Environment management method and device, electronic equipment and storage medium

Abstract

The invention provides an environment management method and device, electronic equipment and a storage medium, and relates to the technical field of environment protection and resource management, and the method comprises the steps: obtaining to-be-predicted environment data and an environment adjustment strategy; inputting the environment data into a target strategy generation model to generate a plurality of dynamic environment candidate schemes; determining a target dynamic environment adjustment scheme from the plurality of dynamic environment candidate schemes based on an environment adjustment strategy; and performing environment management based on the target dynamic environment adjustment scheme. Therefore, according to the scheme, the scientificity and accuracy of environment management decision can be improved, meanwhile, the environment adaptability and flexibility can be enhanced, the management and operation processes can be improved in some scenes, the management cost is reduced, and the working efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of environmental protection and resource management, and particularly to an environmental management method, apparatus, electronic device, and storage medium. Background Art

[0002] With the increasing severity of global climate change and ecological environment problems, environmental rights and interests assets (such as carbon emission rights, water resource use rights, etc.) have received extensive attention as a new type of asset category. However, the traditional management methods of environmental rights and interests assets lack the ability to perform real-time analysis on complex multi-dimensional data, making it difficult to provide comprehensive and accurate support for decision-makers, which restricts their application efficiency and sustainable development.

[0003] In current technologies, artificial intelligence technology has shown strong advantages in data analysis, predictive modeling, and optimization decision-making, providing the possibility to solve the bottleneck problems in the management of environmental rights and interests assets. Therefore, designing an artificial intelligence-based decision support method and system for the management of environmental rights and interests assets has important theoretical value and practical significance. Summary of the Invention

[0004] The present disclosure aims to solve at least one of the technical problems in the related technologies to some extent.

[0005] To this end, one objective of the present disclosure is to propose an environmental management method.

[0006] The second objective of the present disclosure is to propose an environmental management apparatus.

[0007] The third objective of the present disclosure is to propose an electronic device.

[0008] The fourth objective of the present disclosure is to propose a non-transitory computer-readable storage medium.

[0009] The fifth objective of the present disclosure is to propose a computer program product.

[0010] To achieve the above objectives, a first aspect embodiment of the present disclosure proposes an environmental management method, including: obtaining environmental data to be predicted and an environmental adjustment strategy; inputting the environmental data into a target strategy generation model to generate multiple dynamic environmental candidate solutions; determining a target dynamic environmental adjustment solution from the multiple dynamic environmental candidate solutions based on the environmental adjustment strategy; and performing environmental management based on the target dynamic environmental adjustment solution.

[0011] According to an embodiment of the present disclosure, determining a target dynamic environment adjustment scheme from multiple dynamic environment candidate schemes based on the environment adjustment strategy includes: determining an adjustment target based on the environment adjustment strategy; scoring the multiple dynamic environment candidate schemes based on the adjustment target to obtain the respective scores of each dynamic environment candidate scheme; and taking the dynamic environment candidate scheme with the highest score as the target dynamic environment adjustment scheme.

[0012] According to an embodiment of the present disclosure, the adjustment target includes at least one adjustment sub-target, and scoring the multiple dynamic environment candidate schemes based on the adjustment target to obtain the respective scores of each dynamic environment candidate scheme includes: for any dynamic environment candidate scheme, calculating the respective sub-target scores of the dynamic environment candidate scheme based on each adjustment sub-target; and calculating the respective scores of each dynamic environment candidate scheme based on the sub-target scores and the weights of the adjustment sub-targets.

[0013] According to an embodiment of the present disclosure, determining a target dynamic environment adjustment scheme from multiple dynamic environment candidate schemes based on the environment adjustment strategy includes: selecting n dynamic environment screening schemes from the multiple dynamic environment candidate schemes based on the environment adjustment strategy, where n is a positive integer; and fusing the dynamic environment screening schemes according to a preset fusion strategy to generate the target dynamic environment adjustment scheme.

[0014] According to an embodiment of the present disclosure, selecting n dynamic environment screening schemes from the multiple dynamic environment candidate schemes based on the environment adjustment strategy includes: scoring the multiple dynamic environment candidate schemes based on the environment adjustment strategy to obtain the respective scores of each dynamic environment candidate scheme; sorting the dynamic environment candidate schemes according to the scores, and selecting the top n dynamic environment candidate schemes as the dynamic environment screening schemes.

[0015] According to an embodiment of the present disclosure, generating the target policy generation model includes: obtaining historical environment processing data; generating training samples based on the historical environment processing data; inputting the training samples into an initial policy generation model to output a prediction result; and training the initial policy generation model based on the prediction result to generate the target policy generation model.

[0016] According to an embodiment of the present disclosure, the method further includes: converting the target dynamic environment adjustment scheme into one or more of chart data, map data, and interactive data.

[0017] To achieve the above object, an embodiment of the second aspect of the present disclosure provides an environmental management device, including: an acquisition module configured to acquire environmental data to be predicted and an environmental adjustment strategy; an input module configured to input the environmental data into a target policy generation model to generate a plurality of dynamic environmental candidate solutions; a generation module configured to determine a target dynamic environmental adjustment solution from the plurality of dynamic environmental candidate solutions based on the environmental adjustment strategy; and a management module configured to perform environmental management based on the target dynamic environmental adjustment solution.

[0018] To achieve the above object, an embodiment of the third aspect of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the environmental management method as described in the embodiment of the first aspect of the present disclosure is implemented.

[0019] To achieve the above object, an embodiment of the fourth aspect of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the environmental management method as described in the embodiment of the first aspect of the present disclosure.

[0020] To achieve the above object, an embodiment of the fifth aspect of the present disclosure provides a computer program product, including a computer program, where the computer program is used to implement the environmental management method as described in the embodiment of the first aspect of the present disclosure when executed by a processor.

[0021] Thus, through this solution, the scientificity and accuracy of environmental management decisions can be improved, and at the same time, the environmental adaptability and flexibility can be enhanced. In some scenarios, the management and operation processes can also be improved, the management cost can be reduced, and the work efficiency can be increased. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a schematic diagram of an environmental management method according to an embodiment of the present disclosure;

[0023] Figure 2 is a schematic diagram of another environmental management method according to an embodiment of the present disclosure;

[0024] Figure 3 is a schematic diagram of another environmental management method according to an embodiment of the present disclosure;

[0025] Figure 4 is a schematic diagram of an environmental management device according to an embodiment of the present disclosure;

[0026] Figure 5 is a schematic diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] Embodiments of the present disclosure will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where like or similar reference numerals denote like or similar elements or elements having like or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present disclosure, and should not be construed as a limitation of the present disclosure.

[0028] In the technical solution of the present disclosure, the acquisition, storage, use, processing, etc. of data all comply with the relevant regulations of relevant laws and regulations.

[0029] It should be noted that in the embodiments of the present application, some industry-existing solutions such as certain software, components, models, etc. may be mentioned. They should be considered exemplary. The purpose is only to illustrate the feasibility in the implementation of the technical solution of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0030] Figure 1 is a schematic diagram of an environmental management method according to an embodiment of the present disclosure. As Figure 1 shown, the environmental management method includes the following steps:

[0031] S101, acquiring environmental data to be predicted and an environmental adjustment strategy.

[0032] The environmental management method of the embodiments of the present application can be applied to the formulation of environmental adjustment strategies in resource management scenarios such as carbon emission right management scenarios and water resource use right management scenarios. The execution subject of the environmental management of the embodiments of the present application can be the environmental management device of the embodiments of the present application, and this environmental management device can be set on an electronic device.

[0033] In the embodiments of the present disclosure, the environmental data to be predicted can collect data related to environmental rights and interests through a sensor network, an online database, manual entry, etc., including but not limited to carbon emissions, water resource utilization rates, market transaction data, etc.; clean, normalize, and extract features from the collected data to form a high-quality data set.

[0034] It should be noted that the environmental adjustment strategy is designed in advance, and can be a historical environmental adjustment strategy or an artificially designed environmental adjustment strategy, and no limitation is made here.

[0035] S102, inputting the environmental data into a target strategy generation model to generate a plurality of dynamic environmental candidate solutions.

[0036] It should be noted that the target strategy generation model in the embodiments of the present disclosure is a model for generating candidate solutions based on environmental data. This target strategy generation model is pre-trained and can be stored in the storage space of an electronic device for convenient retrieval and use when needed.

[0037] In the embodiments of the present disclosure, the target policy generation model does not generate only a single environmental dynamic adjustment plan, but can generate multiple dynamic environment candidate plans for providing to decision-makers for selection or further processing.

[0038] S103. Determine a target dynamic environment adjustment plan from multiple dynamic environment candidate plans based on an environment adjustment policy.

[0039] It should be noted that the environment adjustment policy is an adjustment rule designed in advance, and the environment adjustment policy may include an adjustment direction.

[0040] In the embodiments of the present disclosure, there are various methods for determining a target dynamic environment adjustment plan from multiple dynamic environment candidate plans based on an environment adjustment policy, and no specific limitation is made here.

[0041] In a possible implementation manner, a preset plan determination algorithm can be used to calculate multiple dynamic environment candidate plans to determine an optimal target dynamic environment adjustment plan.

[0042] In another possible implementation manner, multiple dynamic environment candidate plans can also be input into a plan determination model to generate a target dynamic environment adjustment plan. The plan determination model is pre-trained and can be stored in the storage space of an electronic device for convenient retrieval and use when needed.

[0043] S104. Perform environment management based on the target dynamic environment adjustment plan.

[0044] In a possible implementation example, taking carbon emission right management as an example, carbon emission data of industrial enterprises can be collected, including historical emissions, industry benchmark values, and market transaction prices. Then, a deep learning model is used to predict future emission trends and evaluate the market value of carbon assets. Then, based on the prediction results, a reinforcement learning model is applied to formulate a trading strategy for the enterprise's carbon emission rights. Finally, an optimization plan is provided, such as purchasing additional emission rights or investing in emission reduction technologies.

[0045] In another possible implementation example, taking water resource use right management as an example, regional water consumption, precipitation, and water resource allocation data can be collected first. Then, a time series analysis model is applied to predict future water resource supply and demand changes. Then, a water use optimization plan is provided, such as adjusting water intake quotas or optimizing irrigation patterns.

[0046] In an embodiment of the present disclosure, first, environmental data to be predicted and an environmental adjustment strategy are obtained. Then, the environmental data is input into a target policy generation model to generate multiple dynamic environmental candidate solutions. Subsequently, based on the environmental adjustment strategy, a target dynamic environmental adjustment solution is determined from the multiple dynamic environmental candidate solutions. Finally, environmental management is carried out based on the target dynamic environmental adjustment solution. In this way, through this solution, the scientificity and accuracy of environmental management decisions can be improved, the environmental adaptability and flexibility can be enhanced, and in some scenarios, the management and operation processes can also be improved, the management costs can be reduced, and the work efficiency can be increased.

[0047] In an embodiment of the present disclosure, to generate a target policy generation model, first, historical environmental processing data is obtained. Then, training samples are generated based on the historical environmental processing data. Subsequently, the training samples are input into an initial policy generation model to output a prediction result. Finally, the initial policy generation model is trained based on the prediction result to generate a target policy generation model.

[0048] It should be noted that the training samples generated based on the historical environmental processing data include original labels. When training the initial policy generation model based on the prediction result, the loss value can be calculated based on the prediction result and the original labels, and the model parameters of the initial policy generation model can be adjusted based on the loss value until the training end condition is reached to generate a target policy generation model.

[0049] It should be noted that the training end condition can be that the loss value reaches a preset range, or the number of training times reaches a preset number of training times, or the training time reaches a preset training time, etc.

[0050] In the above embodiment, to determine a target dynamic environmental adjustment solution from multiple dynamic environmental candidate solutions based on the environmental adjustment strategy, it can also be through Figure 2 For further explanation, the method includes:

[0051] S201, determining an adjustment target based on the environmental adjustment strategy.

[0052] In an embodiment of the present disclosure, the environmental adjustment strategy may include multiple adjustment targets or may include one adjustment target, and no limitation is made here. For example, the environmental adjustment strategy may include one or more adjustment targets such as low cost, good treatment effect, and short treatment cycle.

[0053] S202, scoring the multiple dynamic environmental candidate solutions based on the adjustment target to obtain the respective scores of each dynamic environmental candidate solution.

[0054] In an embodiment of the present disclosure, for any candidate dynamic environment solution, the respective sub-goal scores of the candidate dynamic environment solution based on each adjustment sub-goal can be calculated, and then based on the sub-goal scores and the weights of the respective adjustment sub-goals, the respective scores of each candidate dynamic environment solution can be calculated.

[0055] It should be noted that the weights of the sub-goals are pre-designed and can be changed according to actual design requirements, and no specific limitations are imposed here.

[0056] There can be various methods for calculating the respective sub-goal scores of the candidate dynamic environment solution based on each adjustment sub-goal, and no specific limitations are imposed here. In one possible implementation, the calculation can be performed through a preset scoring algorithm to calculate the respective scores of each candidate dynamic environment solution. The scoring algorithm can be a natural language algorithm or a scoring algorithm in related technologies, etc.

[0057] S203. Select the candidate dynamic environment solution with the highest score as the target dynamic environment adjustment solution.

[0058] In an embodiment of the present disclosure, first, the adjustment goals are determined based on the environment adjustment strategy, then multiple candidate dynamic environment solutions are scored based on the adjustment goals to obtain the respective scores of each candidate dynamic environment solution, and finally, the candidate dynamic environment solution with the highest score is selected as the target dynamic environment adjustment solution. By scoring multiple candidate dynamic environment solutions, the optimal solution with the highest score can be selected as the target dynamic environment adjustment solution.

[0059] In the above embodiment, to determine the target dynamic environment adjustment solution from multiple candidate dynamic environment solutions based on the environment adjustment strategy, it can also be achieved through Figure 3 For further explanation, the method includes:

[0060] S301. Select n candidate dynamic environment screening solutions from multiple candidate dynamic environment solutions, where n is a positive integer.

[0061] In an embodiment of the present disclosure, there can be various methods for selecting n candidate dynamic environment screening solutions from multiple candidate dynamic environment solutions, and no specific limitations are imposed here.

[0062] In one possible implementation, multiple candidate dynamic environment solutions can be scored first based on the environment adjustment strategy to obtain the respective scores of each candidate dynamic environment solution, and then the candidate dynamic environment solutions are sorted according to the scores, and the top n candidate dynamic environment solutions are selected as the candidate dynamic environment screening solutions.

[0063] It should be noted that the scoring of multiple candidate dynamic environment solutions based on the environment adjustment strategy can refer to the content in the above embodiment and will not be elaborated here.

[0064] In S302, the dynamic environment screening solutions are integrated according to a preset integration strategy to generate a target dynamic environment adjustment solution.

[0065] In the embodiments of the present disclosure, there can be multiple preset integration strategies, which are not limited here. For example, it can include selecting the common part from multiple dynamic environment screening solutions as the basic strategy, and then integrating the other different parts according to a preset integration algorithm as the individual strategy, and combining the basic strategy and the individual strategy to generate a target dynamic environment adjustment solution.

[0066] In a possible implementation manner, first, based on the environment adjustment strategy, n dynamic environment screening solutions are selected from multiple dynamic environment candidate solutions, where n is a positive integer. Then, the dynamic environment screening solutions are integrated according to a preset integration strategy to generate a target dynamic environment adjustment solution. In this way, multiple dynamic environment candidate solutions are screened through the environment adjustment strategy, and the screened solutions are integrated, which can improve the comprehensive performance of the solution.

[0067] In a possible implementation manner, the target dynamic environment adjustment solution can also be converted into one or more of chart data, map data, and interaction data. Then, the chart data, map data, and interaction data are displayed through a display device. There can be multiple types of such display devices. For example, it can include a display screen, a microphone, a three-dimensional imaging device, etc.

[0068] Corresponding to the environment management methods provided in the above several embodiments, an embodiment of the present disclosure also provides an environment management device. Since the environment management device provided in the embodiments of the present disclosure corresponds to the environment management methods provided in the above several embodiments, the implementation manners of the above environment management methods are also applicable to the environment management device provided in the embodiments of the present disclosure and will not be described in detail in the following embodiments.

[0069] Figure 4 is a schematic diagram of an environment management device according to an embodiment of the present disclosure. As Figure 4 shown, the environment management device 400 includes: an acquisition module 410, an input module 420, a generation module 430, and a management module 440.

[0070] Among them, the acquisition module 410 is used to acquire environment data to be predicted and an environment adjustment strategy.

[0071] The input module 420 is used to input the environment data into a target strategy generation model to generate multiple dynamic environment candidate solutions.

[0072] The generation module 430 is used to determine a target dynamic environment adjustment solution from multiple dynamic environment candidate solutions based on the environment adjustment strategy.

[0073] A management module 440 for performing environment management based on the target dynamic environment adjustment plan.

[0074] According to an embodiment of the present disclosure, determining a target dynamic environment adjustment plan from multiple dynamic environment candidate plans based on an environment adjustment strategy includes: determining an adjustment target based on the environment adjustment strategy; scoring the multiple dynamic environment candidate plans based on the adjustment target to obtain the respective scores of each dynamic environment candidate plan; and taking the dynamic environment candidate plan with the highest score as the target dynamic environment adjustment plan.

[0075] According to an embodiment of the present disclosure, the adjustment target includes at least one adjustment sub-target. Scoring the multiple dynamic environment candidate plans based on the adjustment target to obtain the respective scores of each dynamic environment candidate plan includes: for any dynamic environment candidate plan, calculating the respective sub-target scores of the dynamic environment candidate plan based on each adjustment sub-target; and calculating the respective scores of each dynamic environment candidate plan based on the sub-target scores and the weights of the adjustment sub-targets.

[0076] According to an embodiment of the present disclosure, determining a target dynamic environment adjustment plan from multiple dynamic environment candidate plans based on an environment adjustment strategy includes: selecting n dynamic environment screening plans from the multiple dynamic environment candidate plans based on the environment adjustment strategy, where n is a positive integer; and fusing the dynamic environment screening plans according to a preset fusion strategy to generate a target dynamic environment adjustment plan.

[0077] According to an embodiment of the present disclosure, selecting n dynamic environment screening plans from multiple dynamic environment candidate plans based on an environment adjustment strategy includes: scoring the multiple dynamic environment candidate plans based on the environment adjustment strategy to obtain the respective scores of each dynamic environment candidate plan; sorting the dynamic environment candidate plans according to the scores, and selecting the top n dynamic environment candidate plans as the dynamic environment screening plans.

[0078] According to an embodiment of the present disclosure, generating a target policy generation model includes: obtaining historical environment processing data; generating training samples based on the historical environment processing data; inputting the training samples into an initial policy generation model to output a prediction result; and training the initial policy generation model based on the prediction result to generate a target policy generation model.

[0079] According to an embodiment of the present disclosure, the method further includes: converting the target dynamic environment adjustment plan into one or more of chart data, map data, and interactive data.

[0080] To implement the above embodiments, the embodiments of the present disclosure also propose an electronic device 500. Figure 5FIG. 0 is a schematic diagram of an electronic device according to an embodiment of the present disclosure, as Figure 5 shown. The electronic device 500 includes: a processor 501 and a memory 502 communicatively connected to the processor. The memory 502 stores instructions executable by at least one processor. The instructions are executed by at least one processor 501 to implement the environmental management method as described in the present disclosure Figures 1 - 3 embodiment.

[0081] To implement the above embodiments, an embodiment of the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to implement the environmental management method as described in the present disclosure Figures 1 - 3 embodiment.

[0082] To implement the above embodiments, an embodiment of the present disclosure also provides a computer program product, including a computer program, which implements the environmental management method as described in the present disclosure when executed by a processor Figures 1 - 3 embodiment.

[0083] It should be noted that personal information from users should be collected for legal and reasonable purposes and not shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after obtaining the informed consent of the user, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization including authorizing the relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others with access to the personal information data comply with their privacy policies and procedures.

[0084] This application anticipates providing embodiments where users can selectively block the use or access of personal information data. That is, the present disclosure anticipates providing hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, the risk can be minimized by restricting data collection and deleting the data. In addition, when applicable, personal identifiers are removed from such personal information to protect the privacy of the user.

[0085] In the foregoing descriptions of the embodiments, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without conflict, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0086] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "a plurality of" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0087] Any process or method description represented in a flowchart or described otherwise herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of the present application includes additional implementations, where functions may be executed in a substantially simultaneous manner or in an order opposite to that shown or discussed, according to the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0088] Logic and / or steps represented in a flowchart or described otherwise herein, for example, can be considered as a sequenced list of executable instructions for implementing a logical function, and can be embodied specifically in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" can be any device that contains, stores, communicates, propagates, or transports a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable medium on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0089] It should be understood that each part of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0090] Those of ordinary skill in the art can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0091] In addition, in each embodiment of the present application, each functional unit can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0092] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. An environmental management method, characterized in that: include: Obtain environmental data to be predicted and environmental adjustment strategies; Inputting the environmental data into a target strategy generation model to generate a plurality of dynamic environmental candidate solutions; Determining a target dynamic environment adjustment solution from a plurality of dynamic environment candidate solutions based on the environment adjustment strategy; Perform environmental management based on the target dynamic environmental adjustment plan.

2. The method according to claim 1, characterized in that The step of determining a target dynamic environment adjustment solution from a plurality of dynamic environment candidate solutions based on the environment adjustment strategy includes: Determining an adjustment target based on the environmental adjustment strategy; Scoring the plurality of dynamic environment candidate solutions based on the adjustment target to obtain a score for each of the dynamic environment candidate solutions; The dynamic environment candidate solution with the highest score is used as the target dynamic environment adjustment solution.

3. The method according to claim 2, characterized in that The adjustment target includes at least one adjustment sub-target, and scoring the plurality of dynamic environment candidate solutions based on the adjustment target to obtain a score for each of the dynamic environment candidate solutions includes: For any dynamic environment candidate solution, calculating the respective sub-goal score of the dynamic environment candidate solution based on each adjustment sub-goal; Based on the sub-goal scores and the weights of the adjusted sub-goals, the scores of each of the dynamic environment candidate solutions are calculated.

4. The method according to claim 1, characterized in that The step of determining a target dynamic environment adjustment solution from a plurality of dynamic environment candidate solutions based on the environment adjustment strategy includes: Selecting n dynamic environment screening solutions from the plurality of dynamic environment candidate solutions based on the environment adjustment strategy, where n is a positive integer; The dynamic environment screening scheme is fused according to a preset fusion strategy to generate the target dynamic environment adjustment scheme.

5. The method according to claim 4, characterized in that The selecting n dynamic environment screening solutions from the plurality of dynamic environment candidate solutions based on the environment adjustment strategy includes: Scoring the plurality of dynamic environment candidate solutions based on the environment adjustment strategy to obtain a score for each of the dynamic environment candidate solutions; The dynamic environment candidate solutions are sorted according to the scores, and the first n dynamic environment candidate solutions are selected as the dynamic environment screening solutions.

6. The method according to any one of claims 1 to 5, characterized in that Generating the target strategy generation model includes: Obtain historical environmental processing data; Generate training samples based on the historical environment processing data; Inputting the training samples into an initial strategy generation model to output a prediction result; The initial strategy generation model is trained based on the prediction result to generate the target strategy generation model.

7. The method according to any one of claims 1 to 5, characterized in that The method further comprises: The target dynamic environment adjustment scheme is converted into one or more of chart data, map data, and interactive data.

8. An environmental management device, characterized in that: include: An acquisition module is used to acquire environmental data to be predicted and environmental adjustment strategies; An input module, used for inputting the environmental data into a target strategy generation model to generate a plurality of dynamic environmental candidate solutions; A generating module, configured to determine a target dynamic environment adjustment scheme from a plurality of dynamic environment candidate schemes based on the environment adjustment strategy; A management module is used to perform environment management based on the target dynamic environment adjustment solution.

9. An electronic device, characterized in that: Including memory and processor; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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