Section erosion and deposition deformation equation obtaining method and device, equipment and medium

Abstract

The invention relates to the technical field of computers, and discloses a section erosion and deposition deformation equation obtaining method, device and equipment and a medium, and the method comprises the steps: predicting the erosion and deposition area of a target section according to the river channel data of the target section, the erosion and deposition deformation empirical parameters, the iteration period time length and the correction coefficient. According to the predicted erosion and deposition area of the target section, the actual erosion and deposition area, the river channel data, the iteration adjustment coefficient and the time duration of the iteration period, the variable quantity of the correction coefficient is obtained. And when it is determined that the iteration period is within the period range specified by the iteration stopping condition and the variable quantity of the correction coefficient does not meet the iteration stopping condition, entering the next iteration period. And according to the variable quantity of the correction coefficient of the iteration period and the correction coefficient, determining the correction coefficient of the next iteration period and the variable quantity of the correction coefficient, and obtaining the final correction coefficient until the variable quantity of the correction coefficient obtained in the target iteration period meets the iteration stopping condition and the target iteration period is within the period range.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and particularly to a method, device, equipment and medium for obtaining a cross-section scouring and silting deformation equation. Background Art

[0002] The existing calculation of the change in the scouring and silting area of a river channel cross-section is obtained based on a water and sediment mathematical model, and the change in the cross-sectional area at each moment and each cross-section is solved, wherein the model includes a scouring and silting deformation equation.

[0003] Among them, the scouring and silting deformation equation for solving the change in the cross-sectional area includes 4 mutually independent empirical parameters, and the values need to be given manually respectively. The method for manually giving the empirical parameters is as follows: After setting the values based on experience and running the model, compare the area change calculated by the model with the measured cross-sectional area change, and perform manual adjustment according to the gap and then perform repeated calculations. In most cases, the measured sediment data is relatively scarce, and it is difficult to determine the values of the 4 empirical parameters based on the limited measured data.

[0004] Since these 4 parameters need to be given for each cross-section, and the cross-sections included in the reservoir or river channel target area included in the model may reach hundreds or thousands, it is unrealistic for researchers to manually test the 4 parameters of all cross-sections. Usually, the values are simply segmented, that is, the river channel is segmented, and the values of the empirical parameters of all cross-sections in the same river section are the same, so as to reduce the workload of adjusting parameters, but this will obviously result in a loss of simulation accuracy. Summary of the Invention

[0005] In view of this, the present invention provides a method, device, equipment and medium for obtaining a cross-section scouring and silting deformation equation, so as to solve the problem of loss of simulation accuracy caused by manually giving the values of empirical parameters respectively and then manually adjusting each parameter according to the measured cross-sectional area, and the values of the empirical parameters of all cross-sections in the same river section being the same.

[0006] In a first aspect, the present invention provides a method for obtaining a cross-section scouring and silting deformation equation, the method comprising:

[0007] Input the river channel data in the target cross-section to be obtained, the scouring and silting deformation empirical parameters corresponding to the target cross-section, the time length corresponding to the iteration period, and the correction coefficient of the scouring and silting area of the target cross-section in the current iteration period into a pre-configured cross-section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target cross-section in the current iteration period, wherein the target cross-section is any one of multiple cross-sections included in the target area;

[0008] Obtain the change amount of the correction coefficient in the current iteration period according to the predicted scouring and silting area corresponding to the target cross-section, the actually measured scouring and silting area corresponding to the target cross-section to be obtained, the river channel data, the pre-configured iteration adjustment coefficient, and the time length corresponding to the iteration period;

[0009] When it is determined that the current iteration period is within the period range specified by the iteration stop condition and the change amount of the correction coefficient does not meet the iteration stop condition, enter the next iteration period. Determine the correction coefficient of the next iteration period according to the change amount of the correction coefficient and the correction coefficient of the current iteration period, and re-determine the change amount of the correction coefficient in the next iteration period;

[0010] Until the change amount of the correction coefficient obtained in the first target iteration period finally meets the iteration stop condition and the first target iteration period is within the period range, obtain the final change amount of the correction coefficient. The first target iteration period is any iteration period after the current iteration period;

[0011] Determine the final correction coefficient according to the correction coefficient of the previous period of the first target iteration period and the change amount of the correction coefficient determined in the first target iteration period;

[0012] Update the cross-section erosion and deposition deformation equation according to the final correction coefficient to obtain the final cross-section erosion and deposition deformation equation.

[0013] A method for obtaining a cross-section erosion and deposition deformation equation provided by the present invention has the following advantages:

[0014] After predicting the erosion and deposition area in the current iteration period by this method according to the river channel data, erosion and deposition deformation empirical parameters of the target cross-section, and the time length of the current iteration period, combined with the correction coefficient. Then, by comparing the predicted erosion and deposition area with the actual erosion and deposition area, combined with the iteration adjustment coefficient and the iteration period time length, calculate the change amount of the correction coefficient. If the change amount of the correction coefficient in the current iteration period does not meet the iteration stop condition, enter the next iteration period, update the correction coefficient and continue the calculation. When the change amount of the correction coefficient meets the preset iteration stop condition, end the iteration and obtain the final correction coefficient. Apply the final correction coefficient to the cross-section erosion and deposition area calculation equation to accurately simulate the change of the erosion and deposition area of the reservoir river channel cross-section. By automatically iteratively adjusting a single parameter of the correction coefficient, it reduces the calculation time and labor cost of manually trying multiple empirical parameter values. And for each cross-section, the appropriate correction coefficient corresponding to the cross-section is obtained according to the above method for obtaining the cross-section erosion and deposition deformation equation, avoiding the loss of simulation accuracy caused by the same empirical parameter value for all cross-sections in the same river reach.

[0015] In an optional implementation manner, the river channel data includes: the sediment concentration of the target cross-section, the water surface width information, the water flow velocity information, and the water depth information of the target cross-section;

[0016] Predict the scouring and silting area corresponding to the target section in the current iteration cycle according to the pre-acquired river channel data in the target section, the scouring and silting deformation experience parameters corresponding to the target section, the time length corresponding to the iteration cycle, and the correction coefficient of the scouring and silting area of the target section in the current iteration cycle, specifically including:

[0017] Determine the sediment-carrying capacity parameter of the target section according to the water flow velocity information, the scouring and silting deformation experience parameters, the acceleration of gravity, and the water depth information of the target section;

[0018] Input the sediment concentration, the sediment-carrying capacity parameter, the water surface width information, the scouring and silting deformation experience parameters, and the correction coefficient into the pre-configured section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target section in the current iteration cycle.

[0019] Specifically, by combining the actual river channel data to determine key parameters (such as sediment concentration, sediment-carrying capacity parameter, scouring and silting deformation experience parameters, etc.) for predicting the scouring and silting area, it can more comprehensively reflect the actual scouring and silting situation of the river channel and more accurately predict the scouring and silting area of the target section.

[0020] In an alternative embodiment, the scouring and silting deformation experience parameters include: the dry density of sediment corresponding to the target section, the recovery saturation coefficient of the target section, and the sediment settling velocity of the target section;

[0021] Input the sediment concentration, the sediment-carrying capacity parameter, the water surface width information, the scouring and silting deformation experience parameters, and the correction coefficient into the pre-configured section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target section in the current iteration cycle. The pre-configured section scouring and silting deformation equation is expressed by the following expression:

[0022]

[0023] Wherein, i is the identification information of the target section, ρ’ is the dry density of sediment corresponding to the target section, A i is the scouring and silting area corresponding to the target section to be predicted in the current iteration cycle, t is the time length corresponding to the iteration cycle, α i is the recovery saturation coefficient of the target section, w i is the sediment settling velocity of the target section, B i is the water surface width information of the target section, S i is the sediment concentration in the target section, S i,* is the sediment-carrying capacity parameter of the target section, and β is the correction coefficient of the target section.

[0024] Specifically, the model incorporates empirical parameters such as dry unit weight of sediment, sediment settling velocity, and recovery saturation coefficient. Each of these empirical parameters has a clear physical meaning, making the model highly scientific and reliable. Additionally, a correction coefficient β is introduced, and the model dynamically adjusts the value of the correction coefficient β according to the actual situation, adjusts the predicted scouring and silting area result, reduces the dependence on initial parameters, avoids calculation errors caused by improper parameter selection in traditional methods, and further improves the prediction accuracy.

[0025] In an alternative embodiment, the river channel data further includes: the spacing information between the target cross-section and the next cross-section adjacent to the target cross-section in the target area. Based on the predicted scouring and silting area corresponding to the target cross-section, the pre-acquired actual scouring and silting area corresponding to the target cross-section, the river channel data, the pre-configured iterative adjustment coefficient, and the time length corresponding to the iterative cycle, the change amount of the correction coefficient in the current iterative cycle is obtained, specifically including:

[0026] Based on the predicted scouring and silting area corresponding to the target cross-section and the pre-acquired actual scouring and silting area corresponding to the target cross-section, determine the scouring and silting area error amount;

[0027] Based on the spacing information, the time length corresponding to the iterative cycle, the scouring and silting area error amount, and the iterative adjustment coefficient, determine the change amount of the correction coefficient in the current iterative cycle.

[0028] Specifically, based on the spacing information, the time length corresponding to the iterative cycle, and the scouring and silting area error amount, determine the change amount of the correction coefficient in the current iterative cycle. By introducing the iterative adjustment coefficient (λ) to control the iterative step size, optimize the calculation efficiency, and ensure the convergence rate of the change amount of the correction coefficient.

[0029] In an alternative embodiment, based on the spacing information, the time length corresponding to the iterative cycle, the scouring and silting area error amount, and the iterative adjustment coefficient, determine the change amount of the correction coefficient in the current iterative cycle, which is expressed by the following expression:

[0030]

[0031] Where, Δβ is the change amount of the correction coefficient in the current iterative cycle, ΔA is the scouring and silting area error amount of the target cross-section, Δx is the spacing information, Δt is the time length corresponding to the iterative cycle, and λ is the iterative adjustment coefficient, which is used to control the iterative rate and convergence.

[0032] Specifically, for each target cross-section, the spacing information (Δx) and the iterative cycle time length (Δt) in the expression are fixed. When the change amount of the correction coefficient (Δβ) is smaller, it proves that the scouring and silting area error amount (ΔA) is smaller, and the scouring and silting area prediction module is more accurate.

[0033] In an alternative embodiment, when it is determined that the first target iteration period is within the period range specified by the iteration stop condition, determining whether the change amount of the correction coefficient obtained in the first target iteration period meets the iteration stop condition includes:

[0034] When the absolute value of the change amount of the correction coefficient determined in the first target iteration period is less than or equal to the first preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the iteration stop condition;

[0035] Or, when the change amount of the correction coefficient obtained in each of a continuous preset number of iteration periods including the first target iteration period is greater than the first preset threshold, but the difference between the change amounts of the correction coefficients obtained in every two adjacent iteration periods is less than or equal to the second preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the iteration stop condition.

[0036] Specifically, when the absolute value of the change amount of the correction coefficient determined in the first target iteration period is less than or equal to the first preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the iteration stop condition. By setting clear stop conditions, it is ensured that the iterative process terminates when the accuracy requirements are met. When the change amount of the correction coefficient in multiple consecutive iteration periods is greater than the first preset threshold, but the difference in the change amount between adjacent periods is less than or equal to the second preset threshold, it indicates that the model is already close to the convergence state, and continuing the iteration cannot significantly improve the result. At this time, stopping the iteration can avoid unnecessary waste of computing resources.

[0037] In an alternative embodiment, when it is determined that the first target iteration period is not within the period range specified by the iteration stop condition, the method further includes:

[0038] According to the predicted scouring and silting area corresponding to the target cross-section obtained in each iteration period and the actual scouring and silting area corresponding to the target cross-section, respectively determine the error amount of the scouring and silting area of the target cross-section in each iteration period;

[0039] When it is determined that the error amount of the scouring and silting area of the target cross-section continuously decreases in all iteration periods including the target iteration period, after increasing the value of the iteration adjustment coefficient according to the preset adjustment rule, re-obtain the change amount of the correction coefficient in each iteration period until the change amount of the correction coefficient finally obtained in the second target iteration period meets the iteration stop condition, and the second target iteration period is within the period range. At this time, obtain the final change amount of the correction coefficient, where the second target iteration period is any iteration period after re-counting the iteration period after the first target iteration period.

[0040] Specifically, by monitoring the scouring and silting area error amount in each iteration cycle and dynamically adjusting the iteration adjustment coefficient according to the change trend of the error amount, the iteration process is optimized to more efficiently approach the true value. When the error amount of the scouring and silting area of the target section continues to decrease, it indicates that the model is gradually approaching the true value. At this time, by increasing the iteration adjustment coefficient, the convergence speed can be accelerated, the number of iterations can be reduced, and the calculation efficiency can be improved.

[0041] In an alternative embodiment, when, in a continuous preset number of iteration cycles including the first target iteration cycle, the change amount of the correction coefficient obtained in each iteration cycle is greater than a first preset threshold, and the difference between the change amounts of the correction coefficients obtained in every two adjacent iteration cycles is greater than a second preset threshold, the method further includes:

[0042] After reducing the value of the iteration adjustment coefficient according to a preset adjustment rule, the change amount of the correction coefficient in each iteration cycle is obtained again until the change amount of the correction coefficient obtained in the third target iteration cycle meets the iteration stop condition and the third target iteration cycle is within the cycle range, and the final change amount of the correction coefficient is obtained, where the third target iteration cycle is any iteration cycle after re-counting the iteration cycles after the first target iteration cycle.

[0043] Specifically, when the change amount of the correction coefficient continues to be large and the difference in the change amounts between adjacent iteration cycles is also large, it indicates that the iteration process may be too intense, resulting in the model results oscillating near the target value and unable to converge stably. By reducing the iteration adjustment coefficient, the iteration speed is slowed down to keep the model stable.

[0044] In an alternative embodiment, when, after adjusting the value of the iteration adjustment coefficient according to a preset adjustment rule and re-counting the iteration cycles, the change amount of the correction coefficient obtained in any cycle within the cycle range still does not meet the iteration stop condition, the method further includes:

[0045] Obtaining the correction coefficient corresponding to the iteration cycle corresponding to the minimum change amount of the correction coefficient within the cycle range as the final correction coefficient.

[0046] Specifically, during the iteration process, if the change amount of the correction coefficient never meets the iteration stop condition and the error amount of the scouring and silting area corresponding to the minimum change amount of the correction coefficient is also the smallest, then selecting the correction coefficient corresponding to the smallest change amount as the final result is the optimal solution, avoiding the problem of being unable to draw a conclusion due to an infinite loop in the iteration process.

[0047] In a second aspect, the present invention provides a device for obtaining a cross-section scouring and silting deformation equation, the device includes:

[0048] A prediction module, configured to input the river channel data in a target cross-section obtained in advance, the scouring and silting deformation empirical parameters corresponding to the target cross-section, the time length corresponding to an iteration period, and the correction coefficient of the scouring and silting area of the target cross-section in the current iteration period into a pre-configured cross-section scouring and silting deformation equation, and predict the scouring and silting area corresponding to the target cross-section in the current iteration period, where the target cross-section is any one of multiple cross-sections included in a target area;

[0049] A processing module, configured to obtain the change amount of the correction coefficient in the current iteration period according to the predicted scouring and silting area corresponding to the target cross-section, the actually obtained scouring and silting area corresponding to the target cross-section, the river channel data, the pre-configured iteration adjustment coefficient, and the time length corresponding to the iteration period; when it is determined that the current iteration period is within the period range specified by the stop iteration condition and the change amount of the correction coefficient does not meet the stop iteration condition, enter the next iteration period, determine the correction coefficient of the next iteration period according to the change amount of the correction coefficient and the correction coefficient of the current iteration period, and re-determine the change amount of the correction coefficient in the next iteration period; until finally the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition and the first target iteration period is within the period range, obtain the final change amount of the correction coefficient, where the first target iteration period is any iteration period after the current iteration period;

[0050] A determination module, configured to determine the final correction coefficient according to the correction coefficient of the previous period of the first target iteration period and the change amount of the correction coefficient determined in the first target iteration period;

[0051] The processing module is further configured to update the cross-section scouring and silting deformation equation according to the final correction coefficient to obtain the final cross-section scouring and silting deformation equation.

[0052] The cross-section scouring and silting deformation equation acquisition device provided by the present invention has the following advantages:

[0053] After predicting the scouring and silting area within the current iteration cycle based on the river channel data of the target section, the scouring and silting deformation empirical parameters, and the time length of the current iteration cycle, and combining with the correction coefficient, by comparing the predicted scouring and silting area with the actual scouring and silting area, and combining with the iterative adjustment coefficient and the time length of the iteration cycle, the change amount of the correction coefficient is calculated. If the change amount of the correction coefficient in the current iteration cycle does not meet the stop iteration condition, enter the next iteration cycle, update the correction coefficient and continue the calculation. When the change amount of the correction coefficient meets the preset stop iteration condition, end the iteration and obtain the final correction coefficient. Apply the final correction coefficient to the cross-section scouring and silting area calculation equation to accurately simulate the change of the scouring and silting area of the reservoir river channel section. By automatically iteratively adjusting a single parameter of the correction coefficient, it reduces the calculation time and labor cost of manually trying multiple empirical parameter values. And for each section, the appropriate correction coefficient corresponding to the section is obtained according to the above-mentioned device for obtaining the cross-section scouring and silting deformation equation, avoiding the same empirical parameter values for all sections in the same river reach, and improving the simulation accuracy of the scouring and silting change of the water passing area of each section of the reservoir river channel.

[0054] In a third aspect, the present invention provides a computer device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the method for obtaining the cross-section scouring and silting deformation equation according to the first aspect or any corresponding implementation manner thereof.

[0055] In a fourth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the method for obtaining the cross-section scouring and silting deformation equation according to the first aspect or any corresponding implementation manner thereof.

[0056] In a fifth aspect, the present invention provides a computer program product, including computer instructions, and the computer instructions are used to cause a computer to execute the method for obtaining the cross-section scouring and silting deformation equation according to the first aspect or any corresponding implementation manner thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required to be used in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are 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.

[0058] Figure 1 It is a schematic flow chart of a method for obtaining a cross-section scouring and silting deformation equation provided by an embodiment of the present invention;

[0059] Figure 2It is a schematic flowchart of another method for obtaining the cross-section erosion and deposition deformation equation provided by an embodiment of the present invention;

[0060] Figure 3 It is a schematic flowchart of yet another method for obtaining the cross-section erosion and deposition deformation equation provided by an embodiment of the present invention;

[0061] Figure 4 It is a structural block diagram of a method for obtaining the cross-section erosion and deposition deformation equation of cross-section S258 provided by an embodiment of the present invention;

[0062] Figure 5 It is a structural block diagram of a method for obtaining the cross-section erosion and deposition deformation equation of cross-section S311 provided by an embodiment of the present invention;

[0063] Figure 6 It is a structural block diagram of a method for obtaining the cross-section erosion and deposition deformation equation of cross-section S382 provided by an embodiment of the present invention;

[0064] Figure 7 It is a structural block diagram of a device for obtaining the cross-section erosion and deposition deformation equation provided by an embodiment of the present invention;

[0065] Figure 8 It is a schematic diagram of the hardware structure of a computer device provided by an embodiment of the present invention. Specific embodiments

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0067] The existing calculation of the change in the erosion and deposition area of the river channel cross-section is obtained based on a water and sediment mathematical model, and the change in the cross-sectional area at each moment and each cross-section is solved, where the model includes an erosion and deposition deformation equation.

[0068] Among them, the erosion and deposition deformation equation for solving the change in the cross-sectional area includes 4 mutually independent empirical parameters, and the values need to be manually given separately. The method for manually giving the empirical parameters is as follows: After setting the values based on experience and running the model, compare the area change calculated by the model with the measured cross-sectional area change, and perform manual adjustment according to the gap and then repeat the calculation. In most cases, the measured sediment data is relatively scarce, and it is difficult to determine the values of the 4 empirical parameters based on the limited measured data.

[0069] Since these four parameters need to be given for each cross-section, and the number of cross-sections in the target area of a reservoir or a river channel can reach hundreds or thousands, it is unrealistic for researchers to manually adjust and test the four parameters of all cross-sections. Usually, they simply take values by segment, that is, divide the river channel into segments, and the empirical parameter values of all cross-sections in the same river segment are the same, so as to reduce the workload of adjusting parameters. However, this will obviously result in a loss of simulation accuracy.

[0070] To solve the above problems, an embodiment of the present invention provides an embodiment of a method for obtaining a cross-section scouring and silting deformation equation. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system (computer device) including a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0071] As mentioned above, the number of cross-sections in the target area of a reservoir or a river channel can reach hundreds or thousands, and the empirical parameter values of each cross-section will be different. To solve the problem of manually giving four empirical parameter values and then separately adjusting the four empirical parameters according to the measured cross-sectional area, this embodiment provides a method for obtaining a cross-section scouring and silting deformation equation, providing a correction coefficient for each cross-section, and automatically adjusting the correction coefficient to replace manually adjusting the four empirical parameters. This can be used in the above-mentioned terminal devices in this embodiment, such as mobile phones, tablet computers, etc. Figure 1 is a schematic flowchart of a method for obtaining a cross-section scouring and silting deformation equation provided by an embodiment of the present invention. As Figure 1 shown, this process includes the following steps:

[0072] Step S101, input the river channel data in the target cross-section to be obtained, the scouring and silting deformation empirical parameters corresponding to the target cross-section, the time length corresponding to the iteration period, and the correction coefficient of the scouring and silting area of the target cross-section in the current iteration period into a pre-configured cross-section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target cross-section in the current iteration period.

[0073] Among them, the target cross-section is any one of the multiple cross-sections included in the target area.

[0074] Specifically, the river channel data in the target cross-section to be obtained, the scouring and silting deformation empirical parameters corresponding to the target cross-section, the time length corresponding to the iteration period, and the correction coefficient of the scouring and silting area of the target cross-section in the current iteration period can be substituted into the cross-section scouring and silting deformation equation, and the scouring and silting deformation equation can be solved to obtain the predicted scouring and silting area corresponding to the target cross-section.

[0075] Step S102: Obtain the change amount of the correction coefficient within the current iteration period based on the predicted scouring and silting area corresponding to the target cross-section, the actually obtained scouring and silting area corresponding to the target cross-section in advance, the river channel data, the pre-configured iterative adjustment coefficient, and the time length corresponding to the iteration period.

[0076] Specifically, pre-construct an equation for solving the change amount of the correction coefficient, and substitute the predicted scouring and silting area corresponding to the target cross-section calculated by the scouring and silting deformation equation as described above, the actually obtained scouring and silting area corresponding to the target cross-section at the same moment from the measured data, the river channel data, the pre-configured iterative adjustment coefficient, and the time length corresponding to the iteration period into the pre-constructed equation for the change amount of the correction coefficient to obtain the change amount of the correction coefficient within the current iteration period.

[0077] Step S103: When it is determined that the current iteration period is within the period range specified by the stop iteration condition and the change amount of the correction coefficient does not meet the stop iteration condition, enter the next iteration period. Determine the correction coefficient for the next iteration period based on the change amount of the correction coefficient and the correction coefficient of the current iteration period, and re-determine the change amount of the correction coefficient in the next iteration period.

[0078] Specifically, the period range of the preset iteration period can be any value (assumed to be ten times). When the number of iterations is less than ten and the change amount of the correction coefficient does not meet the stop iteration condition, automatically enter the next iteration period. Among them, the stop iteration condition can be that the value of the change amount of the correction coefficient is less than or equal to a certain preset threshold. Before entering the next iteration period, it is necessary to determine the correction coefficient for the next iteration period based on the change amount of the correction coefficient and the correction coefficient of the current iteration period, and then re-determine the change amount of the correction coefficient for the next iteration period in the next iteration period.

[0079] Step S104: Until the change amount of the correction coefficient obtained in the first target iteration period finally meets the stop iteration condition and the first target iteration period is within the period range, obtain the final change amount of the correction coefficient.

[0080] Among them, the first target iteration period is any iteration period after the current iteration period.

[0081] Specifically, as described above, when the period range of the iteration period is ten times, when the first target iteration period is within ten times and the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition, that is, the value of the change amount of the correction coefficient is less than or equal to a certain preset threshold, obtain this change amount of the correction coefficient as the final change amount of the correction coefficient.

[0082] Step S105: Determine the final correction coefficient based on the correction coefficient of the cycle before the first target iteration period and the change amount of the correction coefficient determined in the first target iteration period.

[0083] Specifically, the sum of the correction coefficient of the previous cycle of the first target iteration cycle and the change amount of the correction coefficient determined by the first target iteration cycle is the final correction coefficient.

[0084] Step S106, update the cross-section erosion and deposition deformation equation according to the final correction coefficient to obtain the final cross-section erosion and deposition deformation equation.

[0085] The method for obtaining the cross-section erosion and deposition deformation equation provided in this embodiment predicts the erosion and deposition area within the current iteration cycle by combining the correction coefficient based on the river channel data, erosion and deposition deformation empirical parameters, and the time length of the current iteration cycle of the target cross-section. Then, by comparing the predicted erosion and deposition area with the actual erosion and deposition area, and combining the iterative adjustment coefficient and the time length of the iteration cycle, the change amount of the correction coefficient is calculated. If the change amount of the correction coefficient in the current iteration cycle does not meet the stop iteration condition, enter the next iteration cycle, update the correction coefficient and continue the calculation. When the change amount of the correction coefficient meets the preset stop iteration condition, end the iteration to obtain the final correction coefficient. Apply the final correction coefficient to the cross-section erosion and deposition area calculation equation to accurately simulate the change of the erosion and deposition area of the reservoir river channel cross-section. By automatically iteratively adjusting a single parameter of the correction coefficient, the calculation time and labor cost of manually trying multiple empirical parameter values are reduced. And for each cross-section, the appropriate correction coefficient corresponding to the cross-section is obtained according to the above method for obtaining the cross-section erosion and deposition deformation equation, avoiding the same empirical parameter values for all cross-sections in the same river reach, and improving the simulation accuracy of the erosion and deposition change of the water passing area of each cross-section of the reservoir river channel.

[0086] Specifically, the river channel data includes: the sediment concentration of the target cross-section, the water surface width information, the water flow velocity information, and the water depth information of the target cross-section.

[0087] Based on the foregoing embodiment, in an optional embodiment, the specific process of predicting the erosion and deposition area corresponding to the target cross-section in the current iteration cycle according to the pre-obtained river channel data in the target cross-section, the erosion and deposition deformation empirical parameters corresponding to the target cross-section, the time length corresponding to the iteration cycle, and the correction coefficient of the erosion and deposition area of the target cross-section in the current iteration cycle is as follows Figure 2 shown. This embodiment can be used in the above-mentioned mobile terminals, such as mobile phones, tablet computers, etc. Figure 2 It is a schematic flowchart of the method for obtaining the cross-section erosion and deposition deformation equation provided by the embodiment of the present invention, and this process includes the following steps:

[0088] Step S201, determine the sediment-carrying capacity parameter of the target cross-section according to the water flow velocity information, the erosion and deposition deformation empirical parameters, the acceleration due to gravity, and the water depth information of the target cross-section.

[0089] Specifically, the water flow velocity information can be directly measured by a current meter. The sediment carrying capacity parameter of the target cross-section can be calculated through the following expression:

[0090]

[0091] where i is the identification information of the target cross-section, S i,* is the sediment carrying capacity parameter of the target cross-section, U is the water flow velocity information of the target cross-section, g is the acceleration due to gravity, h is the water depth information of the target cross-section, k is a proportionality coefficient, m is an exponential coefficient, and k and m are collectively referred to as fitting parameters, which are usually used to adjust the proportional relationship in the formula to make the actual observed data better fit.

[0092] Step S202: Input the sediment concentration, sediment carrying capacity parameter, water surface width information, scouring and silting deformation empirical parameter, and correction coefficient into a pre-configured cross-section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target cross-section in the current iteration cycle.

[0093] Specifically, as described above, substitute the sediment concentration, sediment carrying capacity parameter, water surface width information, scouring and silting deformation empirical parameter, and the correction coefficient of the scouring and silting area of the target cross-section in the current iteration cycle into the scouring and silting deformation equation to determine the predicted scouring and silting area corresponding to the target cross-section.

[0094] Specifically, by combining actual river channel data to determine key parameters (such as sediment concentration, sediment carrying capacity parameter, scouring and silting deformation empirical parameter, etc.) for predicting the scouring and silting area, it can more comprehensively reflect the actual scouring and silting situation of the river channel and more accurately predict the scouring and silting area of the target cross-section.

[0095] Based on the foregoing embodiments, the scouring and silting deformation empirical parameters include: the dry density of sediment corresponding to the target cross-section, the recovery saturation coefficient of the target cross-section, and the sediment settling velocity of the target cross-section; input the sediment concentration, sediment carrying capacity parameter, water surface width information, scouring and silting deformation empirical parameter, and correction coefficient into a pre-configured cross-section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target cross-section in the current iteration cycle, which is expressed by the following expression:

[0096]

[0097] where i is the identification information of the target cross-section, ρ’ represents the dry density of sediment corresponding to the target cross-section, A i is the scouring and silting area corresponding to the target cross-section to be predicted in the current iteration cycle, t is the time length corresponding to the iteration cycle, α i is the recovery saturation coefficient of the target cross-section, w i is the sediment settling velocity of the target cross-section, B i is the water surface width information of the target cross-section, S i is the sediment concentration in the target cross-section, Si,* α is the sediment-carrying capacity parameter of the target section, and β is the correction coefficient of the target section.

[0098] Among them, in the erosion and deposition deformation equation, the correction coefficient is multiplied by the sediment concentration. Because the order of magnitude of the sediment-carrying capacity parameter itself is small, and the value of the correction coefficient can reach hundreds or thousands, which is very large, and the difference between the values is large, it will be difficult to control the iterative value range and difficult to achieve the algorithm effect.

[0099] Based on the foregoing embodiments, the river channel data further includes: the spacing information between the target section and the next section adjacent to the target section in the target area. According to the predicted erosion and deposition area corresponding to the target section, the pre-acquired actual erosion and deposition area corresponding to the target section, the river channel data, the pre-configured iterative adjustment coefficient, and the time length corresponding to the iterative cycle, obtain the change amount of the correction coefficient in the current iterative cycle. In this embodiment, a method for obtaining the change amount of the correction coefficient is provided, which can be used for the above-mentioned mobile terminals, such as mobile phones, tablet computers, etc. Figure 3 It is a schematic flowchart of a method for obtaining the change amount of the correction coefficient provided by an embodiment of the present invention, as Figure 3 shown, and the process includes the following steps:

[0100] Step S301, determine the erosion and deposition area error amount according to the predicted erosion and deposition area corresponding to the target section and the pre-acquired actual erosion and deposition area corresponding to the target section.

[0101] Specifically, for the target section, assuming that the initial value of the correction coefficient of the target section is β = β0 = 1, substituting it into the erosion and deposition area expression described above, the change amount A of the erosion and deposition area of the target section after the first iterative cycle can be obtained i,0 , and at the same time, obtain the actual erosion and deposition area A corresponding to the target section in the measured data during the same period i,real . Subtract the two ΔA0 = A i,real - A i,0 , and determine the erosion and deposition area error amount ΔA0.

[0102] Step S302, determine the change amount of the correction coefficient in the current iterative cycle according to the spacing information, the time length corresponding to the iterative cycle, the erosion and deposition area error amount, and the iterative adjustment coefficient.

[0103] Specifically, according to the spacing information, the time length corresponding to the iterative cycle, the erosion and deposition area error amount, and the iterative adjustment coefficient, the change amount of the correction coefficient in the current iterative cycle can be determined, which can be expressed by the following change amount expression of the correction coefficient:

[0104]

[0105] Wherein, Δβ is the change amount of the correction coefficient in the current iteration period, ΔA is the scouring and silting area error amount of the target section, Δx is the spacing information, Δt is the time length corresponding to the iteration period, and λ is the iteration adjustment coefficient used to control the iteration rate and convergence.

[0106] Specifically, substituting the spacing information, the time length corresponding to the iteration period, the scouring and silting area error amount ΔA0, and the iteration adjustment coefficient into the above expression of the change amount of the correction coefficient, Δβ0 can be obtained. Among them, β1 = β0 + Δβ0. Substituting β1 into the above scouring and silting area expression, A can be obtained. i,1 . Compare it again with the actual scouring and silting area A corresponding to the same time period of the target section in the measured data i,real to obtain ΔA1, substitute it into the expression of the change amount of the correction coefficient again to obtain Δβ1, get β2, and substitute it into the scouring and silting area expression again to solve the change amount of the scouring and silting area. Repeat the above steps until the change amount of the correction coefficient meets the stop iteration condition.

[0107] In an alternative embodiment, when it is determined that the first target iteration period is within the period range specified by the stop iteration condition, determining whether the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition includes:

[0108] Step a1, when the absolute value of the change amount of the correction coefficient determined in the first target iteration period is less than or equal to the first preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition.

[0109] Specifically, as described above, assume that the period range of the first target iteration period is ten times, and the first preset threshold is le-3. When the number of iterations of the first target iteration period ≤ 10 and the change amount of the correction coefficient , it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition.

[0110] Or,[[]]END]]

[0111] Step a2, when in a continuous preset number of iteration periods including the first target iteration period, the change amount of the correction coefficient obtained in each iteration period is greater than the first preset threshold, but the difference between the change amounts of the correction coefficient obtained in every two adjacent iteration periods is less than or equal to the second preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition.

[0112] Specifically, when in a continuous preset number of iteration periods including the first target iteration period, the change amount of the correction coefficient obtained in each iteration period is greater than the first preset threshold, It is stable for three consecutive iterations. That is, when the difference between the change amounts of the correction coefficients obtained respectively in every two adjacent iteration cycles is less than or equal to the second preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration cycle meets the iteration stop condition. Among them, it is assumed that the second preset threshold is le-5.

[0113] The foregoing embodiment is the case where the target iteration cycle is within the cycle range specified by the iteration stop condition and meets the iteration stop condition.

[0114] In an alternative example, when it is determined that the first target iteration cycle is not within the cycle range specified by the iteration stop condition, the method further includes:

[0115] Step b1: Determine the error amount of the scouring and silting area of the target cross-section in each iteration cycle respectively according to the predicted scouring and silting area corresponding to the target cross-section and the actual scouring and silting area corresponding to the target cross-section obtained respectively in each iteration cycle.

[0116] Step b2: When it is determined that the error amount of the scouring and silting area of the target cross-section continuously decreases in all iteration cycles including the target iteration cycle, after increasing the value of the iteration adjustment coefficient according to the preset adjustment rule, re-obtain the change amount of the correction coefficient in each iteration cycle until the change amount of the correction coefficient obtained in the second target iteration cycle meets the iteration stop condition and the second target iteration cycle is within the cycle range, and then obtain the final change amount of the correction coefficient.

[0117] Among them, the second target iteration cycle is any iteration cycle after re-counting the iteration cycle after the first target iteration cycle.

[0118] Specifically, when the first target iteration cycle does not converge after ten consecutive iterations, that is But if ΔA continues to decrease, then appropriately increase the iteration adjustment coefficient λ. For example, increase λ from 1.0 to 1.5. After the second target iteration cycle re-starts counting from 1, re-obtain the change amount of the correction coefficient in each iteration cycle. When the second target iteration cycle is within the cycle range and the change amount of the correction coefficient obtained in the second target iteration cycle meets the iteration stop condition described above, obtain the final change amount of the correction coefficient according to the correction coefficient of the previous cycle of the second target iteration cycle and the change amount of the correction coefficient determined by the second target iteration cycle.

[0119] On the basis of the foregoing embodiment, when the change amount of the correction coefficient obtained in each iteration cycle in a continuous preset number of iteration cycles including the first target iteration cycle is greater than the first preset threshold and the difference between the change amounts of the correction coefficients obtained respectively in every two adjacent iteration cycles is greater than the second preset threshold, in an alternative example, the method further includes:

[0120] After reducing the value of the iterative adjustment coefficient according to the preset adjustment rule, the change amount of the correction coefficient for each iteration period is obtained again until the change amount of the correction coefficient obtained in the third target iteration period meets the iteration stop condition and the third target iteration period is within the period range, and then the final change amount of the correction coefficient is obtained.

[0121] Wherein, the third target iteration period is any iteration period after re-counting the iteration period after the first target iteration period.

[0122] Specifically, when the first target iteration period does not converge after continuous iteration for ten times and Δβ does not remain stable for three consecutive iterations, the iterative adjustment coefficient λ is appropriately reduced (must be greater than 0) on the basis of 1.0. After the third target iteration period starts counting from 1 again, the change amount of the correction coefficient for each iteration period is obtained again until the change amount of the correction coefficient meets the iteration stop condition described above.

[0123] On the basis of the foregoing embodiment, when the value of the iterative adjustment coefficient is adjusted according to the preset adjustment rule and the iteration period is re-counted, and the change amount of the correction coefficient obtained in any period within the period range still does not meet the iteration stop condition, in an alternative embodiment, the method further includes:

[0124] Obtain the correction coefficient corresponding to the iteration period corresponding to the minimum change amount of the correction coefficient within the period range as the final correction coefficient.

[0125] Specifically, if changing the iterative adjustment coefficient λ according to the above preset adjustment rule still cannot meet the iteration stop condition described above, then take the correction coefficient β corresponding to the time when the change amount of the correction coefficient |Δβ| is the smallest.

[0126] Next, a specific embodiment is given to illustrate the foregoing method for obtaining the cross-section erosion and deposition deformation equation, which specifically includes:

[0127] Suppose there are 400 measured cross-sections of a river-type reservoir, and the cross-sections are measured once a month. It is necessary to build a model to accurately simulate the change trend of the area erosion and deposition area of each cross-section. Obtain the sediment concentration, water surface width information, water flow velocity information, water depth information of the target cross-section, and the spacing information between the target cross-section and the next cross-section adjacent to the target cross-section in the target area from July 1, 2009 to August 1, 2009. The initial terrain of the model is the cross-section measured in July 2009, and the goal is to iteratively obtain the correction coefficient β of each cross-section, so that the change amount of the cross-section erosion and deposition area simulated by the model in August is consistent with the actual measurement. The implementation steps are as follows:

[0128] Step c1, for the target area of the reservoir, obtain river channel data, including: sediment concentration S iThe variation process over time, obtaining the water surface width information B of each cross-section in the river channel after Δt = 30 days i , the water flow velocity information U, the water depth information h of the target cross-section, the spacing information Δx between the target cross-section and the next cross-section adjacent to the target cross-section in the target area, and i is the target cross-section identification information.

[0129] Step c2, adding a correction coefficient β to the traditional cross-section scouring and silting equation:

[0130]

[0131] where i is the identification information of the target cross-section, ρ’ represents the dry bulk density of sediment corresponding to the target cross-section, given according to measured data or experience, and taken as 1; A i is the scouring and silting area corresponding to the i-th cross-section; t is the time length corresponding to the iteration period; α i is the recovery saturation coefficient of the target cross-section, taken as 0.25; w i is the sediment settling velocity of the target cross-section, taken as 0.4 mm / s; B i is the water surface width information of the target cross-section, S i is the sediment concentration in the target cross-section, S i,* is the sediment-carrying capacity parameter of the target cross-section, β is the correction coefficient of the target cross-section, U is the water flow velocity information, g is the acceleration due to gravity, h is the water depth information of the target cross-section, k and m are taken as 0.245 and 0.92 respectively; β is the correction coefficient.

[0132] Step c3, constructing an iterative relationship for Δβ:

[0133]

[0134] where Δβ is the change in the correction coefficient in the current iteration period; ΔA is the scouring and silting area error of the target cross-section; Δx is the spacing information, obtained from measured data; Δt is the time length corresponding to the iteration period, taken as 30 days; λ is the iteration adjustment coefficient, with an initial value of 1.0; used to control the iteration rate and convergence.

[0135] Step c4, using measured data to iteratively solve the correction coefficient β of each cross-section:

[0136] For the i-th cross-section, initially let β = β0 = 1.0, substitute it into Equation (1) to obtain the change in the scouring and silting area A of cross-section i after Δt time i,0 . At the same time, obtain the actual change in the scouring and silting area A of the cross-section according to the measured cross-section topography i,real . Subtract the two to obtain ΔA0. Substitute it into Equation (2) to obtain the change in the correction coefficient Δβ0, and accordingly adjust the coefficient β1 = β0 + Δβ, substitute β1 into Equation (1), and obtain the change in the scouring and silting area A i,1。Compare it with the actual measurement again to obtain ΔA1, substitute it into Equation (2) again to obtain Δβ1, and get β2 according to β2 = β1 + Δβ1. Then substitute it into Equation (1) to solve the change amount A of the scouring and silting area i,2 。Repeat the above steps until the correction coefficient β satisfies one of the following criteria when two adjacent iterations are completed, which means the iteration is completed:

[0137] (I): When it is determined that the first target iteration period is within the period range specified by the stop iteration condition, determine whether the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition:

[0138] (I-1), when the absolute value of the change amount of the correction coefficient determined by the iteration of the first target iteration period is less than or equal to the first preset threshold and the first target iteration period is within 10 times, that is, the change amount of the correction coefficient of the first target iteration period converges to Take the β value at the convergence termination. Among them, Generally take 1e-3.

[0139] (I-2), when the number of iterations of the first target iteration period is within 10 times, and the change amount of the correction coefficient is stable for 3 consecutive iterations. Although |Δβ| > 1e-3, the convergence has tended to be stable at this time, and it is meaningless to iterate anymore. Therefore, take the corresponding β at this time as the iteration final value;

[0140] (II): When it is determined that the first target iteration period is not within the period range specified by the stop iteration condition:

[0141] (II-1): When the change amount of the correction coefficient of the first target iteration period still does not converge to after 10 iterations, but the error amount ΔA of the scouring and silting area continues to decrease, then appropriately increase the iteration adjustment coefficient λ, make its value greater than 1.0, and the adjustment standard of the iteration adjustment coefficient λ is to control the convergence to be completed in 10 iterations. After appropriately increasing the iteration adjustment coefficient λ, the iteration period starts to be counted from zero again.

[0142] (III): When in a continuous preset number of iteration periods including the first target iteration period, the change amount of the correction coefficient obtained in each iteration period is greater than the value, and there is no situation where the change amount of the correction coefficient is stable for 3 consecutive iterations:

[0143] (III-1): Appropriately reduce the iteration adjustment coefficient λ on the basis of 1.0 (must be greater than 0) until the convergence condition of (I) is met.

[0144] (IV): If adjusting the iteration adjustment coefficient λ cannot meet (I), then take the β value corresponding to the minimum |Δβ|.

[0145] The change amount A of the scouring and silting area of the i-th cross-section is obtained according to the above steps i and the determined correction coefficient β. After that, the (i + 1)-th cross-section is solved according to the same steps, and finally the correction coefficient values of all cross-sections are obtained

[0146] Three characteristic cross-sections of the target area of the reservoir are selected, and appropriate correction coefficients are obtained according to the above method for obtaining the cross-section scouring and silting deformation equation as follows

[0147] For cross-section S258, Δx = 1528 m, Δt = 30 days. As Figure 4 shown, first, β = 1 is taken as the initial value and substituted into Equation (1) to calculate the predicted scouring and silting area. Then, the difference between the predicted scouring and silting area and the measured scouring and silting area is calculated to obtain the scouring and silting area error ΔA = 383.6 m 2 . Substitute ΔA into Equation (2) to obtain the correction coefficient error Δβ = 0.089. Then, according to β + Δβ = 1.089, the correction coefficient β for the next iteration cycle is determined to be 1.089. Repeat the above process. After 7 iterations, the convergence condition (I-1) is satisfied, and the correction coefficient β is taken as 1.203 as the correction coefficient of this cross-section. Finally, the scouring and silting area change error is 5.8 m 2 .

[0148] For cross-section S311, Δx = 1243 m, Δt = 30 days. As Figure 5 shown, according to the above method for obtaining the cross-section scouring and silting deformation equation, after 10 iterations, the convergence condition (I-2) is satisfied, and the correction coefficient β is taken as 1.360 as the correction coefficient of this cross-section. Finally, the scouring and silting area error is 8.2 m 2 .

[0149] For cross-section S382, Δx = 1017 m, Δt = 30 days. As Figure 6 shown, after 10 iterations, the convergence condition (IV) is satisfied, and the correction coefficient β is taken as 1.626 as the correction coefficient of this cross-section. Finally, the scouring and silting area error is 113.6 m 2 .

[0150] In this embodiment, a device for obtaining the cross-section scouring and silting deformation equation is also provided. This device is used to implement the above embodiment and the preferred implementation manners, and the parts that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated

[0151] This embodiment provides a device for obtaining the cross-section scouring and silting deformation equation. As Figure 7 shown, it includes: a prediction module 701, a processing module 702, and a determination module 703

[0152] A prediction module 701 is configured to input the river channel data in a target cross-section obtained in advance, the scouring and silting deformation empirical parameters corresponding to the target cross-section, the time length corresponding to the iteration period, and the correction coefficient of the scouring and silting area of the target cross-section in the current iteration period into a pre-configured cross-section scouring and silting deformation equation, and predict the scouring and silting area corresponding to the target cross-section in the current iteration period, where the target cross-section is any one of multiple cross-sections included in the target area;

[0153] A processing module 702 is configured to obtain the change amount of the correction coefficient in the current iteration period according to the predicted scouring and silting area corresponding to the target cross-section, the actually obtained scouring and silting area corresponding to the target cross-section, the river channel data, the pre-configured iteration adjustment coefficient, and the time length corresponding to the iteration period; when it is determined that the current iteration period is within the period range specified by the stop iteration condition and the change amount of the correction coefficient does not meet the stop iteration condition, enter the next iteration period, determine the correction coefficient of the next iteration period according to the change amount of the correction coefficient and the correction coefficient of the current iteration period, and re-determine the change amount of the correction coefficient in the next iteration period; until finally the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition and the first target iteration period is within the period range, obtain the final change amount of the correction coefficient, and the first target iteration period is any iteration period after the current iteration period;

[0154] A determination module 703 is configured to determine the final correction coefficient according to the correction coefficient of the previous period of the first target iteration period and the change amount of the correction coefficient determined in the first target iteration period;

[0155] The processing module 702 is further configured to update the cross-section scouring and silting deformation equation according to the final correction coefficient to obtain the final cross-section scouring and silting deformation equation.

[0156] In an optional embodiment, the prediction module 701 is specifically configured to input the river channel data in a target cross-section obtained in advance, the scouring and silting deformation empirical parameters corresponding to the target cross-section, the time length corresponding to the iteration period, and the correction coefficient of the scouring and silting area of the target cross-section in the current iteration period into a pre-configured cross-section scouring and silting deformation equation, and predict the scouring and silting area corresponding to the target cross-section in the current iteration period, specifically including:

[0157] Determine the sediment-carrying capacity parameter of the target cross-section according to the water flow velocity information, the scouring and silting deformation empirical parameters, the acceleration due to gravity, and the water depth information of the target cross-section;

[0158] Predict the scouring and silting area according to the sediment concentration, the sediment-carrying capacity parameter, the water surface width information, the scouring and silting deformation empirical parameters, and the correction coefficient.

[0159] In an alternative embodiment, the scouring and silting deformation empirical parameters include: the dry density of sediment corresponding to the target cross-section, the recovery saturation coefficient of the target cross-section, and the sediment settling velocity of the target cross-section.

[0160] Based on the sediment concentration, sediment carrying capacity parameter, water surface width information, scouring and silting deformation empirical parameters, and correction coefficient, they are input into a pre-configured cross-section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target cross-section in the current iteration cycle, which is expressed by the following expression:

[0161]

[0162] where i is the identification information of the target cross-section, ρ’ is the dry density of sediment corresponding to the target cross-section, A i is the scouring and silting area corresponding to the target cross-section to be predicted in the current iteration cycle, t is the time length corresponding to the iteration cycle, α i is the recovery saturation coefficient of the target cross-section, w i is the sediment settling velocity of the target cross-section, B i is the water surface width information of the target cross-section, S i is the sediment concentration in the target cross-section, S i,* is the sediment carrying capacity parameter of the target cross-section, and β is the correction coefficient of the target cross-section.

[0163] In an alternative embodiment, the processing module 702 is specifically configured to: the river channel data further includes: the spacing information between the target cross-section and the next cross-section adjacent to the target cross-section in the target area. Based on the predicted scouring and silting area corresponding to the target cross-section, the pre-obtained actual scouring and silting area corresponding to the target cross-section, the river channel data, the pre-configured iteration adjustment coefficient, and the time length corresponding to the iteration cycle, obtain the change amount of the correction coefficient in the current iteration cycle, specifically including:

[0164] Determine the scouring and silting area error amount based on the predicted scouring and silting area corresponding to the target cross-section and the pre-obtained actual scouring and silting area corresponding to the target cross-section;

[0165] Determine the change amount of the correction coefficient in the current iteration cycle based on the spacing information, the time length corresponding to the iteration cycle, the scouring and silting area error amount, and the iteration adjustment coefficient.

[0166] In an alternative embodiment, determining the change amount of the correction coefficient in the current iteration cycle based on the spacing information, the time length corresponding to the iteration cycle, the scouring and silting area error amount, and the iteration adjustment coefficient is expressed by the following expression:

[0167]

[0168] Wherein, Δβ is the change amount of the correction coefficient in the current iteration period, ΔA is the scouring and silting area error amount of the target section, Δx is the spacing information, Δt is the time length corresponding to the iteration period, and λ is the iteration adjustment coefficient used to control the iteration rate and convergence.

[0169] In an optional embodiment, the processing module 702 is specifically configured to determine that the change amount of the correction coefficient obtained in the first target iteration period meets the iteration stop condition when the absolute value of the change amount of the correction coefficient determined in the first target iteration period is less than or equal to the first preset threshold.

[0170] Alternatively, when the change amount of the correction coefficient obtained in each iteration period in a continuous preset number of iteration periods including the first target iteration period is greater than the first preset threshold, but the difference between the change amounts of the correction coefficient obtained in each adjacent two iteration periods is less than or equal to the second preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the iteration stop condition.

[0171] In an optional embodiment, the processing module 702 is further configured to respectively determine the error amount of the scouring and silting area of the target section in each iteration period according to the predicted scouring and silting area corresponding to the target section and the actual scouring and silting area corresponding to the target section obtained in each iteration period.

[0172] When it is determined that the error amount of the scouring and silting area of the target section continuously decreases in all iteration periods including the target iteration period, after increasing the value of the iteration adjustment coefficient according to the preset adjustment rule, the change amount of the correction coefficient in each iteration period is re-obtained until the change amount of the correction coefficient obtained in the second target iteration period finally meets the iteration stop condition and the second target iteration period is within the period range, and the final change amount of the correction coefficient is obtained, where the second target iteration period is any iteration period after re-counting the iteration period after the first target iteration period.

[0173] In an optional embodiment, the processing module 702 is further configured to, when the change amount of the correction coefficient obtained in each iteration period in a continuous preset number of iteration periods including the first target iteration period is greater than the first preset threshold, and the difference between the change amounts of the correction coefficient obtained in each adjacent two iteration periods is greater than the second preset threshold, reduce the value of the iteration adjustment coefficient according to the preset adjustment rule, and then re-obtain the change amount of the correction coefficient in each iteration period until the change amount of the correction coefficient obtained in the third target iteration period finally meets the iteration stop condition and the third target iteration period is within the period range, and the final change amount of the correction coefficient is obtained, where the third target iteration period is any iteration period after re-counting the iteration period after the first target iteration period.

[0174] In an optional embodiment, the processing module 702 is further configured to, when adjusting the value of the iterative adjustment coefficient according to a preset adjustment rule and re-counting the iterative period, and when the change amount of the correction coefficient obtained in any period within the period range still does not meet the iteration stop condition, obtain the correction coefficient corresponding to the iterative period corresponding to the minimum change amount of the correction coefficient within the period range as the final correction coefficient.

[0175] The cross-section erosion and deposition deformation equation acquisition device in this embodiment is presented in the form of functional modules. Here, the module refers to an application specific integrated circuit (ASIC), a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0176] The further function descriptions of the above-mentioned various modules and units are the same as those in the corresponding embodiments above, and will not be repeated here.

[0177] A cross-section erosion and deposition deformation equation acquisition device provided by an embodiment of the present invention predicts the erosion and deposition area within the current iterative period by combining a correction coefficient based on the river channel data, erosion and deposition deformation empirical parameters, and the time length of the current iterative period of the target cross-section. Then, by comparing the predicted erosion and deposition area with the actual erosion and deposition area, and combining the iterative adjustment coefficient and the iterative period time length, the change amount of the correction coefficient is calculated. If the change amount of the correction coefficient in the current iterative period does not meet the iteration stop condition, it enters the next iterative period, updates the correction coefficient and continues the calculation. When the change amount of the correction coefficient meets the preset iteration stop condition, the iteration ends and the final correction coefficient is obtained. Applying the final correction coefficient to the cross-section erosion and deposition area calculation equation accurately simulates the change of the erosion and deposition area of the reservoir river channel cross-section. By automatically iteratively adjusting a single parameter of the correction coefficient, the calculation time and labor cost of manually trying multiple empirical parameter values are reduced. And for each cross-section, an appropriate correction coefficient corresponding to the cross-section is obtained according to the above cross-section erosion and deposition deformation equation acquisition device, avoiding the same empirical parameter values for all cross-sections in the same river reach, and improving the simulation accuracy of the erosion and deposition change of the water passing area of each cross-section of the reservoir river channel.

[0178] An embodiment of the present invention further provides a computer device Figure 8 is a schematic structural diagram of a computer device provided by an optional embodiment of the present invention, as Figure 8As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 8 Take one processor 10 as an example in Figure 8 .

[0179] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include an integrated circuit. The above integrated circuit can be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0180] Among them, the memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiments.

[0181] The memory 20 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device presented by a kind of landing page of a small program, etc. In addition, the memory 20 can include high-speed random access memory and can also include non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 can optionally include a memory remotely set relative to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0182] The memory 20 can include volatile memory, such as random access memory; the memory can also include non-volatile memory, such as flash memory, a hard disk, or a solid-state drive; the memory 20 can also include a combination of the above types of memory.

[0183] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 may be connected through a bus or other means. Figure 8 Taking the connection through the bus as an example.

[0184] The input device 30 can receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED), and a haptic feedback device (e.g., a vibration motor), etc. The above display device includes, but is not limited to, a liquid crystal display, a light emitting diode, a display, and a plasma display. In some alternative embodiments, the display device may be a touch screen.

[0185] The embodiment of the present invention also provides a computer-readable storage medium. The method provided by the embodiment of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be processed by such software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium may further include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiment is implemented.

[0186] A part of the present invention can be applied as a computer program product, such as computer program instructions. When executed by a computer, through the operation of the computer, the methods and / or technical solutions according to the present invention can be called or provided. Those skilled in the art should be able to understand that the forms of existence of computer program instructions in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0187] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for obtaining a cross-section scouring and silting deformation equation, characterized in that: The method comprises: Input the pre-acquired river channel data in the target section, the empirical parameters of scouring and silting deformation corresponding to the target section, the time length corresponding to the iteration cycle, and the correction coefficient of the scouring and silting area of ​​the target section in the current iteration cycle into the pre-configured section scouring and silting deformation equation, and predict the scouring and silting area corresponding to the target section in the current iteration cycle, wherein the target section is any section among the multiple sections included in the target area; According to the predicted scouring and silting area corresponding to the target section, the pre-acquired actual scouring and silting area corresponding to the target section, the river channel data, the pre-configured iterative adjustment coefficient, and the time length corresponding to the iterative cycle, the change amount of the correction coefficient in the current iterative cycle is obtained; When it is determined that the current iteration cycle is within the cycle range specified by the stop iteration condition, and the change amount of the correction coefficient does not meet the stop iteration condition, enter the next iteration cycle, determine the correction coefficient of the next iteration cycle according to the change amount of the correction coefficient and the correction coefficient of the current iteration cycle, and re-determine the change amount of the correction coefficient in the next iteration cycle; Until the change amount of the correction coefficient finally obtained in the first target iteration cycle meets the said stop iteration condition, and the first target iteration cycle is within the said cycle range, the final change amount of the correction coefficient is obtained, and the first target iteration cycle is any iteration cycle after the said current iteration cycle; Determine a final correction coefficient according to the correction coefficient of the previous cycle of the first target iteration cycle and the change amount of the correction coefficient determined in the first target iteration cycle; The cross-section scouring and silting deformation equation is updated according to the final correction coefficient to obtain a final cross-section scouring and silting deformation equation.

2. The method according to claim 1, characterized in that The river data includes: the sediment content of the target section, water surface width information, water flow velocity information, and water depth information of the target section; According to the pre-acquired river channel data in the target section, the empirical parameters of the scouring and silting deformation corresponding to the target section, the time length corresponding to the iteration cycle, and the correction coefficient of the scouring and silting area of ​​the target section in the current iteration cycle, they are input into the pre-configured section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target section in the current iteration cycle, specifically including: Determine the sediment-carrying force parameter of the target section according to the water flow velocity information, the scouring and silting deformation empirical parameter, the gravitational acceleration, and the water depth information of the target section; According to the sediment content, the sediment-carrying force parameter, the water surface width information, the empirical parameter of scouring and silting deformation, and the correction coefficient, they are input into a preconfigured cross-section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target cross-section in the current iteration cycle.

3. The method according to claim 2, characterized in that The empirical parameters of scouring and silting deformation include: dry bulk density of sediment corresponding to the target section, restoration saturation coefficient of the target section, and sediment settling velocity of the target section; The sediment content, the sediment entrainment parameter, the water surface width information, the scouring and silting deformation empirical parameter, and the correction coefficient are input into a preconfigured cross-section scouring and silting deformation equation to predict the scouring and silting area corresponding to the target cross-section in the current iteration cycle. The preconfigured cross-section scouring and silting deformation equation is expressed by the following expression: Where i is the identification information of the target section, ρ' is the dry bulk density of sediment corresponding to the target section, A i is the scouring and silting area corresponding to the target section to be predicted in the current iteration cycle, t is the time length corresponding to the iteration cycle, α i is the restoration saturation coefficient of the target section, w i is the sediment settling velocity of the target section, B i is the water surface width information of the target section, S i is the sediment content in the target section, S i,* is the sand-carrying force parameter of the target section, and β is the correction coefficient of the target section.

4. The method according to claim 2, characterized in that: The river channel data also includes: the distance information between the target section and the next section adjacent to the target section in the target area, the change amount of the correction coefficient in the current iteration cycle is obtained according to the predicted scouring and silting area corresponding to the target section, the pre-acquired actual scouring and silting area corresponding to the target section, the river channel data, the pre-configured iteration adjustment coefficient, and the time length corresponding to the iteration cycle, specifically including: Determine the scouring and silting area error amount according to the predicted scouring and silting area corresponding to the target section and the pre-acquired actual scouring and silting area corresponding to the target section; The change amount of the correction coefficient in the current iteration cycle is determined according to the spacing information, the time length corresponding to the iteration cycle, the error amount of the scouring and silting area, and the iteration adjustment coefficient.

5. The method according to claim 4, characterized in that According to the spacing information, the time length corresponding to the iteration cycle, the scouring and silting area error, and the iteration adjustment coefficient, the change amount of the correction coefficient in the current iteration cycle is determined, which is expressed by the following expression: Among them, Δβ is the change of the correction coefficient in the current iteration cycle, ΔA is the error of the scouring and silting area of ​​the target section, Δx is the spacing information, Δt is the time length corresponding to the iteration cycle, and λ is the iteration adjustment coefficient.

6. The method according to any one of claims 1 to 5, characterized in that: When it is determined that the first target iteration period is within the period range specified by the stop iteration condition, determining whether the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition includes: When the absolute value of the change amount of the correction coefficient determined in the first target iteration period is less than or equal to the first preset threshold, it is determined that the change amount of the correction coefficient obtained in the first target iteration period meets the stop iteration condition; Alternatively, when the change in the correction coefficient obtained in each of a continuous preset number of iteration cycles including the first target iteration cycle is greater than the first preset threshold, but the difference between the change in the correction coefficient obtained in each two adjacent iteration cycles is less than or equal to the second preset threshold, it is determined that the change in the correction coefficient obtained in the first target iteration cycle meets the condition for stopping iteration.

7. The method according to claim 6, characterized in that When it is determined that the first target iteration period is not within the period range specified by the iteration stop condition, the method further includes: According to the predicted scouring and silting area corresponding to the target section obtained in each iteration cycle, and the actual scouring and silting area corresponding to the target section, respectively, the error amount of the scouring and silting area of ​​the target section in each iteration cycle is determined respectively; When it is determined that the error amount of the scouring and silting area of ​​the target section continues to decrease in all iteration cycles including the target iteration cycle, the value of the iteration adjustment coefficient is increased according to the preset adjustment rule, and the change amount of the correction coefficient of each iteration cycle is re-obtained until the change amount of the correction coefficient finally obtained in the second target iteration cycle meets the stop iteration condition, and the second target iteration cycle is within the cycle range, the final change amount of the correction coefficient is obtained, wherein the second target iteration cycle is any iteration cycle after the iteration cycle is recounted after the first target iteration cycle.

8. The method according to claim 7, characterized in that When, in a preset number of consecutive iteration cycles including the first target iteration cycle, the change amount of the correction coefficient obtained in each iteration cycle is greater than the first preset threshold, and the difference between the change amounts of the correction coefficients respectively obtained in every two adjacent iteration cycles is greater than the second preset threshold, the method further includes: After reducing the value of the iterative adjustment coefficient according to the preset adjustment rule, the change of the correction coefficient of each iterative cycle is re-obtained until the change of the correction coefficient finally obtained in the third target iterative cycle meets the stop iteration condition, and the third target iterative cycle is within the cycle range, the final change of the correction coefficient is obtained, wherein the third target iterative cycle is any iterative cycle after recounting the iterative cycles after the first target iterative cycle.

9. The method according to claim 7, characterized in that: When the value of the iterative adjustment coefficient is adjusted according to the preset adjustment rule and the iterative cycle is recounted, if the change amount of the correction coefficient obtained in any cycle within the cycle range still does not meet the stop iteration condition, the method further includes: A correction coefficient corresponding to an iteration period corresponding to a change amount of a minimum correction coefficient within the period range is obtained as the final correction coefficient.

10. A device for obtaining a cross-section scouring and silting deformation equation, characterized in that: The device comprises: A prediction module, for inputting the pre-acquired river channel data in the target section, the empirical parameters of scouring and silting deformation corresponding to the target section, the time length corresponding to the iteration cycle, and the correction coefficient of the scouring and silting area of ​​the target section in the current iteration cycle into the pre-configured section scouring and silting deformation equation, and predicting the scouring and silting area corresponding to the target section in the current iteration cycle, wherein the target section is any section among the multiple sections included in the target area; A processing module, used for obtaining the change amount of the correction coefficient in the current iteration cycle according to the predicted scouring and silting area corresponding to the target section, the pre-acquired actual scouring and silting area corresponding to the target section, the river data, the pre-configured iteration adjustment coefficient, and the time length corresponding to the iteration cycle; when it is determined that the current iteration cycle is within the cycle range specified by the stop iteration condition and the change amount of the correction coefficient does not meet the stop iteration condition, entering the next iteration cycle, determining the correction coefficient of the next iteration cycle according to the change amount of the correction coefficient and the correction coefficient of the current iteration cycle, and re-determining the change amount of the correction coefficient in the next iteration cycle; until the change amount of the correction coefficient obtained in the first target iteration cycle finally meets the stop iteration condition and the first target iteration cycle is within the cycle range, obtaining the final change amount of the correction coefficient, the first target iteration cycle being any iteration cycle after the current iteration cycle; A determination module, configured to determine a final correction coefficient according to a correction coefficient of a previous cycle of the first target iteration cycle and a change amount of the correction coefficient determined in the first target iteration cycle; The processing module is also used to update the cross-section scouring and silting deformation equation according to the final correction coefficient to obtain the final cross-section scouring and silting deformation equation.

11. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for obtaining the cross-section scouring and silting deformation equation according to any one of claims 1 to 9 by executing the computer instructions.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for obtaining a section scouring and silting deformation equation according to any one of claims 1 to 9.

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