Artificial rearing method of litchidius spp. based on growth environment regulation

Abstract

The present application relates to a kind of artificial assisted rearing method of litchi bug based on growth environment regulation, belong to litchi bug breeding technical field, the present application obtains the environmental regulation cost data of each climate characteristic data under the environmental regulation equipment in unit breeding area when environmental regulation, and the climate characteristic data of each subregion in target area within the preset time is obtained Environmental regulation cost data of each subregion in litchi bug unit breeding area when artificial assisted rearing, finally according to the environmental regulation cost data of each subregion in litchi bug unit breeding area when artificial assisted rearing Filtered out recommended artificial assisted rearing area, and according to recommended artificial assisted rearing area is assisted, and the growth environment in assisted rearing area is regulated in real time.The present application selects recommended breeding area, reduces environmental regulation cost, so that breeding cost is controlled within predetermined range, improves the rationality of artificial assisted rearing to litchi bug.

Description

Technical Field

[0001] This invention relates to the field of litchi bug farming technology, and in particular to an artificial breeding method for litchi bugs based on the regulation of the growth environment. Background Technology

[0002] The lychee bug damages the flower spikes and young fruits of lychee and longan, leading to significant yield reductions or affecting fruit quality. Since indoor artificial rearing of lychee bugs is not feasible, current scientific research primarily relies on capturing adult bugs in orchards in spring. This method is time-consuming, labor-intensive, and carries the risk of skin and eye burns from the bug's secretions, causing accidental injuries. Fried lychee bugs are a popular delicacy, and local fruit farmers can earn a considerable income by catching and selling wild lychee bugs. However, catching large numbers of bugs requires substantial manpower and resources, and the complex wild environment exposes farmers to attacks from venomous snakes and insects, resulting in personal injury. In nature, the lychee bug develops from a newly hatched nymph to an adult in just over 80 days, theoretically allowing for multiple generations per year. However, because lychee and longan fruits only once a year, the lychee bug typically has only one generation per year, rarely two. Therefore, by fully simulating the natural environment and creating conditions conducive to the growth and development of the litchi bug, artificial breeding of litchi bugs can be achieved. Specifically, this involves using longan trees, which flower year-round, as food for the litchi bugs. Multiple generations of litchi bugs can be raised annually, reducing breeding costs. This provides litchi bugs year-round for scientific research and also supplies fresh litchi bugs to the catering industry. However, the increased costs associated with creating a favorable growth environment must be fully considered during the breeding process, requiring relevant technical support. Summary of the Invention

[0003] This invention overcomes the shortcomings of the prior art and provides an artificial breeding method for litchi bugs based on the regulation of the growth environment.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] The first aspect of this invention provides a method for artificially cultivating litchi bugs based on the regulation of their growth environment, specifically including:

[0006] Acquire historical climate characteristic data for each sub-region of the target area, and construct a climate characteristic prediction model based on the historical climate characteristic data for each sub-region of the target area;

[0007] The climate characteristic prediction model predicts the climate characteristic data of each sub-region in the target area within a preset time period, and obtains the environmental control cost data of the environmental control equipment when performing environmental control under each climate characteristic data through big data.

[0008] The environmental control cost data of environmental control equipment when conducting environmental control per unit breeding area under various climate characteristic data, as well as the climate characteristic data of each sub-region in the target area within a preset time, are obtained. The environmental control cost data of artificial breeding per unit breeding area of ​​litchi bug in each sub-region is also obtained.

[0009] Based on the environmental control cost data of artificial breeding per unit area of ​​litchi bug in each sub-region, recommended artificial breeding areas are selected, and artificial breeding is carried out according to the recommended artificial breeding areas, with real-time control of the growth environment in the breeding areas.

[0010] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, historical climate characteristic data of each sub-region within the target area are obtained, and a climate characteristic prediction model is constructed based on the historical climate characteristic data of each sub-region within the target area, specifically including:

[0011] Historical climate characteristic data of each sub-region in the target area are obtained through big data, and a climate characteristic prediction model is built based on long short-term memory neural network;

[0012] Historical climate characteristic data of each sub-region in the target area are input into the climate characteristic prediction model for training, and the prediction accuracy of the climate characteristic prediction model is obtained.

[0013] Set a prediction accuracy threshold. When the prediction accuracy is greater than the prediction accuracy threshold, save the model parameters of the climate feature prediction model, end the training, and output the climate feature prediction model.

[0014] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, the climate characteristic data of each sub-region within the target area are predicted within a preset time period using the climate characteristic prediction model, specifically including:

[0015] Acquire climate characteristic data of each sub-region within the target area within a predetermined time period, and input the climate characteristic data of each sub-region within the target area within the predetermined time period into the climate characteristic prediction model for prediction;

[0016] By prediction, the climate characteristic data of each sub-region in the target area within a preset time period are obtained, and the climate characteristic data of each sub-region in the target area within the preset time period are output.

[0017] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, the environmental regulation cost data for each sub-region when artificially rearing litchi bugs per unit rearing area is obtained based on the environmental regulation cost data of the environmental regulation equipment when performing environmental regulation per unit rearing area under the aforementioned climate characteristic data and the climate characteristic data of each sub-region within the target area within a preset time period. Specifically:

[0018] A database is constructed, with each climate characteristic data as the first node and environmental regulation cost data as the second node. A directed descriptive relationship is constructed, and the first node and the second node are connected based on the directed descriptive relationship to construct a topology graph.

[0019] Based on the topology graph, obtain the relevant adjacency matrix, input the relevant adjacency matrix into the database for storage, and configure the relevant query address for each relevant adjacency matrix;

[0020] Climate characteristic data of each sub-region within the target area within a preset time period are input into the database for data matching;

[0021] By matching data, the environmental control cost data of artificial breeding per unit area of ​​litchi bugs in each sub-region is obtained, and the environmental control cost data of artificial breeding per unit area of ​​litchi bugs in each sub-region is output.

[0022] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, recommended artificial rearing areas are selected based on the environmental regulation cost data per unit area of ​​litchi bug rearing in each sub-region. Specifically, this includes:

[0023] Obtain the current cost control data for lychee bug farming, set the farming area data per unit farming area, and initialize the initial number of lychee bug farming areas and the location of the farming areas based on the current cost control data for lychee bug farming.

[0024] The total breeding area data is calculated based on the initial number of litchi bug breeding areas and the breeding area data per unit breeding area. The total cost data for artificial breeding of litchi bugs in all areas is calculated based on the total breeding area data and the environmental control cost data for artificial breeding per unit breeding area of ​​litchi bugs in each sub-region.

[0025] A genetic algorithm is introduced, and the number of generations is set according to the genetic algorithm. A total cost data threshold is set. When the total cost data information of artificial breeding of litchi bugs in all regions is not greater than the total cost data threshold, the initial number of litchi bug breeding areas and the location of the breeding areas are output.

[0026] When the total cost data of artificial breeding of litchi bugs in all regions is greater than the total cost data threshold, genetic iteration is performed based on the genetic algorithm to adjust the number of litchi bug breeding areas or the location of the breeding areas until it is no greater than the total cost data threshold.

[0027] Based on the initial number of litchi bug farming areas and the location of the farming areas, a recommended artificial breeding area is generated and output.

[0028] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, rearing is carried out according to the recommended artificial rearing area, and the growth environment in the rearing area is regulated in real time, specifically including:

[0029] The artificial breeding area is used for breeding, and the threshold range of growth environment data is set to obtain the growth environment data in the breeding area in real time.

[0030] Determine whether the growth environment data in the assisted breeding area is within the growth environment data threshold range. If the growth environment data in the assisted breeding area is within the growth environment data threshold range, then generate a signal that does not require environmental control processing.

[0031] If the growth environment data in the assisted breeding area is not within the threshold range of the growth environment data, then the corresponding litchi bug breeding area is obtained, and a signal requiring environmental regulation is generated based on the corresponding litchi bug breeding area, and environmental regulation is carried out on the area requiring environmental regulation.

[0032] A second aspect of the present invention provides an artificial breeding system for litchi bugs based on growth environment regulation. The system includes a memory and a processor. The memory includes a program for an artificial breeding method for litchi bugs based on growth environment regulation. When the program for an artificial breeding method for litchi bugs based on growth environment regulation is executed by the processor, it implements the steps of the artificial breeding method for litchi bugs based on growth environment regulation as described in any one of the present invention.

[0033] A third aspect of the present invention provides a computer-readable storage medium including a program for an artificial rearing method of litchi bugs based on growth environment regulation, wherein when the program for the artificial rearing method of litchi bugs based on growth environment regulation is executed by the processor, the program implements the steps of the artificial rearing method of litchi bugs based on growth environment regulation as described in any one of the present invention.

[0034] This invention addresses the shortcomings of the prior art and has the following beneficial effects:

[0035] This invention acquires historical climate characteristic data for each sub-region within a target area, constructs a climate characteristic prediction model based on this data, and then predicts the climate characteristic data for each sub-region within a preset time period using this model. It also obtains environmental control cost data for each climate characteristic data point under different environmental control devices, thus acquiring environmental control cost data per unit area of ​​aquaculture under different climate characteristic data points. Furthermore, it acquires environmental control cost data for artificial rearing of litchi bugs per unit area in each sub-region within the preset time period based on the climate characteristic data. Finally, based on the environmental control cost data for artificial rearing of litchi bugs per unit area in each sub-region, recommended artificial rearing areas are selected, and rearing is carried out according to these recommended areas, with real-time control of the growth environment within these areas. This invention estimates environmental control costs based on climate characteristic data for each region, thereby selecting recommended aquaculture areas, reducing environmental control costs, and keeping aquaculture costs within a predetermined range, thus improving the rationality of artificial rearing of litchi bugs. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained from these drawings without creative effort.

[0037] Figure 1 A flowchart illustrating the overall process of artificially fostering litchi bugs based on growth environment regulation is shown.

[0038] Figure 2 A partial flowchart of an artificial breeding method for litchi bugs based on growth environment regulation is shown.

[0039] Figure 3 A system block diagram of an artificial breeding system for litchi bugs based on growth environment regulation is shown. Detailed Implementation

[0040] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0041] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below. Example

[0042] like Figure 1 As shown, the first aspect of this invention provides a method for artificially cultivating litchi bugs based on growth environment regulation, specifically including:

[0043] S102: Obtain historical climate characteristic data for each sub-region of the target area, and construct a climate characteristic prediction model based on the historical climate characteristic data for each sub-region of the target area;

[0044] S104: Predict the climate characteristic data of each sub-region in the target area within a preset time period through the climate characteristic prediction model, and obtain the environmental control cost data of the environmental control equipment when carrying out environmental control under the climate characteristic data through big data.

[0045] S106: Obtain environmental control cost data of environmental control equipment when conducting environmental control per unit breeding area under various climate characteristic data, and obtain environmental control cost data of each sub-region in the target area when artificially raising litchi bugs per unit breeding area in each sub-region within a preset time.

[0046] S108: Based on the environmental control cost data of artificial breeding per unit area of ​​litchi bug in each sub-region, select recommended artificial breeding areas, carry out artificial breeding according to the recommended artificial breeding areas, and control the growth environment in the breeding areas in real time.

[0047] It should be noted that this invention estimates environmental control costs based on climate characteristic data for each region, thereby selecting recommended breeding areas, reducing environmental control costs, and keeping breeding costs within a predetermined range, thus improving the rationality of artificial breeding of litchi bugs.

[0048] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, historical climate characteristic data of each sub-region within the target area are obtained. A climate characteristic prediction model is then constructed based on this data, specifically including:

[0049] Historical climate characteristic data of each sub-region in the target area are obtained through big data, and a climate characteristic prediction model is built based on long short-term memory neural network;

[0050] Historical climate characteristic data of each sub-region in the target area are input into the climate characteristic prediction model for training, and the prediction accuracy of the climate characteristic prediction model is obtained.

[0051] Set a prediction accuracy threshold. When the prediction accuracy exceeds the threshold, save the model parameters of the climate feature prediction model, end the training, and output the climate feature prediction model.

[0052] It should be noted that historical climate characteristic data includes temperature, humidity, seasonal weather characteristics, etc., and the environmental and climate preference characteristics of each region can be obtained through long and short time memory networks.

[0053] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, a climate characteristic prediction model is used to predict the climate characteristic data of each sub-region within the target area within a preset time period, specifically including:

[0054] Acquire climate characteristic data of each sub-region within the target area within a predetermined time period, and input the climate characteristic data of each sub-region within the target area within the predetermined time period into the climate characteristic prediction model for prediction;

[0055] By predicting, the climate characteristic data of each sub-region in the target area within a preset time period are obtained, and the climate characteristic data of each sub-region in the target area within the preset time period are output.

[0056] like Figure 2 As shown, further, in the artificial rearing method for litchi bugs based on growth environment regulation, the environmental regulation cost data for each sub-region when artificially rearing litchi bugs per unit rearing area is obtained based on the environmental regulation cost data of the environmental regulation equipment when performing environmental regulation per unit rearing area under various climatic characteristic data and the climatic characteristic data of each sub-region in the target area within a preset time. Specifically:

[0057] S202: Construct a database, using climate characteristic data as the first node and environmental regulation cost data as the second node, construct a directed descriptive relationship, connect the first node and the second node based on the directed descriptive relationship, and construct a topology graph.

[0058] S204: Obtain the relevant adjacency matrix based on the topology graph, input the relevant adjacency matrix into the database for storage, and configure the relevant query address for each relevant adjacency matrix;

[0059] S206: Input the climate characteristic data of each sub-region in the target area within a preset time into the database for data matching;

[0060] S208: Through data matching, obtain the environmental control cost data of artificial breeding per unit area of ​​litchi bugs in each sub-region, and output the environmental control cost data of artificial breeding per unit area of ​​litchi bugs in each sub-region.

[0061] It should be noted that, since the artificial breeding process mainly involves regulating the living environment data (such as temperature and humidity) of the litchi bug breeding area through environmental control equipment, the control costs required will vary depending on the climate characteristics of the region, such as high temperature weather, extremely low temperature weather, etc., and different temperature and humidity conditions will also lead to changes in environmental control costs. This method can obtain the environmental control cost data of litchi bugs per unit breeding area for artificial breeding in each sub-region.

[0062] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, recommended artificial rearing areas are selected based on the environmental regulation cost data per unit area of ​​litchi bug rearing in each sub-region. Specifically, these include:

[0063] Obtain the current cost control data for lychee bug farming, set the farming area data per unit farming area, and initialize the initial number of lychee bug farming areas and the location of the farming areas based on the current cost control data for lychee bug farming.

[0064] The total breeding area data is calculated based on the initial number of litchi bug breeding areas and the breeding area data per unit breeding area. The total cost data for artificial breeding of litchi bugs in all areas is calculated based on the total breeding area data and the environmental control cost data for artificial breeding per unit breeding area of ​​litchi bugs in each sub-region.

[0065] A genetic algorithm is introduced, and the number of generations is set according to the genetic algorithm. A total cost data threshold is set. When the total cost data information of artificial breeding of litchi bugs in all regions is not greater than the total cost data threshold, the initial number of litchi bug breeding areas and the location of the breeding areas are output.

[0066] When the total cost data of artificial breeding of litchi bugs in all regions is greater than the total cost data threshold, genetic iteration is performed based on the genetic algorithm to adjust the number of litchi bug breeding areas or the location of the breeding areas until it is no greater than the total cost data threshold.

[0067] Based on the initial number of litchi bug farming areas and the location of the farming areas, a recommended artificial breeding area is generated and output.

[0068] It should be noted that this method can select recommended artificial breeding areas, ensuring that the total cost of artificial breeding of litchi bugs in all areas does not exceed the total cost threshold, thereby improving the rationality of breeding.

[0069] Furthermore, in the artificial rearing method for litchi bugs based on growth environment regulation, rearing is carried out according to the recommended artificial rearing area, and the growth environment in the rearing area is regulated in real time, specifically including:

[0070] The artificial breeding area is used for breeding, and the threshold range of growth environment data is set to obtain the growth environment data in the breeding area in real time.

[0071] Determine whether the growth environment data in the foster care area is within the growth environment data threshold range. If the growth environment data in the foster care area is within the growth environment data threshold range, then generate a signal that does not require environmental control processing.

[0072] If the growth environment data in the assisted breeding area is not within the growth environment data threshold range, the corresponding litchi bug breeding area is obtained, and a signal requiring environmental regulation is generated based on the corresponding litchi bug breeding area, and environmental regulation is carried out on the area requiring environmental regulation.

[0073] It should be noted that environmental control is mainly carried out in areas requiring environmental control through environmental control equipment (such as fans, air purifiers, etc.).

[0074] In addition, this method also includes:

[0075] By acquiring energy consumption data of various environmental control devices through big data, and acquiring control cost data of environmental control devices under unit energy consumption data, a performance prediction model is constructed based on deep neural networks.

[0076] Acquire historical performance service data of environmental control equipment, and input the historical performance service data of environmental control equipment into the performance prediction model for training, obtain the trained performance prediction model, and obtain the performance data change characteristics of environmental control equipment within a preset time.

[0077] The performance data change characteristics of the environmental control equipment within the preset time are input into the performance prediction model for prediction, thereby obtaining the performance data of each environmental control equipment and obtaining real-time environmental control demand information.

[0078] The total predicted energy consumption data is calculated based on the performance data of each environmental control device, the real-time environmental control demand information, and the control cost data of the environmental control device under the unit energy consumption data. The estimated environmental control cost data is then calculated based on the total predicted energy consumption data.

[0079] The recommended artificial breeding areas are readjusted and updated based on the estimated environmental control cost data.

[0080] It should be noted that historical performance service data includes data such as temperature rise, temperature drop, and humidity adjustment per unit time. As environmental control equipment has been used for a certain number of years, the same environmental control needs will have different energy consumption (power loss), and different energy consumption will lead to different environmental control costs. This method can further identify better artificial breeding areas for artificial breeding and improve the accuracy of recommendations. Example

[0081] like Figure 3 As shown, the second aspect of the present invention provides a litchi bug artificial rearing system 4 based on growth environment regulation. System 4 includes a memory 41 and a processor 42. The memory 41 includes a litchi bug artificial rearing method program based on growth environment regulation. When the litchi bug artificial rearing method program based on growth environment regulation is executed by the processor 42, the technical solution of Embodiment 1 is implemented. Specifically, it includes:

[0082] Acquire historical climate characteristic data for each sub-region of the target area, and construct a climate characteristic prediction model based on the historical climate characteristic data for each sub-region of the target area.

[0083] The climate characteristic prediction model predicts the climate characteristic data of each sub-region in the target area within a preset time period, and the environmental control cost data of environmental control equipment when carrying out environmental control under each climate characteristic data is obtained through big data.

[0084] The environmental control cost data of environmental control equipment when conducting environmental control per unit breeding area under various climate characteristic data, as well as the climate characteristic data of each sub-region in the target area within a preset time, are obtained. The environmental control cost data of artificial breeding per unit breeding area of ​​litchi bug in each sub-region is also obtained.

[0085] Based on the environmental control cost data of artificial breeding per unit area of ​​litchi bug in each sub-region, recommended artificial breeding areas are selected, and artificial breeding is carried out according to the recommended artificial breeding areas, with real-time control of the growth environment in the breeding areas.

[0086] Furthermore, in the artificial breeding system for litchi bugs based on growth environment regulation, historical climate characteristic data of each sub-region within the target area are acquired. Based on this historical climate characteristic data, a climate characteristic prediction model is constructed, specifically including:

[0087] Historical climate characteristic data of each sub-region in the target area are obtained through big data, and a climate characteristic prediction model is built based on long short-term memory neural network;

[0088] Historical climate characteristic data of each sub-region in the target area are input into the climate characteristic prediction model for training, and the prediction accuracy of the climate characteristic prediction model is obtained.

[0089] Set a prediction accuracy threshold. When the prediction accuracy exceeds the threshold, save the model parameters of the climate feature prediction model, end the training, and output the climate feature prediction model.

[0090] Furthermore, in the artificial breeding system for litchi bugs based on growth environment regulation, a climate characteristic prediction model is used to predict the climate characteristic data of each sub-region within the target area within a preset time period, specifically including:

[0091] Acquire climate characteristic data of each sub-region within the target area within a predetermined time period, and input the climate characteristic data of each sub-region within the target area within the predetermined time period into the climate characteristic prediction model for prediction;

[0092] By predicting, the climate characteristic data of each sub-region in the target area within a preset time period are obtained, and the climate characteristic data of each sub-region in the target area within the preset time period are output.

[0093] Furthermore, in the artificial rearing system for litchi bugs based on growth environment regulation, the environmental regulation cost data for each sub-region of the target area is obtained based on the environmental regulation equipment's environmental regulation cost per unit area of ​​the breeding area under various climatic characteristic data, as well as the climatic characteristic data of each sub-region within a preset time. Specifically:

[0094] Construct a database, using climate characteristic data as the first node and environmental regulation cost data as the second node, build a directed descriptive relationship, and connect the first node and the second node based on the directed descriptive relationship to construct a topology graph;

[0095] The relevant adjacency matrix is ​​obtained based on the topology graph, and the relevant adjacency matrix is ​​input into the database for storage. A relevant query address is configured for each relevant adjacency matrix.

[0096] Climate characteristic data of each sub-region within the target area within a preset time period are input into the database for data matching;

[0097] By matching data, the environmental control cost data of artificial breeding per unit area of ​​litchi bug in each sub-region is obtained, and the environmental control cost data of artificial breeding per unit area of ​​litchi bug in each sub-region is output.

[0098] Furthermore, in the artificial rearing system for litchi bugs based on growth environment regulation, recommended artificial rearing areas are selected based on the environmental regulation cost data per unit area of ​​litchi bug rearing in each sub-region. Specifically, these include:

[0099] Obtain the current cost control data for lychee bug farming, and initialize the initial number of lychee bug farming areas, the farming area per unit, and the location of the farming areas based on the current cost control data for lychee bug farming;

[0100] The total breeding area data is calculated based on the number of litchi bug breeding areas and the breeding area per unit area. The total cost data for artificial breeding of litchi bugs in all areas is calculated based on the total breeding area data and the environmental control cost data for artificial breeding per unit breeding area of ​​litchi bugs in each sub-region.

[0101] A genetic algorithm is introduced, and the number of generations is set according to the genetic algorithm. A total cost data threshold is set. When the total cost data of artificial breeding of litchi bugs in all regions is not greater than the total cost data threshold, the initial number of litchi bug breeding areas, the breeding area data per unit number, and the location of the breeding area are output.

[0102] When the total cost data of artificial breeding of litchi bugs in all regions exceeds the total cost data threshold, genetic iteration is performed based on the genetic algorithm to adjust the number of litchi bug breeding areas, the number of breeding area data per unit, or the location of the breeding area until it does not exceed the total cost data threshold.

[0103] Based on the initial number of litchi bug farming areas, the data on the number of farming areas per unit, and the location of the farming areas, a recommended artificial breeding area is generated and output.

[0104] Furthermore, in the artificial rearing system for litchi bugs based on growth environment regulation, rearing is carried out according to the recommended artificial rearing area, and the growth environment in the rearing area is regulated in real time, specifically including:

[0105] The artificial breeding area is used for breeding, and the threshold range of growth environment data is set to obtain the growth environment data in the breeding area in real time.

[0106] Determine whether the growth environment data in the foster care area is within the growth environment data threshold range. If the growth environment data in the foster care area is within the growth environment data threshold range, then generate a signal that does not require environmental control processing.

[0107] If the growth environment data in the assisted breeding area is not within the growth environment data threshold range, the corresponding litchi bug breeding area is obtained, and a signal requiring environmental regulation is generated based on the corresponding litchi bug breeding area, and environmental regulation is carried out on the area requiring environmental regulation. Example

[0108] A third aspect of the present invention provides a computer-readable storage medium, including a program for artificially assisted rearing of litchi bugs based on growth environment regulation, wherein when the program for artificially assisted rearing of litchi bugs based on growth environment regulation is executed by a processor, the technical solution of embodiment 1 is implemented.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0110] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0111] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0112] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0113] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0114] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for artificially nurturing litchi bugs based on growth environment regulation, characterized in that, Specifically, it includes: Acquire historical climate characteristic data for each sub-region of the target area, and construct a climate characteristic prediction model based on the historical climate characteristic data for each sub-region of the target area; The climate characteristic prediction model predicts the climate characteristic data of each sub-region in the target area within a preset time period, and obtains the environmental control cost data of the environmental control equipment when performing environmental control under each climate characteristic data through big data. Based on the environmental control cost data of environmental control equipment when conducting environmental control per unit breeding area under various climate characteristic data, and the climate characteristic data of each sub-region in the target area within a preset time, the environmental control cost data of artificial breeding per unit breeding area of ​​litchi bug in each sub-region is obtained. Based on the environmental control cost data of artificial breeding per unit breeding area of ​​litchi bug in each sub-region, recommended artificial breeding areas are selected, and artificial breeding is carried out according to the recommended artificial breeding areas, and the growth environment in the breeding areas is controlled in real time. Based on the environmental control cost data of the environmental control equipment per unit breeding area under the aforementioned climate characteristic data, and the climate characteristic data of each sub-region in the target area within a preset time, the environmental control cost data of the litchi bug per unit breeding area under artificial breeding in each sub-region is obtained, specifically: A database is constructed, with each climate characteristic data as the first node and environmental regulation cost data as the second node. A directed descriptive relationship is constructed, and the first node and the second node are connected based on the directed descriptive relationship to construct a topology graph. Based on the topology graph, obtain the relevant adjacency matrix, input the relevant adjacency matrix into the database for storage, and configure the relevant query address for each relevant adjacency matrix; Climate characteristic data of each sub-region within the target area within a preset time period are input into the database for data matching; By matching data, the environmental control cost data of artificial breeding per unit area of ​​litchi bug in each sub-region is obtained, and the environmental control cost data of artificial breeding per unit area of ​​litchi bug in each sub-region is output. Based on the environmental control cost data per unit area of ​​litchi bug cultivation in each sub-region, recommended artificial breeding areas are selected, specifically including: Obtain the current cost control data for lychee bug farming, set the farming area data per unit farming area, and initialize the initial number of lychee bug farming areas and the location of the farming areas based on the current cost control data for lychee bug farming. The total breeding area data is calculated based on the initial number of litchi bug breeding areas and the breeding area data per unit breeding area. The total cost data for artificial breeding of litchi bugs in all areas is calculated based on the total breeding area data and the environmental control cost data for artificial breeding per unit breeding area of ​​litchi bugs in each sub-region. A genetic algorithm is introduced, and the number of generations is set according to the genetic algorithm. A total cost data threshold is set. When the total cost data information of artificial breeding of litchi bugs in all regions is not greater than the total cost data threshold, the initial number of litchi bug breeding areas and the location of the breeding areas are output. When the total cost data of artificial breeding of litchi bugs in all regions is greater than the total cost data threshold, genetic iteration is performed based on the genetic algorithm to adjust the initial number of litchi bug breeding areas or the location of the breeding areas until it is no greater than the total cost data threshold. Based on the initial number of litchi bug farming areas and the location of the farming areas, a recommended artificial breeding area is generated and the recommended artificial breeding area is output. Provide artificial rearing according to the recommended rearing area, and adjust the growth environment in the rearing area in real time, specifically including: The artificial breeding area is used for breeding, and the threshold range of growth environment data is set to obtain the growth environment data in the breeding area in real time. Determine whether the growth environment data in the assisted breeding area is within the growth environment data threshold range. If the growth environment data in the assisted breeding area is within the growth environment data threshold range, then generate a signal that does not require environmental control processing. If the growth environment data in the assisted breeding area is not within the threshold range of the growth environment data, then the corresponding litchi bug breeding area is obtained, and a signal requiring environmental regulation is generated based on the corresponding litchi bug breeding area, and environmental regulation is carried out on the area requiring environmental regulation.

2. The method for artificially cultivating litchi bugs based on growth environment regulation according to claim 1, characterized in that, Obtain historical climate characteristic data for each sub-region within the target area, and construct a climate characteristic prediction model based on the historical climate characteristic data for each sub-region within the target area. Specifically, this includes: Historical climate characteristic data of each sub-region in the target area are obtained through big data, and a climate characteristic prediction model is built based on long short-term memory neural network; Historical climate characteristic data of each sub-region in the target area are input into the climate characteristic prediction model for training, and the prediction accuracy of the climate characteristic prediction model is obtained. Set a prediction accuracy threshold. When the prediction accuracy is greater than the prediction accuracy threshold, save the model parameters of the climate feature prediction model, end the training, and output the climate feature prediction model.

3. The method for artificially cultivating litchi bugs based on growth environment regulation according to claim 1, characterized in that, The climate characteristic prediction model predicts climate characteristic data for each sub-region within a preset time period in the target area, specifically including: Acquire climate characteristic data of each sub-region within the target area within a predetermined time period, and input the climate characteristic data of each sub-region within the target area within the predetermined time period into the climate characteristic prediction model for prediction; By prediction, the climate characteristic data of each sub-region in the target area within a preset time period are obtained, and the climate characteristic data of each sub-region in the target area within the preset time period are output.

4. An artificial rearing system for litchi bugs based on growth environment regulation, characterized in that, The system includes a memory and a processor. The memory includes a program for artificially raising litchi bugs based on growth environment regulation. When the program for artificially raising litchi bugs based on growth environment regulation is executed by the processor, it implements the steps of the artificially raising litchi bugs based on growth environment regulation as described in any one of claims 1-3.

5. A computer-readable storage medium, characterized in that, The method includes a program for artificially raising litchi bugs based on growth environment regulation. When the program is executed by a processor, it implements the steps of the artificially raising litchi bugs based on growth environment regulation as described in any one of claims 1-3.

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