Land ecological greening adaptive planting planning method and system based on AI data

Abstract

The invention discloses a land ecological greening adaptive planting planning method and system based on AI data, and the method comprises the steps: obtaining an overspeed deviation ratio through analyzing the growth speed of an overspeed growing plant in a potential sub-region in different monitoring time periods, evaluating the growth speed change trend of the overspeed growing plant according to the overspeed deviation ratio, and determining the planting quality of the overspeed growing plant. Fluctuating overspeed plants are obtained through identification and distinguishing, an overspeed stable value is obtained through adding, summing and averaging according to the fluctuation degree and the number ratio of the fluctuating overspeed plants, and therefore the growth trend of the overspeed growing plants in the multiple potential interference subareas in different monitoring periods of the historical monitoring period is reflected through the overspeed stable value. The growth condition of the overspeed growing plants in the potential interference sub-region can be known, and the overspeed growing plants in the potential interference sub-region can be planned and managed according to the growth condition of the overspeed growing plants in the potential interference sub-region.

Description

Technical Field

[0001] The present invention relates to the field of greening planting technology, and in particular to a land ecological greening adaptive planting planning method and system based on AI data. Background Art

[0002] In land ecological greening and planting planning, it is necessary to consider some of the impacts that adaptive plants will be subject to in their future growth cycles, such as environmental impacts, impacts of alien species, and mutual impacts between adaptive plants. We now analyze the mutual impacts between adaptive plants and ensure that other adaptive plants around them can obtain sufficient growth resources based on the growth conditions of adaptive plants.

[0003] In the prior art, overgrowing adaptive plants are pruned by pruning. However, when determining overgrowing adaptive plants, overgrowing adaptive plants cannot be accurately identified, which eventually leads to competition between overgrowing adaptive plants and other adaptive plants for growth resources. Therefore, the acquired plant growth data is first analyzed to determine the overspeed sub-region, and the non-overspeed sub-region adjacent to the overspeed sub-region is identified to obtain the potential interference sub-region, and the sub-region is screened. The adaptive plants in the potential interference sub-region are planned in a targeted manner. At the same time, the growth trend of the adaptive plants in the potential interference sub-region is further analyzed, which is conducive to understanding the growth of overgrowing plants in the potential interference sub-region, and the planned pruning time is determined based on the comparison between the growth of overgrowing plants in the potential interference sub-region and the growth of adaptive plants in the normal growth sub-region, so as to balance the competition for growth resources of overgrowing plants according to the planned pruning time, so as to ensure that other surrounding adaptive plants can obtain sufficient growth resources. Summary of the invention

[0004] The purpose of the present invention is to provide a land ecological greening adaptive planting planning method and system based on AI data to solve at least one of the above-mentioned prior art problems.

[0005] First, the land ecological greening adaptive planting planning method based on AI data includes: Step 1: During the historical monitoring period, the growth data of plants in the adapted planting area is obtained through GAN technology, and the growth data is analyzed and processed to output the overspeed sub-area; Step 2: Use GAN technology to monitor and analyze non-speeding sub-areas adjacent to multiple speeding sub-areas to obtain monitoring and analysis data, and analyze and process the monitoring and analysis data to obtain potential interference sub-areas; Step 3: Analyze the growth trends of over-speed growing plants in multiple potential interference sub-areas during different monitoring periods of the historical monitoring cycle to obtain over-speed analysis data, and analyze and process the over-speed analysis data to output the analysis and processing results; The analysis and processing result is an overspeed stable signal or an overspeed unstable signal; Step 4: Based on the analysis and processing results, obtain the planned pruning time to solve the problem that other surrounding adaptive plants cannot grow normally due to the competition of fast-growing adaptive plants for growth resources of other surrounding adaptive plants.

[0006] As a further solution of the present invention, the growth data is analyzed and processed as follows: Establish an analysis matrix, substitute the unit growth mean of the adapted plants in the adapted planting area in different monitoring periods into the analysis matrix, and obtain the analysis matrix ; Among them, j in the analysis matrix is ​​the total number of monitoring periods in the historical monitoring cycle, and i is the total number of sub-areas in the adapted planting area; From the analysis matrix Extract any row data as an analysis set , where m represents the sub-areas in different suitable planting areas; Choose any one from the analysis set , add and average the unit growth means in different monitoring periods to obtain the periodic growth mean; Compare the period growth mean with the period growth mean threshold as follows: If the periodic growth mean is greater than the periodic growth mean threshold, it is marked as an overspeed sub-region; If the periodic growth mean is less than or equal to the periodic growth mean threshold, it is marked as a non-overspeed sub-region.

[0007] As a further solution of the present invention, the unit growth mean is obtained by: The historical monitoring cycle is divided into several monitoring periods. During the monitoring period, the growth image information corresponding to the adapted plants in the adapted planting area is obtained by using the GAN technology, wherein the growth image information includes the growth height; Divide the suitable planting area into several sub-areas, obtain the growth height of the suitable plants in the sub-areas during the monitoring period, calculate the ratio of the growth height of the suitable plants in the sub-areas during the monitoring period to the length of the monitoring period, and obtain the unit growth rate; The unit growth rates corresponding to the adapted plants in the sub-area are added and averaged to obtain the unit growth mean.

[0008] As a further solution of the present invention, the method for obtaining the potential interference sub-area is: Obtain the number of interfering sub-areas, and calculate the ratio with the total number of sub-areas in the adapted planting area to obtain the interference quantity value; The average growth value of the period corresponding to the interference sub-area is subtracted from the normal growth rate of the adapted plant, the absolute value is taken, and the ratio is calculated with the normal growth rate of the adapted plant to obtain the interference degree value; The interference quantity value is multiplied by the interference degree value to obtain the adjacent interference value; If the neighboring interference value is greater than the neighboring interference threshold, an interference analysis signal is generated, and the overspeed sub-region corresponding to the generated interference analysis signal is marked as a potential interference sub-region.

[0009] As a further solution of the present invention, the method for obtaining the interference sub-area is as follows: The GAN technology is used to convert the suitable planting area into a two-dimensional coordinate image, and a super-speed sub-area is randomly selected from multiple super-speed sub-areas, and the suitable plants in the non-super-speed sub-areas adjacent to the super-speed sub-area are analyzed. The process is as follows: The periodic growth mean corresponding to the non-overspeed sub-region is obtained and compared with the normal growth speed of the adapted plant. If the periodic growth mean corresponding to the non-overspeed sub-region is greater than or equal to the normal growth speed of the adapted plant, the non-overspeed sub-region is marked as a normal growth sub-region. If the periodic growth mean corresponding to the non-overspeed sub-region is less than the normal growth speed of the adapted plant, the non-overspeed sub-region is marked as an interference sub-region.

[0010] As a further solution of the present invention, the ultra-speed analysis data analysis and processing process is as follows: The number of plants with excessive fluctuations is counted and the ratio is calculated with the total number of plants with excessive growth in the potential interference sub-area to obtain the fluctuation excessive ratio, which is marked as ; Subtract the overspeed deviation ratio corresponding to the fluctuating overspeed plant from the overspeed deviation ratio threshold, take the absolute value, and calculate the ratio with the overspeed deviation ratio threshold to obtain the unit fluctuation value; The fluctuation values ​​of the corresponding units of the plants with excessive fluctuation speed in the potential interference sub-area are added and averaged to obtain the excessive fluctuation degree value, which is marked as ; Fluctuating overspeed ratio and speed fluctuation degree Substituting into the formula: , the sub-region stability value is calculated ,in, is the preset proportional coefficient; The sub-region stability value corresponding to the potential interference sub-region Perform subtraction, take the absolute value, and obtain the stable difference of the sub-region; All the sub-area stability differences are added and averaged to obtain the overspeed stability value; If the overspeed stability value is greater than or equal to the overspeed stability threshold, an overspeed stability signal is generated; If the overspeed stability value is less than the overspeed stability threshold, an overspeed instability signal is generated.

[0011] As a further solution of the present invention, the method for obtaining the wave superspeed plant is: Randomly select one overgrowing plant from multiple overgrowing plants in the potential interference sub-area for analysis, the process is as follows: Obtain the unit growth rate of the over-speed growing plants in different monitoring periods, and sort them according to the time series of different monitoring periods to obtain the period growth set , where c represents the over-growing plants, and j represents the total number of monitoring periods in the historical monitoring cycle; Based on the time period growth set R, the elements in the time period growth set R are extracted according to the adjacent monitoring time periods to obtain the overspeed analysis group; Subtract two elements in the overspeed analysis group to obtain the difference between adjacent elements, and take the absolute value to obtain the overspeed deviation value; The overspeed deviation value is calculated by ratio with the period growth average threshold value to obtain the overspeed deviation ratio; The overspeed deviation ratio is compared with the overspeed deviation ratio threshold. If the overspeed deviation ratio is greater than the overspeed deviation ratio threshold, the overspeed growing plants with a ratio greater than the overspeed deviation ratio threshold are marked as fluctuating overspeed plants.

[0012] As a further solution of the present invention, the interference growth mean is obtained by: If an overspeed stable signal is generated, the periodic growth means corresponding to the potential interference sub-areas are added and averaged to obtain the interference growth mean; If an overspeed unstable signal is generated, the periodic growth means corresponding to the potential interference sub-areas are compared, the maximum periodic growth mean and the minimum periodic growth mean are extracted, and the sum is added to obtain the mean to obtain the interference growth mean.

[0013] As a further solution of the present invention, the method for obtaining the planned pruning time is: Obtain the height of the adapted plants in the normal growth sub-region, add and average the heights of the adapted plants in the normal growth sub-region, and obtain the height of the normal sub-region; The heights of the normal sub-regions corresponding to the normal growth sub-regions are added and averaged to obtain the normal height mean; Obtain the height of the overgrown plants in the potential interference sub-area, add and average the heights of the overgrown plants in the potential interference sub-area, and obtain the potential interference height; The potential interference heights corresponding to the potential interference sub-areas are added and averaged to obtain the mean interference height; Subtract the average value of the interference height from the average value of the normal height, take the absolute value, and obtain the height planning value; The planned pruning time is obtained by calculating the ratio of the planned height value to the mean value of interference growth.

[0014] Secondly, the land ecological greening adaptation planting planning system based on AI data includes: Overspeed identification module: During the historical monitoring period, the growth data of plants in the adapted planting area is obtained through GAN technology, and the growth data is analyzed and processed to output the overspeed sub-area; Potential differentiation module: monitors and analyzes non-speeding sub-areas adjacent to multiple speeding sub-areas through GAN technology to obtain monitoring and analysis data, and analyzes and processes the monitoring and analysis data to obtain potential interference sub-areas; Interference analysis module: Analyze the growth trends of over-speed growing plants in multiple potential interference sub-areas during different monitoring periods of the historical monitoring cycle to obtain over-speed analysis data, analyze and process the over-speed analysis data, and output the analysis and processing results; The analysis and processing result is an overspeed stable signal or an overspeed unstable signal; Pruning planning module: Based on the analysis and processing results, the planned pruning time is obtained to solve the problem that other adaptive plants around cannot grow normally due to the competition of fast-growing adaptive plants for growth resources.

[0015] Beneficial effects of the present invention: The present invention uses GAN technology to obtain the growth data of plants in the adapted planting area to obtain an overspeed sub-area, and identifies and classifies the non-overspeed sub-areas adjacent to the overspeed sub-area, determines which non-overspeed sub-areas in the non-overspeed sub-area are normal growth sub-areas, and which non-overspeed sub-areas are interference sub-areas, and based on the interference sub-areas, counts the number of interference sub-areas adjacent to the overspeed sub-area and the degree of interference to the adapted plants in the interference sub-areas, and obtains the adjacent interference value, so as to reflect the degree of interference to the growth of the adapted plants in the non-overspeed sub-areas adjacent to the overspeed sub-area through the adjacent interference value, and obtains the interference of the overspeed sub-area on the normal growth of the adapted plants in the adjacent non-overspeed sub-area, thereby not only identifying and distinguishing the non-overspeed sub-areas to determine the interference sub-areas, but also identifying and distinguishing multiple overspeed sub-areas to determine the potential interference sub-areas; The present invention analyzes the growth speed of overspeed-growing plants in potential sub-areas in different monitoring periods to obtain an overspeed deviation ratio, evaluates the growth speed change trend of overspeed-growing plants according to the overspeed deviation ratio, identifies and distinguishes fluctuating overspeed plants, and calculates an overspeed stability value by adding and averaging the fluctuation degree and quantity proportion of the fluctuating overspeed plants, thereby reflecting the growth trend of overspeed-growing plants in multiple potential interference sub-areas in different monitoring periods of a historical monitoring cycle through the overspeed stability value, which is conducive to understanding the growth conditions of overspeed-growing plants in potential interference sub-areas, and planning and managing overspeed-growing plants in potential interference sub-areas according to the growth conditions of overspeed-growing plants in potential interference sub-areas; The present invention obtains a planned pruning time based on a comparison between the growth conditions of over-growing plants in a potential interference sub-area and the growth conditions of adapted plants in a normal growth sub-area, thereby balancing the competition for growth resources among over-growing plants according to the planned pruning time, thereby ensuring that other surrounding adapted plants can obtain sufficient growth resources, thereby maintaining the healthy growth of plants in the entire adapted planting area. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a flow chart of a potential interference sub-region identification method provided by the land ecological greening adaptive planting planning method based on AI data of the present invention; Figure 2 It is a structural schematic diagram of a method for analyzing growth trends of adaptive plants in potential interference sub-regions provided by the method for adaptive planting planning of land ecological greening based on AI data of the present invention; Figure 3 It is a structural schematic diagram of the land ecological greening adaptive planting planning system based on AI data of the present invention; Figure 4 It is a structural schematic diagram of a land ecological greening adaptive planting planning device based on AI data provided in the fourth embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0019] Embodiment 1, Figure 1 A flow chart of a land ecological greening adaptive planting planning method based on AI data provided in the first embodiment of the present invention. The embodiment of the present invention can be applied to identifying the growth conditions of plants in an adaptive planting area. The land ecological greening adaptive planting planning method based on AI data can be executed by a land ecological greening adaptive planting planning system based on AI data. The land ecological greening adaptive planting planning system based on AI data can be implemented by software and / or hardware. The land ecological greening adaptive planting planning system based on AI data can be configured in a land ecological greening adaptive planting planning device based on AI data. Optionally, the land ecological greening adaptive planting planning device based on AI data can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, etc. The embodiment of the present invention does not limit this.

[0020] like Figure 1 As shown, the land ecological greening adaptive planting planning method based on AI data provided by the embodiment of the present invention specifically includes the following steps: Step 1: During the historical monitoring period, the growth data of plants in the adapted planting area is obtained by using the GAN technology, wherein the growth data includes growth image information, and the growth image information is analyzed and processed to output the super-speed sub-area; In some embodiments, the historical monitoring cycle is divided into a number of monitoring periods, and during the monitoring period, the growth image information corresponding to the adapted plants in the adapted planting area is obtained by using the GAN technology, wherein the growth image information includes the growth height; It should be noted that the historical monitoring period is divided by dividing the historical monitoring period into equal time intervals, and the duration of each monitoring period in the historical monitoring period is equal; Divide the suitable planting area into several sub-areas, obtain the growth height of the suitable plants in the sub-areas during the monitoring period, calculate the ratio of the growth height of the suitable plants in the sub-areas during the monitoring period to the length of the monitoring period, and obtain the unit growth rate; It should be noted that the method of dividing the suitable planting area is to divide the suitable planting area into equal areas, and the planting area of ​​each sub-area is equal; The unit growth rates corresponding to the adapted plants in the sub-area are added and averaged to obtain the unit growth mean; Establish an analysis matrix, substitute the unit growth mean of the adapted plants in the adapted planting area in different monitoring periods into the analysis matrix, and obtain the analysis matrix ; Among them, j in the analysis matrix is ​​the total number of monitoring periods in the historical monitoring cycle, and i is the total number of sub-areas in the adapted planting area; For example, from the analysis matrix Extract any row data as an analysis set , where m represents the sub-areas in different suitable planting areas; gather Can be , or etc; Choose any one from the analysis set , add and average the unit growth means in different monitoring periods to obtain the periodic growth mean; Compare the period growth mean with the period growth mean threshold as follows: If the periodic growth mean is greater than the periodic growth mean threshold, the adaptive plants in the sub-region grow rapidly, and the sub-region where the adaptive plants grow rapidly is marked as an overspeed sub-region; If the periodic growth mean is less than or equal to the periodic growth mean threshold, the adaptive plants in the sub-region grow slowly, and the sub-region where the adaptive plants grow slowly is marked as a non-overspeed sub-region; Step 2: Monitor and analyze the non-speeding sub-areas adjacent to the multiple speeding sub-areas through GAN technology to obtain monitoring and analysis data, wherein the monitoring and analysis data includes the neighboring interference value, and the neighboring interference value is analyzed and compared. If the neighboring interference value is greater than the neighboring interference threshold, an interference analysis signal is generated to obtain the potential interference sub-area; In some embodiments, the GAN technology is used to convert the suitable planting area into a two-dimensional coordinate image, a super-speed sub-area is randomly selected from multiple super-speed sub-areas, and the suitable plants in the non-super-speed sub-areas adjacent to the super-speed sub-area are analyzed, and the process is as follows: Obtain the periodic growth mean corresponding to the non-overspeed sub-region and compare it with the normal growth rate of the adapted plant. The process is as follows: If the periodic growth mean corresponding to the non-overspeed sub-region is greater than or equal to the normal growth rate of the adapted plant, the non-overspeed sub-region is marked as a normal growth sub-region; If the periodic growth mean corresponding to the non-superspeed sub-region is less than the normal growth rate of the adapted plant, the non-superspeed sub-region is marked as an interference sub-region; Obtain the number of interfering sub-areas, and calculate the ratio with the total number of sub-areas in the adapted planting area to obtain the interference quantity value; The average growth value of the period corresponding to the interference sub-area is subtracted from the normal growth rate of the adapted plant, the absolute value is taken, and the ratio is calculated with the normal growth rate of the adapted plant to obtain the interference degree value; The interference quantity value is multiplied by the interference degree value to obtain the adjacent interference value; It can be understood that the meaning of the neighboring interference value is: reflecting the degree of interference to the growth of the adaptive plant in the non-superspeed sub-region adjacent to the superspeed sub-region. Specifically, if the neighboring interference value is larger, it means that the growth of the adaptive plant in the non-superspeed sub-region adjacent to the superspeed sub-region is more disturbed. If the neighboring interference value is smaller, the growth of the adaptive plant in the non-superspeed sub-region adjacent to the superspeed sub-region is less disturbed. The neighbor interference value is compared with the neighbor interference threshold, and the process is as follows: If the neighboring interference value is greater than the neighboring interference threshold, it means that the growth of the adaptive plant is disturbed to a greater extent in the non-superspeed sub-region adjacent to the superspeed sub-region, an interference analysis signal is generated, and the superspeed sub-region corresponding to the generated interference analysis signal is marked as a potential interference sub-region; If the neighboring interference value is less than or equal to the neighboring interference threshold, it means that in the non-superspeed sub-region adjacent to the superspeed sub-region, the growth of the adaptive plant is less disturbed, a non-interference analysis signal is generated, and the superspeed sub-region corresponding to the interference analysis signal is marked as a non-potential interference sub-region; The specific implementation scheme of the embodiment of the present invention is as follows: first, the growth data of the plants in the adapted planting area are acquired by GAN technology to obtain an overspeed sub-area, and the non-overspeed sub-areas adjacent to the overspeed sub-area are identified and classified to determine which non-overspeed sub-areas are normal growth sub-areas and which non-overspeed sub-areas are interference sub-areas. Based on the interference sub-areas, the number of interference sub-areas adjacent to the overspeed sub-areas and the degree of interference to the adapted plants in the interference sub-areas are counted to obtain a neighboring interference value, thereby reflecting the degree of interference to the growth of the adapted plants in the non-overspeed sub-areas adjacent to the overspeed sub-areas through the neighboring interference value, and obtaining the interference of the overspeed sub-areas on the normal growth of the adapted plants in the adjacent non-overspeed sub-areas, thereby not only identifying and distinguishing the non-overspeed sub-areas to determine the interference sub-areas, but also identifying and distinguishing multiple overspeed sub-areas to determine the potential interference sub-areas; Embodiment 2, step 3: based on the interference analysis signal, the growth trends of over-speed growing plants in multiple potential interference sub-areas in different monitoring periods of the historical monitoring cycle are analyzed to obtain overspeed analysis data, wherein the overspeed analysis data includes a fluctuation overspeed ratio and an overspeed fluctuation degree value, the fluctuation overspeed ratio and the overspeed fluctuation degree value are analyzed and processed, an overspeed stability value is output, and the overspeed stability value is compared with the overspeed stability threshold value to obtain an analysis and processing result; The analysis and processing results include an overspeed stable signal or an overspeed unstable signal; In some embodiments, one overgrown plant is randomly selected from a plurality of overgrown plants in a potential interfering sub-region for analysis, and the process is as follows: Obtain the unit growth rate of the over-speed growing plants in different monitoring periods, and sort them according to the time series of different monitoring periods to obtain the period growth set , where c represents the over-growing plants, and j represents the total number of monitoring periods in the historical monitoring cycle; Based on the time period growth set R, the elements in the time period growth set R are extracted according to the adjacent monitoring time periods to obtain the overspeed analysis group; Among them, the overspeed analysis group can be , , or ; Subtract two elements in the overspeed analysis group to obtain the difference between adjacent elements, and take the absolute value to obtain the overspeed deviation value; The overspeed deviation value is calculated by ratio with the period growth average threshold value to obtain the overspeed deviation ratio; The overspeed deviation ratio is compared with the overspeed deviation ratio threshold value, and the process is as follows: If the overspeed deviation ratio is greater than the overspeed deviation ratio threshold, the overspeed growth plants greater than the overspeed deviation ratio threshold are marked as fluctuating overspeed plants; If the overspeed deviation ratio is less than or equal to the overspeed deviation ratio threshold, the overspeed growing plants less than or equal to the overspeed deviation ratio threshold are marked as stable overspeed plants; The number of plants with excessive fluctuations is counted and the ratio is calculated with the total number of plants with excessive growth in the potential interference sub-area to obtain the fluctuation excessive ratio, which is marked as ; Subtract the overspeed deviation ratio corresponding to the fluctuating overspeed plant from the overspeed deviation ratio threshold, take the absolute value, and calculate the ratio with the overspeed deviation ratio threshold to obtain the unit fluctuation value; The fluctuation values ​​of the corresponding units of the plants with excessive fluctuation speed in the potential interference sub-area are added and averaged to obtain the excessive fluctuation degree value, which is marked as ; Fluctuating overspeed ratio and speed fluctuation degree Substituting into the formula: , the sub-region stability value is calculated ,in, is a preset scaling factor; and The value is 5.235. The value is 3.748; The sub-region stability value corresponding to the potential interference sub-region Perform subtraction, take the absolute value, and obtain the stable difference of the sub-region; All the sub-area stability differences are added and averaged to obtain the overspeed stability value; It can be understood that the meaning of the overspeed stability value is: reflecting the growth trend of overspeed growing plants in multiple potential interference sub-areas in different monitoring periods of the historical monitoring cycle. Specifically, if this value is higher, it means that the growth trend of overspeed growing plants in the potential interference sub-area is more stable and the fluctuation is smaller; conversely, if this value is lower, it means that the growth trend is more unstable and the fluctuation is greater, which is conducive to understanding the growth conditions of overspeed growing plants in the potential interference sub-area, and planning and managing the overspeed growing plants in the potential interference sub-area according to the growth conditions of overspeed growing plants in the potential interference sub-area; The overspeed stability value is compared with the overspeed stability threshold value, and the process is as follows: If the overspeed stability value is greater than or equal to the overspeed stability threshold, it means that the growth trend of the overspeed growing plants in the potential interference sub-area is more stable and the fluctuation is smaller, and an overspeed stability signal is generated; If the overspeed stability value is less than the overspeed stability threshold, it means that the growth trend of the overspeed growing plants in the potential interference sub-area is more unstable and the fluctuation is greater, generating an overspeed instability signal; The specific implementation scheme of the present invention is as follows: by analyzing the growth speed of overspeed-growing plants in potential sub-areas in different monitoring periods, an overspeed deviation ratio is obtained, and the growth speed change trend of overspeed-growing plants is evaluated according to the overspeed deviation ratio, and fluctuating overspeed plants are identified and distinguished, and the overspeed stability value is calculated by adding and averaging the fluctuation degree and quantity proportion of the fluctuating overspeed plants, so that the growth trend of overspeed-growing plants in multiple potential interference sub-areas in different monitoring periods of the historical monitoring cycle is reflected through the overspeed stability value, which is conducive to understanding the growth conditions of overspeed-growing plants in potential interference sub-areas, and planning and management of overspeed-growing plants in potential interference sub-areas are carried out according to the growth conditions of overspeed-growing plants in potential interference sub-areas; Embodiment 3, step 4: based on the analysis and processing results, obtain the interference growth mean, and analyze based on the interference growth mean to obtain the planned pruning time, so as to solve the problem that other surrounding adaptive plants cannot grow normally due to the competition of rapidly growing adaptive plants for the growth resources of other surrounding adaptive plants; In some embodiments, if an overspeed stabilization signal is generated, the periodic growth means corresponding to the potential interference sub-regions are added and averaged to obtain the interference growth mean; If an overspeed unstable signal is generated, the periodic growth means corresponding to the potential interference sub-areas are compared, the maximum periodic growth mean and the minimum periodic growth mean are extracted, and the sum is added to obtain the mean to obtain the interference growth mean; Obtain the height of the adapted plants in the normal growth sub-region, add and average the heights of the adapted plants in the normal growth sub-region, and obtain the height of the normal sub-region; The heights of the normal sub-regions corresponding to the normal growth sub-regions are added and averaged to obtain the normal height mean; Obtain the height of the overgrown plants in the potential interference sub-area, add and average the heights of the overgrown plants in the potential interference sub-area, and obtain the potential interference height; The potential interference heights corresponding to the potential interference sub-areas are added and averaged to obtain the mean interference height; Subtract the average value of the interference height from the average value of the normal height, take the absolute value, and obtain the height planning value; Calculate the ratio of the planned height value to the mean value of interference growth to obtain the planned pruning time; The meaning of planning pruning time is: by calculating the planned height value between the mean interference height and the mean normal height, and combining the interference growth mean (reflecting the overall growth rate and growth amount of plants in the potential interference sub-area), a relatively accurate pruning time can be obtained, and the growth rate of over-growing plants can be effectively controlled to reduce their growth pressure on surrounding plants.

[0021] The specific implementation scheme of the embodiment of the present invention is: based on the comparison between the growth conditions (especially the height and growth rate) of the over-growing plants in the potential interference sub-area and the growth conditions of the adapted plants in the normal growth sub-area, a planned pruning time is obtained, so as to balance the competition for growth resources among the over-growing plants according to the planned pruning time, so as to ensure that other surrounding adapted plants can obtain sufficient growth resources, thereby maintaining the healthy growth of plants in the entire adapted planting area.

[0022] Example 4, reference Figure 3 , the embodiment of the present invention provides a land ecological greening adaptive planting planning system based on AI data, including: Overspeed identification module: During the historical monitoring period, the growth data of plants in the adapted planting area is obtained through GAN technology, and the growth data is analyzed and processed to output the overspeed sub-area; Potential differentiation module: monitors and analyzes non-speeding sub-areas adjacent to multiple speeding sub-areas through GAN technology to obtain monitoring and analysis data, and analyzes and processes the monitoring and analysis data to obtain potential interference sub-areas; Interference analysis module: Analyze the growth trends of over-speed growing plants in multiple potential interference sub-areas during different monitoring periods of the historical monitoring cycle to obtain over-speed analysis data, analyze and process the over-speed analysis data, and output the analysis and processing results; The analysis and processing result is an overspeed stable signal or an overspeed unstable signal; Pruning planning module: Based on the analysis and processing results, the planned pruning time is obtained to solve the problem that other adaptive plants around cannot grow normally due to the competition of fast-growing adaptive plants for growth resources.

[0023] Example 5, reference Figure 4 The embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, the xxx method described in any one of the above methods is implemented.

[0024] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0025] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0026] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0027] Embodiment 6, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the xxx method as described in any one of the above methods is implemented.

[0028] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0029] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0030] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0031] In the embodiments disclosed in the present application, it should be understood that the disclosed apparatus / terminal equipment and method can be implemented in other ways. For example, the apparatus / terminal equipment embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. One point, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, which may be electrical, mechanical or other forms.

[0032] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0033] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0034] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A land ecological greening adaptive planting planning method based on AI data, characterized in that: The following steps are involved: Step 1: During the historical monitoring period, the growth data of plants in the adapted planting area is obtained through GAN technology, and the growth data is analyzed and processed to output the overspeed sub-area; Step 2: Use GAN technology to monitor and analyze non-speeding sub-areas adjacent to multiple speeding sub-areas to obtain monitoring and analysis data, and analyze and process the monitoring and analysis data to obtain potential interference sub-areas; Step 3: Analyze the growth trends of over-speed growing plants in multiple potential interference sub-areas during different monitoring periods of the historical monitoring cycle to obtain over-speed analysis data, and analyze and process the over-speed analysis data to output the analysis and processing results; The analysis and processing result is an overspeed stable signal or an overspeed unstable signal; Step 4: Based on the analysis and processing results, obtain the planned pruning time to solve the problem that other surrounding adaptive plants cannot grow normally due to the competition of fast-growing adaptive plants for growth resources of other surrounding adaptive plants.

2. The method for adaptive planting planning of land ecological greening based on AI data according to claim 1 is characterized in that: The process of analyzing and processing growth data is as follows: Establish an analysis matrix, substitute the unit growth mean of the adapted plants in the adapted planting area in different monitoring periods into the analysis matrix, and obtain the analysis matrix ; Among them, j in the analysis matrix is ​​the total number of monitoring periods in the historical monitoring cycle, and i is the total number of sub-areas in the adapted planting area; From the analysis matrix Extract any row data as an analysis set , where m represents the sub-areas in different suitable planting areas; Choose any one from the analysis set , add and average the unit growth means in different monitoring periods to obtain the periodic growth mean; Compare the period growth mean with the period growth mean threshold as follows: If the periodic growth mean is greater than the periodic growth mean threshold, it is marked as an overspeed sub-region; If the periodic growth mean is less than or equal to the periodic growth mean threshold, it is marked as a non-overspeed sub-region.

3. The method for adaptive planting planning of land ecological greening based on AI data according to claim 2 is characterized in that: The unit growth mean is obtained as follows: The historical monitoring cycle is divided into several monitoring periods. During the monitoring period, the growth image information corresponding to the adapted plants in the adapted planting area is obtained by using the GAN technology, wherein the growth image information includes the growth height; Divide the suitable planting area into several sub-areas, obtain the growth height of the suitable plants in the sub-areas during the monitoring period, calculate the ratio of the growth height of the suitable plants in the sub-areas during the monitoring period to the length of the monitoring period, and obtain the unit growth rate; The unit growth rates corresponding to the adapted plants in the sub-area are added and averaged to obtain the unit growth mean.

4. The method for adaptive planting planning of land ecological greening based on AI data according to claim 1 is characterized in that: The potential interference sub-area is obtained as follows: Obtain the number of interfering sub-areas, and calculate the ratio with the total number of sub-areas in the adapted planting area to obtain the interference quantity value; The average growth value of the period corresponding to the interference sub-area is subtracted from the normal growth rate of the adapted plant, the absolute value is taken, and the ratio is calculated with the normal growth rate of the adapted plant to obtain the interference degree value; The interference quantity value is multiplied by the interference degree value to obtain the adjacent interference value; If the neighboring interference value is greater than the neighboring interference threshold, an interference analysis signal is generated, and the overspeed sub-region corresponding to the generated interference analysis signal is marked as a potential interference sub-region.

5. The method for adaptive planting planning of land ecological greening based on AI data according to claim 4 is characterized in that: How to obtain the interference sub-area: The GAN technology is used to convert the suitable planting area into a two-dimensional coordinate image, and a super-speed sub-area is randomly selected from multiple super-speed sub-areas, and the suitable plants in the non-super-speed sub-areas adjacent to the super-speed sub-area are analyzed. The process is as follows: The periodic growth mean corresponding to the non-overspeed sub-region is obtained and compared with the normal growth speed of the adapted plant. If the periodic growth mean corresponding to the non-overspeed sub-region is greater than or equal to the normal growth speed of the adapted plant, the non-overspeed sub-region is marked as a normal growth sub-region. If the periodic growth mean corresponding to the non-overspeed sub-region is less than the normal growth speed of the adapted plant, the non-overspeed sub-region is marked as an interference sub-region.

6. The method for adaptive planting planning of land ecological greening based on AI data according to claim 1 is characterized in that: The overspeed analysis data analysis and processing process is as follows: The number of plants with excessive fluctuations is counted and the ratio is calculated with the total number of plants with excessive growth in the potential interference sub-area to obtain the fluctuation excessive ratio, which is marked as ; Subtract the overspeed deviation ratio corresponding to the fluctuating overspeed plant from the overspeed deviation ratio threshold, take the absolute value, and calculate the ratio with the overspeed deviation ratio threshold to obtain the unit fluctuation value; The fluctuation values ​​of the corresponding units of the plants with excessive fluctuation speed in the potential interference sub-area are added and averaged to obtain the excessive fluctuation degree value, which is marked as ; Fluctuating overspeed ratio and speed fluctuation degree Substituting into the formula: , the sub-region stability value is calculated ,in, is the preset proportional coefficient; The sub-region stability value corresponding to the potential interference sub-region Perform subtraction, take the absolute value, and obtain the stable difference of the sub-region; All the sub-area stability differences are added and averaged to obtain the overspeed stability value; If the overspeed stability value is greater than or equal to the overspeed stability threshold, an overspeed stability signal is generated; If the overspeed stability value is less than the overspeed stability threshold, an overspeed instability signal is generated.

7. The method for adaptive planting planning of land ecological greening based on AI data according to claim 6 is characterized in that: The way to obtain the wave speed plant is: Randomly select one overgrowing plant from multiple overgrowing plants in the potential interference sub-area for analysis, the process is as follows: Obtain the unit growth rate of the over-speed growing plants in different monitoring periods, and sort them according to the time series of different monitoring periods to obtain the period growth set , where c represents the over-growing plants, and j represents the total number of monitoring periods in the historical monitoring cycle; Based on the time period growth set R, the elements in the time period growth set R are extracted according to the adjacent monitoring time periods to obtain the overspeed analysis group; Subtract two elements in the overspeed analysis group to obtain the difference between adjacent elements, and take the absolute value to obtain the overspeed deviation value; The overspeed deviation value is calculated by ratio with the period growth average threshold value to obtain the overspeed deviation ratio; The overspeed deviation ratio is compared with the overspeed deviation ratio threshold. If the overspeed deviation ratio is greater than the overspeed deviation ratio threshold, the overspeed growing plants with a ratio greater than the overspeed deviation ratio threshold are marked as fluctuating overspeed plants.

8. The method for adaptive planting planning of land ecological greening based on AI data according to claim 1 is characterized in that: The interference growth mean is obtained as follows: If an overspeed stable signal is generated, the periodic growth means corresponding to the potential interference sub-areas are added and averaged to obtain the interference growth mean; If an overspeed unstable signal is generated, the periodic growth means corresponding to the potential interference sub-areas are compared, the maximum periodic growth mean and the minimum periodic growth mean are extracted, and the sum is added to obtain the mean to obtain the interference growth mean.

9. The method for adaptive planting planning of land ecological greening based on AI data according to claim 8 is characterized in that: The method for obtaining the planned pruning time is: Obtain the height of the adapted plants in the normal growth sub-region, add and average the heights of the adapted plants in the normal growth sub-region, and obtain the height of the normal sub-region; The heights of the normal sub-regions corresponding to the normal growth sub-regions are added and averaged to obtain the normal height mean; Obtain the height of the overgrown plants in the potential interference sub-area, add and average the heights of the overgrown plants in the potential interference sub-area, and obtain the potential interference height; The potential interference heights corresponding to the potential interference sub-areas are added and averaged to obtain the mean interference height; Subtract the average value of the interference height from the average value of the normal height, take the absolute value, and obtain the height planning value; The planned pruning time is obtained by calculating the ratio of the planned height value to the mean value of interference growth.

10. The land ecological greening adaptive planting planning system based on AI data is characterized by: include: Overspeed identification module: During the historical monitoring period, the growth data of plants in the adapted planting area is obtained through GAN technology, and the growth data is analyzed and processed to output the overspeed sub-area; Potential differentiation module: monitors and analyzes non-speeding sub-areas adjacent to multiple speeding sub-areas through GAN technology to obtain monitoring and analysis data, and analyzes and processes the monitoring and analysis data to obtain potential interference sub-areas; Interference analysis module: Analyze the growth trends of over-speed growing plants in multiple potential interference sub-areas during different monitoring periods of the historical monitoring cycle to obtain over-speed analysis data, analyze and process the over-speed analysis data, and output the analysis and processing results; The analysis and processing result is an overspeed stable signal or an overspeed unstable signal; Pruning planning module: Based on the analysis and processing results, the planned pruning time is obtained to solve the problem that other adaptive plants around cannot grow normally due to the competition of fast-growing adaptive plants for growth resources.

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