Intelligent management and control system and method for rice-crab symbiotic ecological breeding

Abstract

This invention discloses an intelligent management and control system and method for rice-crab symbiotic ecological farming, belonging to the field of rice-crab symbiosis technology. The invention first determines the growth and regulation information of rice and crabs, then analyzes the synergistic inhibition relationships between different growth cycles of rice and crabs, and further determines a synergistic mapping table of rice-crab growth cycles. Based on this table, the target regulation cycle corresponding to each growth cycle of crabs is analyzed and obtained, and the target regulation information for each growth cycle of crabs is further analyzed. The growth cycles of crabs are then regulated according to this target regulation information to synchronize them with the corresponding target regulation cycles. By controlling the regulation information, this invention controls the length of the crab growth cycle, maximizing the synergistic effects of rice shading, water circulation, and feeding, and crab weeding, soil loosening, and fertilization, thus significantly improving the stability of the rice paddy ecosystem.

Description

Technical Field

[0001] This invention relates to the field of rice-crab symbiosis technology, specifically to an intelligent management and control system and method for rice-crab symbiosis ecological farming. Background Technology

[0002] The rice-crab symbiosis model achieves double harvest from a single field through the ecological interaction between rice and crabs. Rice provides crabs with a habitat, shade, and natural food, while crabs prey on pests, diseases, and weeds, loosen the soil, and nourish the rice with their metabolites. It has significant advantages in improving land utilization, reducing the use of chemical fertilizers and pesticides, and increasing farmers' income. It has become an important direction for green agricultural development. Therefore, it is crucial to develop an intelligent management and control system for rice-crab symbiosis ecological farming.

[0003] There are still some shortcomings in the management of rice-crab symbiotic ecological farming, which are reflected in the following aspects: (1) Since rice and crab each have a complete growth cycle, the existing technology has not achieved the alignment and collaborative analysis of the time stamps of the growth cycles of rice and crab. This often leads to problems such as the conflict between the molting period of crab and the tillering period of rice, and the overlap between the feeding period of feed and the fertilization period of rice. This not only inhibits the survival rate of crab molting, but also affects the nutrient absorption of rice. Therefore, it is difficult to achieve the goal of high yield of both species.

[0004] (2) Existing technologies rely mainly on human experience for regulation. Key parameters such as water level, water temperature, dissolved oxygen, feed and fertilizer lack quantitative basis. Not only is the coverage of regulatory elements incomplete, but key factors such as ammonia nitrogen, nitrite, aquatic plant coverage and light transmittance are ignored. Moreover, the timing of regulation is blind and does not combine with the dynamic adjustment of the rice-crab growth cycle. Furthermore, existing technologies focus on the management of a single species and lack quantitative modeling of the coupling relationship of the rice-crab growth cycle. The synergistic and inhibitory mechanisms of different growth stages are not clearly defined, and no feasible synergistic regulation method has been formed, making it difficult to support the implementation of intelligent management and control systems. Summary of the Invention

[0005] To address the aforementioned technical shortcomings, the present invention aims to provide an intelligent management and control system and method for rice-crab symbiotic ecological farming.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The first aspect of the present invention provides an intelligent management and control system for rice-crab symbiotic ecological farming, including: an information determination module, used to determine the growth information and control information of rice and crab.

[0007] The growth cycle analysis module is used to analyze the synergistic inhibition relationship between different growth cycles of rice and crab based on the growth and regulation information of rice and crab, and then determine the synergistic mapping table of rice and crab growth cycles.

[0008] The growth cycle regulation module is used to analyze the target regulation cycle corresponding to each growth cycle of the crab based on the rice-crab co-growth cycle mapping table, and then analyze the target regulation information of each growth cycle of the crab to regulate each growth cycle of the crab so that each growth cycle of the crab is synchronized with the corresponding target regulation cycle.

[0009] The second aspect of this invention provides an intelligent management and control method for rice-crab symbiotic ecological farming, comprising: Step 1, determining the growth information and control information of rice and crab. Step 2: Based on the growth and regulation information of rice and crab, analyze the synergistic inhibition relationship between different growth cycles of rice and crab, and then determine the synergistic mapping table of rice and crab growth cycles. Step 3: Based on the rice-crab co-growth cycle mapping table, analyze and obtain the target regulation cycle corresponding to each growth cycle of the crab, then analyze and obtain the target regulation information for each growth cycle of the crab, and regulate each growth cycle of the crab according to the target regulation information to synchronize each growth cycle of the crab with the corresponding target regulation cycle.

[0010] The beneficial effects of the present invention are as follows: (1) The present invention quantifies the time stamp alignment and coupling coordination of the growth cycles of rice and crabs, accurately identifies the synergistic and inhibitory relationships of each stage, constructs a rice-crab growth cycle synergistic mapping table, controls the regulation information, and then controls the length of the crab growth cycle, fundamentally solving the problems of mismatched growth rhythm, conflict between molting and fertilization, and competition between feed and nutrients in traditional farming, maximizing the synergistic effect of rice shading, water circulation, and feed supply with crab weeding, soil loosening, and fertilization, and greatly improving the stability of the rice paddy ecosystem.

[0011] (2) This invention develops a replicable and scalable intelligent management and control technology system for rice-crab symbiosis, solving the problems of fragmentation, qualitativeity, and difficulty in large-scale application of existing technologies, and providing key technical support for the intelligent upgrading of the rice-crab integrated farming industry. It can ensure the optimal synergistic effect without violating the natural growth law of rice and crabs. The control measures are mild and controllable, easy to implement in the field, and will not cause abnormal growth due to excessive adjustment. Its practicality is far superior to purely theoretical optimization schemes. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0014] Figure 2 This is a schematic diagram of the implementation steps of the method of the present invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Reference Figure 1 As shown, the first aspect of the present invention provides an intelligent management and control system for rice-crab symbiotic ecological farming, including: an information information determination module for determining the growth information and control information of rice and crabs.

[0017] In a specific example, the process of determining the growth cycle and regulation information of rice and crab is as follows: The growth information includes each growth cycle and the corresponding time period. The growth cycle of rice includes the seedling stage, transplanting and greening stage, tillering stage, jointing and booting stage, heading and flowering stage, grain filling and ripening stage, and harvesting stage. The growth cycle of crab includes the seedling release stage, rapid growth stage, stable growth stage, molting stage, fattening and accumulating stage, and harvesting stage. The corresponding time period is used as the timestamp of each growth cycle, and then the growth cycles of rice and crab are aligned based on the timestamps to obtain the rice-crab growth time series map.

[0018] The control information includes several control elements corresponding to each growth cycle of rice and each growth cycle of river crabs: water temperature, water level, water exchange frequency, water exchange volume, dissolved oxygen in the water, pH value, ammonia nitrogen content, nitrite content, fertilizer type, fertilization frequency, fertilization amount, fertilization time, ventilation volume, light transmittance, shading rate, feed type, feeding amount, feeding frequency, feeding time, aquatic plant coverage rate, and aquatic plant removal cycle.

[0019] The growth cycle analysis module is used to analyze the synergistic inhibition relationship between different growth cycles of rice and crab based on the growth and regulation information of rice and crab, and then determine the synergistic mapping table of rice and crab growth cycles.

[0020] In a specific example, the synergistic inhibition relationship between different growth cycles of rice and crab is analyzed based on the growth and regulation information of rice and crab. The specific analysis process is as follows: S1. Based on the growth and regulation information of rice, a rice growth matrix is ​​constructed. The rows and columns in the rice growth matrix correspond to different growth cycles of rice and different regulation elements in the regulation information corresponding to different growth cycles. After normalizing the rice growth matrix, the entropy weight of each regulation element is calculated using the entropy weight method. The regulation elements corresponding to different growth cycles in the normalized growth matrix are multiplied by their corresponding entropy weights and summed to obtain the comprehensive regulation index of different growth cycles of rice.

[0021] It should be noted that the entropy weight of each regulatory element is calculated using the entropy weight method. The specific process is as follows: For any regulatory element corresponding to any growth cycle, the proportion of that regulatory element in the total proportion of the regulatory elements in all cycles is calculated. Based on this, a proportion matrix is ​​calculated. Then, the information entropy of each regulatory element is calculated based on the proportion matrix. The information entropy is subtracted from 1 to obtain the difference coefficient of each regulatory element. The difference coefficient of any regulatory element corresponding to any growth cycle is divided by the sum of the difference coefficients of that regulatory element in all growth cycles to obtain the entropy weight of that regulatory element. The entropy weight of each regulatory element is obtained accordingly. The method for calculating the information entropy is existing technology and will not be described in detail here.

[0022] S2. The comprehensive regulatory index of each growth cycle of the river crab is obtained by analyzing the above method.

[0023] S3. Based on the comprehensive regulation index of rice and crab growth cycles, the coupling coordination index of rice and crab growth cycles is calculated.

[0024] It should be noted that the coupling coordination degree between the rice comprehensive regulation index and the river crab comprehensive regulation index was calculated as follows: First, the comprehensive regulation index of rice at each growth cycle and the comprehensive regulation index of river crab at each growth cycle were respectively denoted as... and Then, the coupling degree of each growth cycle of rice and crab can be calculated. : Then, the coordination degree of rice-crab growth cycles was calculated. : Thus, the coupling coordination index of each growth cycle of rice and crab can be calculated. : , where i and j represent the growth cycle numbers of rice and crab, respectively, and i and j are both positive integers.

[0025] In a specific example, the process of determining the rice-crab growth cycle coordination mapping table is as follows: For any growth cycle of the crab, the coupling coordination index of each growth cycle of the rice corresponding to that growth cycle is sorted from largest to smallest to obtain the coordination mapping table of each growth cycle of the rice corresponding to that growth cycle of the crab. Based on this, the coordination mapping table of each growth cycle of the crab corresponding to each growth cycle of the rice can be obtained, which is collectively referred to as the rice-crab growth cycle mapping table.

[0026] The growth cycle regulation module is used to analyze the target regulation cycle corresponding to each growth cycle of the crab based on the rice-crab co-growth cycle mapping table, and then analyze the target regulation information of each growth cycle of the crab to regulate each growth cycle of the crab so that each growth cycle of the crab is synchronized with the corresponding target regulation cycle.

[0027] In a specific example, the analysis yields the target regulation cycle corresponding to each growth cycle of the river crab. The specific analysis process is as follows: A1. First, based on the rice-crab growth time series map, the initial growth cycle of the river crab is recorded as the primary regulation cycle, and the rice growth cycle with the same timestamp as the primary regulation cycle of the river crab is recorded as the reference regulation cycle. At the same time, the adjacent cycles before and after the reference regulation cycle are obtained and recorded together with the reference regulation cycle as each candidate regulation cycle. Then, based on the rice-crab growth cycle coordination mapping table, the coupling coordination index between the primary regulation cycle and each candidate regulation cycle is obtained. The candidate regulation cycle corresponding to the maximum coupling coordination index is recorded as the target regulation cycle of the primary regulation cycle.

[0028] A2. The next growth cycle after the initial growth cycle of the crab is recorded as the secondary regulation cycle. The target regulation cycle of the primary regulation cycle and the next rice growth cycle of the target regulation cycle are re-recorded as each alternative regulation information. According to the rice-crab growth cycle coordination mapping table, the coupling coordination index between the secondary regulation cycle and each alternative regulation cycle is obtained. The alternative regulation cycle corresponding to the maximum coupling coordination index is recorded as the target regulation cycle of the secondary regulation cycle.

[0029] A3. Repeat A1-A2 until the target regulation cycle for each growth cycle of the crab is obtained.

[0030] It should be noted that the target regulation cycles of two adjacent crab growth cycles may overlap, but there is no cross relationship. When the target regulation cycles of two adjacent crab growth cycles overlap, the crab growth cycle with the larger coupling coordination index is selected for regulation first.

[0031] It should be noted that if the timestamp of a certain growth cycle of the crab is inconsistent with the timestamp of the corresponding target regulation cycle, the length of the growth cycle of the crab can be controlled through the regulation information, thereby making the growth cycle of the crab overlap with the target regulation cycle. However, when controlling the length of the growth cycle of the crab, the overlap length between the growth cycle of the crab and the target regulation shall not exceed 15 days. If the timestamp of a certain growth cycle of the crab is consistent with the timestamp of the corresponding target regulation cycle, then the regulation of the growth cycle of the crab will completely overlap with the corresponding target regulation cycle.

[0032] For example, the initial growth cycle of the crab, i.e., the seedling release period, is recorded as the primary regulation cycle. The growth cycle of rice with the same time stamp as the primary regulation cycle is retrieved, and the rice seedling period is determined as the reference regulation cycle. The transplanting and greening period of the right adjacent cycle of the reference regulation cycle is obtained. The reference regulation cycle and the adjacent cycle are used together as the candidate regulation cycles of the primary regulation cycle, i.e., the candidate regulation cycles are the rice seedling period and the transplanting and greening period. The pre-constructed rice-crab growth cycle coordination mapping table is retrieved, and the coupling coordination index between the primary regulation cycle and each candidate regulation cycle is obtained. The rice seedling period corresponding to the maximum value of the coupling coordination index is selected as the target regulation cycle of the primary regulation cycle.

[0033] The next growth cycle after the primary regulation cycle of the crab, namely the first molting period, is designated as the secondary regulation cycle. The target regulation cycle of the primary regulation cycle, the rice seedling stage, and the next rice growth cycle after the target regulation cycle, the transplanting and greening stage, are retrieved and used as alternative regulation cycles for the secondary regulation cycle. That is, the alternative regulation cycles are the rice seedling stage and the transplanting and greening stage. The rice-crab growth cycle coordination mapping table is retrieved, and the coupling coordination index between the secondary regulation cycle and each alternative regulation cycle is obtained. The rice seedling stage corresponding to the maximum value of the coupling coordination index is selected as the target regulation cycle for the secondary regulation cycle.

[0034] In a specific example, the analysis obtains the target regulation information for each growth cycle of the crab. The specific analysis process is as follows: the target regulation cycle of each growth cycle of the crab, the rice-crab growth time series map, and the rice-crab growth cycle collaborative mapping table are input into a pre-trained growth regulation model. The growth regulation model outputs the overlap length between each growth cycle of the crab and the corresponding target cycle, as well as the target regulation information for each growth cycle of the crab.

[0035] In a specific example, the training process of the growth regulation model is as follows: the training samples of the growth regulation model are obtained through simulation using a rice-crab co-culture simulation platform.

[0036] After preprocessing the training samples, they are divided into training set and validation set according to a preset ratio. The training set and validation set are input into the preset Attention-LSTM model. The overlap length between each growth cycle of the crab and the corresponding target cycle and the target regulation information of each growth cycle of the crab are solved with the constraint of maximizing the comprehensive growth index of the entire growth cycle of rice-crab co-culture. Based on this, the growth regulation model is trained.

[0037] It should be noted that preprocessing includes aligning, denoising, and standardizing the time-series data in the training sample set, unifying the timestamp scale and data dimensions, and constructing a time-series feature matrix, where the horizontal axis represents the time series, and the vertical axis represents the characteristics of rice growth cycle, crab growth cycle, and environmental regulation, etc.

[0038] It should also be noted that the Attention-LSTM model includes an input layer, an LSTM layer, an attention layer, and an output layer. The input layer takes into account the target regulation cycle of each growth cycle of the crab, the rice-crab growth time series map, and the rice-crab growth cycle co-mapping table. The LSTM layer consists of two LSTM network layers with 128 and 64 hidden units respectively, and uses Dropout (dropout rate 0.2) to prevent overfitting. The attention layer introduces a self-attention mechanism, with the number of attention heads set to 4. The output layer includes two branches: the regulation information branch outputs several-dimensional continuous values ​​(corresponding to several quantifiable regulation measures), and the cycle overlap branch outputs the overlap length between each growth cycle of the crab under the current regulation measure and the corresponding target cycle.

[0039] It should also be noted that during model training, in order to ensure the reproducibility of the growth regulation model, relevant personnel can customize the hyperparameters, tool environment, and saving method during the growth regulation model training. For example, the hyperparameters can be set as follows: learning rate of 0.1, number of decision trees of 100 (initial value, which can be adjusted during training iterations), initial iteration rounds of 100, and early stopping strategy to control training termination. The tool environment can be Python 3.9, NumPy 1.24.3, and Pandas 1.5.3, etc. The saving method can be .pkl format files, etc. No specific restrictions are imposed here.

[0040] It should also be noted that, in addition to the comprehensive growth index of rice and crab as a constraint, the model also includes all control parameters that can be set by relevant staff, which are all non-negative and within the range of engineering feasibility, as well as Dropout and regularization terms to enforce constraints on model complexity and avoid overfitting, etc., which will not be elaborated here.

[0041] It should also be noted that the comprehensive growth indicators include rice growth indicators and crab growth indicators. Rice growth indicators include plant height, number of tillers, leaf area index, and dry matter accumulation, etc., and each indicator should show a monotonically increasing trend or a reasonable periodic fluctuation trend over time. Crab growth indicators include weight gain rate, molting cycle, activity level, and feeding intensity, etc., and should maintain continuous and stable positive growth. Rice and crab growth indicators of the same dimension are selected, and after Min-Max normalization, they are weighted and summed to obtain the comprehensive growth indicators of rice and crab for each growth cycle, where each dimension has equal weight. Then, the comprehensive growth indicators of rice and crab for each growth cycle are added together to obtain the comprehensive growth indicators for the entire growth cycle of rice-crab co-culture.

[0042] In a specific example, the training samples of the growth regulation model are obtained through simulation using the rice-crab co-culture simulation platform. The specific analysis process is as follows: The Ecopath ecosystem energy flow model is used to conduct steady-state and dynamic simulations of the rice-crab co-culture complex ecosystem. The rice-crab growth time series map, the rice-crab growth cycle synergistic mapping table, and the target regulation cycle of each growth cycle of the crab are input into the Ecopath ecosystem energy flow model.

[0043] Using the Ecopath ecosystem energy flow model, the overlap duration between each growth cycle of the crab and the corresponding target regulation cycle is first set. Within the preset overlap duration, each regulation element in the regulation information is coupled, and then the comprehensive growth index of the entire growth cycle of rice-crab co-culture is simulated under different regulation information within the preset overlap duration.

[0044] It should be noted that the Ecopath ecosystem energy flow model is a publicly available modeling technique, and will not be elaborated upon here.

[0045] By changing the overlap duration between each growth cycle of the crab and the corresponding target regulation cycle, and repeating the above simulation process, the comprehensive growth index of the entire growth cycle of rice-crab co-culture under different regulation information within different overlap durations is obtained, and the training samples of the growth regulation model are obtained accordingly.

[0046] It should be noted that if the timestamp of a certain growth cycle of the crab is inconsistent with the timestamp of the corresponding target regulation cycle, the length of the growth cycle of the crab can be controlled through the regulation information, thereby making the growth cycle of the crab overlap with the target regulation cycle. However, when controlling the length of the growth cycle of the crab, the overlap length between the growth cycle of the crab and the target regulation shall not exceed 15 days. If the timestamp of a certain growth cycle of the crab is consistent with the timestamp of the corresponding target regulation cycle, then the regulation of the growth cycle of the crab will completely overlap with the corresponding target regulation cycle.

[0047] This invention generates standardized training samples covering multiple scenarios and working conditions through forward simulation calculations, and then utilizes Attention... The LSTM deep learning model learns the synergistic laws and regulatory mapping relationships of the rice-crab growth cycle, enabling rapid optimization reasoning under the goal of maximizing comprehensive growth indicators. At the same time, it meets the requirements of engineering feasibility, constraints and real-time control, improving the practicality and generalization ability of the solution.

[0048] In a specific example, the growth cycle of the crab is regulated according to the target regulation information. During the regulation process, the growth indicators of rice, the growth indicators of the crab, and the real-time regulation information are monitored by preset monitoring equipment, and the time-series monitoring data is uploaded to the data storage center.

[0049] It should be noted that relevant staff can dynamically adjust the growth control model based on the actual planting and breeding area, variety, and climate conditions, without making specific restrictions here; the equipment operation and data collection involved in the control process all adopt existing mature technologies, which will not be elaborated here.

[0050] Reference Figure 2 As shown, the second aspect of the present invention provides an intelligent management and control method for rice-crab symbiotic ecological farming, comprising: Step 1, determining the growth information and control information of rice and crabs. Step 2: Based on the growth and regulation information of rice and crab, analyze the synergistic inhibition relationship between different growth cycles of rice and crab, and then determine the synergistic mapping table of rice and crab growth cycles. Step 3: Based on the rice-crab co-growth cycle mapping table, analyze and obtain the target regulation cycle corresponding to each growth cycle of the crab, then analyze and obtain the target regulation information for each growth cycle of the crab, and regulate each growth cycle of the crab according to the target regulation information to synchronize each growth cycle of the crab with the corresponding target regulation cycle.

[0051] The examples described in this invention are not limited to the specific embodiments listed above. The examples are merely illustrative to facilitate understanding of the invention and do not constitute a limitation on the scope of protection of this invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of this invention should be included within the scope of protection.

[0052] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A smart management and control system for rice-crab symbiotic ecological farming, characterized in that, Includes the following modules and steps: The relevant information determination module is used to determine the growth and regulation information of rice-crab farming. The growth cycle analysis module is used to analyze the synergistic inhibition relationship between different growth cycles of rice and crab based on the growth and regulation information of rice and crab, and then determine the synergistic mapping table of rice and crab growth cycles. The growth cycle regulation module is used to analyze the target regulation cycle corresponding to each growth cycle of the crab based on the rice-crab co-growth cycle mapping table, and then analyze the target regulation information of each growth cycle of the crab to regulate each growth cycle of the crab so that each growth cycle of the crab is synchronized with the corresponding target regulation cycle.

2. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 1, characterized in that, The specific process for determining the growth cycle and regulation information of rice-crab is as follows: The growth information includes each growth cycle and the corresponding time period. The growth cycle of rice includes the seedling stage, transplanting and greening stage, tillering stage, jointing and booting stage, heading and flowering stage, grain filling and ripening stage, and harvesting stage. The growth cycle of river crab includes the seedling release stage, rapid growth stage, stable growth stage, molting stage, fattening and fertilization stage, and harvesting stage. The corresponding time period is used as the timestamp of each growth cycle. Then, based on the timestamp, the growth cycles of rice and river crab are aligned to obtain the rice-crab growth time series map. The control information includes several control elements corresponding to each growth cycle of rice and each growth cycle of river crabs: water temperature, water level, water exchange frequency, water exchange volume, dissolved oxygen in the water, pH value, ammonia nitrogen content, nitrite content, fertilizer type, fertilization frequency, fertilization amount, fertilization time, ventilation volume, light transmittance, shading rate, feed type, feeding amount, feeding frequency, feeding time, aquatic plant coverage rate, and aquatic plant removal cycle.

3. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 2, characterized in that, Based on the growth and regulation information of rice-crab, the synergistic inhibition relationship between different growth cycles of rice-crab was analyzed. The specific analysis process is as follows: S1. Based on the growth and regulation information of rice, a rice growth matrix is ​​constructed. The rows and columns in the rice growth matrix correspond to each growth cycle of rice and each regulation element in the regulation information corresponding to each growth cycle. After normalizing the rice growth matrix, the entropy weight of each regulation element is calculated using the entropy weight method. The regulation elements corresponding to each growth cycle in the normalized growth matrix are multiplied by their corresponding entropy weights and summed to obtain the comprehensive regulation index of each growth cycle of rice. S2. The comprehensive regulatory index of each growth cycle of the river crab is obtained by analyzing the above method. S3. Based on the comprehensive regulation index of rice and crab growth cycles, the coupling coordination index of rice and crab growth cycles is calculated.

4. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 3, characterized in that, The specific process for determining the rice-crab growth cycle collaborative mapping table is as follows: For any growth cycle of the river crab, the coupling coordination index of each growth cycle of rice corresponding to that growth cycle is sorted from largest to smallest to obtain the coordination mapping table of each growth cycle of rice corresponding to that growth cycle of the river crab. Based on this, the coordination mapping table of each growth cycle of rice corresponding to each growth cycle of the river crab can be analyzed and obtained. The combined table is called the rice-crab growth cycle mapping table.

5. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 4, characterized in that, The analysis yielded the target regulation cycles corresponding to each growth cycle of the crab. The specific analysis process is as follows: A1. First, based on the rice-crab growth time series map, the initial growth cycle of the crab is recorded as the first-level regulation cycle, and the rice growth cycle with the same timestamp as the first-level regulation cycle of the crab is recorded as the reference regulation cycle. At the same time, the adjacent cycles before and after the reference regulation cycle are obtained and recorded together with the reference regulation cycle as each candidate regulation cycle. Then, based on the rice-crab growth cycle coordination mapping table, the coupling coordination index between the first-level regulation cycle and each candidate regulation cycle is obtained. The candidate regulation cycle corresponding to the maximum coupling coordination index is recorded as the target regulation cycle of the first-level regulation cycle. A2. The next growth cycle after the initial growth cycle of the crab is recorded as the secondary regulation cycle. The target regulation cycle of the primary regulation cycle and the next rice growth cycle of the target regulation cycle are re-recorded as each alternative regulation information. According to the rice-crab growth cycle coordination mapping table, the coupling coordination index between the secondary regulation cycle and each alternative regulation cycle is obtained. The alternative regulation cycle corresponding to the maximum coupling coordination index is recorded as the target regulation cycle of the secondary regulation cycle. A3. Repeat A1-A2 until the target regulation cycle for each growth cycle of the crab is obtained.

6. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 5, characterized in that, The analysis yielded target regulation information for each growth cycle of the crab, and the specific analysis process is as follows: The target regulation cycle of each growth cycle of the crab, the rice-crab growth time series map, and the rice-crab growth cycle co-mapping table are input into the pre-trained growth regulation model. The growth regulation model outputs the overlap length between each growth cycle of the crab and the corresponding target cycle, as well as the target regulation information of each growth cycle of the crab.

7. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 6, characterized in that, The training process of the growth regulation model is as follows: Training samples for the growth regulation model were obtained through simulation using a rice-crab co-culture simulation platform. After preprocessing the training samples, they are divided into training set and validation set according to a preset ratio. The training set and validation set are input into the preset Attention-LSTM model. The overlap length between each growth cycle of the crab and the corresponding target cycle and the target regulation information of each growth cycle of the crab are solved with the constraint of maximizing the comprehensive growth index of the entire growth cycle of rice-crab co-culture. Based on this, the growth regulation model is trained.

8. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 7, characterized in that, The training samples for the growth regulation model were obtained through simulation using a rice-crab co-culture simulation platform. The specific analysis process is as follows: The Ecopath ecosystem energy flow model was used to conduct steady-state and dynamic simulations of the rice-crab co-culture complex ecosystem. The rice-crab growth time series map, the rice-crab growth cycle synergistic mapping table, and the target regulation cycle of each growth cycle of the crab were input into the Ecopath ecosystem energy flow model. Using the Ecopath ecosystem energy flow model, the overlap time between each growth cycle of the crab and the corresponding target regulation cycle is first set. Within the preset overlap time, each regulation element in the regulation information is coupled, and then the comprehensive growth index of the whole growth cycle of rice-crab co-culture is simulated under different regulation information within the preset overlap time. By changing the overlap duration between each growth cycle of the crab and the corresponding target regulation cycle, and repeating the above simulation process, the comprehensive growth index of the entire growth cycle of rice-crab co-culture under different regulation information within different overlap durations is obtained, and the training samples of the growth regulation model are obtained accordingly.

9. The intelligent management and control system for rice-crab symbiotic ecological farming according to claim 8, characterized in that, The process involves regulating the growth cycle of the crabs according to the target regulation information. During the regulation process, the growth indicators of rice, the growth indicators of crabs, and real-time regulation information are monitored by preset monitoring equipment, and the time-series monitoring data is uploaded to the data storage center.

10. A method executed using the intelligent management and control system for rice-crab symbiotic ecological farming as described in any one of claims 1-9, characterized in that, include: Step 1: Determine the growth and regulation information of rice-crab farming; Step 2: Based on the growth and regulation information of rice and crab, analyze the synergistic inhibition relationship between different growth cycles of rice and crab, and then determine the synergistic mapping table of rice and crab growth cycles. Step 3: Based on the rice-crab co-growth cycle mapping table, analyze and obtain the target regulation cycle corresponding to each growth cycle of the crab, then analyze and obtain the target regulation information for each growth cycle of the crab, and regulate each growth cycle of the crab according to the target regulation information to synchronize each growth cycle of the crab with the corresponding target regulation cycle.

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