CN116542124B - Auxiliary modeling method for distributed hydrologic model - Google Patents
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Abstract
The application relates to an auxiliary modeling method of a distributed hydrological model, which utilizes ontology technology to formally express case knowledge of the existing distributed hydrological model to obtain an ontology file storing the formalized case knowledge; determining a distributed hydrological model case matched with the research area information in the ontology file based on a case-based reasoning algorithm according to the research area information to be modeled, and obtaining modeling data corresponding to the distributed hydrological model case; and obtaining auxiliary modeling data of the distributed hydrological model of the research area according to the modeling data. The method disclosed by the application realizes that the research area to be modeled is matched with the most similar historical case based on the case reasoning method, so that modeling data of the case can be provided for assisting modeling, and the accuracy and the high efficiency of the modeling of the distributed hydrologic model are greatly improved.
Description
Technical Field
The application relates to the application field of distributed hydrologic models, in particular to an auxiliary modeling method of a distributed hydrologic model.
Background
In the simulation and application of the distributed hydrologic model, a modeler needs to understand the principle, structure and operation method of the hydrologic model, grasp hydrologic field knowledge, and familiarize with the geographical environment characteristics of a research area to understand the source, processing method and flow of model input data. For this reason, modelers, especially non-hydrologic model expert users, often need to expend a great deal of time and effort to learn and build up experience.
Disclosure of Invention
Based on the above, the purpose of the application is to provide an auxiliary modeling method of a distributed hydrological model, which is based on a case-based reasoning method to match the most similar historical cases to a research area to be modeled, so that modeling data of the cases can be provided to assist a user in modeling, and the accuracy and the high efficiency of the modeling of the distributed hydrological model are greatly improved.
The embodiment of the application discloses an auxiliary modeling method of a distributed hydrological model, which comprises the following steps:
acquiring a plurality of distributed hydrological model cases, wherein the distributed hydrological model cases comprise case problems and solutions;
determining key concepts, inter-concept relationships, concept key attributes and constraint conditions of the distributed hydrological model case; wherein the inter-concept relationship comprises at least one of: structural, spatial and semantic relationships; wherein the structural relationships are used to describe associations between cases, case questions, and solutions, and the spatial relationships are used to describe associations between case study areas;
constructing a distributed hydrological model case ontology by using an ontology representation language and an ontology construction tool according to the key concepts, the inter-concept relations, the concept key attributes and the constraint conditions;
extracting corresponding specific description information from the distributed hydrologic model case according to the distributed hydrologic model case body;
converting specific description information of each distributed hydrological model case into instance objects of corresponding concept classes or attributes of the instance objects in the distributed hydrological model case body one by one through an ontology construction tool, and establishing relations among the instance objects, wherein the relations comprise the structural relations, the spatial relations and the semantic relations, so as to generate an ontology file;
acquiring research area information to be modeled, acquiring the ontology file, determining a distributed hydrological model case matched with the research area information in the ontology file based on a case reasoning algorithm according to the research area information and the ontology file, and acquiring modeling data corresponding to the distributed hydrological model case;
and obtaining auxiliary modeling data of the distributed hydrological model of the research area according to the modeling data.
In one embodiment, the step of determining key concepts, inter-concept relationships, concept key attributes, and constraints of the distributed hydrological model case comprises:
determining key concepts, inter-concept relationships, concept key attributes and constraint conditions of the distributed hydrological model case according to the case problem and the solution; wherein the case questions include model application objectives, simulation objectives, and study area characteristics; the solution includes input data features.
In one embodiment, the study area characteristics include study area name, area, elevation range, annual average temperature, and annual average precipitation; the input data characteristics include data name, data topic, data source, spatial resolution, and density of the rain gauge station.
In one embodiment, the structural relationship comprises a partial to global relationship; the spatial relationship includes proximity, phase, coincidence, and crossover relationships; the semantic relationships include parent-child relationships, relationships between classes and instances of classes.
In one embodiment, the ontology representation language employs Web Ontology Language and the ontology construction tool employs Prot g.
In one embodiment, in the step of constructing the distributed hydrologic model case ontology by using the ontology representation language and the ontology construction tool, the key concepts are represented as classes, the concept key attributes are represented as data attributes, and the inter-concept relationships are represented as object attributes.
In one embodiment, the step of obtaining the research area information to be modeled and obtaining the ontology file, determining a distributed hydrological model case matched with the research area information in the ontology file based on a case-based reasoning algorithm according to the research area information and the ontology file, and obtaining modeling data corresponding to the distributed hydrological model case includes:
and acquiring research area information and model type information to be modeled, acquiring the ontology file, determining a distributed hydrological model case matched with the research area information and the model type information in the ontology file based on a case reasoning algorithm according to the research area information, the model type information and the ontology file, and acquiring modeling data corresponding to the distributed hydrological model case.
In one embodiment, the step of obtaining auxiliary modeling data of the distributed hydrological model of the investigation region from the modeling data further comprises: and displaying the auxiliary modeling data on a computer operation interface.
The embodiment of the application also discloses a computer readable storage medium, on which a computer program is stored, and when the computer program runs, the device where the computer readable storage medium is controlled to execute the method according to any one of the above embodiments.
The embodiment of the application also discloses a computer device, comprising a processor and a memory, wherein the memory comprises a computer program, and the computer program realizes the method according to any one of the above embodiments when being executed by the processor.
The auxiliary modeling method of the distributed hydrologic model obtains a plurality of distributed hydrologic model cases, wherein the distributed hydrologic model cases comprise case problems and solutions; determining key concepts, inter-concept relationships, concept key attributes and constraint conditions of the distributed hydrological model cases according to the plurality of distributed hydrological model cases; wherein the inter-concept relationship comprises at least one of: structural, spatial and semantic relationships; wherein the structural relationships are used to describe associations between cases, case questions, and solutions, and the spatial relationships are used to describe associations between case study areas; constructing a distributed hydrological model case ontology by using an ontology representation language and an ontology construction tool according to the key concepts, the inter-concept relations, the concept key attributes and the constraint conditions; according to the distributed hydrological model case body, extracting corresponding specific description information from each distributed hydrological model case respectively; converting the specific description information of each distributed hydrological model case into example objects of corresponding concept classes or attributes of the example objects in the distributed hydrological model case body one by one through an ontology construction tool, establishing relations among the example objects, including the structural relation, the spatial relation and the semantic relation, and generating an ontology file after conversion is completed; acquiring research area information to be modeled, acquiring the ontology file, determining a distributed hydrological model case matched with the research area information in the ontology file based on a case reasoning algorithm according to the research area information and the ontology file, and acquiring modeling data corresponding to the distributed hydrological model case; and obtaining auxiliary modeling data of the distributed hydrological model of the research area according to the modeling data. According to the method, the existing distributed hydrological model cases are structured and semantically expressed through the ontology technology, so that the ontology file of the existing cases is obtained, and the most similar existing cases are matched with the research area to be modeled based on the case reasoning method, so that modeling data of the existing cases can be provided to assist a user in modeling, and the accuracy and the high efficiency of the distributed hydrological model modeling are greatly improved.
For a better understanding and implementation, the present application is described in detail below with reference to the drawings.
Drawings
FIG. 1 is a schematic flow chart of an auxiliary modeling method of a distributed hydrological model according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
Referring to fig. 1, an embodiment of the application discloses an auxiliary modeling method of a distributed hydrological model, which includes the following steps:
s101: acquiring a plurality of distributed hydrological model cases, wherein the distributed hydrological model cases comprise case problems and solutions;
s102: determining key concepts, inter-concept relationships, concept key attributes and constraint conditions of the distributed hydrological model case; wherein the inter-concept relationship comprises at least one of: structural, spatial and semantic relationships; wherein the structural relationships are used to describe associations between cases, case questions, and solutions, and the spatial relationships are used to describe associations between case study areas;
s103: constructing a distributed hydrological model case ontology by using an ontology representation language and an ontology construction tool according to the key concepts, the inter-concept relations, the concept key attributes and the constraint conditions;
s104: extracting corresponding specific description information from the distributed hydrologic model case according to the distributed hydrologic model case body;
s105: converting specific description information of each distributed hydrological model case into instance objects of corresponding concept classes or attributes of the instance objects in the distributed hydrological model case body one by one through an ontology construction tool, and establishing relations among the instance objects, wherein the relations comprise the structural relations, the spatial relations and the semantic relations, so as to generate an ontology file;
s106: acquiring research area information to be modeled, acquiring the ontology file, determining a distributed hydrological model case matched with the research area information in the ontology file based on a case reasoning algorithm according to the research area information and the ontology file, and acquiring modeling data corresponding to the distributed hydrological model case;
s107: and obtaining auxiliary modeling data of the distributed hydrological model of the research area according to the modeling data.
The auxiliary modeling method of the distributed hydrologic model obtains a plurality of distributed hydrologic model cases, wherein the distributed hydrologic model cases comprise case problems and solutions; determining key concepts, inter-concept relationships, concept key attributes and constraint conditions of the distributed hydrologic model cases according to the contents of the distributed hydrologic model cases; wherein the inter-concept relationship comprises at least one of: structural, spatial and semantic relationships; wherein the structural relationships are used to describe associations between cases, case questions, and solutions, and the spatial relationships are used to describe associations between case study areas; constructing a distributed hydrological model case ontology by using an ontology representation language and an ontology construction tool according to the key concepts, the inter-concept relations, the concept key attributes and the constraint conditions; according to the distributed hydrological model case body, extracting corresponding specific description information from each distributed hydrological model case respectively; converting the specific description information of each distributed hydrological model case into example objects of corresponding concept classes or attributes of the example objects in the distributed hydrological model case body one by one through an ontology construction tool, establishing relations among the example objects, including the structural relation, the spatial relation and the semantic relation, and generating an ontology file after conversion is completed; acquiring research area information to be modeled, acquiring the ontology file, determining a distributed hydrological model case matched with the research area information in the ontology file based on a case reasoning algorithm according to the research area information and the ontology file, and acquiring modeling data corresponding to the distributed hydrological model case; and obtaining auxiliary modeling data of the distributed hydrological model of the research area according to the modeling data. According to the method, the existing distributed hydrological model cases are structured and semantically expressed through the ontology technology, so that the ontology file of the existing cases is obtained, and the most similar existing cases are matched with the research area to be modeled based on the case reasoning method, so that modeling data of the existing cases can be provided to assist a user in modeling, and the accuracy and the high efficiency of the distributed hydrological model modeling are greatly improved.
The auxiliary modeling method for the distributed hydrologic model in the embodiment of the application takes a computer as an execution main body.
For step S101, one or a class of distributed hydrologic models, such as a SWAT hydrologic model or a SWAT hydrologic model modified version, is selected according to the study or application needs, and a number of distributed hydrologic model cases are acquired corresponding to the selected distributed hydrologic model, wherein the distributed hydrologic model cases include case problems and solutions.
The distributed hydrologic model case refers to an application or research case of the distributed hydrologic model, wherein the application or simulation application of the distributed hydrologic model in a research area is recorded, and generally, the distributed hydrologic model case at least comprises two parts of contents of a case problem and a solution.
The step may be to obtain the plurality of distributed hydrologic model cases from academic papers recorded with the distributed hydrologic model cases or related professional website data in a computer, and specifically, the distributed hydrologic model cases may be crawled to related websites through a crawler program in the computer.
The step may also be to directly obtain the plurality of distributed hydrological model cases from a database storing the distributed hydrological model cases in a computer.
For step S102, determining key concepts, inter-concept relationships, key concept attributes, and constraint conditions of the distributed hydrological model case; wherein the inter-concept relationship comprises at least one of: structural, spatial and semantic relationships; wherein the structural relationships are used to describe associations between cases, case questions, and solutions, and the spatial relationships are used to describe associations between case study areas;
this step may be performed under the direction of a domain expert, who has a rich theoretical knowledge and application experience of the hydrologic model domain, especially for the selected distributed hydrologic model domain, which may determine key concepts, inter-concept relationships, key concept attributes and constraints of the distributed hydrologic model case by analyzing, summarizing and abstracting the distributed hydrologic model case.
The step may also be to analyze, summarize and abstract the plurality of distributed hydrologic model cases in a computer by using an artificial intelligence algorithm or by using a special model obtained by training, so as to obtain key concepts, inter-concept relationships, key concept attributes and constraint conditions of the distributed hydrologic model cases.
The key concepts are key concepts in the distributed hydrologic model case, and specifically, whether the key concepts are key concepts can be determined according to the characteristics of the distributed hydrologic model case and modeling requirements. In the case of a distributed hydrological model, for example, it is generally referred to describing characteristics of a study area including study area name, spatial location, and describing or embodying input data characteristics of the model, such as data sources, then the determined key concepts may include "study area characteristics", "spatial location", "study area name", "input data characteristics", and so on.
Specifically, each key concept has attributes, and the same concept may have various attributes, for example, the "study area feature" concept may have attributes such as "area", "spatial range coordinates", and the like. In this embodiment, key attributes of the concept are mainly determined, and attributes that are not key to the concept may be omitted, and specifically, whether the key attributes are determined according to characteristics of the distributed hydrological model case and modeling requirements may be determined. Meanwhile, different key concepts have certain relations including semantic relations, other relations and the like, such as part-to-whole relations, attribute-to-host relations and the like.
The inter-concept relationships express relationships between different concepts, such as the semantic relationships, which may also be custom relationships. In this embodiment, the inter-concept relationship includes at least one of: structural relationships, spatial relationships, and semantic relationships.
Wherein the structural relationships are used to describe associations between cases, case questions, and solutions, and the spatial relationships are used to describe associations between case study areas.
In particular, the structural relationship describes a relationship of a concept to a content structure of a case of a distributed hydrological model, for example, the concept of "study area characteristics" is associated with a case problem of the distributed hydrological model, and the concept of "input data characteristics" is associated with a solution of the distributed hydrological model, and further, the concept of "input data characteristics" can be associated with the case of the distributed hydrological model through the case problem or the solution. In one embodiment, the structural relationship includes a partial to an overall relationship.
The spatial relationship describes the spatial positional relationship of the study areas of the distributed hydrological model case, e.g., one study area is next to another study area, the corresponding spatial relationship is "contiguous". The spatial relationships in this embodiment include adjacent, contiguous, coincident, and intersecting relationships.
The semantic relationship refers to a relationship of concepts in semantics, such as a context, a synonymous relationship, an antisense relationship, and the like. In particular, in this embodiment, the semantic relationship is defined according to an ontology representation language and an ontology construction tool, including parent-child relationships, relationships between classes and instances of classes.
The constraint condition may be a constraint on a relationship between concepts or a constraint on a concept attribute. For example, a case must have a case question, and a "study area" must have the attribute of "study area name".
In this embodiment, determining key concepts, inter-concept relationships, concept key attributes, and constraint conditions of the distributed hydrological model case according to the case problem and the solution; wherein the case questions include model application objectives, simulation objectives, and study area characteristics; the solution includes input data features.
The model application purpose expresses the hydrologic problem to be solved in the distributed hydrologic model case or the purpose of developing the model application, for example, the model application purpose is to perform hydrologic response simulation of water quality simulation or land utilization change.
The simulation targets express specific simulation contents in the case of the distributed hydrological model, such as runoff, sediment and pollutants.
The study area characteristics mainly refer to information of the study area related to distributed hydrological model modeling, such as spatial position of the study area, topography conditions, other environmental conditions and the like, and can also include names of the study area.
In one embodiment, the study area characteristics include study area name, area, elevation range, annual average temperature, and annual average precipitation; the input data characteristics include data name, data topic, data source, spatial resolution, and density of the rain gauge station. The data theme expresses the content of the data, for example, the data content is DEM, soil, or land utilization.
Referring to table 1, an example of a concept ontology obtained by analyzing, summarizing and abstracting a distributed hydrological model case is given. From which the individual key concepts of the case and the relationships between them can be seen.
TABLE 1
For step S103, according to the key concepts, the relationships between concepts, the key attributes of the concepts and the constraint conditions, the ontology expression language and the ontology construction tool are utilized to construct the ontology of the distributed hydrologic model case, so that the ontology of the distributed hydrologic model case includes the concepts and the relationships between concepts of the distributed hydrologic model case.
Wherein the ontology representation language may employ Web Ontology Language (OWL), XML or RDF, and the ontology construction tool may employ Prot g e, ontoEdit, webOnto or Ontolingua. Preferably, in this embodiment, the ontology representation language is Web Ontology Language and the ontology construction tool is Prot g.
Specifically, the key concepts may be represented as classes (classes), the key concept attributes are represented as data attributes (data properties), and the inter-concept relationships are represented as object attributes (object properties) in the ontology construction tool, so as to be converted into a machine-readable form, and obtain the distributed hydrological model case ontology. In one example, according to the key concepts, the relationships between concepts, the key attributes of the concepts and the constraint conditions, the key concepts such as "case problem", "study area name", etc. are filled into classes (class) of the ontology construction tool, the concept attributes are filled into data attributes (data properties) of the corresponding classes (class), the relationships between concepts are filled into object attributes (object properties), and after filling, the exported file is in machine-readable form, so that the construction of the distributed hydrological model case ontology is completed.
Wherein the machine-readable form refers to an expression form converted by an ontology construction tool into a form capable of being understood, analyzed, inferred and shared by a machine.
For step S104, according to the distributed hydrologic model case body, corresponding detailed description information is extracted from the distributed hydrologic model case.
The specific description information is specific information in the distributed hydrologic model case, for example, the word "SWAT" appearing in the case is specific description information of the concept of "model" in the case.
In order to uniformly convert the existing distributed hydrologic model cases into the expression form of the distributed hydrologic model case body, the specific description information in the existing distributed hydrologic model cases needs to be extracted according to the distributed hydrologic model case body. The concrete extraction includes concrete information of instance objects (or instances) corresponding to respective concept classes and attributes of the instance objects, for example, extract the word "SWAT" from the case text, which corresponds to an instance (input) of the concept class which is "model".
The step can extract specific description information from the distributed hydrologic model case through manual judgment, specifically, an operation instruction of a user is obtained, the specific description information is extracted from the distributed hydrologic model case according to the operation instruction, and meanwhile, a mapping relation can be established between the extracted specific description information and a corresponding concept class or attribute in the distributed hydrologic model case body. Of course, the mature model can also be adopted to automatically extract specific description information from the distributed hydrologic model case according to the constructed distributed hydrologic model case body in a computer.
For step S105, the specific description information of each distributed hydrologic model case is converted into the instance object or the attribute of the instance object of the corresponding concept class in the distributed hydrologic model case body one by one through the ontology construction tool, and the relationship between the instance objects is established, and after all cases are converted, an ontology file is generated.
The specific description information of the distributed hydrologic model case and the corresponding concept class and concept attribute in the distributed hydrologic model case body are respectively established with a mapping relation, for example, a 'Zhujiang river basin' in the distributed hydrologic model case is mapped into an example object of the concept of a 'research area', and then the attribute of the example object, such as the area and the spatial range coordinates of the Zhujiang river basin, can be determined, and meanwhile, the corresponding attribute information can be filled in.
When the relationship between the instance objects is established, according to the structural relationship, the spatial relationship and the semantic relationship, which are included in the conceptual relationship determined in step S102, and the specific description information of the distributed hydrological model case extracted in step S104, it is determined which relationship is consistent with the instance objects or which relationship is simultaneously available between the instance objects, so that the relationship between the instance objects is established respectively. For example, if a polygon corresponding to the boundary of two research areas of the distributed hydrologic model case shares one side, namely an adjacent area without coincidence, then the spatial relationship is established as 'connection'; as another example, if there is a case object a, a case problem object AP, then the relationship between a and AP is established as follows: a "case question" AP, wherein the relationship "case question" may be determined at step S102.
In one embodiment, the step of generating the ontology file is followed by: and importing the generated ontology file into a graph database for storage. The map data can be stored in a map database to be conveniently called according to the requirement.
For step S106, obtaining the information of the research area to be modeled and obtaining the ontology file, determining a distributed hydrological model case in the ontology file, which is matched with the information of the research area, based on a case-based reasoning algorithm according to the information of the research area and the ontology file, and obtaining modeling data corresponding to the solution of the distributed hydrological model case. In particular, the ontology file may be obtained from the graph database.
According to the method, the ontology file can be searched and inferred based on a case-based reasoning algorithm according to limited information of a research area to be modeled, and the most similar distributed hydrologic model case is obtained, so that modeling data corresponding to a solution of the distributed hydrologic model case is extracted from the ontology file and can be used as modeling guidance. Specifically, when a user models a distributed hydrological model for a research area, the user can input relevant information of the research area, such as research area characteristics, so that based on a case reasoning algorithm, the most similar distributed hydrological model case is obtained from the ontology file storing a plurality of existing cases through accurate and rapid retrieval reasoning, and modeling data of the case in the ontology file is obtained. The modeling data is specific description information stored in the related concept class and attribute of the most similar distributed hydrologic model case when the ontology file is constructed, and the specific description information of the data source, the data theme, the rainfall station density and the like can be obtained by reading the related concept class and attribute of the distributed hydrologic model case, for example, reading the 'input data characteristic'.
In one embodiment, model type information to be modeled may also be obtained for matching. Specifically, research area information and model type information to be modeled are obtained, the ontology file is obtained, distributed hydrological model cases matched with the research area information and the model type information in the ontology file are determined based on a case reasoning algorithm according to the research area information, the model type information and the ontology file, and modeling data corresponding to the distributed hydrological model cases are obtained.
In this embodiment, the ontology file may store several cases, where the cases may be the same type of model, for example, all the models are the SWAT hydrologic model, or may be different types of models, for example, including other models besides the SWAT hydrologic model. Therefore, when case matching is performed based on a case reasoning algorithm, model type information to be modeled, which is input by a user, can be acquired, and the most similar historical case is determined according to the research area information and the quick retrieval reasoning of the model type information in the ontology file.
For step S107, auxiliary modeling data of the distributed hydrological model of the investigation region is obtained according to the modeling data. The auxiliary modeling data is data for assisting user modeling obtained according to the modeling data.
Specifically, the modeling data of the matched distributed hydrologic model case can be directly used as the auxiliary modeling data, the modeling data can be obtained through a case reasoning algorithm, and then reasoning is carried out by combining other related information or constraint conditions, so that the obtained data is used as the auxiliary modeling data. In this embodiment, the auxiliary modeling data may be directly model input data when the research area performs distributed hydrological model modeling.
Further, after the modeling data is obtained, the auxiliary modeling data can be displayed on a computer operation interface, so that a user can refer to the auxiliary modeling data in modeling. In addition, the auxiliary modeling data can be uploaded to the data sharing platform, so that a user can download the auxiliary modeling data file from the data sharing platform.
The application relates to the field of distributed hydrologic models, thousands of case research documents are published in the field of the distributed hydrologic models, rich case knowledge is accumulated, the case knowledge can be applied to modeling of the distributed hydrologic models, and according to the embodiment of the application, most similar distributed hydrologic model cases are matched for a research area to be modeled by a case-based reasoning (CBR) method in artificial intelligence, so that modeling data reference and guidance can be provided for a user according to modeling data of the most similar distributed hydrologic model cases.
Furthermore, considering that the existing distributed hydrologic model cases have semantic heterogeneous problems such as ambiguity and ambiguity, and lack of uniform standard vocabulary/concepts, the semantic heterogeneous problems are difficult to share and reuse by different systems, knowledge reasoning cannot be effectively supported, application of a case-based reasoning method in auxiliary modeling of the distributed hydrologic model is greatly hindered, the embodiment of the application further carries out structuring and semantic expression on the existing distributed hydrologic model cases through ontology technology, the ontology technology is often applied to building general models of various knowledge fields in the computer field, the general models of the knowledge fields comprise relations between basic terms and terms (or relations between concepts and concepts) in the knowledge fields, so that ontology files comprising a plurality of the distributed hydrologic model cases are obtained, application of a case-based reasoning method can be better supported, and the application of the case-based method can be more accurately and efficiently matched to the most similar distributed hydrologic model cases.
Referring to fig. 2, the embodiment of the present application further discloses a computer device 401, including a memory 402 and a processor 403, where the memory 402 includes a computer program 404, and the computer program 404 implements the method according to any one of the embodiments above when executed by the processor 403.
Wherein the processor 403 may comprise one or more processing cores. The processor 403 utilizes various interfaces and wiring to connect various portions within the computer device 401, performs various functions of the computer device 401 and processes data by executing or executing instructions, programs, code sets or instruction sets stored in the memory 402 and invoking data in the memory 402, alternatively the processor 403 may be implemented in at least one hardware form in digital signal processing (Digital Signal Processing, DSP), field-programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programble Logic Array, PLA). The processor 403 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the touch display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 403 and may be implemented by a single chip.
The Memory 402 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 402 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 402 may be used to store instructions, programs, code sets, or instruction sets. The memory 402 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as touch instructions, etc.), instructions for implementing the various method embodiments described above, etc.; the storage data area may store data or the like referred to in the above respective method embodiments. The memory 402 may also optionally be at least one storage device located remotely from the aforementioned processor 403.
The embodiment of the application also discloses a computer readable storage medium, on which a computer program is stored, and when the computer program is executed, the computer readable storage medium is controlled to implement the method according to any one of the above embodiments. That is, it will be understood by those skilled in the art that all or part of the steps in implementing the methods of the embodiments described above may be implemented by a program stored in a storage medium, where the program includes several instructions for causing a device (which may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps in the methods of the embodiments described herein. The computer program may comprise computer program code, which may be in source code form, object code form, executable file or in some intermediate form, etc. And the aforementioned storage medium includes: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the jurisdiction's jurisdiction and the patent practice, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to the jurisdiction and the patent practice.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the spirit of the present application, and the present application is intended to encompass such modifications and improvements.
Claims (9)
1. An auxiliary modeling method of a distributed hydrological model is characterized by comprising the following steps:
acquiring a plurality of distributed hydrological model cases, wherein the distributed hydrological model cases comprise case problems and solutions;
determining key concepts, inter-concept relationships, concept key attributes and constraint conditions of the distributed hydrological model case; wherein the inter-concept relationship comprises at least one of: structural, spatial and semantic relationships; wherein the structural relationships are used to describe associations between cases, case questions, and solutions, and the spatial relationships are used to describe associations between case study areas;
constructing a distributed hydrological model case ontology by using an ontology representation language and an ontology construction tool according to the key concepts, the inter-concept relations, the concept key attributes and the constraint conditions;
extracting corresponding specific description information from the distributed hydrologic model case according to the distributed hydrologic model case body;
converting specific description information of each distributed hydrological model case into instance objects of corresponding concept classes or attributes of the instance objects in the distributed hydrological model case body one by one through an ontology construction tool, and establishing relations among the instance objects, wherein the relations comprise the structural relations, the spatial relations and the semantic relations, so as to generate an ontology file;
acquiring research area information to be modeled, acquiring the ontology file, determining a distributed hydrological model case matched with the research area information in the ontology file based on a case reasoning algorithm according to the research area information and the ontology file, and acquiring modeling data corresponding to the distributed hydrological model case;
obtaining auxiliary modeling data of a distributed hydrological model of the research area according to the modeling data;
the step of determining key concepts, inter-concept relationships, key concept attributes and constraint conditions of the distributed hydrological model case comprises the following steps:
determining key concepts, inter-concept relationships, concept key attributes and constraint conditions of the distributed hydrological model case according to the case problem and the solution; wherein the case questions include model application objectives, simulation objectives, and study area characteristics; the solution includes input data features.
2. The method of assisted modeling of a distributed hydrological model according to claim 1, wherein the study area characteristics include study area name, area, elevation range, annual average temperature and annual average precipitation; the input data characteristics include data name, data topic, data source, spatial resolution, and density of the rain gauge station.
3. The method of assisted modeling of a distributed hydrological model according to claim 1, wherein the structural relationship comprises a partial to global relationship; the spatial relationship includes proximity, phase, coincidence, and crossover relationships; the semantic relationships include parent-child relationships, relationships between classes and instances of classes.
4. The method of claim 1, wherein the ontology representation language is Web Ontology Language and the ontology construction tool is Prot g.
5. The method of claim 4, wherein in the step of constructing the case ontology of the distributed hydrologic model by using the ontology representation language and the ontology construction tool, the key concepts are represented as classes, the concept key attributes are represented as data attributes, and the inter-concept relationships are represented as object attributes.
6. The method for assisted modeling of a distributed hydrological model as claimed in claim 1, wherein,
the step of obtaining the research area information to be modeled and obtaining the ontology file, determining a distributed hydrological model case matched with the research area information in the ontology file based on a case-based reasoning algorithm according to the research area information and the ontology file, and obtaining modeling data corresponding to the distributed hydrological model case comprises the following steps:
and acquiring research area information and model type information to be modeled, acquiring the ontology file, determining a distributed hydrological model case matched with the research area information and the model type information in the ontology file based on a case reasoning algorithm according to the research area information, the model type information and the ontology file, and acquiring modeling data corresponding to the distributed hydrological model case.
7. The method for assisted modeling of a distributed hydrological model as claimed in claim 1, wherein,
the step of obtaining auxiliary modeling data of the distributed hydrological model of the research area according to the modeling data further comprises the following steps: and displaying the auxiliary modeling data on a computer operation interface.
8. A computer readable storage medium having stored thereon a computer program, characterized in that the computer readable storage medium is controlled to perform the method according to any of claims 1-7 when said computer program is run.
9. A computer device comprising a processor and a memory, the memory comprising a computer program which, when executed by the processor, implements the method of any of claims 1-7.
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