Method, device and equipment for recommending mooring position of aquaculture facility and storage medium

Abstract

The application provides a culture facility mooring position recommendation method, device, equipment and storage medium, and the method comprises the steps of: acquiring monitoring data of a to-be-predicted area; based on environmental parameter sets, position information and aquatic product category information of a plurality of position points in a preset time sequence, a disease occurrence probability zoning map corresponding to each time point in the preset time sequence is constructed; based on the facility coordinate position of the current culture mooring area, multi-dimensional calculation recommendation is performed in the disease occurrence probability zoning map of each time point to obtain a target recommended mooring position. According to the constructed disease occurrence probability zoning map, the occurrence probability of aquatic diseases is considered, and the multi-dimensional comprehensive distance recommendation method is used to recommend the mooring position, so that the technical problems that the mooring position of the culture ship cannot be predicted and the accuracy of the recommended mooring position is low are solved, and the accuracy of predicting and recommending the mooring position of the culture facility is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aquaculture big data application, and particularly relates to a culture facility mooring position recommendation method and device, equipment and a storage medium. BACKGROUND

[0002] The outbreak and prevalence of diseases currently faced by aquaculture pose a threat to the healthy development of marine ranching and freshwater aquaculture, and the consequences caused by them are becoming more and more serious. The development and application of information monitoring technology in aquaculture have become a trend, and new generation information technology and big data mining and display technology applications are emerging. In view of the current development background of big data, how to integrate and utilize aquaculture data resources, process large-scale monitoring of aquaculture environment related data, and make comprehensive mining and application and visual display of aquaculture big data is a problem to be solved by the present application.

[0003] In order to effectively reduce the occurrence of breeding diseases, it is necessary to change the position of the breeding area regularly according to the environmental information, however, the mooring position of the ocean aquaculture ship is mainly determined according to the nutrient substances in the current breeding environment, which cannot visually predict the mooring position of the aquaculture ship, and the factors considered in determining the mooring position are too single, resulting in low accuracy of recommending suitable mooring position. SUMMARY

[0004] The present application provides a culture facility mooring position recommendation method, device, equipment and storage medium, which aims to improve the visualization and accuracy of predicting and recommending the mooring position of the culture facility.

[0005] The present application provides a culture facility mooring position recommendation method, comprising:

[0006] Obtaining monitoring data of a to-be-predicted area, wherein the monitoring data comprises a set of environmental parameters of a plurality of position points in the to-be-predicted area at a preset time sequence, position information and water product type information;

[0007] Based on the set of environmental parameters of the plurality of position points at the preset time sequence, the position information and the water product type information, a disease occurrence probability zoning map corresponding to each time point in the preset time sequence of the to-be-predicted area is constructed;

[0008] Based on the facility coordinate position of the current breeding mooring area, multi-dimensional calculation recommendation is performed in the disease occurrence probability zoning map corresponding to each time point, to obtain a target recommended mooring position.

[0009] Optionally, the application provides a method for recommending a mooring position of a cultivation facility. The method comprises the following steps: constructing a disease occurrence probability zoning map or a cultivation suitability map corresponding to each time point in a preset time sequence for the to-be-predicted area based on a set of environmental parameters of the plurality of position points in the preset time sequence, position information, and aquatic product category information, wherein the method comprises the following steps:

[0010] obtaining a disease occurrence probability corresponding to each time point for each position point based on the set of environmental parameters of each position point in the preset time sequence and the aquatic product category information, and a pre-constructed aquatic disease occurrence probability knowledge base, wherein the aquatic disease occurrence probability knowledge base comprises a set of environmental parameters when a target disease occurs, an aquatic disease probability conversion matrix, and an environmental tolerance range of the aquatic product category;

[0011] for any time point, connecting position points having the same disease occurrence probability based on the disease occurrence probability corresponding to the time point for each position point to form a plurality of annular probability contour maps;

[0012] dividing and marking a plurality of regions of different hazard levels in the probability contour map based on the disease occurrence probability in the probability contour map and a preset hazard degree threshold to form the disease occurrence probability zoning map.

[0013] Optionally, the application provides a method for recommending a mooring position of a cultivation facility. The time points in the preset time sequence comprise a plurality of future time points. The method comprises the following steps: performing multi-dimensional calculation recommendation in the disease occurrence probability zoning map corresponding to each time point based on a facility coordinate position of a current cultivation mooring area to obtain a target recommended mooring position, wherein the method comprises the following steps:

[0014] for the disease occurrence probability zoning map corresponding to any future time point, calculating a plurality of alternative mooring areas based on the facility coordinate position and each target region having the lowest hazard level in the disease occurrence probability zoning map;

[0015] calculating a comprehensive comparison distance between the current cultivation mooring area and each alternative mooring area based on the facility coordinate position and the coordinate position of each alternative mooring area in the future time point;

[0016] comparing the comprehensive comparison distance of each alternative mooring area with a preset comparison threshold, and determining the target recommended mooring position corresponding to the future time point based on the comparison result.

[0017] Optionally, the application provides a method for recommending a mooring position of a cultivation facility. The method comprises the following steps: calculating a plurality of alternative mooring areas based on the facility coordinate position and each target region having the lowest hazard level in the disease occurrence probability zoning map, wherein the method comprises the following steps:

[0018] Calculate the distance between the facility coordinate position and each target area with the lowest hazard level, and select a preset number of target areas as alternative mooring areas based on the distance.

[0019] Optionally, according to the aquaculture facility mooring position recommendation method provided by the present application, the comprehensive comparison distance between the current aquaculture mooring area and each alternative mooring area is calculated based on the facility coordinate position and the coordinate position of each alternative mooring area corresponding to the future time point, which comprises:

[0020] Calculate the target distance between the current aquaculture mooring area and each alternative mooring area based on the facility coordinate position and the coordinate position of each alternative mooring area.

[0021] Calculate the probability difference between the current aquaculture mooring area and each alternative mooring area.

[0022] Based on the probability difference and the target distance corresponding to each alternative mooring area, the comprehensive comparison distance between the current aquaculture mooring area and each alternative mooring area is calculated according to a preset comprehensive comparison algorithm.

[0023] Optionally, according to the aquaculture facility mooring position recommendation method provided by the present application, the comprehensive comparison distance of each alternative mooring area is compared with a preset comparison threshold value, and based on the comparison result, the target recommended mooring position corresponding to the future time point is determined, which comprises:

[0024] Compare the comprehensive comparison distance of each alternative mooring area with a preset comparison threshold value.

[0025] If the minimum value in the comparison result is the preset comparison threshold value, the facility coordinate position of the current aquaculture mooring area is taken as the target recommended mooring position.

[0026] If the minimum value in the comparison result is the comprehensive comparison distance, the coordinate position of the alternative mooring area corresponding to the minimum value is taken as the target recommended mooring position.

[0027] Optionally, according to the aquaculture facility mooring position recommendation method provided by the present application, after the comprehensive comparison distance of each alternative mooring area is compared with a preset comparison threshold value, and based on the comparison result, the target recommended mooring position corresponding to the future time point is determined, it further comprises:

[0028] According to a preset update time period, return to execute the step of obtaining the monitoring data of the area to be predicted to dynamically update the target recommended mooring position.

[0029] The application further provides a breeding facility mooring position recommendation device, comprising:

[0030] An acquisition module is configured to acquire monitoring data of a to-be-predicted area, wherein the monitoring data comprises a set of environmental parameters, position information, and aquatic product type information of a plurality of position points in the to-be-predicted area at a preset time sequence.

[0031] A construction module is configured to construct a disease occurrence probability zoning map corresponding to each time point in the preset time sequence based on the set of environmental parameters, position information, and aquatic product type information of the plurality of position points at the preset time sequence.

[0032] A calculation recommendation module is configured to perform multi-dimensional calculation recommendation in the disease occurrence probability zoning map corresponding to each time point based on a facility coordinate position of a current breeding mooring area to obtain a target recommended mooring position.

[0033] The application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the breeding facility mooring position recommendation method according to any one of the above when executing the program.

[0034] The application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program is executable by a processor to implement the breeding facility mooring position recommendation method according to any one of the above.

[0035] The application further provides a computer program product comprising a computer program, wherein the computer program is executable by a processor to implement the breeding facility mooring position recommendation method according to any one of the above.

[0036] The breeding facility mooring position recommendation method, device, equipment, and storage medium provided by the application provide a basis for prediction and change of a breeding facility mooring position by constructing a disease occurrence probability zoning map corresponding to each time point based on a set of environmental parameters, position information, and aquatic product type information of a plurality of position points at a preset time sequence, and further consider aquatic disease occurrence probability, recommend a mooring position by a multi-dimensional comprehensive distance recommendation method, and improve the visualization degree and accuracy of prediction and recommendation of a breeding facility mooring position. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0038] Figure 1 is one of the flow diagrams of the aquaculture facility mooring position recommendation method provided by the present application;

[0039] Figure 2 is a structural diagram of the aquaculture facility mooring position recommendation device provided by the present application;

[0040] Figure 3 is a structural diagram of the electronic device provided by the present application. DETAILED DESCRIPTION

[0041] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0042] The terms used in one or more embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of the present application. The singular forms "a", "said" and "the" used in one or more embodiments of the present application are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in one or more embodiments of the present application means and includes any or all possible combinations of one or more associated listed items.

[0043] It should be understood that although the terms first, second, etc. may be used in one or more embodiments of the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of one or more embodiments of the present application, first can also be referred to as second, and similarly, second can also be referred to as first. Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon" or "in response to determining".

[0044] The following will be described in combination with Figure 1 The example embodiments of the present application will be described in detail.

[0045] As Figure 1 shown is a flowchart of an aquaculture facility mooring position recommendation method according to an embodiment of the present application. As Figure 1 shown, the aquaculture facility mooring position recommendation method comprises:

[0046] Step S10, obtaining monitoring data of the to-be-predicted area, wherein the monitoring data comprises a set of environmental parameters of a plurality of position points in the to-be-predicted area at a preset time sequence, position information, and water product species information;

[0047] It should be noted that the monitoring data refers to data in a limited sea area of a culture facility such as a culture ship or a large water area, and the length of the preset time sequence is not limited, for example, the current time point is t0, and the length of the time period is T, T includes past time points and future time points; the set of environmental parameters comprises a plurality of environmental parameters, including water temperature, PH, dissolved oxygen, turbidity chlorophyll, transparency, nitrate, weather information, salinity, water pressure, density, meteorological data, current speed, and nutritional status parameter information; the position information of the position points represents the latitude and longitude information of the position points; and the water product species represents at least one water product biological species, such as fish and shrimp.

[0048] Specifically, the environmental parameters of the to-be-predicted area can be obtained by crawling a relevant parameter source website, for example, by obtaining the temperature at each time point in the preset time sequence through a weather forecast website. In another implementation manner, the set of environmental parameters of the plurality of position points at the past time period and the current time point can be obtained by monitoring through a pre-set monitoring device. The position points of the monitoring device can be uniformly and regularly distributed in the data generation area or the to-be-predicted area. Preferably, the monitoring device can predict the environmental parameters corresponding to a future time period based on the set of environmental parameters at the past time period and the current time point, for example, the environmental parameters corresponding to the future time period can be predicted by using a data model prediction and a statistical prediction, so as to obtain the set of environmental parameters of the plurality of position points in the to-be-predicted area at the preset time sequence. Preferably, the value of the environmental parameter is a daily average value or a value at a time point in a day.

[0049] Step S20, constructing a disease occurrence probability zoning map or a culture suitability zoning map corresponding to each time point in the preset time sequence of the to-be-predicted area based on the set of environmental parameters of the plurality of position points at the preset time sequence, the position information, and the water product species information;

[0050] Specifically, the following steps are performed for the set of environmental parameters of each time point in the preset time sequence:

[0051] As an implementable manner, based on the environmental parameter set of the plurality of position points in a preset time sequence and the aquatic product category information, a disease occurrence probability of a target disease that each position point needs to predict is queried in a pre-constructed aquatic disease occurrence probability knowledge base, wherein the pre-constructed aquatic disease occurrence probability knowledge base comprises an environmental parameter set when the target disease occurs, an aquatic disease probability conversion matrix and an aquatic product category tolerance environmental range, and the target disease is one or more of aquatic diseases.

[0052] Further, after the disease occurrence probability of each position point is calculated, based on the position information of each position point, a plurality of marker points are formed, and each marker point is marked, and further, based on the disease occurrence probability corresponding to each position point, the marker points with the same disease occurrence probability are connected to form a closed ring, which is an occurrence probability contour map, wherein the occurrence probability contour map can comprise a plurality of contours, and it should be noted that the contour map is also called the isogram, which is a graph that represents the continuous distribution and gradual change of a quantity characteristic by connecting equal value points, and the contour map adopts the projection of the curve (i.e. the contour) formed by connecting equal value points on the plane to represent the parameter, and the contour map comprises the hypsographic map, the isotherm map and the like, and in the embodiment of the present application, it is the isodisease occurrence probability contour map. After the contour map is completed, based on the disease occurrence probability in the probability contour map and a preset harm degree threshold, the probability contour map is divided into a plurality of regions of different harm levels to form a disease occurrence probability zoning map corresponding to each time point, and the preset harm degree threshold can be dynamically set according to the actual division, a plurality of thresholds can be set for division, which is not specifically limited herein, for example, based on the disease occurrence probability in the occurrence probability contour map, the region with a disease occurrence probability higher than 0.8 is divided into a high-risk area, the region with a disease occurrence probability higher than 0.6 and lower than 0.8 is divided into a susceptible area, and the region with a disease occurrence probability lower than 0.2 is divided into a suitable area. Thus, the breeding area can be visually classified and zoned, and the disease occurrence situation can be intuitively understood based on the disease occurrence probability zoning map of each future time point, thereby providing a basis for predicting and recommending changes of the mooring position of the breeding facility.

[0053] In step S30, based on the facility coordinate position of the current breeding mooring area, multi-dimensional calculation recommendation is performed in the disease occurrence probability zoning map corresponding to each time point to obtain a target recommended mooring position.

[0054] It should be noted that the facility coordinate position is the latitude and longitude position corresponding to the current breeding facility, and the multi-dimensional calculation recommendation is a processing method of recommendation based on the facility coordinate position of the current breeding mooring area in the disease occurrence probability zoning map corresponding to each time point in combination with a plurality of calculation methods, such as the Euclidean distance, the Mahalanobis distance, the vector similarity and the probability difference.

[0055] Specifically, the following steps are performed for the disease occurrence probability zoning map corresponding to any future time point:

[0056] As an implementable manner, in each region of the disease occurrence probability zoning map classified by hazard levels, target regions with the lowest hazard levels are determined, target distances, such as Euclidean distance, Mahalanobis distance, etc., between the current aquaculture mooring region and each target region are calculated based on the facility coordinate position and the coordinate position of each target region, and the probability difference between the current aquaculture mooring region and each target region is calculated, further, the comprehensive comparison distance between the current aquaculture mooring region and each target region is calculated based on the probability difference and the target distance corresponding to each target region. Then, the comprehensive comparison distance of each target region is compared with a preset comparison threshold, thereby determining the target recommended mooring position corresponding to the future time point, wherein the preset comparison threshold can be set based on actual conditions, which is not specifically limited here.

[0057] In order to reduce the amount of calculation and improve the efficiency of position recommendation, in another implementable manner, in each region of the disease occurrence probability zoning map classified by hazard levels, target regions with the lowest hazard levels are determined, the center coordinate position of each target region is calculated, and then the distance between the center coordinate position of each target region and the facility coordinate position is calculated, and a plurality of target regions with shorter distance are selected as the first recommended alternative mooring region, for example, 5 target regions are selected as the alternative mooring region, in another implementable manner, the probability difference corresponding to each target region can also be calculated according to the disease occurrence probability corresponding to the facility coordinate position and each target region, and then the alternative mooring region is comprehensively calculated by combining the probability difference and the distance. Further, the target distance between the current aquaculture mooring region and each alternative mooring region is calculated based on the facility coordinate position and the coordinate position of each alternative mooring region, and the probability difference between the current aquaculture mooring region and each alternative mooring region is calculated, and then the comprehensive comparison distance between the current aquaculture mooring region and each alternative mooring region is calculated based on the probability difference and the target distance corresponding to each alternative mooring region. Then, the comprehensive comparison distance of each alternative mooring region is compared with a preset comparison threshold, thereby determining the target recommended mooring position corresponding to the future time point.

[0058] In addition, if the facility coordinate position of the current aquaculture mooring region changes, steps S10 to S30 are returned to execute to re-recommend the target recommended mooring position.

[0059] The embodiment of the present application realizes the disease occurrence probability zoning map corresponding to each time point by the above scheme based on the environmental parameter set, position information and aquatic product category information of the plurality of position points in the preset time sequence, provides a basis for predicting and changing the mooring position of the aquaculture facility, and further considers the aquatic disease occurrence probability, recommends the mooring position through the multi-dimensional comprehensive distance recommendation method, and improves the visualization degree and accuracy of predicting and recommending the mooring position of the aquaculture facility.

[0060] In an embodiment, the step S20 of constructing the disease occurrence probability zoning map corresponding to each time point of the to-be-predicted area in the preset time sequence based on the environmental parameter set, position information and aquatic product category information of the plurality of position points in the preset time sequence comprises:

[0061] In an embodiment, the step S21 of acquiring the disease occurrence probability corresponding to each time point of each position point based on the environmental parameter set and aquatic product category information of each position point in the preset time sequence through the pre-constructed aquatic disease occurrence probability knowledge base comprises:

[0062] In an embodiment, the step S22 of connecting the position points with the same disease occurrence probability to form a plurality of annular probability contour maps based on the disease occurrence probability corresponding to each time point of each position point comprises:

[0063] In an embodiment, the step S23 of dividing and marking a plurality of regions with different damage levels in the probability contour map based on the disease occurrence probability in the probability contour map and the preset damage degree threshold value to form the disease occurrence probability zoning map comprises:

[0064] It should be noted that the different aquatic categories and their prone diseases are classified and arranged, the knowledge base of different disease occurrence environmental parameters is established, and the probabilities of different categories of diseases in the same region are different.

[0065] Specifically, the environmental parameter set, the aquatic product category information and the target disease category of the to-be-predicted area are acquired through the pre-constructed aquatic disease occurrence probability knowledge base, the environmental parameter set, the aquatic disease probability conversion matrix and the aquatic product category tolerance environmental range when the target disease occurs are acquired, and then the disease occurrence probability corresponding to each position point is calculated according to the environmental parameter set of each position point, the environmental parameter set when the target disease occurs, the aquatic disease probability conversion matrix and the aquatic product category tolerance environmental range. The disease occurrence probability calculation formula is as follows:

[0066] Pi = 1 - |Qi - Q0| / S * B

[0067] wherein, P i represents the disease occurrence probability of the i-th position point, Q i represents the environmental parameter set of the i-th position point, Q0 represents the environmental parameter set when the target disease occurs, B represents the aquatic disease probability conversion matrix, and S represents the environmental range tolerated by the aquatic product species.

[0068] Further, the position points with the same disease occurrence probability are connected by a smooth curve to draw a two-dimensional probability contour map, so that the position points with the same disease occurrence probability are connected to form one layer after another closed loop, and each loop corresponds to a specific disease occurrence probability. Further, after the probability contour map is completed, based on the disease occurrence probability in the probability contour map and a preset damage degree threshold, the probability contour map is divided and marked into regions of different damage levels, thereby forming the disease occurrence probability zoning map. For example, the division can be performed according to a preset proportion threshold, and based on the disease occurrence probability of each position point, the first 20% is divided into one level, 20% to 40% is divided into one level, 40% to 60% is divided into one level, and the remaining 40% is divided into one level. Since the map reflects the disease occurrence probability in the entire monitoring area, different colors can be used to render different probability contours when displayed to distinguish and enhance the visual effect.

[0069] Understandably, based on the aquatic disease occurrence probability value P i of each spatial position point at each time point and the position information of the spatial position point L i , the correlation data set information [Pi, L i ](i = 1, 2, 3,..., n) is obtained, and then based on the correlation data set information, the zoning map of the monitoring area at each time point is dynamically drawn, wherein L i is a two-dimensional or three-dimensional spatial coordinate parameter, including longitude, latitude and depth information.

[0070] The embodiment of the present application realizes the calculation of the disease occurrence probability of each position point at each time point based on the environmental parameter set, position information and aquatic product species information of a plurality of position points in a predetermined time sequence in a to-be-predicted area, thereby constructing the disease occurrence probability zoning map of the to-be-predicted area corresponding to each time point in a predetermined time sequence, and laying a foundation for the prediction of the mooring position of the breeding facility.

[0071] In an embodiment, the step S30 of calculating the target recommended mooring position based on the facility coordinate position of the current aquaculture mooring area in the disease occurrence probability zoning map corresponding to each time point comprises the following steps:

[0072] The step S31 comprises the following steps:

[0073] Preferably, the plurality of alternative mooring areas can also be generated according to other maps, such as the aquaculture suitability zoning map and the disease occurrence probability zoning map described in the present embodiment.

[0074] The step S31 comprises the following steps:

[0075] The step S311 comprises the following steps:

[0076] Specifically, the following steps are performed for the disease occurrence probability zoning map corresponding to each future time point:

[0077] The step S31 comprises the following steps:

[0078] The step S32 comprises the following steps:

[0079] The step S32 comprises the following steps:

[0080] The step S321 comprises the following steps:

[0081] The step S322 comprises the following steps:

[0082] Step S323, based on the probability difference value corresponding to each of the alternative mooring areas and the target distance, a preset comprehensive comparison algorithm is used to calculate the comprehensive comparison distance between the current aquaculture mooring area and each of the alternative mooring areas.

[0083] Specifically, for any future time point: based on the coordinate position of the facility and the coordinate position of each of the alternative mooring areas, the target distance between the current aquaculture mooring area and each of the alternative mooring areas is calculated, and based on the disease occurrence probability corresponding to the current aquaculture mooring area and the disease occurrence probability corresponding to each of the alternative mooring areas, the probability difference value between the current aquaculture mooring area and each of the alternative mooring areas is calculated respectively, further, based on each of the target distances, the fuel, aquaculture loss and other consumption costs corresponding to each of the alternative mooring areas are calculated, and then based on the probability difference value and the consumption cost corresponding to each of the alternative mooring areas, a preset comprehensive comparison algorithm is used to calculate the comprehensive comparison distance between the current aquaculture mooring area and each of the alternative mooring areas. The formula of the preset comprehensive comparison algorithm is as follows:

[0084]

[0085] Wherein, Y Eco represents the cumulative sum of the generated fuel, aquaculture loss and other cost difference values from t0 to P time period, Y Har represents the cumulative sum of the generated probability difference values between two points from t0 to P time period, Y Per represents the cumulative sum of the generated effective health aquaculture conditions between two points from t0 to P time period, wherein the effective health aquaculture condition represents an effective condition that reaches an effective environmental condition, such as effective accumulated temperature. L i represents the coordinate position of the alternative mooring area, L0 represents the coordinate position of the facility, P represents the time point in the preset time sequence, P=t0+nt, P is a safety correction coefficient (generally taken as 0.9, and increases with the distance from the shore).

[0086] Step S33, respectively compare the comprehensive comparison distance of each of the alternative mooring areas with a preset comparison threshold, and based on the comparison result, determine the target recommended mooring position corresponding to the future time point.

[0087] The above step S33 includes:

[0088] Step S331, respectively compare the comprehensive comparison distance of each of the alternative mooring areas with a preset comparison threshold;

[0089] Step S332, if the minimum value in the comparison result is the preset comparison threshold, the facility coordinate position of the current aquaculture mooring area is taken as the target recommended mooring position;

[0090] Step S333, if the minimum value in the comparison result is the integrated comparison distance, the coordinate position of the alternative mooring area corresponding to the minimum value is taken as the target recommended mooring position.

[0091] Specifically, the integrated comparison distance of each alternative mooring area is compared with the preset comparison threshold respectively, if the minimum value in the comparison result corresponding to each alternative mooring area is the preset comparison threshold, it is proved that the best recommended position is the facility coordinate position of the current aquaculture mooring area, and then the facility coordinate position of the current aquaculture mooring area is taken as the target recommended mooring position, if the minimum value in the comparison result is the integrated comparison distance of a certain alternative mooring area, the coordinate position of the alternative mooring area corresponding to the minimum value is taken as the target recommended mooring position, wherein the preset comparison threshold can be set based on actual situation, which is not limited here, and the determination method of the target recommended mooring position is as follows:

[0092] F Recommend = min(||Distance(L i ,L0,P),A||,B),i = 1,2,…,N

[0093] Wherein, F Recommend represents the target recommended mooring position function, ||Distance(L i ,L0,P),A|| represents the distance value between two matrices; Distance(L i ,L0,P) represents the matrix corresponding to the integrated comparison distance between the current aquaculture mooring area and the alternative mooring area, L i represents the coordinate position of the alternative mooring area, N represents the number of alternative mooring areas, L0 represents the facility coordinate position, P represents the time point in the preset time sequence, wherein P = t0+nt, P < T, t0 represents the current time point, T represents the length of input preset time sequence, A represents the preset standard distance matrix, and B represents the preset comparison threshold. Further, the disease occurrence probability zoning map of the target recommended mooring position at the future time point is highlighted.

[0094] Further, after obtaining the target recommended mooring position, the step of obtaining the monitoring data of the to-be-predicted area can be performed again according to a preset update time period to dynamically update the target recommended mooring position, where the preset update time period can be dynamically set according to actual conditions, for example, the preset update time period is t1, where t0≤t1≤nt, and the target recommended mooring position is updated again every t1 time to enable the position recommendation to cover the calculation result each time.

[0095] The embodiment of the present application realizes, in the disease occurrence probability partition map corresponding to each time point, consideration of the aquatic disease occurrence probability, recommendation of the mooring position by a multi-dimensional comprehensive distance recommendation method, and improvement of the visualization degree, automation degree and accuracy of the mooring position recommendation.

[0096] The aquaculture facility mooring position recommendation device provided by the present application is described below, and the aquaculture facility mooring position recommendation device described below can be correspondingly referred to the aquaculture facility mooring position recommendation method described above.

[0097] As shown in Figure 2 The aquaculture facility mooring position recommendation device of the embodiment of the present application comprises:

[0098] The obtaining module 10 is configured to obtain monitoring data of a to-be-predicted area, where the monitoring data comprises a set of environmental parameters of a plurality of position points in the to-be-predicted area at a preset time sequence, position information and water product type information.

[0099] The construction module 20 is configured to construct a disease occurrence probability partition map corresponding to each time point in the preset time sequence based on the set of environmental parameters of the plurality of position points at the preset time sequence, the position information and the water product type information.

[0100] The calculation recommendation module 30 is configured to perform multi-dimensional calculation recommendation in the disease occurrence probability partition map corresponding to each time point based on the facility coordinate position of the current aquaculture mooring area to obtain a target recommended mooring position.

[0101] Optionally, the construction module 20 is further configured to:

[0102] Based on the set of environmental parameters of each position point at the preset time sequence and the water product type information, a disease occurrence probability knowledge base of aquatic diseases is pre-constructed to obtain the disease occurrence probability of each position point at each time point, where the disease occurrence probability knowledge base of aquatic diseases comprises a set of environmental parameters when a target disease occurs, an aquatic disease probability conversion matrix and a water product type tolerance environment range.

[0103] For any one time point, based on the disease occurrence probability of each position point corresponding to the time point, the position points with the same disease occurrence probability are connected to form a plurality of annular probability contour maps;

[0104] Based on the disease occurrence probability in the probability contour map and a preset damage degree threshold, the probability contour map is divided and marked into a plurality of regions of different damage levels to form the disease occurrence probability partition map.

[0105] Optionally, the computing recommendation module 30 is further configured to:

[0106] For the disease occurrence probability partition map corresponding to any one future time point, based on the facility coordinate position and each target region with the lowest damage level in the disease occurrence probability partition map, a plurality of alternative berthing regions are calculated.

[0107] Based on the facility coordinate position and the coordinate position of each alternative berthing region in the future time point, the comprehensive comparison distance between the current aquaculture berthing region and each alternative berthing region is calculated.

[0108] The comprehensive comparison distance of each alternative berthing region is compared with a preset comparison threshold, and based on the comparison result, the target recommended berthing position corresponding to the future time point is determined.

[0109] Optionally, the computing recommendation module 30 is further configured to:

[0110] The distance between the facility coordinate position and each target region with the lowest damage level is calculated, and a preset number of target regions are selected as alternative berthing regions based on the distance.

[0111] Optionally, the computing recommendation module 30 is further configured to:

[0112] Based on the facility coordinate position and the coordinate position of each alternative berthing region, the target distance between the current aquaculture berthing region and each alternative berthing region is calculated.

[0113] The probability difference between the current aquaculture berthing region and each alternative berthing region is calculated.

[0114] Based on the probability difference and the target distance corresponding to each alternative berthing region, the comprehensive comparison distance between the current aquaculture berthing region and each alternative berthing region is calculated according to a preset comprehensive comparison algorithm.

[0115] Optionally, the computing recommendation module 30 is further configured to:

[0116] The comprehensive comparison distance of each alternative berthing region is compared with a preset comparison threshold;

[0117] If the minimum value in the comparison result is the preset comparison threshold, the facility coordinate position of the current aquaculture mooring area is taken as the target recommended mooring position.

[0118] If the minimum value in the comparison result is the comprehensive comparison distance, the coordinate position of the alternative mooring area corresponding to the minimum value is taken as the target recommended mooring position.

[0119] Optionally, the aquaculture facility mooring position recommendation device further comprises:

[0120] The disease occurrence probability zoning map of the target recommended mooring position at the future time point is highlighted.

[0121] Optionally, the aquaculture facility mooring position recommendation device further comprises:

[0122] If the facility coordinate position of the current aquaculture mooring area changes, the step of obtaining the monitoring data of the to-be-predicted area is performed again to re-recommend the target recommended mooring position.

[0123] It should be noted that the above device provided by the embodiments of the present application can realize all the method steps realized by the above method embodiments and achieve the same technical effects. Therefore, the same parts and beneficial effects of the method embodiments will not be described in detail herein.

[0124] Figure 3 An example of an entity structure diagram of an electronic device is shown, which can include a processor 310, a memory 320, a communication interface 330, and a communication bus 340. The processor 310, the memory 320, and the communication interface 330 can communicate with each other through the communication bus 340. The processor 310 can invoke the logical instructions in the memory 320 to execute the aquaculture facility mooring position recommendation method, which includes: obtaining monitoring data of a to-be-predicted area, wherein the monitoring data includes a set of environmental parameters of a plurality of position points in the to-be-predicted area at a preset time sequence, position information, and aquatic product species information; based on the set of environmental parameters of the plurality of position points at the preset time sequence, the position information, and the aquatic product species information, constructing a disease occurrence probability zoning map corresponding to each time point of the to-be-predicted area at a preset time sequence; and based on the facility coordinate position of the current aquaculture mooring area, performing multi-dimensional calculation recommendation in the disease occurrence probability zoning map corresponding to each time point to obtain a target recommended mooring position.

[0125] In addition, the logic instructions in the memory 320 described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0126] In another aspect, the present application also provides a non-transitory computer readable storage medium having stored thereon a computer program, which, when executed by a processor, implements a method for recommending a mooring position of a culture facility, the method comprising: obtaining monitoring data of a to-be-predicted area, wherein the monitoring data comprises a set of environmental parameters, position information, and aquatic product type information of a plurality of position points in the to-be-predicted area at a preset time sequence; constructing a disease occurrence probability zoning map corresponding to each time point in the preset time sequence for the to-be-predicted area based on the set of environmental parameters, position information, and aquatic product type information of the plurality of position points at the preset time sequence; and performing multi-dimensional calculation recommendation in the disease occurrence probability zoning map corresponding to each time point based on a facility coordinate position of a current culture mooring area to obtain a target recommended mooring position.

[0127] In another aspect, the present application also provides a computer program product comprising a computer program, which can be stored on a non-transitory computer-readable storage medium, and the computer program can be executed by a processor to enable a computer to perform the aquaculture facility mooring position recommendation method provided by the above method, which comprises: obtaining monitoring data of a to-be-predicted area, wherein the monitoring data comprises a set of environmental parameters, position information, and aquatic product type information of a plurality of position points in the to-be-predicted area at a preset time sequence; constructing a disease occurrence probability zoning map corresponding to each time point in the preset time sequence of the to-be-predicted area based on the set of environmental parameters, position information, and aquatic product type information of the plurality of position points at the preset time sequence; and performing multi-dimensional calculation recommendation in the disease occurrence probability zoning map corresponding to each time point based on the facility coordinate position of the current aquaculture mooring area to obtain a target recommended mooring position. The device embodiments described above are only illustrative, wherein the units illustrated as separate components can or can not be physically separated, and the components illustrated as units can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Some or all modules can be selected to achieve the purpose of the present embodiment scheme according to actual needs. Those skilled in the art can understand and implement it without creative labor.

[0128] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software and the necessary general hardware platform, and of course, can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in terms of contribution to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0129] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for recommending mooring locations for aquaculture facilities, characterized in that, include: Acquire monitoring data of the area to be predicted, wherein the monitoring data includes a set of environmental parameters, location information and aquatic product type information of multiple location points in the area to be predicted over a preset time series; Based on the environmental parameter set, location information and aquatic product type information of the multiple location points in the preset time series, a disease occurrence probability partition map corresponding to each time point in the preset time series of the area to be predicted is constructed. The time points in the preset time series include multiple future time points. For any future point in time corresponding to the disease occurrence probability zoning map, calculate the facility coordinates of the current aquaculture mooring area and the distance between each target area with the lowest hazard level in the disease occurrence probability zoning map, and select a preset number of target areas as alternative mooring areas based on the distance. Based on the coordinates of the facility and the coordinates of each alternative mooring area at the future time point, the comprehensive comparative distance between the current aquaculture mooring area and each of the alternative mooring areas is calculated. The comprehensive comparison distance of each of the candidate mooring areas is compared with a preset comparison threshold, and the target recommended mooring location corresponding to the future time point is determined based on the comparison results.

2. The method for recommending mooring locations for aquaculture facilities according to claim 1, characterized in that, The step of constructing a disease occurrence probability partition map for each time point in the preset time series based on the environmental parameter set, location information, and aquatic product type information of the multiple location points includes: Based on the set of environmental parameters and aquatic product type information of each location point in a preset time series, the probability of disease occurrence at each location point at each time point is obtained through a pre-constructed aquatic disease occurrence probability knowledge base. The aquatic disease occurrence probability knowledge base includes the set of environmental parameters when the target disease occurs, the aquatic disease probability transformation matrix, and the environmental tolerance range of aquatic product types. For any given time point, based on the probability of disease occurrence at each location point at that time point, connect the location points with the same probability of disease occurrence to form multiple circular probability contour maps. Based on the disease occurrence probability and preset hazard level threshold in the probability contour map, the probability contour map is divided and marked into multiple regions with different hazard levels to form the disease occurrence probability zoning map.

3. The method for recommending mooring locations for aquaculture facilities according to claim 1, characterized in that, The calculation of the comprehensive comparative distance between the current aquaculture mooring area and each of the candidate mooring areas, based on the coordinates of the facility and the coordinates of each candidate mooring area at the future time point, includes: Based on the coordinates of the facility and the coordinates of each of the alternative mooring areas, the target distance between the current aquaculture mooring area and each of the alternative mooring areas is calculated. Calculate the probability difference between the current aquaculture mooring area and each of the alternative mooring areas; Based on the probability difference and target distance corresponding to each of the alternative mooring areas, the comprehensive comparison distance between the current aquaculture mooring area and each of the alternative mooring areas is calculated according to a preset comprehensive comparison algorithm.

4. The method for recommending mooring locations for aquaculture facilities according to claim 1, characterized in that, The step of comparing the comprehensive comparison distance of each of the candidate mooring areas with a preset comparison threshold, and determining the target recommended mooring location corresponding to the future time point based on the comparison results, includes: The comprehensive comparison distance of each of the candidate mooring areas is compared with a preset comparison threshold. If the minimum value in the comparison results is the preset comparison threshold, then the facility coordinates of the current aquaculture mooring area are taken as the target recommended mooring location. If the minimum value in the comparison results is the comprehensive comparison distance, then the coordinates of the alternative mooring area corresponding to the minimum value are taken as the target recommended mooring location.

5. The method for recommending mooring locations for aquaculture facilities according to claim 1, characterized in that, After comparing the comprehensive comparison distance of each of the candidate mooring areas with a preset comparison threshold, and determining the target recommended mooring location corresponding to the future time point based on the comparison results, the method further includes: Based on the preset update time period, return to the step of obtaining monitoring data of the area to be predicted in order to dynamically update the target recommended mooring position.

6. A mooring location recommendation device for aquaculture facilities, characterized in that, include: The acquisition module is used to acquire monitoring data of the area to be predicted, wherein the monitoring data includes a set of environmental parameters, location information and aquatic product type information of multiple location points in the area to be predicted in a preset time series; The construction module is used to construct a disease occurrence probability partition map for each time point in the preset time series of the area to be predicted, based on the environmental parameter set, location information and aquatic product type information of the multiple location points in the preset time series. The time points in the preset time series include multiple future time points. The recommendation module is used to calculate the distance between the facility coordinates of the current aquaculture mooring area and the target areas with the lowest hazard levels in the disease occurrence probability zoning map corresponding to any future time point, and select a preset number of target areas as alternative mooring areas based on the distance; and calculate the comprehensive comparison distance between the current aquaculture mooring area and each of the alternative mooring areas based on the facility coordinates and the coordinates of each alternative mooring area at the future time point. The comprehensive comparison distance of each of the candidate mooring areas is compared with a preset comparison threshold, and the target recommended mooring location corresponding to the future time point is determined based on the comparison results.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for recommending mooring locations for aquaculture facilities as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for recommending mooring locations for aquaculture facilities as described in any one of claims 1 to 5.

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