Seedling raising and fertilization control method and system for forestry engineering
By analyzing plant growth data and the degree of impact, and combining this with ant colony optimization to adjust fertilization equipment parameters, the problem of inaccurate fertilization under different varieties and growth cycles was solved, achieving precise control of seedling fertilization and improving seedling quality.
Patent Information
- Application Number
- CN202511118619.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-11
- Publication Date
- 2025-11-21
AI Technical Summary
Existing methods fail to take into account differences in plant varieties and growth cycles, resulting in inaccurate fertilization effects and affecting seedling quality.
By acquiring growth data of different varieties of plants in each growth cycle, and using ant colony optimization and outlier detection algorithms to analyze the growth abnormality index and its impact, the control parameters of the fertilization equipment are adjusted to achieve precision fertilization.
It improves the precision and effectiveness of fertilization, ensuring that the optimal fertilization needs of plants at different growth stages are met, and enhances seedling quality.
Smart Images
Figure CN120982276A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of fertilization control, in particular to a seedling fertilization control method and system for forestry engineering. BACKGROUND
[0002] In the development of modern forestry, the fertilization link in seedling cultivation and management is an important link to ensure the sustainable reproduction and expansion of forestry resources. High-quality seedling fertilization control provides a large number of high-quality seedlings for afforestation, which is an important starting point for improving forest coverage and establishing forest ecosystems. Implementing scientific seedling fertilization control can accurately regulate the environmental conditions of seed germination and seedling growth, and fundamentally guarantee the quality of forestry resources.
[0003] In related technologies, self-propelled watering carts and other fertilization equipment are usually used in combination with pre-set control parameters such as sprinkling irrigation pressure, sprinkling irrigation opening, and sprinkling irrigation flow to fertilize the plants being cultivated. However, since the plants requiring fertilization usually have different varieties and different growth cycles, different numerical control parameters are required for fertilizing plants of different varieties and different growth cycles, which results in the fact that the existing method cannot accurately fertilize plants without considering the actual situation of different varieties and growth cycles of plants, thereby reducing the fertilization effect. SUMMARY
[0004] In order to solve the technical problem that the existing method cannot accurately fertilize plants without considering the actual situation of different varieties and growth cycles of plants, thereby reducing the fertilization effect, the purpose of the present application is to provide a seedling fertilization control method and system for forestry engineering, and the technical solution adopted is as follows:
[0005] The present application provides a seedling fertilization control method for forestry engineering, which comprises:
[0006] At each parameter value of the control parameters of different types of fertilization equipment, growth data of plants of different varieties in different dimensions at each growth cycle is obtained;
[0007] The growth abnormality index of the target variety in the target growth period under the target parameter value is obtained according to the differences in the growth data of the same dimension of each plant of the target variety in the target growth period under the target parameter value; the influence degree of the target variety in the target growth period under the target control parameter is obtained according to the changes of each parameter value of the target control parameter and the changes of the growth abnormality index of the target variety in the target growth period under each parameter value of the target control parameter;
[0008] The influence difference degree of the target variety in the target growth period under the target control parameter is obtained according to the differences in the influence degree between the target growth period and the adjacent growth period of the target variety under the target control parameter; the control ambiguity degree of the target variety in the target growth period under the target control parameter is obtained according to the differences in the influence difference degree between the target variety and other varieties in the target growth period under the target control parameter.
[0009] Based on the control ambiguity degree of each variety in each growth period under each control parameter, and combined with the ant colony algorithm, seedling and fertilization control is performed on the plants.
[0010] Further, the growth abnormality index of the target variety in the target growth period under the target parameter value comprises:
[0011] The data points formed by the growth data of each plant of the target variety in the target growth period under the target parameter value in all dimensions are input into an outlier factor detection algorithm, and the outlying degree of each plant of the target variety in the target growth period under the target parameter value is output.
[0012] The fertilization effect evaluation value of each plant of the target variety in the target growth period under the target parameter value is obtained according to the differences between the outlying degree of each plant of the target variety in the target growth period under the target parameter value and the overall level of the outlying degree of all plants of the target variety in the target growth period.
[0013] The average value of the fertilization effect evaluation value of all plants of the target variety in the target growth period under the target parameter value is taken as the growth abnormality index of the target variety in the target growth period under the target parameter value.
[0014] Further, the fertilization effect evaluation value of each plant of the target variety in the target growth period under the target parameter value comprises:
[0015] The average of the outlying degrees of all plants of the target variety at the target parameter value in the target growth period is taken as the overall outlying degree of the target variety at the target parameter value in the target growth period.
[0016] The difference between the outlying degree and the overall outlying degree of each plant of the target variety at the target parameter value in the target growth period is negatively correlated to obtain the fertilization effect evaluation value of each plant of the target variety at the target parameter value in the target growth period.
[0017] Further, the obtaining of the influence degree of the target variety at the target growth period under the target control parameter comprises:
[0018] According to the order of the parameter values of the target control parameter from small to large, the growth anomaly indexes of the target variety at the target growth period under each parameter value of the target control parameter are sorted to obtain a growth anomaly index sequence.
[0019] According to the difference between the two adjacent growth anomaly indexes in the growth anomaly index sequence and the difference between the parameter values corresponding to the two adjacent growth anomaly indexes, the influence degree of the target variety at the target growth period under the target control parameter is obtained.
[0020] Further, the obtaining of the influence degree of the target variety at the target growth period under the target control parameter according to the difference between the two adjacent growth anomaly indexes in the growth anomaly index sequence and the difference between the parameter values corresponding to the two adjacent growth anomaly indexes comprises:
[0021] In the growth anomaly index sequence, the absolute value of the difference between any two adjacent growth anomaly indexes is taken as the numerator, the absolute value of the difference between the parameter values corresponding to any two adjacent growth anomaly indexes is taken as the denominator, and the ratio is taken as the relative change degree between any two adjacent growth anomaly indexes.
[0022] The average of the relative change degrees between all adjacent two growth anomaly indexes in the growth anomaly index sequence is negatively correlated to obtain the influence degree of the target variety at the target growth period under the target control parameter.
[0023] Further, the obtaining of the influence difference degree of the target variety at the target growth period under the target control parameter comprises:
[0024] Two growth periods adjacent to the target growth period of the target variety are taken as reference growth periods of the target growth period.
[0025] An absolute value of a difference between the influence difference coefficient of the target variety under the target control parameter between the target growth period and each reference growth period is taken as an influence difference coefficient of the target variety under the target control parameter between the target growth period and each reference growth period.
[0026] A sum value of the influence difference coefficient of the target variety under the target control parameter between the target growth period and all reference growth periods is taken as an influence difference degree of the target variety under the target control parameter in the target growth period.
[0027] Further, the obtaining of the control ambiguity degree of the target variety under the target control parameter in the target growth period comprises:
[0028] An absolute value of a difference between the influence difference degree of the target variety under the target control parameter in the target growth period and each other variety is taken as a control ambiguity factor of the target variety under the target control parameter in the target growth period and each other variety.
[0029] An accumulated value of the control ambiguity factor of the target variety under the target control parameter in the target growth period and all other varieties is normalized to obtain the control ambiguity degree of the target variety under the target control parameter in the target growth period.
[0030] Further, the seedling fertilization control of the plant comprises:
[0031] The standard weight value of the target variety under the target control parameter in the target growth period is adjusted according to the control ambiguity degree of the target variety under the target control parameter in the target growth period to obtain an adjusted weight value of the target variety under the target control parameter in the target growth period.
[0032] The data points formed by the growth data of each plant of different varieties under each parameter value of different types of control parameters in each growth period in all dimensions are taken as nodes used by the ant colony algorithm, and the adjusted weight values of different varieties under different control parameters in each growth period are taken as pheromones of each node, and the nodes and pheromones are input into the ant colony algorithm, and the best control parameter combination of the fertilization equipment is output, and the plant is controlled by seedling fertilization by using the best control parameter combination.
[0033] Further, the obtaining of the adjusted weight value of the target variety under the target control parameter in the target growth period comprises:
[0034] A product value of the control ambiguity degree and the standard weight value of the target variety under the target control parameter in the target growth period is taken as a weight adjustment amount of the target variety under the target control parameter in the target growth period.
[0035] The difference between the standard weight value of the target variety under the target control parameter in the target growth period and the weight adjustment amount is taken as the adjustment weight value of the target variety under the target control parameter in the target growth period.
[0036] The application further provides a seedling fertilization control system for forestry engineering, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of any one of the seedling fertilization control methods for forestry engineering when executing the computer program.
[0037] The application has the following beneficial effects:
[0038] The application considers that the existing method cannot accurately fertilize plants under the actual condition that the variety and growth period of the plants are not considered, thereby reducing the fertilization effect, and therefore, firstly, growth data of plants of different varieties in different dimensions in each growth period is collected under each parameter value of different types of control parameters of a fertilization device, considering that the fertilization effect of plants of different varieties in different growth periods is different under different parameter values of specific control parameters, and therefore, the difference of growth data of plants of the same variety in the same growth period in each dimension is analyzed under the target parameter value, the abnormality degree of the growth state of plants of the same variety in the same growth period under the fertilization work of the target parameter value is reflected through the obtained growth abnormality index, considering that the influence degree of the target control parameter on the fertilization effect of the plants is different with the change of the different parameter values of the target control parameter of the fertilization device, the influence degree of the target control parameter on the plants in the target growth period is reflected through the obtained influence degree, and the irrelevance between the growth state of plants of the target variety in the target growth period and the target control parameter is reflected through the obtained control ambiguity degree, and then, based on the control ambiguity degree of each variety in each growth period under each control parameter, and in combination with the ant colony algorithm, the seedling fertilization control of the plants is performed, so that the plants can be accurately fertilized under the actual condition, and the fertilization effect is improved. BRIEF DESCRIPTION OF DRAWINGS
[0039] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor.
[0040] Figure 1 A seedling fertilization control method flow chart for forestry engineering provided by an embodiment of the application. DETAILED DESCRIPTION
[0041] In order to further clarify the technical means and effects taken by the present application to achieve the predetermined object of the application, the specific embodiments, structure, features and effects of a seedling fertilization control method and system for forestry engineering according to the present application are described in detail below in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.
[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0043] The specific scheme of the seedling fertilization control method and system for forestry engineering provided by the present application is described below in combination with the drawings.
[0044] Please refer to Figure 1 which shows a flow chart of a seedling fertilization control method for forestry engineering provided by an embodiment of the present application, the method comprises:
[0045] Step S1: Obtain the growth data of different varieties of plants in different dimensions in each growth cycle at each parameter value of different types of control parameters of the fertilization equipment.
[0046] In the management of forestry engineering, a large number of seedling plants need to be fertilized, in order to improve the fertilization efficiency, self-propelled watering carts and other fertilization equipment are usually used for fertilization work, but since the fertilization equipment usually faces plants of different varieties and different growth cycles, only using the pre-set control parameters (sprinkling pressure, sprinkling opening, sprinkling flow, etc.) of the fertilization equipment cannot effectively perform the fertilization work.
[0047] In the process of multiple fertilization work, relevant personnel usually set different parameter values for a certain control parameter of the fertilization equipment, and collect the growth data of each plant at different parameter values set, in order to evaluate the fertilization effect, therefore, the embodiment of the present application first extracts from the database the growth data of different varieties of plants in different dimensions in each growth cycle at each parameter value of different types of control parameters of the fertilization equipment, wherein the dimensions of the growth data usually include plant height, stem diameter, NDVI data, etc., the number and type of dimensions can also be set by the implementer according to the specific implementation scene, which is not limited here.
[0048] Step S2: taking any type of control parameter as a target control parameter, taking any parameter value of the target control parameter as a target parameter value, taking any variety as a target variety, taking any growth cycle of each plant of the target variety as a target growth cycle, obtaining a growth anomaly index of the target variety in the target growth cycle under the target parameter value according to the difference of the growth data of each plant of the target variety in the same dimension in the target growth cycle under the target parameter value, and obtaining the influence degree of the target variety in the target growth cycle under the target control parameter according to the change of each parameter value of the target control parameter and the change of the growth anomaly index of the target variety in the target growth cycle under each parameter value of the target control parameter.
[0049] Since the multifunctional self-propelled watering vehicle can adjust the control parameters according to the actual seedling raising process, it can mainly move, irrigate and apply pesticides according to the program setting or the instructions of the remote controller, for example, the irrigation speed can be easily changed, the fertilizer formula can be switched at any time, and the use is simple, but in the actual use process, the height, span and stability are not considered, which leads to poor fertilization and irrigation effect on the plants on the seedling tray, and the fertilization effect on different varieties of plants in different growth cycles is different under different parameter values of the control parameters, so it is necessary to analyze the adjustability of the fertilization and irrigation effect of the self-propelled watering vehicle on different varieties and growth cycles of plants.
[0050] Therefore, the embodiment of the present application first takes any type of control parameter as a target control parameter, takes any parameter value of the target control parameter as a target parameter value, takes any variety as a target variety, takes any growth cycle of each plant of the target variety as a target growth cycle, then analyzes the difference of the growth data of each plant of the target variety in the target growth cycle in the same dimension under the target parameter value, reflects the abnormal degree of the growth state of the plants of the target variety in the same growth cycle under the fertilization work of the target parameter value through the obtained growth anomaly index, and analyzes the correlation between the growth anomaly index of the target variety in the target growth cycle under different parameter values of the target parameter and the change of the parameter value of the target parameter, so as to accurately analyze the influence degree of the target control parameter on the target variety in the target growth cycle.
[0051] Preferably, in one embodiment of the present application, the method for obtaining the growth anomaly index of the target variety in the target growth cycle under the target parameter value specifically comprises:
[0052] Firstly, the data points of the growth data of each plant of the target variety under the target parameter value in all dimensions of the target growth cycle are input into the outlier factor detection algorithm, and the outlier degree of each plant of the target variety under the target parameter value in the target growth cycle is output, wherein the outlier factor detection algorithm is a technical means familiar to those skilled in the art, and will not be repeated here.
[0053] Then, the smaller the outlier degree of a certain plant relative to the overall level of the outlier degree of all plants, the lower the fertilization effect on the plant under the fertilization work of the target parameter value, and the more abnormal the growth state of the plant, so according to the difference between the outlier degree of each plant of the target variety under the target parameter value in the target growth cycle and the overall level of the outlier degree of all plants of the target variety in the target growth cycle, the fertilization effect evaluation value of each plant of the target variety under the target parameter value in the target growth cycle is obtained, and the larger the fertilization effect evaluation value, the worse the fertilization effect on the plant.
[0054] Preferably, in an embodiment of the present application, the method for obtaining the fertilization effect evaluation value of each plant of the target variety under the target parameter value in the target growth cycle specifically comprises:
[0055] The average value of the outlier degree of all plants of the target variety under the target parameter value in the target growth cycle is taken as the overall outlier degree of the target variety under the target parameter value in the target growth cycle.
[0056] The difference between the outlier degree and the overall outlier degree of each plant of the target variety under the target parameter value in the target growth cycle is negatively correlated, and the fertilization effect evaluation value of each plant of the target variety under the target parameter value in the target growth cycle is obtained.
[0057] As an example, in an embodiment of the present application, the expression of the fertilization effect evaluation value of each plant of the target variety under the target parameter value in the target growth cycle can be specifically, for example:
[0058]
[0059] Wherein, A i represents the fertilization effect evaluation value of the i th plant of the target variety under the target parameter value in the target growth cycle; C i represents the outlier degree of the i th plant of the target variety under the target parameter value in the target growth cycle; represents the overall outlying degree of the target variety under the target parameter value in the target growth period; exp() represents an exponential function with the natural constant e as the base, which is used for negative correlation mapping processing, and it should be noted that in other embodiments of the present application, negative correlation mapping can also be realized by other basic mathematical operations, which will not be described here.
[0060] Further, the average of the fertilization effect evaluation values of all plants of the target variety under the target parameter value in the target growth period is taken as the growth anomaly index of the target variety under the target parameter value in the target growth period.
[0061] The variation of the parameter value of the target control parameter of the fertilization device is closer to the uniform distribution for the variation of the growth anomaly index of the target variety under different parameter values in the target growth period, which proves that the target control parameter is better for controlling the fertilization effect. For example, in the variation within the reasonable range of fertilization, as the spraying rate increases, the water and fertilizer concentration absorbed by the plants in the seedling area increases faster, and the growth level of the plants is affected by the increase of the water and fertilizer accumulation under the spraying rate, so the spraying rate has a greater impact on the fertilization effect of the plants. Therefore, the influence degree of the target variety under the target control parameter in the target growth period can be obtained according to the variation of each parameter value of the target control parameter and the variation of the growth anomaly index of the target variety under each parameter value of the target control parameter in the target growth period, and the influence degree of the target control parameter on the target plant in the target growth period is reflected by the influence degree.
[0062] Preferably, in an embodiment of the present application, the method for obtaining the influence degree of the target variety under the target control parameter in the target growth period specifically comprises:
[0063] According to the order from small to large of the parameter values of the target control parameter, the growth anomaly indexes of the target variety under each parameter value of the target control parameter in the target growth period are sorted to obtain a growth anomaly index sequence, and the influence degree of the target variety under the target control parameter in the target growth period is obtained according to the difference between the adjacent two growth anomaly indexes in the growth anomaly index sequence and the difference between the parameter values corresponding to the adjacent two growth anomaly indexes.
[0064] Preferably, in an embodiment of the present application, the method for obtaining the influence degree of the target variety under the target control parameter in the target growth period further comprises:
[0065] In the growth anomaly index sequence, the absolute value of the difference between any adjacent two growth anomaly indexes is taken as the numerator, the absolute value of the difference between the parameter values corresponding to any adjacent two growth anomaly indexes is taken as the denominator, and the ratio is taken as the relative change degree between any adjacent two growth anomaly indexes.
[0066] The smaller the relative change degree between two adjacent abnormal growth indexes is, the greater the influence degree of the target control parameter on the target variety in the target growth period is, and thus the average of the relative change degrees between all adjacent abnormal growth indexes in the abnormal growth index sequence can be negatively correlated and normalized, the calculation result is limited in the range of [0, 1], and thus the influence degree of the target control parameter on the target variety in the target growth period is obtained.
[0067] In an embodiment of the present application, the negative correlation normalization processing can be implemented by using a negative exponential function with the natural constant e as the base or a function form of 1-norm(), wherein norm() represents a normalization function. In an embodiment of the present application, the normalization processing can be specifically, for example, a maximum-minimum value normalization processing. In other embodiments of the present application, other normalization methods can be selected according to the specific range of values, or the normalization processing can be implemented by using an activation function and a hyperbolic tangent function. Details are not described and limited herein.
[0068] As an example, in an embodiment of the present application, the expression of the influence degree of the target control parameter on the target variety in the target growth period can be specifically, for example,
[0069]
[0070] wherein S represents the influence degree of the target control parameter on the target variety in the target growth period; represents the nth abnormal growth index in the abnormal growth index sequence; represents the (n+1)th abnormal growth index in the abnormal growth index sequence, wherein the nth abnormal growth index and the (n+1)th abnormal growth index are adjacent; n represents the parameter value corresponding to the nth abnormal growth index in the abnormal growth index sequence; n+1 represents the parameter value corresponding to the (n+1)th abnormal growth index in the abnormal growth index sequence; N represents the number of abnormal growth indexes in the abnormal growth index sequence, i.e., the number of parameter values of the target control parameter, and thus N-1 represents the number of adjacent abnormal growth indexes in the abnormal growth index sequence; exp() represents an exponential function with the natural constant e as the base, and is used for negative correlation normalization processing.
[0071] The influence degree of the target control parameter on the target variety in each growth period can be obtained by the same method.
[0072] Step S3: obtaining the influence difference degree of the target variety under the target control parameter in the target growth period according to the difference between the influence degrees of the target variety under the target control parameter between the target growth period and the adjacent growth period, and obtaining the control fuzziness degree of the target variety under the target control parameter in the target growth period according to the difference between the influence difference degrees of the target variety and other varieties under the target control parameter in the target growth period.
[0073] Since the parameter control of the fertilization process itself is not directly causally related to the fertilization effect of the seedling plant, that is, under the condition that the environmental factors are relatively consistent, the fertilization effect of the seedling plant is mainly affected by the fertilization equipment, and the feedback performance of the target variety under the target control parameter shows that there is a change condition of the parameter value of the target control parameter, which indicates that the target control parameter is not good for the fertilization effect, therefore, the embodiment of the present application first analyzes the difference between the influence degrees of the target variety under the target control parameter between the target growth period and the adjacent growth period, and reflects the influence degree of the target control parameter on the target plant in the target growth period through the obtained influence degree.
[0074] Preferably, in an embodiment of the present application, the method for obtaining the influence difference degree of the target variety under the target control parameter in the target growth period specifically comprises:
[0075] Two growth periods adjacent to the target growth period of the target variety are taken as the reference growth periods of the target growth period, and the absolute value of the difference between the influence degrees of the target variety under the target control parameter between the target growth period and each reference growth period is taken as the influence difference coefficient between the target variety under the target control parameter between the target growth period and each reference growth period.
[0076] The sum of the influence difference coefficients of the target variety under the target control parameter between the target growth period and all reference growth periods is taken as the influence difference degree of the target variety under the target control parameter in the target growth period.
[0077] It should be noted that for the first growth period and the last growth period, there is only one adjacent growth period, that is, the first growth period and the last growth period each have only one reference growth period, therefore, in order to facilitate the smoothness of subsequent calculation, the influence difference coefficient between the target variety under the target control parameter between the first growth period and the corresponding reference growth period can be directly taken as the influence difference degree of the target variety under the target control parameter in the first growth period, and similarly, the influence difference coefficient between the target variety under the target control parameter between the last growth period and the corresponding reference growth period can be directly taken as the influence difference degree of the target variety under the target control parameter in the last growth period.
[0078] The influence difference degree of each variety under the target control parameter in each growth cycle can be obtained by the same method, and then the difference between the influence difference degrees of the target variety and other varieties under the target control parameter in the target growth cycle is analyzed. The control ambiguity degree reflects the growth state of the target variety in the target growth cycle and the irrelevance between the target control parameter. The greater the control ambiguity degree, the less the relevance between the change of the target control parameter and the fertilization effect of the target variety in the target growth cycle. Subsequently, based on the control ambiguity degree of each variety under each control parameter in each growth cycle, and combined with the ant colony algorithm, the plant can be precisely controlled for fertilization to improve the fertilization effect.
[0079] Preferably, in an embodiment of the present application, the method for obtaining the control ambiguity degree of the target variety under the target control parameter in the target growth cycle specifically comprises:
[0080] The absolute value of the difference between the influence difference degrees of the target variety and each other variety under the target control parameter in the target growth cycle is taken as the control ambiguity factor between the target variety and each other variety under the target control parameter in the target growth cycle, and then the cumulative value of the control ambiguity factors between the target variety and all other varieties under the target control parameter in the target growth cycle is normalized to limit the calculation result in the range of [0, 1], thereby obtaining the control ambiguity degree of the target variety under the target control parameter in the target growth cycle.
[0081] As an example, in an embodiment of the present application, the expression of the control ambiguity degree of the target variety under the target control parameter in the target growth cycle can be specifically as follows:
[0082]
[0083] Wherein, Q represents the control ambiguity degree of the target variety under the target control parameter in the target growth cycle; ΔS represents the influence difference degree of the target variety under the target control parameter in the target growth cycle; ΔS m represents the influence difference degree of the mth other variety under the target control parameter in the target growth cycle; |ΔS-ΔS m | represents the control ambiguity factor between the target variety and the mth other variety under the target control parameter in the target growth cycle; M represents the number of other varieties except the target variety; norm() represents a normalization function for normalization.
[0084] The control ambiguity degree of each variety under each type of control parameter in each growth cycle can be obtained by the same method.
[0085] Step S4: based on the control ambiguity of each variety in each growth cycle under each control parameter, and combined with the ant colony algorithm, the seedling fertilization control of the plant is performed.
[0086] The greater the control ambiguity, the less the connection between the change of the target control parameter and the fertilization effect of the plant of the target variety in the target growth cycle, so in order to improve the final fertilization effect, the parameter type with strong control ability needs to be prioritized, and therefore, based on the control ambiguity of each variety in each growth cycle under each control parameter, and combined with the ant colony algorithm, the seedling fertilization control of the plant is performed, so as to realize more accurate fertilization of the plant and improve the fertilization effect.
[0087] Preferably, in an embodiment of the present application, the method for performing the seedling fertilization control of the plant specifically comprises:
[0088] According to the control ambiguity of the target variety in the target growth cycle under the target control parameter, the standard weight value of the target variety in the target growth cycle under the target control parameter is adjusted to obtain the adjusted weight value of the target variety in the target growth cycle under the target control parameter.
[0089] Preferably, in an embodiment of the present application, the method for obtaining the adjusted weight value of the target variety in the target growth cycle under the target control parameter specifically comprises:
[0090] The product value of the control ambiguity of the target variety in the target growth cycle under the target control parameter and the standard weight value is taken as the weight adjustment amount of the target variety in the target growth cycle under the target control parameter, and the difference between the standard weight value and the weight adjustment amount of the target variety in the target growth cycle under the target control parameter is taken as the adjusted weight value of the target variety in the target growth cycle under the target control parameter, wherein the standard weight value is a known value set by the fertilization equipment.
[0091] Through the same method as described above, the adjusted weight value of each variety in each growth cycle under each type of control parameter can be obtained, the data points formed by the growth data of each plant of different varieties in each growth cycle under each parameter value of different types of control parameters are taken as the nodes used by the ant colony algorithm, and the adjusted weight values of different varieties in each growth cycle under different control parameters are taken as the pheromone of each node, the nodes and the pheromone are input into the ant colony algorithm, and the optimal control parameter combination of the fertilization equipment is output, and the optimal control parameter combination is used to perform the seedling fertilization control of the plant, wherein the ant colony algorithm is a technical means well known to those skilled in the art, and will not be described here.
[0092] It is to be noted that the sequential order of the above-described embodiments of the present application only for the purpose of description, but not the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.
[0093] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments.
Claims
1. A method for controlling seedling fertilization in forestry engineering, characterized in that, The method includes: Under the control parameters of different types of fertilization equipment, growth data of different varieties of plants in different dimensions of each growth cycle were obtained. Using any type of control parameter as the target control parameter, any value of the target control parameter as the target parameter value, any variety as the target variety, and any growth cycle of each plant of the target variety as the target growth cycle, the growth abnormality index of the target variety in the target growth cycle is obtained based on the differences in growth data of each plant of the target variety in the same dimension of the target growth cycle under the target parameter value. The degree of influence of the target variety in the target growth cycle under the target control parameter is obtained based on the changes in the values of each parameter of the target control parameter and the changes in the growth abnormality index of the target variety under the values of each parameter of the target control parameter in the target growth cycle. Based on the difference in the degree of influence of the target variety under the target control parameters between the target growth cycle and adjacent growth cycles, the degree of influence difference of the target variety under the target control parameters in the target growth cycle is obtained; based on the difference in the degree of influence difference between the target variety under the target control parameters and other varieties in the target growth cycle, the degree of control fuzziness of the target variety under the target control parameters in the target growth cycle is obtained. Based on the degree of control fuzziness of each variety under each control parameter at each growth cycle, and combined with the ant colony algorithm, seedling fertilization control is carried out on the plants.
2. The method for controlling seedling fertilization in forestry engineering according to claim 1, characterized in that, The abnormal growth index of the target variety at the target growth cycle, obtained under the target parameter values, includes: The data points consisting of the growth data of each plant of the target variety under the target parameter value in all dimensions of the target growth cycle are input into the outlier detection algorithm, and the outlier degree of each plant of the target variety under the target parameter value in the target growth cycle is output. Based on the difference between the outlier degree of each plant of the target variety in the target growth cycle and the overall level of the outlier degree of all plants of the target variety in the target growth cycle under the target parameter values, the fertilization effect evaluation value of each plant of the target variety in the target growth cycle under the target parameter values is obtained. The average value of the fertilization effect assessment of all plants of the target variety under the target parameter value during the target growth cycle is used as the growth abnormality index of the target variety during the target growth cycle under the target parameter value.
3. The method for controlling seedling cultivation and fertilization in forestry engineering according to claim 2, characterized in that, The evaluation values of fertilization effect for each plant of the target variety at the target growth cycle, under the obtained target parameter values, include: The average outlier degree of all plants of the target variety under the target parameter value during the target growth cycle is taken as the overall outlier degree of the target variety under the target parameter value during the target growth cycle. By negatively correlating the difference between the outlier degree of each plant of the target variety and the overall outlier degree during the target growth cycle under the target parameter values, the fertilization effect evaluation value of each plant of the target variety during the target growth cycle under the target parameter values is obtained.
4. The method for controlling seedling fertilization in forestry engineering according to claim 1, characterized in that, The degree of influence of the target variety on the target growth cycle under the obtained target control parameters includes: According to the parameter values of the target control parameters in ascending order, the growth abnormality index of the target variety under each parameter value of the target control parameters in the target growth cycle is sorted to obtain the growth abnormality index sequence. Based on the difference between two adjacent growth abnormality indices in the growth abnormality index sequence, and the difference in the parameter values corresponding to the two adjacent growth abnormality indices, the degree of influence of the target variety on the target growth cycle under the target control parameters is obtained.
5. A method for controlling seedling fertilization in forestry engineering according to claim 4, characterized in that, The step of obtaining the degree of influence of the target variety on the target growth cycle under the target control parameters based on the difference between two adjacent growth abnormality indices in the growth abnormality index sequence and the difference in the parameter values corresponding to the two adjacent growth abnormality indices includes: In the growth abnormality index sequence, the absolute value of the difference between any two adjacent growth abnormality indices is used as the numerator, and the absolute value of the difference between the parameter values corresponding to any two adjacent growth abnormality indices is used as the denominator. The ratio is used as the relative degree of change between any two adjacent growth abnormality indices. The average relative change between all adjacent growth abnormality indices in the growth abnormality index sequence is negatively correlated and normalized to obtain the degree of influence of the target variety on the target growth cycle under the target control parameters.
6. The method for controlling seedling fertilization in forestry engineering according to claim 1, characterized in that, The degree of difference in the impact of the target variety under the target control parameters on the target growth cycle includes: The two growth cycles adjacent to the target growth cycle of the target variety are used as reference growth cycles for the target growth cycle. The absolute value of the difference between the degree of influence of the target variety under the target control parameters and the target growth cycle and each reference growth cycle is used as the influence difference coefficient of the target variety under the target control parameters between the target growth cycle and each reference growth cycle. The sum of the influence difference coefficients between the target variety and all reference growth cycles under the target control parameters is taken as the influence difference degree of the target variety under the target control parameters in the target growth cycle.
7. The method for controlling seedling fertilization in forestry engineering according to claim 1, characterized in that, The degree of control fuzziness of the target variety under the target control parameters during the target growth cycle includes: The absolute value of the difference in the degree of influence between the target variety and each other variety under the target control parameters during the target growth cycle is used as the control fuzziness factor between the target variety and each other variety under the target control parameters during the target growth cycle. The cumulative value of the control fuzzy factor between the target variety and all other varieties under the target control parameters during the target growth cycle is normalized to obtain the control fuzziness degree of the target variety under the target control parameters during the target growth cycle.
8. A method for controlling seedling fertilization in forestry engineering according to claim 2, characterized in that, The control of seedling fertilization includes: Based on the degree of control fuzziness of the target variety under the target control parameters in the target growth cycle, the standard weight value of the target variety under the target control parameters in the target growth cycle is adjusted to obtain the adjusted weight value of the target variety under the target control parameters in the target growth cycle. The data points, which are the growth data of each plant of different varieties in each growth cycle under each parameter value of different types of control parameters, are used as nodes in the ant colony algorithm. The adjustment weight values of different varieties under different control parameters in each growth cycle are used as pheromones for each node. Each node and pheromone are input into the ant colony algorithm, and the optimal combination of control parameters for the fertilization equipment is output. The optimal combination of control parameters is used to control the seedling fertilization of the plants.
9. A method for controlling seedling fertilization in forestry engineering according to claim 1, characterized in that, The adjustment weight values for the target variety under the target control parameters during the target growth cycle include: The product of the degree of control fuzziness and the standard weight value of the target variety under the target control parameters in the target growth cycle is used as the weight adjustment amount of the target variety under the target control parameters in the target growth cycle. The difference between the standard weight value of the target variety under the target control parameters in the target growth cycle and the weight adjustment amount is used as the adjustment weight value of the target variety under the target control parameters in the target growth cycle.
10. A seedling fertilization control system for forestry engineering, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 9.