An aquaculture water quality parameter spatial distribution model construction method

Abstract

The application relates to the technical field of aquaculture, in particular to a water quality parameter space distribution model construction method for aquaculture, which comprises the following steps: constructing a cuboid space three-dimensional coordinate system of a culture pond, inserting water quality parameter values into eight fixed coordinate points of the cuboid; calculating four intersection point coordinates of a plane and four Z axes of the cuboid and corresponding water quality parameter values; performing linear interpolation according to X-axis and Y-axis directions respectively to obtain the four intersection point coordinates and the corresponding water quality parameter values; connecting the intersection point coordinates of the X-axis and the Y-axis to divide the plane into four rectangles; connecting two diagonal points in a certain rectangle to divide the certain rectangle into two triangles; performing vector cross product and point product on any point in the triangle to calculate the water quality parameter value of the any point; drawing a plurality of planes orthogonal to the Z axis according to a fixed step length; and constructing a water quality parameter space distribution model. The application solves the problem that the existing method is limited to single-point monitoring and cannot understand the water quality conditions of other positions of the culture pond.

Description

Technical Field

[0001] This invention relates to the field of aquaculture technology, and in particular to a method for constructing a spatial distribution model of aquaculture water quality parameters. Background Technology

[0002] Pond aquaculture is the most widely used aquaculture method in my country. The quality of the water in the pond directly affects the growth of aquatic products. Therefore, ensuring water safety is a necessary way to achieve healthy aquaculture.

[0003] Currently, scholars both domestically and internationally have conducted extensive research on the prediction of water quality parameters in aquaculture ponds. While studies such as Huan Juan et al.'s proposed dissolved oxygen prediction model based on K-means clustering and ELM neural networks have improved the accuracy of dissolved oxygen prediction, and Liu Shuangyin et al.'s use of ant colony optimization and support vector machines to predict and analyze pH levels in aquaculture ponds, these studies are limited to single-point monitoring and cannot provide information on water quality at other locations within the pond. To address the limitations of single-point monitoring, scholars have studied the spatial distribution of water quality parameters. However, research on spatial distribution model algorithms for water quality parameters using interpolation methods is still relatively limited. Summary of the Invention

[0004] To address the shortcomings of existing methods, this invention first uses linear interpolation to construct a plane α orthogonal to the Z-axis and then divides plane α into regular triangles. Next, for each triangle in plane α, the parameter values ​​at any point in the plane are obtained using the cross product and dot product methods between vectors. This process is repeated along the Z-axis with a fixed step size to draw a sufficient number of planes. Finally, a four-dimensional interpolation method is used to construct a spatial distribution model of the aquaculture pond's water quality parameters, providing a basis for precise control and comprehensive management of aquaculture pond water quality.

[0005] The technical solution adopted in this invention is: a method for constructing a spatial distribution model of aquaculture water quality parameters, comprising the following steps:

[0006] Step 1: Construct a three-dimensional coordinate system in the cuboid space of the aquaculture pond, and insert the water quality parameter values ​​into the eight fixed coordinate points of the cuboid;

[0007] Step 2: Select a fixed z-value and section a plane orthogonal to the Z-axis. Calculate the coordinates of the four intersection points of the plane and the four Z-axis of the cuboid, and the corresponding water quality parameter values. Perform linear interpolation along the X-axis and Y-axis to obtain the coordinates of the four intersection points and the corresponding water quality parameter values. Connect the intersection points of the X-axis and Y-axis to divide the plane into four rectangles. Connect the two diagonal points within a rectangle to divide the rectangle into two triangles.

[0008] Furthermore, the formula for calculating the water quality parameter values ​​at the nine points of the four rectangles is as follows:

[0009]

[0010]

[0011]

[0012]

[0013]

[0014]

[0015]

[0016]

[0017]

[0018] Where x1 and x2 are two coordinates on the X-axis of the cuboid space, y1 and y2 are two coordinates on the Y-axis of the cuboid space, z1 and z2 are two coordinates on the Z-axis of the cuboid space, x, y, and z are the coordinates of points on the plane, and f() is the water quality parameter value corresponding to the coordinates.

[0019] Further water quality parameters include: temperature, pH value, and dissolved oxygen (DO) value.

[0020] Step 3: Perform the cross product and dot product of vectors on any point within the triangle to calculate the water quality parameter value at any point;

[0021] Furthermore, the formula for the parameter value at any point is:

[0022]

[0023] Where (xa,ya), (xb,yb), and (xc,yc) are the coordinates of the three fixed points of the triangle, and fa, fb, and fc are the water quality parameter values ​​corresponding to the coordinates of the three fixed points of the triangle.

[0024] Step 4: Draw several planes orthogonal to the Z-axis with a fixed step size, and repeat steps 2 and 3.

[0025] Step 5: Define all planar parameters as surface matrices, use different colors to represent data values, and construct a spatial distribution model of water quality parameters.

[0026] The beneficial effects of this invention are:

[0027] 1. The four-dimensional spatial distribution model of water quality parameters in aquaculture ponds constructed using spatial interpolation methods can accurately predict water quality parameter data at unsampled points in the aquaculture ponds. Under experimental conditions, the simulated and actual measurements of temperature, pH, and DO were compared. The RMSE values ​​were 0.567, 0.242, and 0.165, respectively, and the MAE values ​​were 0.471, 0.192, and 0.146, respectively. The error between the measured and predicted values ​​of water quality parameters was small, and the surface model has good practicality for studying the spatial distribution of water quality parameters in aquaculture ponds. Attached Figure Description

[0028] Figure 1 This is a flowchart of the method for constructing a spatial distribution model of aquaculture water quality parameters according to the present invention;

[0029] Figure 2 This is a schematic diagram of linear interpolation in this invention;

[0030] Figure 3 This is a diagram of the four-dimensional spatial distribution model of the present invention;

[0031] Figure 4 This is a diagram showing the relationship between the vector cross product and the dot product of the present invention;

[0032] Figure 5 This is a schematic diagram of the planar division of triangles according to the present invention;

[0033] Figure 6 This is a temperature simulation graph from MATLAB.

[0034] Figure 7 This is a MATLAB simulation of pH levels.

[0035] Figure 8 This is a MATLAB simulation result (DO). Detailed Implementation

[0036] The present invention will be further described below with reference to the accompanying drawings and embodiments. The drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0037] Linear interpolation estimates the value of the interpolation point based on the two data points to its left and right. In essence, it allocates the weight of the values ​​of the two neighboring points based on the distance from the interpolation point to the two neighboring points.

[0038] like Figure 2 As shown, given (x0, y0) and (x1, y1), we need to find the value of y at a point x between x0 and x1.

[0039] Linear interpolation has the following relationship:

[0040]

[0041] Expanding equation (1) yields:

[0042]

[0043] Therefore, when any point x between x0 and x1 is known, its corresponding y value can be calculated.

[0044] like Figure 1 As shown, a method for constructing a spatial distribution model of aquaculture water quality parameters includes the following steps:

[0045] Step 1: Construct a three-dimensional coordinate system for the aquaculture pond, such as... Figure 3 As shown, the three-dimensional coordinate system is represented by the X, Y, and Z axes. A cuboid-shaped aquaculture pond is constructed, and the water quality parameter values ​​of the eight endpoints of the aquaculture pond are inserted into the corresponding coordinate positions of the three-dimensional coordinate system. The values ​​of the eight endpoints are f(x1,y1,z1), f(x2,y1,z1), f(x2,y2,z1), f(x1,y2,z1), f(x1,y1,z2), f(x2,y1,z2), f(x2,y2,z2), and f(x1,y2,z2).

[0046] Step 2: Select a fixed z value, use the known points to perform spatial linear interpolation, construct a plane α orthogonal to the Z-axis, and divide the α plane into triangles;

[0047] Specifically, it includes:

[0048] Setp1: Construct any orthogonal plane α along the Z-axis, such as Figure 3 The plane formed by the four points Q1, E, P2, and P1;

[0049] Step 2: First, perform linear interpolation along the Z-axis and use formulas (3) to (6) to calculate the values ​​of points Q1, E, P2, and P1 on plane α respectively.

[0050]

[0051]

[0052]

[0053]

[0054] The coordinates of Q1, E, P2, and P1 are (x1, y2, z), (x1, y1, z), (x1, y1, z), and (x2, y1, z), respectively.

[0055] Step 3: Then use formulas (7) to (8) to perform linear interpolation on Q1, E, P1, and P2 in the Y-axis direction to obtain the values ​​of points Q3 and P3;

[0056]

[0057] Step 4: Finally, use formula (9) to perform linear interpolation along the X-axis to obtain the value of point M:

[0058]

[0059] Step 5: Perform linear interpolation along the X-axis to obtain the values ​​of points M1 and M2;

[0060]

[0061]

[0062] Step 6: Divide the four rectangles on plane α into triangles, such as... Figure 5 The division shown is only an example of one triangular division method in this invention. In reality, each rectangle has two triangular division methods, and there are a total of 16 division methods for four rectangles, which will not be listed here.

[0063] Step 3: Divide the plane α, which is orthogonal to the Z-axis, into a uniform grid, and use the cross product and dot product of vectors to solve for the numerical value of any point in the triangular plane;

[0064] like Figure 4 As shown, given the three vertices A, P, and Q of a triangle with corresponding coordinates (xa, ya), (xb, yb), and (xb, yb) and values ​​fa, fb, and fc respectively, the parameter value f at any point H inside the triangle can be obtained using the relationship between the cross product and dot product of vectors.

[0065] Its vector relationship is:

[0066]

[0067] Then we have:

[0068]

[0069] Expanding determinant (12) yields:

[0070]

[0071] The f value of any point H inside the triangle can be determined by equation (12).

[0072] Step 4: Draw several planes α orthogonal to the Z-axis with a fixed step size, and repeat steps 2-3;

[0073] Step 5: Define all planar parameters as surface matrices, use different colors to represent data values, and construct a spatial distribution model of water quality parameters.

[0074] The spatial distribution model of water quality parameters was validated by inserting the collected data of water quality parameters such as temperature, pH, and DO into the spatial distribution model and performing simulations using MATLAB.

[0075] Figure 6 , 7 Figure 8 shows the MATLAB simulation results of temperature, pH, and DO. As can be seen from the figure, the temperature, pH, and DO values ​​do not change much in the horizontal direction, but in the vertical direction, there is obvious stratification and uniform distribution, and the values ​​decrease as the depth of the aquaculture pond increases.

[0076] To further verify the reliability of the spatial distribution model of this invention, the actual sensor measurements and MATLAB simulation values ​​at six points (10,25,0.1), (10,25,1.9), (75,25,0.1), (75,25,1.9), (140,25,0.1), and (140,25,1.9) were compared, and the relative deviation, RMSE, and MAE were calculated. The calculations showed that the measured values ​​of the water quality parameters were basically consistent with the values ​​of the spatial distribution model, with very small relative deviations for temperature, pH, and DO. The RMSE values ​​for temperature, pH, and DO were 0.567, 0.242, and 0.165, respectively; and the MAE values ​​were 0.471, 0.192, and 0.146, respectively. This indicates that the four-dimensional spatial distribution model of this invention can well fit the spatial distribution of water quality parameters in aquaculture ponds, has good predictive performance, and can meet the requirements for accurate prediction of the spatial distribution of water quality parameters in aquaculture ponds.

[0077] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for constructing a spatial distribution model of aquaculture water quality parameters, characterized in that, Includes the following steps: Step 1: Construct a three-dimensional coordinate system in the cuboid space of the aquaculture pond, and insert the water quality parameter values ​​into the eight fixed coordinate points of the cuboid; Step 2: Select a fixed z-value and section a plane orthogonal to the Z-axis. Calculate the coordinates of the four intersection points of the plane and the four Z-axis of the cuboid, and the corresponding water quality parameter values. Perform linear interpolation along the X-axis and Y-axis to obtain the coordinates of the four intersection points and the corresponding water quality parameter values. Connect the intersection points of the X-axis and Y-axis to divide the plane into four rectangles. Connect the two diagonal points within a rectangle to divide the rectangle into two triangles. The formula for calculating the water quality parameter values ​​at 9 points across four rectangles is as follows: （3） （4） （5） （6） （7） （8） （9） （10） （11） in, x 1, x Let 2 be two coordinates on the x-axis of the cuboid space, y1 and y2 be two coordinates on the y-axis of the cuboid space, z1 and z2 be two coordinates on the z-axis of the cuboid space, and x, y, and z be the coordinates of a point on the plane. f () represents the water quality parameter value corresponding to the coordinate; Water quality parameters include: temperature, pH value, and dissolved oxygen (DO) value; Step 3: Perform the cross product and dot product of vectors on any point within the triangle to calculate the water quality parameter value at any point; Step 4: Draw several planes orthogonal to the Z-axis with a fixed step size, and repeat steps 2 and 3. Step 5: Define all planar parameters as surface matrices, use different colors to represent data values, and construct a spatial distribution model of water quality parameters.

2. The method for constructing a spatial distribution model of aquaculture water quality parameters according to claim 1, characterized in that, The formula for the parameter value at any point is: （14） in,( xa,ya ), ( xb,yb ), ( xc,yc ( ) represents the coordinates of the three fixed points of the triangle. fa , fb , fc These are the water quality parameter values ​​corresponding to the coordinates of the three fixed points of the triangle.

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