain region, the fitting calculation is performed from the lowest to the highest order. The fitting calculation starts with order 5. If the R-squared value meets the standard, the calculation stops. However, if the R-squared value at order 21 also does not meet the standard, the calculation stops, and the fitted tidal level data corresponding to order 21 is retained. When acquiring telemetry tidal level data, abnormal data interception and processing are performed, after which automatic fitting can be performed. Simultaneously, fitting is enabled, and R-squared values ​​of multiple orders are displayed, allowing users to quickly find the desired order, view the effect, determine high and low tides, and ensure the data is truly effective.

[0095] In some embodiments, obtaining tide data within a preset time period specifically includes the following steps:

[0096] When the preset time point is reached, the tide level data for the preset time period of the previous day is obtained.

[0097] Data fitting time setting: Closed before open, for example: July 31 means fitting the tide level data from 0:00 on July 31 to 0:00 on August 1; fitting the previous day's data begins after 8:00 AM each day. If there is manual measurement at 8:00 AM today, fitting can begin after correction; if no manual measurement is performed, fitting will be delayed by 1 hour.

[0098] In some embodiments, the main steps of the tide level data abrupt change point calibration method are as follows:

[0099] Different rules are set for each station based on its extreme values ​​and characteristic values ​​(e.g., water level data should be between the highest and lowest water levels, and rainfall data should be within the range of the maximum rainfall in 5 minutes). If the data is outside the range, it will be blocked and requires manual verification.

[0100] Staff log into the relevant system page to check if any data has been blocked. If data has been blocked, it needs to be processed first. The blocked data can be corrected or confirmed to be correct.

[0101] Fitted data time setting: closed before open, such as: July 31 means fitting the tide level data from 0:00 on July 31 to 0:00 on August 1;

[0102] The data from the previous day will be fitted starting at 8 AM each day. (If manual measurement is performed at 8 AM today, the data can be fitted immediately after correction; otherwise, the data will be fitted one hour later.)

[0103] Specifically, the fitting calculation process for the abrupt change points in the tidal data is as follows:

[0104] To obtain the corrected tide level, in order to better fit the data, the default is to take 1 hour before and after each day's data, which is convenient for interpolation when the start and end points are abrupt data.

[0105] The data contains abrupt change points (i.e., data points that change too much due to factors such as typhoons and instrument malfunctions). Calculate the difference between two adjacent data points. Since the data is not at a fixed interval of 6 minutes, calculate the minute increment value k (assuming the time interval between data points A and B is 10 minutes, then k = (BA) / 10).

[0106] The average of all k values ​​is calculated, and the average is multiplied by 5 as a threshold (the higher the multiplier, the more points need to be interpolated, and the more points are far from the line; a minimum of 3 times, and 2 times may result in a straight line). Values ​​exceeding the threshold are removed. Then, the threshold calculation is repeated with the remaining k values ​​until all differences are within the average.

[0107] The largest k value (maxk) is obtained from the remaining k values ​​and used as the basis for change.

[0108] Group the data, loop through all the data, put the first data into the first group, and calculate the growth value k for the subsequent data and the last data in the group. If the growth value k is less than maxk, they are grouped into the same group; if the growth value k is greater than maxk, a new group is created.

[0109] Mutation points will only be a minority, so a large amount of data is normal data and a small amount of data is mutation data. Data points with a large amount of data are taken as normal data points, and linear interpolation is used to interpolate the mutation points.

[0110] The data is sorted chronologically, then a specific order is selected for fitting calculations. The R-squared value is calculated for both the fitted and processed data; the closer the R-squared value is to 1, the better the fit between the line and the points. (Assuming a certain location's tidal level requires an R-squared value of 99.8%). If the R-squared value does not meet 99.8%, the order is changed and the calculation continues. For this location, the calculation order is defined from 5 to 21. The calculation is performed from smallest to largest order. The calculation stops when the R-squared value meets the standard; if even order 21 does not meet the standard, the data from order 21 is retained.

[0111] Due to formula relationships and other reasons, fitting operations are not performed when there are too few data points.

[0112] Please see Figure 4 The above method for calibrating abrupt changes in tidal data can be applied to specific scenarios:

[0113] S1. By connecting to the tide level data, start the calculation to obtain the absolute value k of the change per minute;

[0114] S2. Average all k values, and multiply the average by 5 to use as the boundary value. Remove values ​​that exceed the boundary value. Continue the boundary value calculation with the remaining k values ​​until all differences are within the average value.

[0115] S3. Obtain the largest k value (maxk) from the remaining k values ​​as the basis for change;

[0116] S4. Group the data. Loop through all the data. Put the first data into the first group. Calculate the growth value k for the subsequent data and the last data in the group. If the growth value k is less than maxk, they are grouped into the same group.

[0117] S5. Obtain data points from a large amount of data as normal data points, and interpolate abrupt change points;

[0118] S6. Process the data, then select the order for fitting calculation, and calculate the R-squared value for the fitted data and the processed data until the calculation result meets the requirements.

[0119] This application provides a method for calibrating abrupt changes in tidal data based on minute increment values. This method can effectively avoid misreporting and incorrect filling of tidal data, suppress errors in the source of monitoring data, ensure data accuracy, provide data support for the timely and daily compilation of water level data, significantly improve the real-time performance, intelligence, and efficiency of hydrological data compilation, and better serve the needs of social and economic development.

[0120] The compilation of tidal data requires accuracy and timeliness. Interpolation methods based on correlation or historical similarity cannot meet these requirements. This method calculates the time points and values ​​of high and low tides based on average changes over time, reducing errors. Data filtered for abrupt changes is more meaningful. During manual verification, high and low tides can be quickly located based on reference values. Furthermore, this method can calculate higher orders, offering more options. This method reduces the workload of tidal data compilers and effectively improves work efficiency.

[0121] Please see Figure 5 In another embodiment, a storage medium 510 stores a computer program, which is executed by a processor 520 to perform the steps in the tide level data mutation point calibration method in the above embodiments.

[0122] When it is necessary to calibrate abrupt changes in tidal data, tidal data within a preset time period is acquired, and the absolute value of the change between every two adjacent tidal data points is calculated. Boundary value removal is performed on all absolute values ​​of change to obtain the remaining absolute values. The maximum value among these remaining absolute values ​​is then used as the basis value for the change. Abrupt change data is then retrieved from all tidal data based on this basis value. Data interpolation is performed on the abrupt changes, and the interpolated tidal data is sorted chronologically. After processing, a fitting calculation is performed based on the selected endpoint to obtain the fitted tidal data. This method allows for the retrieval and calibration of abrupt change data in tidal data, effectively reducing the workload of tidal data compilation personnel and improving work efficiency.

[0123] Finally, it should be noted that although the above embodiments have been described in the text and drawings of this application, this should not limit the scope of patent protection of this application. Any technical solutions that are based on the essential concept of this application and utilize the content described in the text and drawings of this application, resulting in equivalent structural or procedural substitutions or modifications, as well as the direct or indirect application of the technical solutions of the above embodiments to other related technical fields, are all included within the scope of patent protection of this application.

Claims

1. A method for calibrating abrupt changes in tide level data, characterized in that, include: Obtain tide level data within a preset time period; Calculate the absolute value of the change between any two adjacent tide levels; Perform a boundary value removal operation on the absolute values ​​of all calculated change values ​​to obtain the absolute values ​​of the remaining change values. Perform the boundary value removal operation again on the absolute values ​​of the remaining change values ​​until the absolute values ​​of the remaining change values ​​are all within the boundary values. The maximum value among the absolute values ​​of the remaining changes is used as the basis for the change, and the abrupt change data points in all tide level data are obtained. Data interpolation is performed on mutation data points; The interpolated tide data is sorted according to time sequence, and then fitted according to the selected order to obtain the fitted tide data. The boundary value removal operation specifically includes the following steps: The average of the absolute values ​​of all calculated changes is then multiplied by a preset factor to serve as the boundary value. Remove the absolute value of the change that exceeds the limit value; The specific steps for obtaining abrupt change data points from all tide level data are as follows: Loop through all the tide data and group the data, first putting the first tide data into the first group; Then, when grouping the tide data sequentially, the change value between the tide data to be grouped and the tide data after the previous group is calculated. If the absolute value of the calculated change is less than the value on which the change is based, the tide data that needs to be grouped will be assigned to the group containing the tide data after the previous group. If the absolute value of the calculated change is greater than the value on which the change is based, a new group is created, and the tide data that needs to be grouped is added to the new group. Tide level data in groups with fewer than a preset number of data points are considered as abrupt change data points.

2. The tidal level data abrupt change point calibration method according to claim 1, characterized in that, The specific steps for obtaining tide data within a preset time period include: When tide data is received, tide data that is not within the preset range is intercepted, and tide data that was not intercepted within the preset time period is obtained.

3. The tidal level data abrupt change point calibration method according to claim 2, characterized in that, After intercepting tide data that is outside the preset range, the following steps are also included: Once the intercepted tide data is manually verified and corrected, the corrected tide data will be added to the tide data that was not intercepted within the preset time period.

4. The tidal level data abrupt change point calibration method according to claim 1, characterized in that, After obtaining the fitted and calculated tide level data, the following steps are also included: The R-squared value is calculated for the fitted tide level data and the sorted tide level data. If the R-squared value is less than the preset value, the order is changed and the fitting calculation is performed again. Then, the R-squared value is calculated again with the refitted tide data and the sorted tide data until the R-squared value meets the preset value, and the final fitted tide data is obtained.

5. The tidal data abrupt change point calibration method according to claim 4, characterized in that, It also includes the following steps: When the order is changed from small to large to reach the preset order, if the R-squared value calculated from the refitted tide data and the sorted tide data does not meet the preset value, then the tide data obtained by fitting and calculating according to the preset order is retained.

6. The tidal level data abrupt change point calibration method according to claim 1, characterized in that, The process of obtaining tide data within a preset time period specifically includes the following steps: When the preset time point is reached, the tide level data for the preset time period of the previous day is obtained.

7. A storage medium storing a computer program, characterized in that, The computer program is executed by the processor to perform the steps in the tide level data mutation point calibration method as described in any one of claims 1-6.

Images