CN110175769B - Asset value evaluation method, device and system based on micro-service architecture - Google Patents
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Abstract
The invention discloses an asset value evaluation method, device and system based on a micro-service architecture, wherein the method comprises the following steps: the client uploads the user input information and the user input information to the server; sequentially creating an evaluation main body field model and the relation thereof, and an index alternative library field model and the relation thereof; the client calls an index candidate library field model to select an index, corresponding relation information of the index and an evaluation object is uploaded to the server, and a corresponding relation field model and a corresponding relation between the index and the evaluation object are created; the server calls the model and the relation thereof to be transmitted to the client, and the client determines the weight of each evaluation index according to the model and the relation; the client uploads the scoring method to the server to create an asset evaluation index scoring model and a relationship thereof; the server side constructs an asset value evaluation model according to the evaluation index weights, the asset evaluation index scoring model and the relationship between the evaluation index weights and the asset evaluation index scoring model; and calling the asset value evaluation model of the server by the client, executing model operation and evaluating the asset value.
Description
Technical Field
The disclosure belongs to the technical field of budget management, and relates to an asset value evaluation method, device and system based on a micro-service architecture.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the continuous promotion of the innovation of the power system, the asset operation efficiency and the benefit status and the benefit are increasingly outstanding, the asset value evaluation mechanism of each area is established, the asset benefit level of each area is scientifically evaluated, the incentive and constraint action of budget management can be fully exerted, the accurate allocation of resources is promoted, and the investment return level is improved.
However, the inventor finds that the informatization practice of large internet enterprises, large central enterprises and large foreign enterprises proves that: based on the traditional centralized IT architecture and application mode, the explosive business growth cannot be dealt with. An application architecture for flexibly and agilely coping with business changes gradually becomes a trend, and a micro-service architecture system becomes an important direction for informatization transformation of large enterprises. The information planning of the thirteen five networks of China makes a general technical route of 'one platform, one system, multiple scenes and micro application', and promotes a new generation system construction mode based on a micro service architecture.
Disclosure of Invention
Aiming at the defects in the prior art, one or more embodiments of the disclosure provide an asset value evaluation method, device and system based on a micro-service architecture, an asset value evaluation model is built, the asset value evaluation online assessment and the full-process tracking analysis are realized, the asset value evaluation model is quickly and flexibly built through the system, the asset value evaluation model logic is visually checked, and the flexible foreground configuration modification model is supported according to the change of management requirements.
According to one aspect of one or more embodiments of the present disclosure, there is provided an asset value evaluation method based on a micro service architecture.
An asset value evaluation method based on a micro-service architecture comprises the following steps:
the client uploads asset evaluation subject information to the server; the server receives asset evaluation subject information to create an evaluation subject field model and a relation thereof;
the client uploads user input information to the server; the server receives user input information to create an index alternative library field model and the relation thereof;
the client calls an index selection index of the field model of the index alternative library, corresponding relation information of the index and an evaluation object is uploaded to the server, and the server receives the corresponding relation information of the index and the evaluation object to establish a corresponding relation field model of the index and the evaluation object and a relation between the index and the evaluation object;
the server side calls an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of indexes and evaluation objects and the relation thereof and transmits the models to the client side, and the client side adopts a Delphi method and an entropy weight method according to the model and determines the weight of each evaluation index according to the weighted sum of the proportion;
the client uploads the scoring method to the server, and the server receives the scoring method to create an asset evaluation index scoring model and a relationship thereof;
the server side constructs an asset value evaluation model according to the evaluation index weights, the asset evaluation index scoring model and the relationship between the evaluation index weights and the asset evaluation index scoring model;
and calling the asset value evaluation model of the server by the client, executing model operation and evaluating the asset value.
Further, in the method, the specific steps of creating the evaluation subject domain model and the relationship thereof include:
the client converts the asset evaluation subject information into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the serialized asset evaluation subject information, performs deserialization processing, creates an evaluation subject field model and a relationship thereof, and establishes a corresponding relationship between the evaluation subjects;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, when a server side initiates multiple data requests to a client side in the establishment of the evaluation subject domain model and the relationship thereof, some requests are combined into one network request.
Further, in the method, the specific steps of creating the index candidate library domain model and the relationship thereof include:
the client converts user input information into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the serialized user input information, carries out deserialization processing, creates an index alternative library field model and the relation of the model, and establishes an index alternative library; the index candidate library comprises the classification, the property, the index name, an evaluation object and a calculation formula of the index;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof include:
the client calls an index selection index of the field model of the index alternative library, converts the corresponding relation information of the index and the evaluation object into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the information of the corresponding relation between the serialized indexes and the evaluation objects, carries out deserialization processing, creates a corresponding relation field model and the relation between the indexes and the evaluation objects, establishes an index system and configures a calculation formula of the indexes;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, when the data volume transmitted from the client to the server in the corresponding relation field model of the created index and the evaluation object and the relation thereof is larger than a preset threshold value, the data to be transmitted is compressed and transmitted.
Further, in the method, the specific step of determining the weight of each evaluation index includes:
the server side calls the unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of the indexes and the evaluation objects, serialize the models into JSON and transmit the JSON to the client side;
the client is loaded to the Webexcel control, and the control calculation engine executes index weight calculation according to a preset algorithm; the pre-algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to the weighted sum of the proportion.
Further, in the method, the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
the client converts the scoring method into a view model, and uploads the view model serialization to the server through REST service call;
the server receives a serialized scoring method, performs deserialization processing and creates an asset evaluation index scoring model and a relationship thereof;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, when the client performs asset value evaluation, the models are serialized to the client to establish a data model and a metadata model of the client.
Further, in the method, the asset value evaluation model includes an asset operating efficiency level evaluation model, a capitalization budget allocation model, and a capitalization budget allocation model;
the specific steps of the client for asset value evaluation comprise:
the method comprises the steps that a client encapsulates an asset value evaluation model request into a JSON object, and calls a server REST FUL service to obtain a model definition after serialization;
and returning the client to be loaded by the Webexcel control, executing model operation, drawing the control and rendering the page, and displaying the model operation result.
According to one aspect of one or more embodiments of the present disclosure, there is provided a microservice architecture-based asset value evaluation system.
An asset value evaluation system based on a micro-service architecture is based on the asset value evaluation method based on the micro-service architecture, and the system comprises the following steps: client and server.
According to one aspect of one or more embodiments of the present disclosure, there is provided an asset value evaluation method based on a micro service architecture.
An asset value evaluation method based on a micro-service architecture is realized at a server side and comprises the following steps:
receiving asset evaluation subject information uploaded by a client to establish an evaluation subject field model and a relation thereof;
receiving a user input information creation index alternative library field model uploaded by a client and a relation thereof;
receiving corresponding relation information of indexes and evaluation objects uploaded by a client to establish a corresponding relation field model of the indexes and the evaluation objects and a relation of the corresponding relation field model;
calling an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of indexes and evaluation objects and the relation thereof, transmitting the model to a client side, and determining the weight of each evaluation index according to the weighted sum of the proportion by adopting a Delphi method and an entropy weight method;
receiving a scoring method uploaded by a client to establish an asset evaluation index scoring model and a relationship thereof;
constructing an asset value evaluation model according to the evaluation index weights, the asset evaluation index scoring model and the relationship between the evaluation index weights and the asset evaluation index scoring model; and calling the asset value evaluation model of the server by the client, executing model operation and evaluating the asset value.
Further, in the method, the specific steps of creating the evaluation subject domain model and the relationship thereof include:
receiving serialized asset evaluation subject information uploaded by a client, performing deserialization processing, creating an evaluation subject field model and a relationship thereof, and establishing a corresponding relationship between evaluation subjects;
and calling the unified storage service persistence processing evaluation subject field model and the relation thereof.
Further, in the method, when a server side initiates multiple data requests to a client side in the establishment of the evaluation subject domain model and the relationship thereof, some requests are combined into one network request.
Further, in the method, the specific steps of creating the index candidate library domain model and the relationship thereof include:
the server receives serialized user input information uploaded by the client, performs deserialization processing, creates an index alternative library field model and a relation thereof, and establishes an index alternative library; the index candidate library comprises the classification, the property, the index name, an evaluation object and a calculation formula of the index;
and calling the unified storage service persistence processing evaluation subject field model and the relation thereof.
Further, in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof include:
the server receives the corresponding relation information of the serialized indexes and the evaluation objects uploaded by the client, carries out deserialization processing, creates a corresponding relation field model of the indexes and the evaluation objects and the relation of the model, establishes an index system and configures a calculation formula of the indexes;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, the specific step of determining the weight of each evaluation index includes:
the server side calls the unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of the indexes and the evaluation objects, serialize the models into JSON and transmit the JSON to the client side; loading the client to the Webexcel control, and executing index weight calculation by the control calculation engine according to a preset algorithm; the pre-algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to the weighted sum of the proportion.
Further, in the method, the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
the server receives the serialized scoring method uploaded by the client, performs deserialization processing and creates an asset evaluation index scoring model and a relationship thereof;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
According to an aspect of one or more embodiments of the present disclosure, there is provided a computer-readable storage medium.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method of asset value assessment based on a microservice architecture.
In accordance with an aspect of one or more embodiments of the present disclosure, an electronic device is provided.
An electronic device comprising a processor and a computer-readable storage medium, the processor to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the asset value evaluation method based on the microservice architecture.
According to one aspect of one or more embodiments of the present disclosure, there is provided an asset value evaluation method based on a micro service architecture.
An asset value evaluation method based on a micro-service architecture is realized at a client, and the method comprises the following steps:
uploading user input information to a server for creating an evaluation subject domain model and a relationship thereof;
uploading user input information to a server for creating an index alternative library field model and a relation thereof;
calling an index candidate library field model to select an index, and uploading corresponding relation information of the index and an evaluation object to a server for creating a corresponding relation field model and a corresponding relation of the index and the evaluation object;
the receiving server side calls an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of the index and the evaluation object and the relation thereof, and determines the weight of each evaluation index according to the Delphi method and the entropy weight method and the proportion weighting summation;
uploading the scoring method to a server for creating an asset evaluation index scoring model and a relationship thereof;
and calling the asset value evaluation model constructed by the server according to the evaluation index weight, the asset evaluation index scoring model and the relationship of the evaluation index weight and the asset evaluation index scoring model, executing model operation and evaluating the asset value.
Further, in the method, the specific steps of creating the evaluation subject domain model and the relationship thereof include:
and converting the asset evaluation subject information into a view model, uploading view model serialization to a server through REST service call for deserialization, creating an evaluation subject field model and a relationship thereof, and establishing a corresponding relationship between the evaluation subjects.
Further, in the method, the specific steps of creating the index candidate library domain model and the relationship thereof include:
converting user input information into a view model, serializing the view model, calling the view model through REST service, uploading the view model to a server, performing deserialization processing, creating an index alternative library field model and a relation of the model, and establishing an index alternative library; the index candidate library comprises the classification, the property, the index name, the evaluation object and the calculation formula of the index.
Further, in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof include:
and calling an index candidate library field model to select an index, converting the corresponding relation information of the index and an evaluation object into a view model, serializing the view model, calling the REST service and uploading the view model to a server for deserializing, creating a corresponding relation field model of the index and the evaluation object and the relation of the model, establishing an index system, and configuring a calculation formula of the index.
Further, in the method, when the data volume transmitted from the client to the server in the corresponding relation field model of the created index and the evaluation object and the relation thereof is larger than a preset threshold value, the data to be transmitted is compressed and transmitted.
Further, in the method, the specific step of determining the weight of each evaluation index includes:
the receiving server side calls a unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of an index and an evaluation object, and serialize the models into JSON;
the client is loaded to the Webexcel control, and the control calculation engine executes index weight calculation according to a preset algorithm; the pre-algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to the weighted sum of the proportion.
Further, in the method, the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
and converting the scoring method into a view model, and uploading view model serialization to a server through REST service call for deserialization and creating an asset evaluation index scoring model and a relationship thereof.
Further, in the method, when the client performs asset value evaluation, the models are serialized to the client to establish a data model and a metadata model of the client.
Further, in the method, the asset value evaluation model includes an asset operating efficiency level evaluation model, a capitalization budget allocation model, and a capitalization budget allocation model;
the specific steps of the client for asset value evaluation comprise:
the method comprises the steps that a client encapsulates an asset value evaluation model request into a JSON object, and calls a server REST FUL service to obtain a model definition after serialization;
and returning the client to be loaded by the Webexcel control, executing model operation, drawing the control and rendering the page, and displaying the model operation result.
According to an aspect of one or more embodiments of the present disclosure, there is provided a computer-readable storage medium.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method of asset value assessment based on a microservice architecture.
In accordance with an aspect of one or more embodiments of the present disclosure, an electronic device is provided.
An electronic device comprising a processor and a computer-readable storage medium, the processor to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the asset value evaluation method based on the microservice architecture.
The beneficial effect of this disclosure:
according to the asset value evaluation method, device and system based on the micro-service architecture, by constructing asset value evaluation index systems of all regions and comparing asset values of regions at the same level, budget adjustment and compilation of a company can be assisted, the value of the company is led by pre-calculation, and the management and control capability of the company is improved; the overall service consciousness of basic level business personnel is improved, and electric power service is formulated reasonably; weak links of the power grid in each area are found in time, and accurate investment of the power grid is strengthened. A new generation of information system is built based on a micro-service architecture, an asset value evaluation model is supported and built, online evaluation of asset value evaluation is achieved, a capital value evaluation model is quickly and flexibly built through a system in a whole-process tracking analysis mode, logic of the asset value evaluation model is visually checked, and flexible model modification through foreground configuration according to changes of management requirements is supported. The asset value evaluation, assessment and analysis report function is provided, and assessment scores and ranking related factors are analyzed, and analysis results are displayed graphically.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is a flow diagram of a microservice architecture-based asset worth evaluation method in accordance with one or more embodiments.
The specific implementation mode is as follows:
technical solutions in one or more embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in one or more embodiments of the present disclosure, and it is apparent that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be derived by one of ordinary skill in the art based on one or more embodiments of the disclosure without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
It is noted that the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and systems according to various embodiments of the present disclosure. It should be noted that each block in the flowchart or block diagrams may represent a module, a segment, or a portion of code, which may comprise one or more executable instructions for implementing the logical function specified in the respective embodiment. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Without conflict, the embodiments and features of the embodiments in the present disclosure may be combined with each other, and the present disclosure will be further described with reference to the drawings and the embodiments.
The noun explains:
micro-service architecture: micro service Architecture (micro service Architecture) is an architectural concept that aims to achieve decoupling of solutions by breaking down functionality into discrete services. The microservice architecture splits a large single application and service into several or even tens of supporting microservices, which may extend individual components rather than the entire application stack to meet service level agreements. The microservice architecture creates applications around business domain components that can be developed, managed, and iterated independently. The use of cloud architecture and platform-based deployment, management, and service functions in decentralized components makes product delivery simpler.
Example one
According to one aspect of one or more embodiments of the present disclosure, there is provided an asset value evaluation method based on a micro service architecture.
As shown in fig. 1, an asset value evaluation method based on a micro-service architecture includes:
the S1 client uploads the asset evaluation subject information to the server; the server receives asset evaluation subject information to create an evaluation subject field model and a relation thereof;
s2 the client uploads the user input information to the server; the server receives user input information to create an index alternative library field model and the relation thereof;
s3, the client calls an index alternative library field model selection index, corresponding relation information of the index and the evaluation object is uploaded to the server, and the server receives the corresponding relation information of the index and the evaluation object to establish a corresponding relation field model of the index and the evaluation object and the relation of the model;
s4, the server side calls an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of indexes and evaluation objects and the relation thereof, and transmits the models to the client side, and the client side adopts a Delphi method and an entropy weight method according to the model and determines the weight of each evaluation index according to the weighted sum of the proportion;
s5, the client uploads the scoring method to the server, and the server receives the scoring method to create an asset evaluation index scoring model and a relationship thereof;
s6, the server side constructs an asset value evaluation model according to the evaluation index weights, the asset evaluation index scoring model and the relationship between the evaluation index weights and the asset evaluation index scoring model;
and S7, calling the asset value evaluation model of the server by the client, executing model operation and evaluating the asset value.
Further, in the method, the specific steps of creating the evaluation subject domain model and the relationship thereof include:
the client converts the asset evaluation subject information into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the serialized asset evaluation subject information, performs deserialization processing, creates an evaluation subject field model and a relationship thereof, and establishes a corresponding relationship between the evaluation subjects;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, when a server side initiates multiple data requests to a client side in the establishment of the evaluation subject domain model and the relationship thereof, some requests are combined into one network request.
In S1 of the present embodiment, an evaluation subject and an evaluation subject correspondence relationship are established. And converting the evaluation subject information into a view model, serializing the view model, transmitting the serialized view model to a server through REST service call, creating an evaluation subject field model and a relation thereof after deserialization, and calling the uniform storage service for persistence processing. The number of times of establishing network connection is reduced as much as possible, and if a plurality of data requests need to be initiated in some scenes, whether some of the requests can be combined into one network request or not can be considered to be sent out once.
Further, in the method, the specific steps of creating the index candidate library domain model and the relationship thereof include:
the client converts user input information into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the serialized user input information, carries out deserialization processing, creates an index alternative library field model and the relation of the model, and establishes an index alternative library; the index candidate library comprises the classification, the property, the index name, an evaluation object and a calculation formula of the index;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
In S2 of the present embodiment, an index candidate library is created. And establishing an index alternative library, and maintaining the classification, the property, the index name, the evaluation object and the calculation formula of the index. Converting user input information into an index library view model, serializing the view model, transmitting the view model to a server through REST service call, creating an index alternative library field model and the relation thereof after deserializing, and calling the uniform storage service persistence processing. Only the required data is taken to the client, and the data is transmitted to the client no matter whether the data is useful or useless, and part of the necessary data of the server is transmitted to the client according to the actual functional requirements of the client.
Further, in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof include:
the client calls an index selection index of the field model of the index alternative library, converts the corresponding relation information of the index and the evaluation object into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the information of the corresponding relation between the serialized indexes and the evaluation objects, carries out deserialization processing, creates a corresponding relation field model and the relation between the indexes and the evaluation objects, establishes an index system and configures a calculation formula of the indexes;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, when the data volume transmitted from the client to the server in the corresponding relation field model of the created index and the evaluation object and the relation thereof is larger than a preset threshold value, the data to be transmitted is compressed and transmitted.
In S3 of the present embodiment, an index system is established. And selecting indexes from the index alternative library, maintaining the corresponding relation between the selected indexes and the evaluation object, and configuring a calculation formula of the indexes. And converting the corresponding relation information of the index and the evaluation object into a relation view model, serializing the relation view model, transmitting the serialized relation view model to a server through REST service call, creating a corresponding relation field model of the index and the evaluation object and the relation of the model after deserialization, and calling the persistence processing of the unified storage service. When the amount of data to be transmitted is large, the amount of data to be transmitted should be reduced by compression to improve the performance of transmission.
Further, in the method, the specific step of determining the weight of each evaluation index includes:
the server side calls the unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of the indexes and the evaluation objects, serialize the models into JSON and transmit the JSON to the client side;
the client is loaded to the Webexcel control, and the control calculation engine executes index weight calculation according to a preset algorithm; the pre-algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to the weighted sum of the proportion.
In this embodiment S4, a construction index weight determination method is provided. And determining the weight of each evaluation index by adopting a Delphi method and an entropy weight method and according to proportional weighted summation. And calling the unified storage service, acquiring an evaluation model, serializing the evaluation model into JSON, transmitting the JSON to a front end, loading the JSON to a Webexcel control, and executing index weight calculation by a control calculation engine according to a preset algorithm. For data which may be used for multiple times, the data should be cached at the client, so as to avoid the interaction with the server for multiple times to obtain the same data.
Further, in the method, the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
the client converts the scoring method into a view model, and uploads the view model serialization to the server through REST service call;
the server receives a serialized scoring method, performs deserialization processing and creates an asset evaluation index scoring model and a relationship thereof;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
In S5 of the present embodiment, a construction index scoring method is used. And converting the scoring method into an index scoring view model, serializing the view model, calling and transmitting the view model to a server through REST Ful, creating the index scoring model and the relation thereof after deserializing, and calling the uniform storage service for persistence processing. For some partial page refreshing and background processing processes and some scenes with low consistency requirements, in order to improve the user interactivity, an asynchronous mode should be used.
Further, in the method, when the client performs asset value evaluation, the models are serialized to the client to establish a data model and a metadata model of the client.
In the serialization processing of this embodiment, the following innovative technical solutions are adopted:
the models are serialized to the client to establish the data Model and the metadata Model of the client, so that the interaction times can be effectively reduced, the client can only access the data Model and the metadata Model of the client normally and can not access data randomly, the service Model of the server is not serialized to the client directly, but has different Face models (different Model appearances) according to different application scenes, and the Face models are serialized to the client instead of the original service Model, so that the client only takes required data, and useless data of some current scenes can not be loaded to the client.
Further, in the method, the asset value evaluation model includes an asset operating efficiency level evaluation model, a capitalization budget allocation model, and a capitalization budget allocation model;
the specific steps of the client for asset value evaluation comprise:
the method comprises the steps that a client encapsulates an asset value evaluation model request into a JSON object, and calls a server REST FUL service to obtain a model definition after serialization;
and returning the client to be loaded by the Webexcel control, executing model operation, drawing the control and rendering the page, and displaying the model operation result.
And evaluating the asset operation efficiency level.
Selecting an asset operation efficiency level evaluation model, packaging the model request into a JSON object, calling a back-end REST FUL service after serialization to obtain a model definition, returning to the front end and then loading by a Webexcel control, executing model operation, drawing the control and rendering a page, and displaying a model operation result.
Capital budget allocation is performed.
Selecting a capital budget allocation model, packaging the model request into a JSON object, calling a rear-end REST FUL service to obtain model definition after serialization, returning to a front end, loading by a Webexcel control, executing model operation, drawing the control and rendering a page, and displaying a model operation result.
Cost budget allocation is performed.
Selecting a capital budget allocation model, packaging the model request into a JSON object, calling a rear-end REST FUL service to obtain model definition after serialization, returning to a front end, loading by a WEBEXCEL control, executing model operation, drawing the control and rendering a page, and displaying a model operation result.
In the embodiment, based on a micro-service architecture, a set of asset value evaluation model is built through three functional modules of asset value evaluation system management, evaluation model management and evaluation model application, and asset value evaluation is evaluated in an online manner and is subjected to whole-process tracking analysis.
The system quickly and flexibly constructs the asset value evaluation model, visually checks the logic of the asset value evaluation model, flexibly configures the modification model according to the change of management requirements, analyzes factors related to assessment scores and ranks, graphically displays analysis results, and realizes advanced application of the model.
By means of an informatization construction means, an asset value evaluation index system of each region is constructed, and compared with the asset values of the regions at the same level, budget adjustment and compilation of a company can be assisted, the introduction of the budget to the company value is realized, and the management and control capability of the company is improved; the overall service consciousness of basic level business personnel is improved, and electric power service is formulated reasonably; weak links of the power grid in each area are found in time, and accurate investment of the power grid is strengthened. The invention aims to provide an asset value evaluation application and improve the asset value evaluation management level. The asset value evaluation model based on the micro-service architecture comprises three functional modules, namely asset value evaluation system management, evaluation model management and evaluation model application, and a set of built asset value evaluation models are established to realize an asset value evaluation intelligent display platform.
Example two
According to one aspect of one or more embodiments of the present disclosure, there is provided a microservice architecture-based asset value evaluation system.
An asset value evaluation system based on a micro-service architecture is based on the asset value evaluation method based on the micro-service architecture, and the system comprises the following steps: client and server.
In this embodiment, the asset value evaluation model system of the present invention implements modularization of the Web application system itself based on Java EE Servlet 3.0Web Fragment, and the server side implements modularized development and management based on Java EE Web Fragment and Spring frame. And the model driven architecture is used, and the application implementation is carried out by adopting an assembling method instead of a developing method. The dependency between the modules is stated in the configuration information of the Spring IoC container, all the modules run in the Spring IoC container at the same time, and various technologies of Spring Web MVC and Spring AOP can be fully used to simplify the development of the functional modules. The method supports accessing the relational database in various modes through JPA/O-R Mapping/JDBC, and supports various database products. The front-end framework supports AMD specification, modular development can be well carried out by using AMD, loading can be carried out as required, and the running performance of the front end is greatly improved. The front-end framework uses a responsive layout technique to provide a more comfortable interface and better user experience for users of different terminals. The platform defines a unified UI specification, a unified page style. The front-end framework applies an MVC (model View controller) mode and adopts an MVC bidirectional binding technology, thereby simplifying the complexity of front-end codes and reusing the codes to the maximum extent.
EXAMPLE III
According to one aspect of one or more embodiments of the present disclosure, there is provided an asset value evaluation method based on a micro service architecture.
An asset value evaluation method based on a micro-service architecture is realized at a server side and comprises the following steps:
receiving asset evaluation subject information uploaded by a client to establish an evaluation subject field model and a relation thereof;
receiving a user input information creation index alternative library field model uploaded by a client and a relation thereof;
receiving corresponding relation information of indexes and evaluation objects uploaded by a client to establish a corresponding relation field model of the indexes and the evaluation objects and a relation of the corresponding relation field model;
calling an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of indexes and evaluation objects and the relation thereof, transmitting the model to a client side, and determining the weight of each evaluation index according to the weighted sum of the proportion by adopting a Delphi method and an entropy weight method;
receiving a scoring method uploaded by a client to establish an asset evaluation index scoring model and a relationship thereof;
constructing an asset value evaluation model according to the evaluation index weights, the asset evaluation index scoring model and the relationship between the evaluation index weights and the asset evaluation index scoring model; and calling the asset value evaluation model of the server by the client, executing model operation and evaluating the asset value.
Further, in the method, the specific steps of creating the evaluation subject domain model and the relationship thereof include:
receiving serialized asset evaluation subject information uploaded by a client, performing deserialization processing, creating an evaluation subject field model and a relationship thereof, and establishing a corresponding relationship between evaluation subjects;
and calling the unified storage service persistence processing evaluation subject field model and the relation thereof.
Further, in the method, when a server side initiates multiple data requests to a client side in the establishment of the evaluation subject domain model and the relationship thereof, some requests are combined into one network request.
Further, in the method, the specific steps of creating the index candidate library domain model and the relationship thereof include:
the server receives serialized user input information uploaded by the client, performs deserialization processing, creates an index alternative library field model and a relation thereof, and establishes an index alternative library; the index candidate library comprises the classification, the property, the index name, an evaluation object and a calculation formula of the index;
and calling the unified storage service persistence processing evaluation subject field model and the relation thereof.
Further, in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof include:
the server receives the corresponding relation information of the serialized indexes and the evaluation objects uploaded by the client, carries out deserialization processing, creates a corresponding relation field model of the indexes and the evaluation objects and the relation of the model, establishes an index system and configures a calculation formula of the indexes;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Further, in the method, the specific step of determining the weight of each evaluation index includes:
the server side calls the unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of the indexes and the evaluation objects, serialize the models into JSON and transmit the JSON to the client side; loading the client to the Webexcel control, and executing index weight calculation by the control calculation engine according to a preset algorithm; the pre-algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to the weighted sum of the proportion.
Further, in the method, the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
the server receives the serialized scoring method uploaded by the client, performs deserialization processing and creates an asset evaluation index scoring model and a relationship thereof;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
Example four
According to an aspect of one or more embodiments of the present disclosure, there is provided a computer-readable storage medium.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method of asset value assessment based on a microservice architecture.
EXAMPLE five
In accordance with an aspect of one or more embodiments of the present disclosure, an electronic device is provided.
An electronic device comprising a processor and a computer-readable storage medium, the processor to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the asset value evaluation method based on the microservice architecture.
EXAMPLE six
According to one aspect of one or more embodiments of the present disclosure, there is provided an asset value evaluation method based on a micro service architecture.
An asset value evaluation method based on a micro-service architecture is realized at a client, and the method comprises the following steps:
uploading user input information to a server for creating an evaluation subject domain model and a relationship thereof;
uploading user input information to a server for creating an index alternative library field model and a relation thereof;
calling an index candidate library field model to select an index, and uploading corresponding relation information of the index and an evaluation object to a server for creating a corresponding relation field model and a corresponding relation of the index and the evaluation object;
the receiving server side calls an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of the index and the evaluation object and the relation thereof, and determines the weight of each evaluation index according to the Delphi method and the entropy weight method and the proportion weighting summation;
uploading the scoring method to a server for creating an asset evaluation index scoring model and a relationship thereof;
and calling the asset value evaluation model constructed by the server according to the evaluation index weight, the asset evaluation index scoring model and the relationship of the evaluation index weight and the asset evaluation index scoring model, executing model operation and evaluating the asset value.
Further, in the method, the specific steps of creating the evaluation subject domain model and the relationship thereof include:
and converting the asset evaluation subject information into a view model, uploading view model serialization to a server through REST service call for deserialization, creating an evaluation subject field model and a relationship thereof, and establishing a corresponding relationship between the evaluation subjects.
Further, in the method, the specific steps of creating the index candidate library domain model and the relationship thereof include:
converting user input information into a view model, serializing the view model, calling the view model through REST service, uploading the view model to a server, performing deserialization processing, creating an index alternative library field model and a relation of the model, and establishing an index alternative library; the index candidate library comprises the classification, the property, the index name, the evaluation object and the calculation formula of the index.
Further, in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof include:
and calling an index candidate library field model to select an index, converting the corresponding relation information of the index and an evaluation object into a view model, serializing the view model, calling the REST service and uploading the view model to a server for deserializing, creating a corresponding relation field model of the index and the evaluation object and the relation of the model, establishing an index system, and configuring a calculation formula of the index.
Further, in the method, when the data volume transmitted from the client to the server in the corresponding relation field model of the created index and the evaluation object and the relation thereof is larger than a preset threshold value, the data to be transmitted is compressed and transmitted.
Further, in the method, the specific step of determining the weight of each evaluation index includes:
the receiving server side calls a unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of an index and an evaluation object, and serialize the models into JSON;
the client is loaded to the Webexcel control, and the control calculation engine executes index weight calculation according to a preset algorithm; the pre-algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to the weighted sum of the proportion.
Further, in the method, the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
and converting the scoring method into a view model, and uploading view model serialization to a server through REST service call for deserialization and creating an asset evaluation index scoring model and a relationship thereof.
Further, in the method, when the client performs asset value evaluation, the models are serialized to the client to establish a data model and a metadata model of the client.
Further, in the method, the asset value evaluation model includes an asset operating efficiency level evaluation model, a capitalization budget allocation model, and a capitalization budget allocation model;
the specific steps of the client for asset value evaluation comprise:
the method comprises the steps that a client encapsulates an asset value evaluation model request into a JSON object, and calls a server REST FUL service to obtain a model definition after serialization;
and returning the client to be loaded by the Webexcel control, executing model operation, drawing the control and rendering the page, and displaying the model operation result.
EXAMPLE seven
According to an aspect of one or more embodiments of the present disclosure, there is provided a computer-readable storage medium.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method of asset value assessment based on a microservice architecture.
Example eight
In accordance with an aspect of one or more embodiments of the present disclosure, an electronic device is provided.
An electronic device comprising a processor and a computer-readable storage medium, the processor to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the asset value evaluation method based on the microservice architecture.
These computer-executable instructions, when executed in a device, cause the device to perform methods or processes described in accordance with various embodiments of the present disclosure.
In the present embodiments, a computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for performing various aspects of the present disclosure. The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembly instructions, Instruction Set Architecture (ISA) instructions, machine related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry can execute computer-readable program instructions to implement aspects of the present disclosure by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A asset value evaluation method based on a micro-service architecture is characterized by comprising the following steps:
the client uploads asset evaluation subject information to the server; the server receives asset evaluation subject information to create an evaluation subject field model and a relation thereof;
the client uploads user input information to the server; the server receives user input information to create an index alternative library field model and the relation thereof;
the client calls an index selection index of the field model of the index alternative library, corresponding relation information of the index and an evaluation object is uploaded to the server, and the server receives the corresponding relation information of the index and the evaluation object to establish a corresponding relation field model of the index and the evaluation object and a relation between the index and the evaluation object;
the server side calls an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of indexes and evaluation objects and the relation thereof and transmits the models to the client side, and the client side adopts a Delphi method and an entropy weight method according to the model and determines the weight of each evaluation index according to the weighted sum of the proportion;
the client uploads the scoring method to the server, and the server receives the scoring method to create an asset evaluation index scoring model and a relationship thereof;
the server side constructs an asset value evaluation model according to the evaluation index weights, the asset evaluation index scoring model and the relationship between the evaluation index weights and the asset evaluation index scoring model;
the client calls an asset value evaluation model of the server, executes model operation and evaluates the asset value;
the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
the client converts the scoring method into a view model, and uploads the view model serialization to the server through REST service call; the server receives a serialized scoring method, performs deserialization processing and creates an asset evaluation index scoring model and a relationship thereof;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
2. The asset value evaluation method based on the micro-service architecture as claimed in claim 1, wherein the specific steps of creating the evaluation subject domain model and the relationship thereof comprise:
the client converts the asset evaluation subject information into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the serialized asset evaluation subject information, performs deserialization processing, creates an evaluation subject field model and a relationship thereof, and establishes a corresponding relationship between the evaluation subjects;
the server side calls a unified storage service persistence processing evaluation main body field model and the relation of the model;
and/or in the method, when a server side initiates multiple data requests to a client side in the establishment of the evaluation subject domain model and the relationship thereof, combining some requests into a network request;
and/or in the method, the specific steps of creating the index candidate library field model and the relation thereof comprise:
the client converts user input information into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the serialized user input information, carries out deserialization processing, creates an index alternative library field model and the relation of the model, and establishes an index alternative library; the index candidate library comprises the classification, the property, the index name, an evaluation object and a calculation formula of the index;
the server side calls a unified storage service persistence processing evaluation main body field model and the relation of the model;
and/or in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof comprise:
the client calls an index selection index of the field model of the index alternative library, converts the corresponding relation information of the index and the evaluation object into a view model, and uploads the view model serialization to the server through REST service call;
the server receives the information of the corresponding relation between the serialized indexes and the evaluation objects, carries out deserialization processing, creates a corresponding relation field model and the relation between the indexes and the evaluation objects, establishes an index system and configures a calculation formula of the indexes;
the server side calls a unified storage service persistence processing evaluation main body field model and the relation of the model;
and/or in the method, when the data volume transmitted from the client to the server in the corresponding relation field model of the establishment index and the evaluation object and the relation thereof is larger than a preset threshold value, compressing the data to be transmitted for transmission;
and/or in the method, the specific step of determining the weight of each evaluation index comprises the following steps:
the server side calls the unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of the indexes and the evaluation objects, serialize the models into JSON and transmit the JSON to the client side;
the client is loaded to the Webexcel control, and the control calculation engine executes index weight calculation according to a preset algorithm; the preset algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to proportional weighted summation;
and/or, in the method, when the client side evaluates the asset value, each model is serialized to the client side to establish a data model and a metadata model of the client side;
and/or, in the method, the asset value evaluation model comprises an asset operating efficiency level evaluation model, a capitalization budget allocation model, and a capitalization budget allocation model;
the specific steps of the client for asset value evaluation comprise:
the method comprises the steps that a client encapsulates an asset value evaluation model request into a JSON object, and calls a server REST FUL service to obtain a model definition after serialization;
and returning the client to be loaded by the Webexcel control, executing model operation, drawing the control and rendering the page, and displaying the model operation result.
3. A microservice-architecture-based asset value evaluation system, based on a microservice-architecture-based asset value evaluation method according to any one of claims 1-2, the system comprising: client and server.
4. An asset value evaluation method based on a micro-service architecture is characterized in that the method is realized at a server side and comprises the following steps:
receiving asset evaluation subject information uploaded by a client to establish an evaluation subject field model and a relation thereof;
receiving a user input information creation index alternative library field model uploaded by a client and a relation thereof;
receiving corresponding relation information of indexes and evaluation objects uploaded by a client to establish a corresponding relation field model of the indexes and the evaluation objects and a relation of the corresponding relation field model;
calling an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of indexes and evaluation objects and the relation thereof, transmitting the model to a client side, and determining the weight of each evaluation index according to the weighted sum of the proportion by adopting a Delphi method and an entropy weight method;
receiving a scoring method uploaded by a client to establish an asset evaluation index scoring model and a relationship thereof;
constructing an asset value evaluation model according to the evaluation index weights, the asset evaluation index scoring model and the relationship between the evaluation index weights and the asset evaluation index scoring model; the client side calls the asset value evaluation model of the server side, executes model operation and evaluates the asset value;
the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
the server receives the serialized scoring method uploaded by the client, performs deserialization processing and creates an asset evaluation index scoring model and a relationship thereof;
and the server side calls the unified storage service persistence processing evaluation main body field model and the relation thereof.
5. The asset value evaluation method based on the micro-service architecture as claimed in claim 4, wherein the specific steps of creating the evaluation subject domain model and the relationship thereof comprise:
receiving serialized asset evaluation subject information uploaded by a client, performing deserialization processing, creating an evaluation subject field model and a relationship thereof, and establishing a corresponding relationship between evaluation subjects;
calling a unified storage service persistence processing evaluation subject field model and the relation thereof;
and/or in the method, when a server side initiates multiple data requests to a client side in the establishment of the evaluation subject domain model and the relationship thereof, combining some requests into a network request;
and/or in the method, the specific steps of creating the index candidate library field model and the relation thereof comprise:
the server receives serialized user input information uploaded by the client, performs deserialization processing, creates an index alternative library field model and a relation thereof, and establishes an index alternative library; the index candidate library comprises the classification, the property, the index name, an evaluation object and a calculation formula of the index;
calling a unified storage service persistence processing evaluation subject field model and the relation thereof;
and/or in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof comprise:
the server receives the corresponding relation information of the serialized indexes and the evaluation objects uploaded by the client, carries out deserialization processing, creates a corresponding relation field model of the indexes and the evaluation objects and the relation of the model, establishes an index system and configures a calculation formula of the indexes;
the server side calls a unified storage service persistence processing evaluation main body field model and the relation of the model;
and/or in the method, the specific step of determining the weight of each evaluation index comprises the following steps:
the server side calls the unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of the indexes and the evaluation objects, serialize the models into JSON and transmit the JSON to the client side; loading the client to the Webexcel control, and executing index weight calculation by the control calculation engine according to a preset algorithm; the preset algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to proportional weighted summation.
6. An asset value evaluation method based on a micro-service architecture is characterized by being realized at a client, and comprises the following steps:
uploading user input information to a server for creating an evaluation subject domain model and a relationship thereof;
uploading user input information to a server for creating an index alternative library field model and a relation thereof;
calling an index candidate library field model to select an index, and uploading corresponding relation information of the index and an evaluation object to a server for creating a corresponding relation field model and a corresponding relation of the index and the evaluation object;
the receiving server side calls an evaluation main body field model and the relation thereof, an index alternative library field model and the relation thereof, and a corresponding relation field model of the index and the evaluation object and the relation thereof, and determines the weight of each evaluation index according to the Delphi method and the entropy weight method and the proportion weighting summation;
uploading the scoring method to a server for creating an asset evaluation index scoring model and a relationship thereof;
calling an asset value evaluation model constructed by the server according to the evaluation index weight, the asset evaluation index scoring model and the relationship between the evaluation index weight and the asset evaluation index scoring model, executing model operation and evaluating the asset value;
the specific steps of creating the asset evaluation index scoring model and the relationship thereof include:
converting the scoring method into a view model, uploading view model serialization to a server through REST service call for deserialization and creating an asset evaluation index scoring model and a relation thereof; and when the client evaluates the asset value, serializing the models to the client to establish a data model and a metadata model of the client.
7. The asset value evaluation method based on the micro-service architecture as claimed in claim 6, wherein the specific steps of creating the evaluation subject domain model and the relationship thereof comprise:
converting asset evaluation subject information into a view model, uploading view model serialization to a server through REST service call for deserialization processing, creating an evaluation subject field model and a relationship thereof, and establishing a corresponding relationship between evaluation subjects;
and/or in the method, the specific steps of creating the index candidate library field model and the relation thereof comprise:
converting user input information into a view model, serializing the view model, calling the view model through REST service, uploading the view model to a server, performing deserialization processing, creating an index alternative library field model and a relation of the model, and establishing an index alternative library; the index candidate library comprises the classification, the property, the index name, an evaluation object and a calculation formula of the index;
and/or in the method, the specific steps of creating the corresponding relation field model of the index and the evaluation object and the relation thereof comprise:
calling an index candidate library field model to select an index, converting corresponding relation information of the index and an evaluation object into a view model, serializing the view model, calling the REST service, uploading the view model to a server, performing deserialization processing, creating a corresponding relation field model of the index and the evaluation object and a relation of the corresponding relation field model, establishing an index system, and configuring a calculation formula of the index;
and/or in the method, when the data volume transmitted from the client to the server in the corresponding relation field model of the establishment index and the evaluation object and the relation thereof is larger than a preset threshold value, compressing the data to be transmitted for transmission;
and/or in the method, the specific step of determining the weight of each evaluation index comprises the following steps:
the receiving server side calls a unified storage service to acquire asset evaluation subject information, create an evaluation subject field model, an index alternative library field model and a corresponding relation field model of an index and an evaluation object, and serialize the models into JSON;
the client is loaded to the Webexcel control, and the control calculation engine executes index weight calculation according to a preset algorithm; the preset algorithm adopts a Delphi method and an entropy weight method, and determines the weight of each evaluation index according to proportional weighted summation.
8. The asset value evaluation method based on the micro-service architecture as claimed in claim 6, wherein in the method, the asset value evaluation model comprises an asset operation efficiency level evaluation model, a capital budget allocation model and a capital budget allocation model;
the specific steps of the client for asset value evaluation comprise:
the method comprises the steps that a client encapsulates an asset value evaluation model request into a JSON object, and calls a server REST FUL service to obtain a model definition after serialization;
and returning the client to be loaded by the Webexcel control, executing model operation, drawing the control and rendering the page, and displaying the model operation result.
9. A computer-readable storage medium having stored thereon a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method for asset value assessment based on a microservice architecture according to any of claims 4-5 or claims 6-8.
10. An electronic device comprising a processor and a computer-readable storage medium, the processor to implement instructions; a computer readable storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform a method of asset value assessment based on a microservice architecture according to any of claims 4-5 or claims 6-8.
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