Float type tide prediction method for tide water level monitoring

Abstract

The invention relates to the technical field of tide prediction, and discloses a float-type tide prediction method for tide water level monitoring, which comprises the following steps: acquiring tide water level value data of a growth trend before an early warning time point, marking the corresponding time as a to-be-analyzed time interval, performing similarity analysis in combination with a tide water level growth period, and obtaining a to-be-analyzed time interval; identifying a tidal water level increasing time period with high similarity with the to-be-analyzed time interval; predicting the time value when the tidal water level reaches the tidal water level warning value based on the high-similarity tidal water level increasing time period, and obtaining the current prevention and control time period. According to the method, the tidal water level prediction accuracy is improved, the model is constructed for each tidal water level increasing time period, the time period with high similarity with the to-be-analyzed interval is found for prediction, accurate model support is provided for prediction, proper prevention and control measures can be selected in combination with historical prevention and control data, and the prediction accuracy is improved. Resource utilization is optimized while disaster loss is reduced, and scientific and effective tidal water level prevention and control are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of tide prediction, and in particular to a float type tide prediction method for tidal water level monitoring. Background Art

[0002] In marine activities, the monitoring and early warning of tidal water levels are of vital importance and are directly related to navigation safety, fishery operations and marine engineering construction. As a classic means of water level monitoring, float-type tidal prediction captures water level changes by setting floats on the sea surface and using their characteristics of rising and falling with the tides. However, although float-type tidal prediction is widely used as a traditional means of water level monitoring, in actual use, the analysis of tidal water level change trends is not in-depth enough and cannot be accurately predicted, making it difficult for the accuracy of the prediction results to meet actual needs. When abnormal changes in tidal water levels occur and early warnings are issued, there is a lack of information on how to optimize resource utilization while ensuring prevention and control effects. This affects the safe development and sustainable development of marine activities. Summary of the invention

[0003] The object of the present invention is to provide a float type tide prediction method for tidal water level monitoring to solve at least one of the above-mentioned prior art problems.

[0004] The present invention provides a float type tide prediction method for tidal water level monitoring, comprising the following steps: Obtain the tidal water level value data of the growth trend before the warning time point, and 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 high similarity to the time interval to be analyzed; Based on the similarity high tidal water level growth period, the time value when the tidal water level reaches the tidal water level warning value is predicted to obtain the current prevention and control time period.

[0005] Beneficial effects of the present invention: 1. The float-type tidal prediction method provided by the present invention realizes real-time monitoring and early warning of tidal water levels. By using a float-type tidal water level monitoring device, the real-time tidal water level value is compared with the early warning value, and a corresponding signal is generated in time, so that relevant personnel can quickly grasp the change of tidal water level and determine the period of tidal water level growth. It not only intuitively presents the rising trend and provides key trend information for an accurate tidal prediction model, but also helps to extract characteristic parameters of tidal changes, analyze their laws and characteristics, and help researchers and relevant staff better understand tidal conditions; 2. The present invention improves the accuracy of tidal water level prediction. By constructing a model for each tidal water level growth period, the period with high similarity to the interval to be analyzed is found for prediction, providing more accurate model support for the prediction, and selecting appropriate prevention and control measures in combination with historical prevention and control data, thereby optimizing resource utilization while reducing disaster losses and realizing scientific and effective tidal water level control. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0007] Figure 1 It is a flow chart of a float type tide prediction method for tide level monitoring of the present invention; Figure 2 It is a structural schematic diagram of a float type tide prediction system for tide level monitoring of the present invention; Figure 3 The present invention is a structural schematic diagram of a float type tide prediction device for tidal water level monitoring.

[0008] In the figure: 3, computer device; 301, processor; 302, memory; 303, computer program. DETAILED DESCRIPTION

[0009] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0010] Embodiment 1 Figure 1A flowchart of a float-type tide prediction method for tidal water level monitoring provided in the first embodiment of the present invention, the embodiment of the present invention can be applied to the situation of tidal water level monitoring and prediction, the float-type tide prediction method for tidal water level monitoring can be executed by a float-type tide prediction system for tidal water level monitoring, the float-type tide prediction system for tidal water level monitoring can be implemented by software and / or hardware, and the float-type tide prediction system for tidal water level monitoring can be configured in a float-type tide prediction device for tidal water level monitoring. Optionally, a float-type tide prediction device for tidal water level monitoring can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, etc., and the embodiment of the present invention does not limit this.

[0011] The embodiment of the present invention provides a float type tide prediction method for tide level monitoring, which specifically includes the following steps: Step 1: Monitor the tidal water level in real time through a 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; In some embodiments, the predicted sea area is divided into a number of monitoring areas, based on any one of the monitoring areas; A float-type tidal water level monitoring device is used to monitor the tidal water level in real time; Among them, the float type tidal water level monitoring device is mainly composed 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 and the pulley. When the float moves, the displacement sensor is driven by the pulley and will be transmitted to the data acquisition system in real time; The data acquisition system collects and records the electrical signals transmitted by the displacement sensor at set time intervals; Compare the real-time tidal water level value with the tidal water level warning value, wherein the tidal water level warning value is set by technical personnel in this field based on experience, and the tidal water level warning value is less than the tidal water level warning value, and the tidal water level warning value is a key water level value determined comprehensively based on multiple factors such as the geographical environment of the area, historical tidal data, engineering design standards, and possible risks in the context of tidal-related engineering facilities; If the real-time tidal water level value is greater than or equal to the tidal water level warning value, a tidal water level warning signal is generated; otherwise, a tidal water level normal signal is generated; Obtain the monitoring area corresponding to the generated tidal water level warning signal and mark it as the risk monitoring area; Step 2: Based on the risk monitoring area, analyze the historical tidal water level data and identify the period of tidal water level increase; In some embodiments, based on any risk monitoring area, a time value corresponding to generating a tidal water level warning signal is obtained and marked as a warning time point; Mark the tidal water level value data before the warning time point as historical tidal water level value data; Preset monitoring period, wherein the monitoring period is set by technicians in this field based on the historical variation characteristics of tidal water level values; In each monitoring period, the historical tidal water level data series is {h1, h2, ..., hn}, the corresponding time series is {t1, t2, ..., tn}, and the time interval is , where i=1,2,…,n-1, and n represents the number of historical tidal water level data during the monitoring period; Starting from the second data point of the historical tidal water level value, the difference between the latter tidal water level value and the previous tidal water level value of two adjacent data points is calculated in turn to obtain the tidal water level deviation value; If the tidal water level deviation value is greater than zero, the time interval corresponding to the two tidal water level values ​​is marked as a tidal water level growth interval, otherwise, it is marked as a tidal water level non-growth interval; Count the number of all tidal water level growth intervals during the monitoring period, and calculate the ratio with the number of all time intervals during the monitoring period to obtain the ratio of the number of growth intervals; Set the percentage threshold of the number of growth intervals. If the percentage of the number of growth intervals is greater than the percentage threshold, the monitoring period is marked as a tidal water level growth period; otherwise, it is marked as a tidal water level non-growth period. The reason for clarifying the tidal water level growth period is that it allows researchers and relevant staff to intuitively understand the time periods during which the tidal water level is in an upward trend, providing key trend information for subsequent more accurate tidal prediction models. The determination of the growth period is also helpful in extracting characteristic parameters of tidal changes, such as growth rate and growth cycle, and analyzing the laws and characteristics of tidal changes. The technical solution of this embodiment is: monitor the tidal water level in real time through a float-type tidal water level monitoring device, compare the real-time tidal water level value with the warning value set according to experience, generate a warning signal if it is greater than or equal to the warning value, otherwise generate a normal signal, then obtain the warning time point based on the warning signal, and use the tidal water level value before it as historical data. Within a preset monitoring period, analyze the historical data, calculate the water level difference between adjacent data points to determine the growth interval, and count the proportion of the number of growth intervals. If it is greater than the set threshold, it is marked as a tidal water level growth period; This will enable real-time monitoring and early warning of tidal water levels, intuitively present the rising trend of tidal water levels, provide key trend information for accurate tidal prediction models, and help extract characteristic parameters of tidal changes, analyze their laws and characteristics, and help researchers and related staff better understand tidal conditions.

[0012] Embodiment 2 Based on the above embodiments, Figure 1 As shown, a float-type tide prediction method for tidal water level monitoring provided by an embodiment of the present invention specifically includes the following steps: 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, and 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 high similarity to the time interval to be analyzed; In some embodiments, the warning time point is obtained, and the historical tidal water level value data sequence is obtained as {h1, h2, ..., hn}, and the corresponding time series is {t1, t2, ..., tn}; Starting from the data point closest to the warning time point, traverse the historical tidal water level value data in reverse chronological order, obtain the time interval with the most recent growth trend before the warning time point, and mark it as the time interval to be analyzed; For example, the data point closest to the warning time point is , then starting from j, let , keep moving forward i; In 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 and repeat the calculation of the change value to determine whether it continues to grow; Once the change value is less than or equal to zero, the traversal stops. At this time, from the last data point that satisfies the change value greater than zero to The corresponding time interval is the most recent time interval with a growth trend before the warning time point; Obtain the tidal water level value data sequence for the time interval to be analyzed; Obtain all tidal water level growth periods and the corresponding tidal water level value data, and build a long short-term memory network (LSTM) model based on the tidal water level value data of each growth period, that is, the tidal water level growth model corresponding to the growth period; The specific process of constructing the tidal water level growth model is as follows: Determine the structure of the LSTM model, which includes one or more LSTM layers and an optional fully connected layer (Dense layer); For example, a model consisting of 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, which can capture the long-term dependencies and complex patterns in the tidal level time series. The second LSTM layer is also set with 64 neurons to further extract features from the data. Finally, the features output by the LSTM layer are mapped to a scalar value through the fully connected layer, that is, the predicted tidal level value at the next time point. In the process of model building, the choice of activation function also needs to be considered. The LSTM layer usually uses the sigmoid function and the tanh function to control the gating mechanism and cell state update. The fully connected layer can use the linear activation function (that is, 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. Select an appropriate loss function. Since the tidal water level is predicted, the mean square error (MSE) is a commonly used loss function, which can measure the average square error between the predicted value and the actual value; Select an optimizer to update the model weights. For example, the Adam optimizer is a commonly used optimizer that combines the advantages of Adagrad and RMSProp and can adaptively adjust the learning rate. You can set the learning rate of the Adam optimizer to, for example, 0.001. This value can be adjusted through experiments to obtain the best training effect. The tidal water level value data sequence of the time interval to be analyzed is input into the trained tidal water level growth model, and the input data is processed to output the predicted tidal water level value at the next time point in the time interval to be analyzed; The calculation formula for the difference value U between the predicted tidal water level value and the actual tidal water level value is: , where m is the number of tidal water level values ​​in the time interval to be analyzed, is the pth predicted tidal level value, is the actual tidal water level value of the pth time; It should be noted that the tidal water level data for the time interval to be analyzed is the actual tidal water level value; The difference degree value reflects the ratio of the average deviation between the predicted value and the actual value to the sum of the means of the two. 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 means that the deviation between the predicted value and the actual value is relatively large, and the accuracy of the prediction needs to be improved. Obtain the difference degree values ​​corresponding to all tidal water level growth periods, set the difference degree threshold, and mark the tidal water level growth period that is less than the difference degree threshold as a similar tidal water level growth period, otherwise, mark it as a non-similar tidal water level growth period; The minimum value of the difference degree value in the similar growth period is extracted and marked as the similarity high tidal water level growth period; It should be noted that if there is no similar tidal water level increase period, it is necessary to 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., which affect tidal changes; First, by constructing the tidal water level growth model of all growth periods, and then judging the tidal water level growth period with high similarity to the tidal water level value data sequence of the interval to be analyzed, the role is: first, to provide more accurate model support for subsequent predictions. Different tidal water level growth periods have different change rules. By constructing an LSTM model for each growth period, the relationship between the tidal water level changes in the period can be deeply explored. When a growth period with high similarity to the interval to be analyzed is found, the law learned by the model of the period is used to predict the subsequent tidal water level of the interval to be analyzed, thereby significantly improving the accuracy of the prediction; second, it can increase the accuracy of the prediction. 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 the historical growth period, the abnormal trend of tidal water level changes can be discovered in time, and disaster warnings such as storm surges can be issued in advance. For example, if it is found that the interval to be analyzed is similar to the tidal water level growth period when a storm surge occurred in history, the time when the tidal water level reaches the warning value can be predicted, and then the corresponding disaster prevention plan can be launched in time to evacuate personnel and strengthen facilities to reduce the losses caused by the disaster; Step 4: Based on the similarity high tidal water level growth period, predict the time value when the tidal water level reaches the tidal water level warning value, and obtain the corresponding prevention and control measures; In some embodiments, based on similar high tidal water level growth periods, a corresponding tidal water level growth model is obtained; 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, and obtain the current prevention and control time period; The prevention and control time period is used by technical personnel to make advance prevention and control adjustments and reasonable scheduling within the time when the tidal water level reaches the tidal water level warning value; Obtain the control time period from the warning time point to the predicted time value of the tidal water level in the historical data, and mark it as the historical control time period; Among them, historical data also includes prevention and control measures corresponding to the historical prevention and control time period; It should be noted that the extracted historical prevention and control time period is the data of effective prevention and control results, that is, after the tidal water level value reaches the tidal water level warning value and technical personnel have taken prevention and control measures, the data at the end of the prevention and control time period is the data of reaching the tidal water level warning value; Based on each historical prevention and control period, the corresponding historical tidal water level prediction value sequence and historical tidal water level actual value are obtained, wherein the historical tidal water level actual value is the actual value of the tidal water level monitored after the prevention and control measures have been taken; In a two-dimensional coordinate system, draw the historical tidal water level prediction value change curve and the historical tidal water level actual value change curve; Calculate the area of ​​the closed figure formed by the historical tidal water level prediction value change curve and the X-axis and the area of ​​the closed figure formed by the historical tidal water level actual value change curve and the X-axis respectively, and perform difference calculation to obtain the area deviation value, which is the prevention and control intensity value; The reason for taking the area deviation value as the prevention and control intensity value is that the closed figure area enclosed by the historical tidal water level prediction value change curve and the X-axis, and the closed figure area enclosed by the historical tidal water level actual value change curve and the X-axis, respectively reflect the predicted tidal water level changes and the actual tidal water level changes during the historical prevention and control period from different angles. By calculating the difference between the two areas to obtain the area deviation value, this change difference can be quantified, intuitively reflecting the degree of deviation between the predicted value and the actual value, thereby measuring the impact of prevention and control measures on tidal water level changes under historical circumstances, that is, the prevention and control intensity; Compare the historical prevention and control time periods with the current prevention and control time periods, mark the historical prevention and control time periods that are greater than the current protection time period as the time period to be selected, and mark the historical prevention and control time periods that are less than or equal to the current protection time period as the non-selected time period; Get 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 value, and mark it as the final selected time period; Use the prevention and control measures corresponding to the final selected time period to carry out current tidal water level control; The reason for selecting the minimum value of the prevention and control intensity is that the prevention and control intensity value actually reflects the resource input and operation intensity in the prevention and control process. A smaller prevention and control intensity value means that on the premise of achieving effective prevention and control, the human, material, financial and other resources consumed are relatively less, or the prevention and control operations taken are relatively simple. Selecting the minimum value can avoid the waste of resources caused by excessive prevention and control on the basis of ensuring the prevention and control effect, realize the reasonable allocation and efficient use of resources, and enable relevant personnel to dispatch resources more scientifically and obtain the maximum prevention and control benefit with the minimum investment; The technical solution of this embodiment is: by obtaining the tidal water level value data of the growth trend before the warning time point and the time interval to be analyzed, a long-short term memory network model of each tidal water level growth period is constructed, the time interval data to be analyzed is input into the model to obtain a predicted value, and the tidal water level growth period with high similarity is screened out by calculating the difference between the predicted value and the actual value, and then the corresponding tidal water level growth model is obtained based on the period, the tidal water level warning value is input to obtain the predicted time value, the current prevention and control time period is calculated, and by comparing the relevant data of the historical prevention and control time period, the prevention and control measures corresponding to the historical prevention and control time period with the smallest prevention and control intensity value are selected to carry out the current tidal water level prevention and control; This can provide more accurate model support for tidal water level prediction, improve prediction accuracy by using model rules for similar time periods, detect abnormal tidal water level trends in a timely manner, issue disaster warnings in advance, and select appropriate prevention and control measures to optimize resource utilization and reduce disaster losses while ensuring prevention and control effects.

[0013] Embodiment 3 Based on the above embodiments, Figure 2 As shown, a float type tide prediction system for tide level monitoring provided by an embodiment of the present invention specifically includes: Risk monitoring area acquisition module: real-time monitoring of tidal water level through float type, identification of real-time tidal water level value data, generation of tidal water level warning signal, and acquisition of risk monitoring area; Water level growth period acquisition module: Based on the risk monitoring area, analyze the historical tidal water level data and identify the tidal water level growth period; 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, and 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 high similarity to the time interval to be analyzed; Water level prediction and control module: similarity high tidal water level growth period, 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.

[0014] Embodiment 4 like Figure 3 As shown, an embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored on the memory 302. When the computer program 303 is executed on the processor 301, a float-type tide prediction method for tidal water level monitoring as described in any one of the above methods is implemented.

[0015] The computer device 3 may be a computing device such as a desktop computer, a notebook, a palm computer, a cloud server, etc. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302 .

[0016] Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0017] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0018] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a 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 memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0019] Embodiment 5 An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program implements a float-type tide prediction method for tidal water level monitoring as described in any one of the above methods.

[0020] 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, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0021] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0022] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0023] In the embodiments disclosed in the present application, it should be understood that the disclosed apparatus / terminal equipment and method can be implemented in other ways. For example, the apparatus / terminal equipment embodiments described above are only illustrative, for example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0024] Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, which may be electrical, mechanical or other forms.

[0025] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0026] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0027] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A float type tide prediction method for tidal water level monitoring, characterized in that: The following steps are involved: Obtain the tidal water level value data of the growth trend before the warning time point, and 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 high similarity to the time interval to be analyzed; Among them, the process of identifying the tidal water level growth period with high similarity to the time interval to be analyzed is: 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 in the time interval to be analyzed; Calculate the difference between the predicted tidal water level and the actual tidal water level, and identify similar growth periods; The minimum value of the difference degree value in the similar growth period is extracted and marked as the similarity high tidal water level growth period; Based on the similarity high tidal water level growth period, the time value when the tidal water level reaches the tidal water level warning value is predicted to obtain the current prevention and control time period.

2. A float type tide 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 of continuous growth of tidal water level data at the warning time point.

3. A float type tide prediction method for tidal water level monitoring according to claim 1, characterized in that: The process of the difference degree value is: The calculation formula of the difference degree value U is: , where m is the number of tidal water level values ​​in the time interval to be analyzed, is the pth predicted tidal level value, is the actual tidal water level value at the pth time.

4. A float type tide prediction method for tidal water level monitoring according to claim 1, characterized in that: The process of identifying and acquiring similar growth periods is as follows: Obtain the difference degree values ​​corresponding to all tidal water level growth periods, and mark the tidal water level growth periods that are less than the difference degree threshold as similar tidal water level growth periods.

5. A float type tide prediction method for tide 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: The tidal water level warning value is input into the tidal water level growth model, the predicted time value is output, and the difference between the predicted time value and the warning time value is calculated to obtain the current prevention and control time period.

6. A float type tide prediction method for tide level monitoring according to claim 1, characterized in that: The following steps are also included: Analyze the current prevention and control time period and the historical prevention and control time period to obtain current prevention and control measures.

7. A float type tide prediction method for tide level monitoring according to claim 6, characterized in that: The process of obtaining the current prevention and control measures is as follows: Obtain the control time period from the warning time point to the predicted time value of the tidal water level in the historical data, marked as the historical control time period. The historical data also includes the control measures corresponding to the historical control time period; Analyze and process each historical prevention and control period and calculate the prevention and control intensity value; Get 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 final selected time period; Use the prevention and control measures corresponding to the final selected time period as the current prevention and control measures to carry out current tidal water level control.

8. A float type tide prediction method for tide level monitoring according to claim 7, characterized in that: The process of obtaining the time period to be selected is as follows: Mark the historical prevention and control time periods that are longer than the current protection time period as the time period to be selected.

9. A float type tide prediction method for tide level monitoring according to claim 7, characterized in that: The process of obtaining the prevention and control intensity value is as follows: Obtain the historical tidal water level prediction value sequence and historical tidal water level actual value corresponding to each historical prevention and control time period; Fitting the historical tidal water level prediction value change curve and the historical tidal water level actual value change curve; The area of ​​the closed figure enclosed by the historical tidal water level prediction value change curve and the X-axis and the area of ​​the closed figure enclosed by the historical tidal water level actual value change curve and the X-axis are calculated respectively, and the difference is calculated to obtain the prevention and control intensity value.

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