A float-type tidal prediction method for tidal water level monitoring

Abstract

The present invention relates to the technical field of tidal prediction, and discloses a float-type tidal prediction method for tidal water level monitoring, which includes the following steps: obtaining tidal water level value data of the growth trend before the warning time point, marking the corresponding time as the time interval to be analyzed, and then combining the tidal water level growth period for similarity analysis to identify the tidal water level growth period with high similarity to the time interval to be analyzed; predicting the time value when the tidal water level reaches the tidal water level warning value based on the tidal water level growth period with high similarity, and obtaining the current prevention and control time period. The present invention improves the accuracy of tidal water level prediction. By constructing a model for each tidal water level growth period, finding the period with high similarity to the interval to be analyzed for prediction, providing relatively accurate model support for prediction, and being able to select appropriate prevention and control measures in combination with historical prevention and control data, it can optimize resource utilization while reducing disaster losses and achieve scientific and effective prevention and control of tidal water levels.

Description

Technical Field

[0001] The present invention relates to the technical field of tidal prediction, and particularly relates to a buoy-type tidal prediction method for tidal water level monitoring. Background Art

[0002] In marine activities, the monitoring and early warning of tidal water levels are crucial, which are directly related to navigation safety, fishery operations, and marine engineering construction. As a classic water level monitoring method, buoy-type tidal prediction captures water level changes by setting buoys on the sea surface and utilizing their characteristics of rising and falling with the tides.

[0003] However, although buoy-type tidal prediction is widely used as a traditional water level monitoring method, in actual use, its analysis of the changing trend of tidal water levels is not deep enough, and it cannot accurately predict, making the accuracy of the prediction results difficult to meet actual needs. When an abnormal change in tidal water level occurs and an early warning is issued, there is a lack of research on how to optimize resource utilization while ensuring the prevention and control effect. This has affected the safe development and sustainable development of marine activities. Summary of the Invention

[0004] The purpose of the present invention is to provide a buoy-type tidal prediction method for tidal water level monitoring to solve at least one of the above-mentioned problems in the prior art.

[0005] The present invention provides a buoy-type tidal prediction method for tidal water level monitoring, including the following steps:

[0006] Obtain the tidal water level value data of the growth trend before the early warning time point, mark the corresponding time as the time interval to be analyzed, and then conduct a similarity analysis in combination with the tidal water level growth period to identify the tidal water level growth period with a high similarity to the time interval to be analyzed;

[0007] Predict the time value when the tidal water level reaches the tidal water level warning value based on the tidal water level growth period with a high similarity, and obtain the current prevention and control time period.

[0008] Advantages of the Present Invention

[0009] 1. The buoy-type tidal prediction method provided by the present invention realizes real-time monitoring and early warning of tidal water levels. By using a buoy-type tidal water level monitoring device, the real-time tidal water level value is compared with the warning value, and corresponding signals are generated in a timely manner, enabling relevant personnel to quickly grasp the changes in tidal water levels. At the same time, by determining the tidal water level growth period, not only can the rising trend be intuitively presented, providing key trend information for an accurate tidal prediction model, but also it helps to extract tidal change characteristic parameters, analyze their laws and characteristics, and assist researchers and relevant staff in better understanding the tidal situation;

[0010] 2. The present invention improves the accuracy of tidal water level prediction. By constructing models for each tidal water level growth period, it finds periods with high similarity to the interval to be analyzed for prediction, providing relatively accurate model support for prediction. Moreover, it can select appropriate prevention and control measures in combination with historical prevention and control data, optimize resource utilization while reducing disaster losses, and achieve scientific and effective prevention and control of tidal water levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0012] Figure 1 is a flowchart of a float - type tidal prediction method for tidal water level monitoring according to the present invention;

[0013] Figure 2 is a schematic structural diagram of a float - type tidal prediction system for tidal water level monitoring according to the present invention;

[0014] Figure 3 is a schematic structural diagram of a float - type tidal prediction device for tidal water level monitoring according to the present invention.

[0015] In the figure: 3. Computer device; 301. Processor; 302. Memory; 303. Computer program. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0017] Embodiment 1

[0018] Figure 1The flowchart of a float - type tidal prediction method provided by Embodiment 1 of the present invention. The embodiments of the present invention are applicable to the situation of tidal water level monitoring and prediction. This float - type tidal prediction method for tidal water level monitoring can be executed by a float - type tidal prediction system for tidal water level monitoring. This float - type tidal prediction system for tidal water level monitoring can be implemented by software and / or hardware, and this float - type tidal prediction system for tidal water level monitoring can be configured in a float - type tidal prediction device for tidal water level monitoring. Optionally, a float - type tidal prediction device for tidal water level monitoring can be an electronic device, and this electronic device can be a notebook, a desktop computer, a smart tablet, etc. The embodiments of the present invention do not limit this.

[0019] A float - type tidal prediction method provided by the embodiments of the present invention specifically includes the following steps:

[0020] Step 1: Real - time monitor through the float - type tidal water level, identify the real - time tidal water level value data, generate a tidal water level warning signal, and obtain the risk monitoring area;

[0021] In some embodiments, divide the predicted sea area into several monitoring areas, based on any one of the monitoring areas;

[0022] Use a float - type tidal water level monitoring device to real - time monitor the tidal water level value;

[0023] Among them, the float - type tidal water level monitoring device mainly consists of a float, a connecting cable, a pulley, and a displacement sensor. The float floats on the water surface and moves up and down with the rise and fall of the tidal water level. The connecting cable connects the float to the pulley. When the float moves, it drives the displacement sensor through the pulley, and the data will be real - time transmitted to the data acquisition system;

[0024] The data acquisition system collects and records the electrical signals transmitted by the displacement sensor at a set time interval;

[0025] Compare the real - time tidal water level value with the tidal water level warning value. Among them, the tidal water level warning value is set by those skilled in the art according to experience, and the tidal water level warning value is less than the tidal water level warning threshold. The tidal water level warning threshold is a key water level value comprehensively determined according to various factors such as the geographical environment of the area, historical tidal data, engineering design standards, and possible risks in the context of engineering facilities related to tides;

[0026] If the real - time tidal water level value is greater than or equal to the tidal water level warning value, generate a tidal water level warning signal, otherwise, generate a tidal water level normal signal;

[0027] Obtain the monitoring area corresponding to the generated tidal water level warning signal and mark it as the risk monitoring area;

[0028] Step 2: Based on the risk monitoring area, analyze the historical tidal water level value data and identify the tidal water level rising period;

[0029] In some embodiments, based on any risk monitoring area, obtain the time value corresponding to the generated tidal water level warning signal and mark it as the warning time point;

[0030] Mark the tidal water level value data before the warning time point as the historical tidal water level value data;

[0031] Preset a monitoring period, where the monitoring period is summarized and set by those skilled in the art according to the historical change characteristics of the tidal water level value;

[0032] In each monitoring period, the historical tidal water level value data sequence is {h1, h2,..., hn}, and the corresponding time sequence is {t1, t2,..., tn}, and the time interval , where i = 1, 2,..., n - 1, and n represents the number of historical tidal water level value data in the monitoring period;

[0033] Starting from the second data point of the historical tidal water level value, calculate the difference between the latter tidal water level value and the former tidal water level value of two adjacent data points in sequence to obtain the tidal water level deviation value;

[0034] If the tidal water level deviation value is greater than zero, mark the time interval corresponding to these two tidal water level values as the tidal water level rising interval, otherwise, mark it as the tidal water level non-rising interval;

[0035] Count the number value of all tidal water level rising intervals in the monitoring period and calculate the ratio with the number of all time intervals in the monitoring period to obtain the ratio of the number of rising intervals;

[0036] Set a ratio threshold of the number of rising intervals. If the ratio of the number of increasing intervals is greater than the ratio threshold of the number of rising intervals, mark this monitoring period as the tidal water level rising period, otherwise, mark it as the tidal water level non-rising period;

[0037] The reason for clarifying the tidal water level rising period is that it can enable researchers and relevant staff to intuitively understand in which time periods the tidal water level is on the rising trend, provide key trend information for subsequent more accurate tidal prediction models, and the determination of the rising period helps to extract characteristic parameters of tidal changes, such as the rising rate and rising period, and can analyze the laws and characteristics of tidal changes;

[0038] The technical solution of this embodiment is as follows: The tidal water level is monitored in real time by a float-type tidal water level monitoring device. The real-time tidal water level value is compared with a warning value set according to experience. If it is greater than or equal to the warning value, a warning signal is generated; otherwise, a normal signal is generated. Then, based on the warning signal, the warning time point is obtained, and the tidal water level value before it is used as historical data. Within a preset monitoring period, the historical data is analyzed, the water level difference between adjacent data points is calculated to determine the growth interval, and the proportion of the number of growth intervals is counted. If it is greater than the set threshold, it is marked as the tidal water level growth period;

[0039] Thus, the tidal water level can be monitored and warned in real time, the rising trend of the tidal water level can be intuitively presented, key trend information can be provided for an accurate tidal prediction model, and it is also helpful to extract tidal change characteristic parameters, analyze its laws and characteristics, and help researchers and relevant staff better understand the tidal situation.

[0040] Embodiment 2

[0041] Based on the above embodiment, as Figure 1 shown, a float-type tidal prediction method for tidal water level monitoring provided by an embodiment of the present invention specifically includes the following steps:

[0042] Step 3: Based on the tidal water level growth period, obtain the tidal water level value data of the growth trend before the warning time point, mark the corresponding time as the time interval to be analyzed, and then perform similarity analysis in combination with the tidal water level growth period to identify the tidal water level growth period with a high similarity to the time interval to be analyzed;

[0043] In some embodiments, the warning time point is obtained, and the historical tidal water level value data sequence is {h1, h2,..., hn}, and the corresponding time sequence is {t1, t2,..., tn};

[0044] Starting from the data point closest to the warning time point, traverse the historical tidal water level value data in reverse order in time sequence, obtain the nearest time interval in the growth trend before the warning time point, and mark it as the time interval to be analyzed;

[0045] Exemplarily, the data point closest to the warning time point is , then starting from j, let , and continuously move i forward;

[0046] During the reverse traversal process, for each data point i, calculate the tidal water level change value between it and the previous data point i - 1 (if i - 1 exists). If the change value is greater than zero, continue to traverse the next data point forward, and repeat the calculation of the change value to determine whether it continues to grow;

[0047] Once the change value is less than or equal to zero, stop traversing. At this time, from the last data point that satisfies the change value being greater than zero to the corresponding time interval is the time interval with the most recent growth trend before the warning time point;

[0048] Obtain the tidal water level value data sequence for the time interval to be analyzed;

[0049] Obtain all tidal water level growth periods and the corresponding tidal water level value data, and respectively construct a Long Short-Term Memory (LSTM) model based on the tidal water level value data of each growth period, which is the tidal water level growth model corresponding to the growth period;

[0050] The specific process of constructing the tidal water level growth model is as follows:

[0051] Determine the structure of the LSTM model, including one or more LSTM layers, and an optional fully connected layer (Dense layer);

[0052] For example, a model containing two LSTM layers and one fully connected layer can be constructed. The first LSTM layer can be set with a certain number of neurons, such as 64. It can capture the long-term dependencies and complex patterns in the tidal water level time series. The second LSTM layer is also set with 64 neurons to further extract features from the data. Finally, the fully connected layer maps the features output by the LSTM layer to a scalar value, which is the predicted tidal water level value at the next time point;

[0053] During the model construction process, the selection of activation functions also needs to be considered. The sigmoid function and the tanh function are usually used inside the LSTM layer to control the gating mechanism and cell state update. The fully connected layer can use a linear activation function (i.e., no activation function is used) because predicting the tidal water level value is a regression problem, and the linear activation function is suitable for outputting continuous values;

[0054] Select an appropriate loss function. Since it is to predict the tidal water level value, the Mean Squared Error (MSE) is a commonly used loss function, which can measure the average squared error between the predicted value and the actual value;

[0055] Select an optimizer to update the weights of the model. For example, the Adam optimizer is a commonly used optimizer. It combines the advantages of Adagrad and RMSProp and can adaptively adjust the learning rate. The learning rate of the Adam optimizer can be set, such as 0.001, and this value can be adjusted through experiments to obtain the best training effect;

[0056] Input the tidal water level value data sequence of the time interval to be analyzed into the trained tidal water level growth model, process it according to the input data, and output the predicted tidal water level value at the next time point of the time interval to be analyzed;

[0057] Calculate the difference degree value U between the predicted tidal water level value and the actual tidal water level value. The calculation formula of U is: , where m is the number of tidal water level values in the time interval to be analyzed, is the p-th predicted tidal water level value, is the p-th actual tidal water level value;

[0058] It should be noted that the tidal water level value data of the time interval to be analyzed is the actual tidal water level value;

[0059] The difference degree value reflects the ratio of the average deviation between the predicted value and the actual value to the sum of their means. If this ratio is small, it means that the deviation between the predicted value and the actual value is relatively small and the prediction result is relatively accurate. On the contrary, if the ratio is large, it indicates that the deviation between the predicted value and the actual value is relatively large and the accuracy of the prediction needs to be improved;

[0060] Obtain the difference degree values corresponding to all tidal water level growth periods, set a difference degree threshold, and mark the tidal water level growth periods with difference degree values less than the threshold as similar tidal water level growth periods, otherwise, mark them as non-similar tidal water level growth periods;

[0061] Extract the minimum value of the difference degree values in the similar growth periods and mark it as the high-similarity tidal water level growth period;

[0062] It should be noted that if there are no similar tidal water level growth periods, analyze whether there are special environmental factors in the time interval to be analyzed, such as abnormal meteorological conditions, sudden changes in ocean circulation, etc. that affect the tidal changes;

[0063] First, by constructing the tidal water level growth models for all growth periods, and then determining the role of the tidal water level growth periods with similar high tidal water level values to the data sequence of the tidal water level values in the interval to be analyzed is as follows: One is to provide more accurate model support for subsequent predictions. Different tidal water level growth periods have different variation laws. By constructing LSTM models for each growth period, the relationship between the tidal water level changes within that period can be deeply explored. When a growth period with a high similarity to the interval to be analyzed is found, the laws learned by the model of that period are used to predict the subsequent tidal water levels in the interval to be analyzed, thus significantly improving the prediction accuracy; The other is to increase the prediction accuracy. Marine disasters such as storm surges are often accompanied by abnormal growth of tidal water levels. By analyzing the similarity between the interval to be analyzed and historical growth periods, abnormal trends in the tidal water level changes can be discovered in a timely manner, and early warnings for disasters such as storm surges can be issued. For example, if it is found that the interval to be analyzed is similar to the tidal water level growth period during a certain storm surge in history, the time when the tidal water level reaches the warning value is predicted, and then the corresponding disaster prevention and control plan is activated in a timely manner to evacuate people and strengthen facilities, reducing the losses caused by the disaster;

[0064] Step Four: Based on the tidal water level growth periods with high similarity, and predict the time value when the tidal water level reaches the tidal water level warning value, and obtain the corresponding prevention and control measures;

[0065] In some embodiments, based on the tidal water level growth periods with high similarity, obtain the corresponding tidal water level growth models;

[0066] Input the tidal water level warning value into the tidal water level growth model, output the predicted time value, calculate the difference between the predicted time value and the warning time value to obtain the current prevention and control time period;

[0067] The prevention and control time period is used by those skilled in the art to perform early prevention and control adjustments and reasonable scheduling within the time when the tidal water level reaches the tidal water level warning value;

[0068] Obtain the prevention and control time periods in the historical data when the tidal water level is between the warning time point and the predicted time value, and mark them as historical prevention and control time periods;

[0069] Among them, the historical data also includes the prevention and control measures corresponding to the historical prevention and control time periods;

[0070] It should be noted that the extracted historical prevention and control time periods are data of effective prevention and control results, that is, the data that do not reach the tidal water level warning value at the end of the prevention and control time period after the tidal water level value reaches the tidal water level warning value and after those skilled in the art have taken prevention and control measures;

[0071] Based on each historical prevention and control time period, obtain the corresponding historical tidal water level prediction value sequence and the actual historical tidal water level value, where the actual historical tidal water level value is the actual tidal water level value monitored after the prevention and control measures;

[0072] In a two-dimensional coordinate system, plot the change curve of the historical tidal water level prediction value and the change curve of the actual historical tidal water level value;

[0073] Calculate the area of the closed figure formed by the change curve of the historical tidal water level prediction value and the X-axis and the area of the closed figure formed by the change curve of the actual historical tidal water level value and the X-axis respectively, and perform a difference calculation to obtain the area deviation value, which is the prevention and control intensity value;

[0074] The reason for taking the area deviation value as the prevention and control intensity value is that: the area of the closed figure formed by the change curve of the historical tidal water level prediction value and the X-axis, and the area of the closed figure formed by the change curve of the actual historical tidal water level value and the X-axis respectively reflect the predicted tidal water level change and the actual tidal water level change situation during the historical prevention and control time period from different perspectives. By calculating the difference between the two areas to obtain the area deviation value, this change difference can be quantified, intuitively reflecting the deviation degree between the predicted value and the actual value, so as to measure the influence effect of the prevention and control measures on the tidal water level change in the historical situation, that is, the prevention and control intensity;

[0075] Compare each historical prevention and control time period with the current prevention and control time period. Mark the historical prevention and control time periods that are greater than the current prevention and control time period as the time periods to be selected, and mark the historical prevention and control time periods that are less than or equal to the current prevention and control time as non-selected time periods;

[0076] Obtain all the time periods to be selected and their corresponding prevention and control intensity values, extract the minimum value of the prevention and control intensity values, and mark it as the final selected time period;

[0077] Use the prevention and control measures corresponding to the final selected time period to carry out the current tidal water level prevention and control;

[0078] The reason for choosing the minimum value of the prevention and control intensity value is that: the prevention and control intensity value actually reflects the resource input and operation intensity in the prevention and control process, etc. A smaller prevention and control intensity value means that relatively fewer resources such as manpower, material resources, and financial resources are consumed under the premise of achieving effective prevention and control, or the prevention and control operations taken are relatively simpler. Choosing the minimum value can avoid resource waste caused by over-prevention and control on the basis of ensuring the prevention and control effect, realize the reasonable allocation and efficient utilization of resources, so that relevant personnel can more scientifically dispatch resources and obtain the maximum prevention and control benefit with the minimum input;

[0079] The technical solution of this embodiment is as follows: By obtaining the tidal water level value data of the growth trend before the warning time point and the time interval to be analyzed, then constructing a long short-term memory network model for each tidal water level growth period, inputting the data of the time interval to be analyzed into the model to obtain the predicted value, screening out the tidal water level growth periods with high similarity by calculating the difference degree value between the predicted value and the actual value, then obtaining the corresponding tidal water level growth model based on this period, inputting the tidal water level warning value to obtain the predicted time value, calculating the current prevention and control time period, and by comparing the relevant data of the historical prevention and control time periods, selecting the prevention and control measures corresponding to the historical prevention and control time period with the smallest prevention and control intensity value for the current tidal water level prevention and control;

[0080] Thus, it can provide more accurate model support for tidal water level prediction, improve the prediction accuracy by using the model rules of similar time periods, and can timely detect abnormal trends of tidal water levels, issue disaster warnings in advance, and can also optimize resource utilization while ensuring the prevention and control effect by selecting appropriate prevention and control measures, reducing disaster losses.

[0081] Embodiment Three

[0082] Based on the above embodiments, as Figure 2 shown, a buoy-type tidal prediction system for tidal water level monitoring provided by an embodiment of the present invention specifically includes:

[0083] Risk monitoring area acquisition module: Real-time monitoring is carried out through the buoy-type tidal water level, and the real-time tidal water level value data is identified to generate a tidal water level warning signal and obtain the risk monitoring area;

[0084] Water level growth period acquisition module: Based on the risk monitoring area, analyze the historical tidal water level value data and identify the tidal water level growth period;

[0085] Similarity judgment module: Based on the tidal water level growth period, obtain the tidal water level value data of the growth trend before the warning time point, mark the corresponding time as the time interval to be analyzed, and then conduct similarity analysis in combination with the tidal water level growth period to identify the tidal water level growth period with high similarity to the time interval to be analyzed;

[0086] Water level prediction and prevention and control module: The tidal water level growth period with high similarity, and predict the time value when the tidal water level reaches the tidal water level warning value, and obtain the corresponding prevention and control measures.

[0087] Embodiment Four

[0088] As Figure 3As shown in the figure, an embodiment of the present invention further provides a computer device 3, including: a memory 302, a processor 301, and a computer program 303 stored on the memory 302. When the computer program 303 is executed on the processor 301, it implements a float-type tidal prediction method for tidal water level monitoring as described in any one of the above methods.

[0089] The computer device 3 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302.

[0090] Figure 3 These are merely examples of the computer device 3 and do not constitute a limitation on the computer device 3. It may include more or fewer components than shown in the figure, or combine certain components, or have different components. For example, it may also include input / output devices, network access devices, etc.

[0091] The so-called processor 301 may be a central processing unit (CPU), and the processor 301 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0092] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as the hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 3. Further, the memory 302 may also include both the internal storage unit and the external storage device of the computer device 3. The memory 302 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or will be output.

[0093] Example 5

[0094] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it implements a float-type tidal prediction method for tidal water level monitoring as described in any one of the above methods.

[0095] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above embodiment methods of this application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0096] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0097] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0098] In the embodiments disclosed in the present application, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / terminal device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0099] Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0100] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0101] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0102] The above has described an embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as used to limit the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A float-type tidal prediction method for tidal water level monitoring, characterized in that, It includes the following steps: Obtain the tidal water level value data of the growth trend before the early warning time point, mark the corresponding time as the time interval to be analyzed, and then conduct a similarity analysis in combination with the tidal water level growth period to identify the tidal water level growth period with a high similarity to the time interval to be analyzed; Among them, the process of identifying the tidal water level growth period with a high similarity to the time interval to be analyzed is as follows: Input the tidal water level value data sequence of the time interval to be analyzed into the trained tidal water level growth model, and output the predicted tidal water level value at the next time point of the time interval to be analyzed; Calculate the difference degree value between the predicted tidal water level value and the actual tidal water level value, and identify and obtain the similar growth period; Extract the minimum value of the difference degree value in the similar growth period, and mark it as the high-similarity tidal water level growth period; Based on the high-similarity tidal water level growth period, predict the time value when the tidal water level reaches the tidal water level warning value, and obtain the current prevention and control time period; The process of the difference degree value is as follows: The calculation formula for the difference degree value U is as follows: , where m is the number of tidal water level values in the time interval to be analyzed, is the p-th predicted tidal water level value, is the p-th actual tidal water level value; The process of obtaining the identified similar growth period is as follows: Obtain the difference degree values corresponding to all tidal water level growth periods, and mark the tidal water level growth periods with a value less than the difference degree threshold as similar tidal water level growth periods.

2. A float-type tidal prediction method for tidal water level monitoring according to claim 1, characterized in that, The process of obtaining the time interval to be analyzed is as follows: Extract the time interval during which the tidal water level value data at the early warning time point continues to grow.

3. A float-type tidal prediction method for tidal water level monitoring according to claim 1, characterized in that, The process of obtaining the current prevention and control time period and the historical prevention and control time period is as follows: Input the tidal water level warning value into the tidal water level growth model, output the predicted time value, calculate the difference between the predicted time value and the early warning time value, and obtain the current prevention and control time period.

4. A float - type tidal prediction method for tidal water level monitoring according to claim 1, characterized in that, It also includes the following steps: Analyze the current prevention and control time period and the historical prevention and control time period to obtain the current prevention and control measures.

5. A float-type tidal prediction method for tidal water level monitoring according to claim 4, characterized in that, The process of obtaining the current prevention and control measures is as follows: Obtain the prevention and control time period when the tidal water level in the historical data is between the early warning time point and the predicted time value, and mark it as the historical prevention and control time period. The historical data also includes the prevention and control measures corresponding to the historical prevention and control time period; Analyze and process each historical prevention and control time period, and calculate the prevention and control intensity value; Obtain all the time periods to be selected and the corresponding prevention and control intensity values, extract the minimum value of the prevention and control intensity value, and mark it as the finally selected time period; Use the prevention and control measures corresponding to the finally selected time period as the current prevention and control measures to conduct the current tidal water level prevention and control.

6. A float-type tidal prediction method for tidal water level monitoring according to claim 5, characterized in that, The process of obtaining the time period to be selected is as follows: Mark the historical prevention and control time periods greater than the current prevention and control time period as the time periods to be selected.

7. A float - type tidal prediction method for tidal water level monitoring according to claim 6, characterized in that, The process of obtaining the prevention and control intensity value is as follows: Obtain the historical tidal water level predicted value sequence and the historical tidal water level actual value corresponding to each historical prevention and control time period; Fit the change curves of the historical tidal water level predicted value and the historical tidal water level actual value; Calculate the areas of the closed figures formed by the change curve of the historical tidal water level predicted value and the X-axis and the change curve of the historical tidal water level actual value and the X-axis respectively, and conduct a difference calculation to obtain the area deviation value, and obtain the prevention and control intensity value.

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