CIM-based science park management method, apparatus and device, and medium

Abstract

The invention is applied to the field of data analysis, and discloses a CIM-based science and technology park management method, device and equipment and a medium, and the method comprises the steps: calling a CIM module to construct a science and technology park ecological model through the enterprise operation information, the surrounding environment information and the planning information of all settled enterprises in a science and technology park; calling a preset potential prediction model through the science park ecological model to predict the development potential of each settled enterprise to obtain an enterprise potential value corresponding to each settled enterprise; interaction information among the settled enterprises is obtained through the science and technology park ecological model to generate an interaction net diagram of the science and technology park, and potential influence values of the settled enterprises are determined through the interaction net diagram; and determining a science park development index and a science park contribution factor through the enterprise potential value and the potential influence value to generate a science park operation management report. The objective of the invention is to solve the technical problems of low matching degree between to-be-introduced enterprises and settled enterprises in the science and technology park and low operation service and efficiency of the science and technology park.

Description

Technical Field

[0001] This application belongs to the field of data analysis technology and relates to a CIM-based method, device, equipment and medium for managing science and technology parks. Background Technology

[0002] Industrial science and technology parks can effectively create agglomeration power, drive the development of related industries by sharing resources and overcoming negative externalities, thereby effectively promoting the formation of industrial clusters. How to enhance regional economic competitiveness through the development and management of industrial science and technology parks is a strategic issue in economic development.

[0003] Traditional management methods for science parks typically rely on industry experts combining existing data and experience to assess the development of various enterprises within the park. However, these assessment methods are simple, involve a large amount of manual work, and the results are not always accurate. Consequently, it is difficult to determine the development status of each enterprise within the science park, making it difficult to effectively operate or manage the park based on their development status. Furthermore, it is difficult to identify the enterprises that the science park currently needs to attract, which is detrimental to the effective development of the science park.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a CIM-based management method, device, equipment and medium for science and technology parks, aiming to solve the technical problems of low matching degree between enterprises to be introduced and enterprises already in the science and technology parks, as well as low operation and efficiency of science and technology parks.

[0006] To achieve the above objectives, this application provides a CIM-based science park management method, which includes:

[0007] The CIM module is invoked to construct a science park ecosystem model of the science park by using the enterprise operation information of each enterprise in the science park, the surrounding environment information of the science park, and the planning information of the science park.

[0008] By using the aforementioned science and technology park ecosystem model, a preset potential prediction model is invoked to predict the development potential of each of the resident enterprises, thereby obtaining the enterprise potential value corresponding to each of the resident enterprises.

[0009] By using the science park ecosystem model, the interaction information between the resident enterprises is obtained, an interaction network diagram within the science park is generated, and the potential impact value of each resident enterprise is determined by the interaction network diagram.

[0010] The science park development index is determined by the potential value of each enterprise and the potential impact value of each enterprise, and the science park contribution factor of the science park development index is determined to generate the science park operation and management report.

[0011] To achieve the above objectives, this application provides a CIM-based science park management device, the CIM-based science park management device comprising:

[0012] The construction module is invoked to call the CIM module to construct a science and technology park ecosystem model based on the enterprise operation information of each enterprise in the science and technology park, the surrounding environment information of the science and technology park, and the planning information within the science and technology park.

[0013] The potential value determination module is used to predict the development potential of each of the resident enterprises by calling a preset potential prediction model through the science park ecosystem model, and to obtain the enterprise potential value corresponding to each of the resident enterprises.

[0014] The potential value impact module is used to obtain the interaction information between the resident enterprises through the science park ecosystem model, generate an interaction network diagram within the science park, and determine the potential impact value of each resident enterprise through the interaction network diagram.

[0015] The Science and Technology Park Development Index Determination Module is used to determine the Science and Technology Park Development Index of the Science and Technology Park through the potential value of each enterprise and the potential impact value of each enterprise, and to determine the Science and Technology Park Contribution Factor of the Science and Technology Park Development Index, so as to generate a Science and Technology Park Operation and Management Report.

[0016] This application also provides an electronic device, which includes: a memory, a processor, and a program of the CIM-based science park management method stored in the memory and executable on the processor. When the program of the CIM-based science park management method is executed by the processor, it can implement the steps of the CIM-based science park management method as described above.

[0017] This application also provides a computer-readable storage medium storing a program for implementing a CIM-based science park management method. When the program for the CIM-based science park management method is executed by a processor, it implements the steps of the CIM-based science park management method as described above.

[0018] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the CIM-based science park management method described above.

[0019] This application provides a CIM-based method, apparatus, equipment, and medium for managing science and technology parks. The application constructs a science and technology park ecosystem model by calling a CIM module and utilizing the operational information of each resident enterprise, the surrounding environment of the science and technology park, and the planning information within the science and technology park. Using this ecosystem model, a preset potential prediction model is invoked to predict the development potential of each resident enterprise, yielding the potential value of each enterprise. The ecosystem model is then used to obtain interaction information between the resident enterprises, generating an interaction network diagram within the science and technology park. This interaction network diagram is used to determine the potential impact value of each resident enterprise. Finally, the potential value of each enterprise and the potential impact value are used to determine the science and technology park development index, and the science and technology park contribution factor of the development index is determined, thereby generating a science and technology park operation and management report.

[0020] This application utilizes the CIM module to construct a science park ecosystem model based on operational information of enterprises within the science park, surrounding environmental information, and planning information within the science park. This provides a more intuitive understanding of the distribution of enterprises within the science park. Furthermore, by constructing the science park ecosystem model, it facilitates the quick and accurate acquisition of relevant data on each resident enterprise within the science park. This allows for the analysis of the development potential of each resident enterprise and its potential impact on the development of other resident enterprises within the science park. Compared to existing technologies, this approach provides comprehensive and convenient access to enterprise data, eliminating the need for manual data acquisition or relying on human experience to assess the development of enterprises within the science park, thereby improving the accuracy of enterprise development analysis.

[0021] Furthermore, by utilizing a science park ecosystem model and invoking a pre-defined potential prediction model, the development potential of each resident enterprise can be predicted, thereby determining their potential value. Additionally, based on interaction information among resident enterprises, the potential impact value of each enterprise can be predicted. This allows for a two-pronged evaluation of enterprises within the science park, providing a clear understanding of their development status and interactions, and offering a basis for decision-making in the park's operation and management. Moreover, the development value of the science park can be determined through enterprise potential value and potential impact value, along with the science park's contribution factor to the development index. This enables an assessment of the overall development of the science park. Furthermore, identifying the contribution factor helps pinpoint factors beneficial to the park's development, allowing for the introduction of enterprises matching the park's contribution factor, promoting positive development, and improving the match between introduced enterprises and the park's overall development. The science park operation and management report can also output data including the potential impact value of each resident enterprise, enterprise potential value, the science park's development index, and the science park's contribution factor. This allows users to directly understand the development status within the science park based on the operation and management report, providing a basis for decision-making in the park's operation and management. Attached Figure Description

[0022] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0023] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the first embodiment of the CIM-based science park management method of this application;

[0025] Figure 2 This is a flowchart illustrating the second embodiment of the CIM-based science park management method of this application;

[0026] Figure 3 This is a flowchart illustrating the third embodiment of the CIM-based science park management method of this application;

[0027] Figure 4 This is a schematic diagram of an embodiment of the CIM-based science park management method of this application;

[0028] Figure 5This is a schematic diagram of the equipment structure of the hardware operating environment involved in the CIM-based science park management method in this application embodiment.

[0029] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0030] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] Example 1

[0032] Reference Figure 1 This application provides a CIM-based science park management method. In the first embodiment of this CIM-based science park management method, the CIM-based science park management method includes:

[0033] Step S10: Call the CIM module to construct a science park ecosystem model of the science park by using the enterprise operation information of each enterprise in the science park, the surrounding environment information of the science park, and the planning information of the science park.

[0034] It should be noted that the CIM module is used to construct an ecosystem model of the science park. This model can be a virtual 3D model that simulates the surrounding environment of the science park, the planned layout of buildings and transportation within the park, and the distribution of resident enterprises. The surrounding environment information includes the distribution of surrounding buildings, industries, and transportation. The surrounding area refers to the area at a predetermined distance from the science park, which can be determined based on actual conditions. The CIM module can include a data acquisition module, a data processing module, and a model building module. The data acquisition module is used to collect information about the science park and its surroundings.

[0035] For example, the data acquisition module can utilize drones to collect planning information within the science park and surrounding environmental information within a preset distance. It can also acquire construction drawings from sensors pre-installed within the science park to assist the CIM module in building the science park's ecological model. The module collects sensor data from within the science park and inputs the surrounding environmental information, planning information, sensor data, and construction drawings into the data processing module. This module cleans or processes the surrounding environmental information, planning information, and sensor data to obtain standard surrounding environmental data, standard planning data, and standard sensor data. These standard data represent unified, standardized information on the surrounding environment, planning information, and sensor data. Finally, these standard surrounding environmental data, standard planning data, and standard sensor data are sent to the model building module to construct the science park's ecological model. Specifically, a preliminary simulation model of the science park can be obtained by simulating the distribution of buildings and traffic planning within the park based on standard planning data, and the distribution of surrounding objects based on standard surrounding environment data. This initial model is then adjusted using sensor data to refine the building distribution and traffic planning, resulting in a standard science park simulation model. Next, the distribution and operational information of each resident company within the park are acquired. This company distribution data is input into the standard simulation model via the CIM module, marking the locations of each company. Similarly, the operational information is input into the standard simulation model via the CIM module's model building module, marking the operational information of each company at its corresponding location, thus creating a science park ecosystem model. The operational information and the company locations within the ecosystem model can be hidden, or both can be displayed simultaneously.

[0036] This application's embodiments construct a science park ecosystem model, thereby providing a direct view of the development within and around the science park. Compared to existing technologies that involve watching videos or viewing sand tables of science parks, this approach makes it easier for resident companies, science park managers, and potential tenants to understand the science park's situation, facilitating a two-way selection process between the science park and the companies. Furthermore, by constructing a science park ecosystem model, it is easier to obtain enterprise operational information and interaction information between companies, thus making it easier to assess the current value or development status of the science park.

[0037] Step S20: Using the science park ecosystem model, a preset potential prediction model is called to predict the development potential of each of the resident enterprises, and the enterprise potential value corresponding to each of the resident enterprises is obtained.

[0038] It should be noted that the information stored in the science park's ecosystem model regarding each resident company and its operational details can be updated or deleted periodically. Company operational information is represented by development data, including the company's development stage, type, related information, and structure. A pre-trained potential prediction model can be used to predict the potential value of each resident company. Different company types can correspond to different pre-trained potential prediction models. These models can be trained using neural networks.

[0039] For example, through the science and technology park ecosystem model, the enterprise operation information of each resident enterprise is obtained from the science and technology park ecosystem model, and the development potential of each resident enterprise is predicted by the enterprise operation information and the preset potential prediction model, so as to obtain the enterprise potential value of each resident enterprise.

[0040] In one feasible embodiment, step S20 further includes:

[0041] Step S21: For any of the resident enterprises, obtain the enterprise development stage, enterprise type, enterprise association information, and enterprise structure of the resident enterprise through the science park ecosystem model;

[0042] It should be noted that the operational information of any resident enterprise can be obtained from the science park ecosystem model. This model can utilize a pre-defined potential prediction model to predict the potential value of each resident enterprise. Enterprise operational information includes the enterprise's development stage, enterprise type, related information, and structure. The development stage describes the current development level of the resident enterprise and can be divided into initial, mid-term, and late-term stages. It can be assumed that the development space potential decreases sequentially from the initial to the mid-term and late-term stages, while the development scale potential increases sequentially. The enterprise structure represents the internal operational structure of the resident enterprise, which may include the total number of employees, the types and number of departments, and the management structure. Development space refers to the distance to the late-term development stage, and development scale potential refers to the value of the resident enterprise's output. Enterprise structure affects the enterprise's development status and, consequently, its development potential.

[0043] The preset potential prediction model will call the first prediction model to predict the first potential. When predicting the first potential, the stage potential of the enterprise can be determined based on the development stage of the enterprise. The stage potential is the sum of the development scale potential and the development space potential. At the same time, the structural impact potential of the resident enterprises can be predicted based on the enterprise structure. The first potential is obtained by splicing the structural impact potential and the stage potential.

[0044] Enterprise type refers to the type of production or operation of the resident enterprise. This could be a chip R&D enterprise, a lithography machine enterprise, etc. Enterprise association information includes the target customers of the resident enterprise's products and services, as well as the suppliers of resources needed for its production or operation. The target customers of products and services can be businesses or individual users, and the suppliers of resources can be businesses. The more enterprise types and / or individual users that can be influenced through the enterprise association information, the greater the secondary potential of the resident enterprise.

[0045] Step S22: Determine the preset potential prediction model based on the enterprise type;

[0046] Step S23: Based on the enterprise development stage and enterprise structure, the preset potential prediction model is used to predict the first potential of the resident enterprise and the second potential of the resident enterprise based on the enterprise association information.

[0047] Step S24: Combine the first potential and the second potential to obtain the enterprise potential value.

[0048] It should be noted that the first potential represents the development potential of the resident enterprise itself, while the second potential represents the potential impact of the resident enterprise on other enterprises. "Other enterprises" refers to enterprises other than those resident enterprises; these can be enterprises within or outside the science park. Different enterprise types can correspond to different preset potential prediction models, which can be trained using neural networks. These preset potential prediction models can include a first prediction model and a second prediction model; the first model predicts the first potential, and the second model predicts the second potential. Both the first and second prediction models can be obtained through neural network training. The science park ecosystem model can store the preset potential prediction models corresponding to each enterprise type. These preset potential prediction models can carry labels indicating the enterprise type.

[0049] For example, the steps for training the first prediction model can be as follows: First, determine a first model to be trained; obtain first training samples, including enterprise development stage samples, enterprise structure samples, and first potential labels; input the enterprise development stage samples and enterprise structure samples into the first model to be trained to obtain first potential features; calculate the first loss between the first potential features and the first potential labels, where the first loss can be the distance between the first potential features and the first potential labels; determine whether the first loss is less than a preset loss value; if the first loss is less than or equal to the preset loss value, the first model to be trained is successfully trained, and the first prediction model is obtained; if the first loss is greater than the preset loss value, the first model to be trained is retrained until the first loss is less than or equal to the preset loss value. The preset loss value can be determined based on the actual situation.

[0050] The steps for training the second prediction model are as follows: determine a second model to be trained; obtain second training samples, including enterprise-related information samples and second potential labels; input the enterprise-related information samples into the second model to be trained to obtain second potential features; calculate the second loss between the second potential features and the second potential labels, where the second loss can be the distance between the second potential features and the second potential labels; determine whether the second loss is less than a preset loss value; if the second loss is less than or equal to the preset loss value, the second model to be trained is successfully trained, and the second prediction model is obtained; if the second loss is greater than the preset loss value, the second model to be trained is retrained until the second loss is less than or equal to the preset loss value.

[0051] The steps for training a preset potential prediction model are as follows: First, determine a third model to be trained. Second, obtain third training samples, which include enterprise development stage samples, enterprise structure samples, enterprise related information samples, and enterprise potential value labels corresponding to a specified enterprise type. Third, input the enterprise development stage samples, enterprise structure samples, and enterprise related information samples into the third model to be trained to obtain enterprise potential value features. Calculate the third loss between the enterprise potential value features and the enterprise potential value labels. The third loss can be the distance between the enterprise potential value features and the enterprise potential value labels. Determine whether the third loss is less than a preset loss value. If the third loss is less than or equal to the preset loss value, the third model to be trained is successfully trained, and the preset potential prediction model is obtained. If the third loss is greater than the preset loss value, retrain the third model to be trained until the third loss is less than or equal to the preset loss value.

[0052] For example, steps S21 to S24 include: for any of the resident enterprises, obtaining the enterprise development stage, enterprise type, enterprise association information, and enterprise structure of the resident enterprise through the science park ecosystem model; searching for a preset potential prediction model that matches the enterprise type in the science park ecosystem model; inputting the enterprise development stage, enterprise association information, and enterprise structure into the preset potential prediction model; the preset potential prediction model calls a first prediction model to predict a first potential based on the enterprise development stage and enterprise structure; calling a second prediction model to predict a second potential based on the enterprise association information; and concatenating the first and second potentials to obtain the enterprise potential value. For example, the enterprise potential value can be obtained by weighted summation of the first and second potentials.

[0053] This application embodiment predicts the development potential of the enterprises themselves (first potential) and the potential scope of influence of the enterprises (second potential) respectively, thereby comprehensively assessing the development potential of enterprises in the science park and improving the accuracy of predicting the development potential of enterprises.

[0054] Step S30: Through the science park ecosystem model, obtain the interaction information between the resident enterprises, generate an interaction network diagram within the science park, and determine the potential impact value of each resident enterprise through the interaction network diagram.

[0055] It should be noted that interaction information between resident companies can be input into the science park ecosystem model and stored within the model. This interaction information can be updated periodically. An interaction network diagram is used to represent the data exchange between resident companies within the science park. The diagram is marked with each resident company and the interaction data between them. Users can view the interaction network diagram to intuitively understand the interaction information between resident companies within the science park. Potential impact value represents the influence of a resident company on the development of other resident companies within the science park. For example, interaction information between the resident companies is obtained from the science park ecosystem model, an interaction network diagram within the science park is generated, and the potential impact value of each resident company is determined using this diagram.

[0056] Step S40: Determine the science park development index of the science park by the potential value of each enterprise and the potential impact value of each enterprise, and determine the science park contribution factor of the science park development index, so as to generate the science park operation and management report of the science park.

[0057] It should be noted that the science park development index represents the overall development status of the science park. The development value of a science park is influenced by the individual enterprises within it. The science park contribution factor represents the factors affecting the science park development index, including positive and negative contribution factors. These contribution factors can be determined from enterprise operational information. The science park operation and management report is used to showcase the development status of the science park. This report includes the science park development index, science park contribution factors, and may also include interactive diagrams, the potential impact value of each resident enterprise, and the enterprise's potential value. This allows users or science park managers to understand the science park's development status based on clear data. For example, the science park development index is determined by the potential value and potential impact value of each enterprise, and the science park contribution factors influencing the development index are determined based on these values. The science park operation and management report is then generated based on the enterprise potential value, potential impact value, science park development index, interactive diagram, and science park contribution factors of each resident enterprise. Furthermore, in this embodiment of the application, companies intending to move in can also view the management reports of the science park, which can provide decision-making basis for the operation and management of the science park. This provides a clear decision-making basis for companies intending to move in, facilitating a two-way selection process between the science park and the companies.

[0058] This application embodiment, by calling the CIM module, can construct a science park ecosystem model based on the operational information of each enterprise in the science park, the surrounding environment information, and the planning information within the science park. This allows for a more intuitive understanding of the distribution of enterprises within the science park. Furthermore, by constructing the science park ecosystem model, it is possible to quickly and accurately obtain relevant data on each resident enterprise within the science park. This facilitates the analysis of the development potential of each resident enterprise and the potential factors influencing the development of other resident enterprises within the science park. Compared with existing technologies, it can comprehensively and conveniently obtain enterprise data without relying on manual data acquisition or human experience to assess the development of each enterprise within the science park, thereby improving the accuracy of analyzing the development of each enterprise.

[0059] Furthermore, by utilizing a science park ecosystem model and invoking a pre-defined potential prediction model, the development potential of each resident enterprise can be predicted, thereby determining their potential value. Additionally, based on interaction information among resident enterprises, the potential impact value of each enterprise can be predicted. This allows for a two-pronged evaluation of enterprises within the science park, providing a clear understanding of their development status and interactions, and offering a basis for decision-making in the park's operation and management. Moreover, the development value of the science park can be determined through enterprise potential value and potential impact value, along with the science park's contribution factor to the development index. This enables an assessment of the overall development of the science park. Furthermore, identifying the contribution factor helps pinpoint factors beneficial to the park's development, allowing for the introduction of enterprises matching the park's contribution factor, promoting positive development, and improving the match between introduced enterprises and the park's overall development. The science park operation and management report can also output data including the potential impact value of each resident enterprise, enterprise potential value, the science park's development index, and the science park's contribution factor. This allows users to directly understand the development status within the science park based on the operation and management report, providing a basis for decision-making in the park's operation and management.

[0060] Example 2

[0061] Furthermore, referring to Figure 2 Based on the above embodiments of this application, in another embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, the step of obtaining the interaction information between the various resident enterprises through the science park ecosystem model and generating an interaction network diagram within the science park includes:

[0062] Step A10: Using the science park ecosystem model, determine the enterprise distribution view of each enterprise in the science park and obtain the interaction information between each enterprise.

[0063] Step A20: Obtain the bilateral interaction data between each of the resident enterprises from the interaction information, wherein the bilateral interaction data carries the resident enterprises that conducted the information interaction;

[0064] Step A30: Based on the interaction data between the parties, establish interaction channels between the resident enterprises in the enterprise distribution visualization, and mark the interaction data between the parties on the interaction channels between each pair of resident enterprises to generate the interaction network diagram.

[0065] It should be noted that the enterprise distribution map represents the distribution of enterprises within the science park. The marked position of each enterprise in the enterprise distribution map corresponds to its location within the science park. Bilateral interaction data represents the interaction data between any two enterprises. This data carries the enterprises involved in the information exchange. The interaction channel describes the connection between the two enterprises that have exchanged information. In the enterprise distribution map, the interaction channel can be displayed as a line segment, with the two ends of the line segment representing the enterprises exchanging information. This information exchange can be data exchange or resource exchange. Bilateral data exchange is unidirectional. For example, in the science park, there are enterprises A and B. However, during the development process, only enterprise A obtains resources from enterprise B, while enterprise B does not obtain resources from enterprise A. In this case, the bilateral data exchange between enterprise A and enterprise B is unidirectional. If both enterprises have obtained resources or data from each other, then the two pairs of enterprises can include two bilateral data exchanges. Resources or data can be raw materials needed for the production or operation of the enterprises.

[0066] For example, steps A10 to A30 include: constructing a visual diagram of enterprise distribution for each resident enterprise in the science park using the science park ecosystem model, and obtaining interaction information between each resident enterprise; obtaining two-way interaction data between each pair of resident enterprises from the interaction information, wherein the two-way interaction data carries the resident enterprises that are exchanging information; determining target two-way interaction data in each pair of two-way interaction data; for any target two-way interaction data, finding two resident enterprises in the enterprise distribution diagram that match the target two-way interaction data based on the two resident enterprises carried by the target two-way interaction data, establishing a connection between the two enterprises to obtain an interaction channel; then determining the resident enterprises that supply resources and the resident enterprises that receive resources based on the target two-way interaction data, and determining the interaction direction of the interaction channel between the two enterprises based on the resource supply enterprise and the resource receiving enterprise, wherein the interaction direction is from the resource supply enterprise to the resource receiving enterprise, and marking the target two-way interaction data on the interaction channel. After marking all the two-way interaction data in the interaction information on the enterprise distribution diagram, an interaction network diagram is obtained.

[0067] This application embodiment generates an interactive network map of the science park by generating a science park ecosystem, thereby providing a more intuitive understanding of the development of the science park and making it easier to determine the potential impact value of each resident enterprise.

[0068] In one feasible embodiment, step S30 further includes:

[0069] Step B10: Obtain all target interaction channels of the target interaction enterprise from the interaction network diagram, and determine the target channel value factor of each target interaction channel based on the two-way interaction data on each target interaction channel.

[0070] Step B20: Based on the channel direction of each target interaction channel, classify each target interaction channel to obtain altruistic interaction channels and self-interested interaction channels;

[0071] Step B30: Determine the potential altruistic value based on the number of altruistic interaction channels of the target interactive enterprise and the altruistic channel value factor of each altruistic interaction channel;

[0072] Step B40: Determine the potential value of self-interest based on the number of self-interested interaction channels of the target interactive enterprise and the self-interested channel value factor of each self-interested interaction channel;

[0073] Step B50: Combine the altruistic potential value and the self-interested potential value to obtain the potential impact value.

[0074] It should be noted that the interaction network diagram includes target interactive enterprises, and each target interactive enterprise is marked with a target interactive channel on the diagram. A target interactive enterprise is any enterprise located on the interaction network diagram, and a target interactive channel is an interactive channel related to a target interactive enterprise. A target interactive enterprise may have multiple target interactive channels. Target interactive channels can be divided into altruistic interactive channels and self-interested interactive channels. Altruistic interactive channels are those where the target interactive enterprise provides resources to other enterprises within the science park, while self-interested interactive channels are those where the target interactive enterprise receives resources from other enterprises within the science park. The channel direction represents the direction of resource supply on the target interactive channel. When the target interactive enterprise is a resource supplier, the target interactive channel is classified as an altruistic interactive channel; when the target interactive enterprise is a resource receiver, the target interactive channel is classified as a self-interested interactive channel.

[0075] Altruistic interaction channels are those where the target interacting enterprise is the supplier, while self-interested interaction channels are those where the target interacting enterprise is the receiver. The value factor of a target channel can include both altruistic and self-interested channel value factors. When the target interaction channel is an altruistic influence channel for the target interacting enterprise, the target channel value factor is an altruistic influence factor; conversely, when the target interaction channel is a self-interested influence channel for the target interacting enterprise, the target channel value factor is a self-interested influence factor.

[0076] The target channel value factor represents the impact of data exchanged between the two parties on the development of the target interactive enterprise. The altruistic channel value factor represents the impact of the target interactive enterprise on the receiving enterprises within the altruistic interactive channel. The self-interested channel value factor represents the impact of the target interactive enterprise on the supplying enterprises within the self-interested interactive channel. Both altruistic and self-interested channel value factors can be expressed as the degree of influence. The greater the impact of the target interactive enterprise on the receiving enterprises within the altruistic interactive channel, the greater the altruistic channel value factor; conversely, the greater the impact of the target interactive enterprise on the supplying enterprises within the self-interested interactive channel, the greater the self-interested channel value factor. Altruistic potential value represents the degree of influence the target interactive enterprise has on the development of other enterprises within the science park; the greater the degree of influence, the greater the self-interested potential value. Self-interested potential value represents the degree to which the development of the target interactive enterprise is influenced by other enterprises within the science park; the greater the degree of influence, the greater the altruistic potential value. A target interactive enterprise can have multiple altruistic interactive channels and multiple self-interested interactive channels. The number of altruistic interaction channels refers to the number of altruistic interaction channels of the target enterprise, while the number of self-interested interaction channels refers to the number of self-interested interaction channels of the target enterprise.

[0077] For example, steps B10 to B40 include: obtaining all target interaction channels of the target interaction enterprise from the interaction network diagram, and determining the target channel value factor of each target interaction channel based on the interaction data between the two parties on each target interaction channel; determining the resource interaction identity of the target interaction enterprise based on the channel direction of each target interaction channel, wherein the resource interaction identity represents the identity of the target interaction enterprise on the target interaction channel, and the resource interaction identity can be a resource supplier or a resource receiver; when the resource interaction identity of the target interaction enterprise on the target interaction channel is a resource supplier, the target interaction channel is classified as an altruistic interaction channel; when the resource interaction identity of the target interaction enterprise on the target interaction channel is a resource receiver, the target interaction channel is classified as a self-interested interaction channel; summing the value factors of each altruistic channel to obtain the altruistic value, weighting and summing the altruistic value and the altruistic interaction channel data to obtain the altruistic potential value; summing the value factors of each self-interested channel to obtain the self-interested value, weighting and summing the self-interested value and the self-interested interaction channel data to obtain the self-interested potential value. Any company located within the science park can perform steps B10 through B40 to obtain the potential impact value of the company.

[0078] This application embodiment determines the potential impact value by combining altruistic potential value and self-interest potential value. It assesses the potential impact value of resident enterprises from both altruistic and self-interest perspectives, thereby making the potential impact value more accurate and more conducive to the overall assessment of the development value of resident enterprises.

[0079] In one feasible embodiment, step B10 further includes:

[0080] Step B11: For any of the target interaction channels, obtain the two-way interaction data of the target interaction channel;

[0081] Step B12: Determine the interaction frequency and the interaction feedback data from the interaction data between the two parties. The interaction feedback data includes supply feedback data and receive feedback data.

[0082] Step B13: Determine the intrinsic value of the supply resources and the transformation value of the supply resources from the supply feedback data, and use the ratio of the transformation value of the supply resources to the intrinsic value of the supply resources as the supply value factor;

[0083] Step B14: Determine the received resource intrinsic value and the received resource conversion value from the received feedback data, and use the ratio of the received resource conversion value to the received resource intrinsic value as the received value factor;

[0084] Step B15: Aggregate the supply value factor and the receiving value factor to obtain the feedback value factor;

[0085] Step B16: The target channel value factor is obtained by weighted summation of the interaction frequency and the feedback value factor.

[0086] It should be noted that the interactive data between the two parties includes interaction frequency and interaction feedback data. Interaction frequency refers to the number of times resources are exchanged between any two participating companies. Interaction feedback data refers to the data on the value generated by the resources after the resource exchange between any two participating companies. Interaction feedback data includes supply feedback data and receiving feedback data. Supply feedback data is the data provided by the resource supplier, and receiving feedback data is the data provided by the resource receiver.

[0087] Supply feedback data includes the intrinsic value of supplied resources and the transformed value of supplied resources. The intrinsic value of supplied resources is the cost of the resources supplied by the resource supplier, and the transformed value of supplied resources is the value that the resource supplier receives in return for the resources supplied. Receiving feedback data includes the intrinsic value of received resources and the transformed value of received resources. The intrinsic value of received resources is the cost to the resource receiver for acquiring the resources, and the transformed value of received resources is the value after the resource receiver converts the acquired resources into a finished product. For the same target interaction channel, the intrinsic value of received resources will equal the transformed value of supplied resources. The target interaction channel is any interaction channel on the interaction diagram. The supply value factor represents the level of value obtained by the resource supplier after supplying resources on the target interaction channel; the higher the value obtained, the higher the supply value factor. The receiving value factor represents the level of value transformed by the resource receiver after receiving resources on the target interaction channel; the higher the transformed value, the higher the receiving value factor. Feedback value factors can be used to describe the joint impact of resource interaction between two resident companies on the target interaction channel.

[0088] For example, steps B11 to B16 include: for any of the target interaction channels, acquiring the two-way interaction data of the target interaction channel; determining the interaction frequency and the interaction feedback data from the two-way interaction data, wherein the interaction feedback data includes supply feedback data and reception feedback data; determining the supply resource intrinsic value and supply resource conversion value from the supply feedback data, and using the ratio of the supply resource conversion value to the supply resource intrinsic value as a supply value factor; determining the reception resource intrinsic value and reception resource conversion value from the reception feedback data, and using the ratio of the reception resource conversion value to the reception resource intrinsic value as a reception value factor; summing the supply value factor and the reception value factor on the same target interaction channel to obtain a feedback value factor; and weighted summing the interaction frequency and the feedback value factor to obtain the target channel value factor.

[0089] This application determines the feedback value factor from both the supply and receiving levels, and then determines the target channel value from both the feedback value factor and the interaction frequency level, thereby enabling a more comprehensive determination of the target channel value factor on the target interaction channel.

[0090] Example 3

[0091] Furthermore, referring to Figure 3 Based on the above embodiments of this application, in another embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, the step of determining the science park development index of the science park through the potential value of each enterprise and the potential impact value of each enterprise includes:

[0092] Step C10: Combine the enterprise potential value and the potential impact value of the same resident enterprise to obtain the overall enterprise value of each resident enterprise.

[0093] Step C20: Based on the enterprise type of each enterprise, classify the enterprises in the science park to obtain enterprise category clusters;

[0094] Step C30: Aggregate the overall value of each enterprise in the enterprise category cluster to obtain the category cluster value of each enterprise category cluster;

[0095] Step C40: The values ​​of each of the aforementioned cluster categories are collectively used as the development index of the science and technology park.

[0096] It should be noted that each resident enterprise in the science park ecosystem model has its own corresponding enterprise potential value and potential impact value. By concatenating the potential value and potential impact value of each resident enterprise, the overall enterprise value can be obtained. For example, the potential value and potential impact value can be summed. The overall enterprise value represents the overall development of the resident enterprise, including the enterprise's intrinsic value and its impact value. The overall enterprise value obtained by concatenating the potential value and potential impact value reflects the value of the resident enterprise in multiple dimensions, thus making the prediction of the overall enterprise value more accurate. An enterprise category cluster includes at least one resident enterprise, and all resident enterprises in the enterprise category cluster are of the same type. The science park ecosystem model can include multiple enterprise category clusters. The value of a category cluster is the sum of the overall values ​​of all enterprises in the enterprise category cluster.

[0097] For example, steps C10 to C40 include: concatenating the enterprise potential value and potential impact value of the same resident enterprise to obtain the overall enterprise value of each resident enterprise; classifying the resident enterprises in the science park according to their enterprise types to obtain enterprise category clusters; summing the overall enterprise values ​​of each enterprise category cluster for any enterprise category cluster to obtain the category cluster value of each enterprise category cluster; and using the combined category cluster values ​​as the science park development index. For example, the science park development index can be obtained by summing the values ​​of each category cluster, or by weighted summation of the values ​​of each category cluster. After obtaining the science park development index, a science park value distribution map can be output, which includes the category cluster values ​​corresponding to all enterprise category clusters. This facilitates science park managers' understanding of the development status of various enterprise types within the science park, thereby helping them determine which enterprises to introduce to the science park.

[0098] In one feasible embodiment, step S40 further includes:

[0099] Step D10: Based on the overall value of each of the resident enterprises, select target positive enterprises that are greater than or equal to the preset positive contribution threshold from among the resident enterprises.

[0100] Step D20: Determine the contribution factor of the science park from the target enterprise operation information of the target positive enterprise.

[0101] It should be noted that the preset positive contribution threshold is a critical value for determining the overall value of the target positive enterprise. For example, the preset positive contribution threshold can be determined based on the science park development index and the number of all resident enterprises in the science park. The preset positive contribution threshold can be the ratio of the science park development index to the number of resident enterprises, or any percentage of the science park development index, and can be determined based on the actual situation. The overall value of the target enterprise is the overall value of the target positive enterprise. After determining the target positive enterprise, its operational information can be obtained. Based on the operational information and the overall value of the target enterprise, the science park contribution factor is jointly determined. The target positive enterprise is any resident enterprise whose positive contribution is greater than or equal to the preset positive contribution threshold; there can be multiple target positive enterprises. The operational information of the target enterprise is the operational information of the enterprise corresponding to the target positive enterprise.

[0102] For example, steps D10 to D20 include: obtaining a preset positive contribution threshold; selecting target positive enterprises whose overall value is greater than the preset positive contribution threshold from among the resident enterprises; obtaining the target enterprise operation information of each target positive enterprise; based on the operation information of each target enterprise, counting the number of the same enterprise development stage, enterprise type, enterprise association information, and enterprise structure among each target positive enterprise, respectively obtaining stage distribution, type distribution, association information distribution, and structure distribution; the stage distribution includes the ranking of the number of each enterprise development stage, the type distribution includes the ranking of the number of each enterprise type, the association information distribution includes the ranking of the number of each enterprise association information, and the structure distribution includes the ranking of the number of each enterprise structure. The rankings from high to low are first, second, third, etc., and so on; the rankings from high to low are first, second, third, etc., and so on. In the stage distribution, the top-ranked enterprise development stage is selected as the stage contribution factor; in the type distribution, the top-ranked enterprise type is selected as the type contribution factor; in the related information distribution, the top-ranked enterprise related information is selected as the related information contribution factor; and in the structure distribution, the top-ranked enterprise structure is selected as the structure contribution factor. These stage, type, related, and structure contribution factors are collectively considered as the overall contribution factor to the science park. The stage contribution factor can represent the initial, mid-term, or late-stage development phase; the type contribution factor can represent chip type, process type, etc.; the related contribution factor can represent the scope of influence; and the structure contribution factor can represent the enterprise management structure within the enterprise structure.

[0103] This application embodiment determines the contribution factors of a science and technology park, thereby identifying the factors that have a significant impact on the development of the science and technology park. When introducing enterprises to the science and technology park, it can identify which factors will have a greater positive impact on the development of the science and technology park, and thus select enterprises that are better suited to the development of the science and technology park to settle in.

[0104] Example 4

[0105] Reference Figure 4 This application also provides a CIM-based science park management device, which includes:

[0106] The construction module 10 is invoked to call the CIM module to construct the science park ecosystem model of the science park by using the enterprise operation information of each enterprise in the science park, the surrounding environment information of the science park, and the planning information of the science park.

[0107] The potential value determination module 20 is used to predict the development potential of each of the resident enterprises by calling a preset potential prediction model through the science park ecosystem model, and to obtain the enterprise potential value corresponding to each of the resident enterprises.

[0108] The potential value impact module 30 is used to obtain the interaction information between the resident enterprises through the science park ecosystem model, generate an interaction network diagram within the science park, and determine the potential impact value of each resident enterprise through the interaction network diagram.

[0109] The Science and Technology Park Development Index Determination Module 40 is used to determine the Science and Technology Park Development Index of the Science and Technology Park through the potential value of each enterprise and the potential impact value of each enterprise, and to determine the Science and Technology Park Contribution Factor of the Science and Technology Park Development Index, so as to generate the Science and Technology Park Operation and Management Report of the Science and Technology Park.

[0110] Optionally, the potential value determination module 20 is further configured to:

[0111] For any of the aforementioned resident enterprises, the enterprise development stage, enterprise type, enterprise association information, and enterprise structure of the resident enterprise are obtained through the science and technology park ecosystem model;

[0112] The preset potential prediction model is determined based on the enterprise type;

[0113] The preset potential prediction model predicts the first potential of the resident enterprises based on the enterprise development stage and the enterprise structure, and predicts the second potential of the resident enterprises based on the enterprise association information.

[0114] The enterprise potential value is obtained by combining the first potential and the second potential.

[0115] Optionally, the potential value impact module 30 is further configured to:

[0116] The science park ecosystem model is used to determine the enterprise distribution map of each enterprise in the science park and to obtain the interaction information between each enterprise.

[0117] The interaction data between each of the participating companies is obtained from the interaction information, and the interaction data carries the participating companies that are exchanging information.

[0118] Based on the interaction data between the two parties, an interaction channel is established between the resident enterprises in the enterprise distribution visualization, and the interaction data between the two parties is marked on the interaction channel between each pair of resident enterprises to generate the interaction network diagram.

[0119] Optionally, the potential value impact module 30 is further configured to:

[0120] Obtain all target interaction channels of the target interactive enterprise from the interaction network diagram, and determine the target channel value factor of each target interaction channel based on the two-way interaction data on each target interaction channel.

[0121] Based on the channel direction of each target interaction channel, the target interaction channels are classified into altruistic interaction channels and self-interested interaction channels.

[0122] The potential altruistic value is determined based on the number of altruistic interaction channels of the target interactive enterprise and the altruistic channel value factor of each altruistic interaction channel.

[0123] The potential value of self-interest is determined based on the number of self-interested interaction channels of the target interactive enterprise and the self-interested channel value factor of each self-interested interaction channel.

[0124] By combining the altruistic potential value and the self-interested potential value, the potential impact value is obtained.

[0125] Optionally, the potential value impact module 30 is further configured to:

[0126] For any of the target interaction channels, acquire the interaction data between the two parties in the target interaction channel;

[0127] The interaction frequency and the interaction feedback data are determined from the interaction data between the two parties, wherein the interaction feedback data includes supply feedback data and receive feedback data;

[0128] The intrinsic value of supply resources and the transformation value of supply resources are determined from the supply feedback data, and the ratio of the transformation value of supply resources to the intrinsic value of supply resources is used as the supply value factor.

[0129] The received resource intrinsic value and received resource conversion value are determined from the received feedback data, and the ratio of the received resource conversion value to the received resource intrinsic value is used as the received value factor.

[0130] By aggregating the supply value factor and the receiving value factor, a feedback value factor is obtained;

[0131] The target channel value factor is obtained by weighted summation of the interaction frequency and the feedback value factor.

[0132] Optionally, the science park development index determination module 40 is further used for:

[0133] The enterprise potential value and potential impact value of the same resident enterprise are combined to obtain the overall enterprise value of each resident enterprise.

[0134] Based on the enterprise type of each enterprise, the enterprises in the science and technology park are classified into enterprise category clusters.

[0135] The overall value of each enterprise in the enterprise category cluster is aggregated to obtain the category cluster value of each enterprise category cluster;

[0136] The combined value of each of the aforementioned cluster categories will be used as the development index of the science and technology park.

[0137] Optionally, the science park development index determination module 40 is further used for:

[0138] Based on the overall value of each of the resident enterprises, target positive enterprises with a value greater than or equal to a preset positive contribution threshold are selected from among the resident enterprises.

[0139] The contribution factor of the science park is determined from the target enterprise operation information of the target positive enterprise.

[0140] The CIM-based science park management device provided in this application adopts the CIM-based science park management method in the above embodiments, aiming to solve the technical problems of low matching degree between enterprises to be introduced and enterprises already in the science park, and low operation and efficiency of the science park. Compared with the prior art, the beneficial effects of the CIM-based science park management method provided in this application are the same as those of the CIM-based science park management method provided in the above embodiments, and other technical features in the CIM-based science park management device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0141] Example 5

[0142] This application provides an electronic device, which can be a playback device. The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the CIM-based science park management method in the above embodiments.

[0143] The following is for reference. Figure 5The diagram illustrates a structural schematic of an electronic device suitable for implementing embodiments of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (portable Android devices), PMPs (portable media players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0144] like Figure 5 As shown, an electronic device may include a processing unit (such as a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in ROM (Read-Only Memory) or programs loaded from storage devices into RAM (Random Access Memory). RAM also stores various programs and data required for the operation of the electronic device. The processing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0145] Typically, the following systems can be connected to the I / O interface: input devices such as touchscreens, touchpads, keyboards, mice, image sensors, microphones, tachometers, gyroscopes, etc.; output devices such as LCDs (Liquid Crystal Displays), speakers, vibrators, etc.; storage devices such as magnetic tapes, hard drives, etc.; and communication devices. Communication devices allow electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although electronic devices with various systems are shown in the figures, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0146] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication system, or installed from a storage system, or installed from a ROM. When the computer program is executed by a processing system, it performs the functions defined above in the methods of embodiments of this disclosure.

[0147] The electronic device provided in this application addresses the issues of improving the matching degree between enterprises to be introduced and those already in the science park, as well as the operational services and efficiency of the science park, using the CIM-based science park management method described in Embodiment 1 above. Compared with the prior art, the beneficial effects of the product traffic data allocation provided in this application embodiment are the same as those of the CIM-based science park management method provided in the above embodiments, and other technical features in this CIM-based science park management device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0148] It should be understood that various parts of this disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0149] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0150] Example 6

[0151] This embodiment provides a computer-readable storage medium having computer-readable program instructions stored thereon, which are used to execute the CIM-based science park management method in Embodiment 1 above.

[0152] The computer-readable storage medium provided in this application embodiment may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor devices, apparatuses, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable EPROM (Electrical Programmable Read Only Memory) or flash memory, optical fiber, portable compact disk CD-ROM (compact discread-only memory), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution device, apparatus, or apparatus. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0153] The aforementioned computer-readable storage medium may be included in an electronic device or may exist independently without being assembled into an electronic device.

[0154] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by an electronic device, the electronic device causes the following to occur: Invoke the CIM module to construct a science park ecosystem model based on the operational information of each resident enterprise within the science park, the surrounding environment information of the science park, and the planning information within the science park; Using the science park ecosystem model, invoke a preset potential prediction model to predict the development potential of each resident enterprise, obtaining the potential value of each resident enterprise; Obtain the interaction information between each resident enterprise through the science park ecosystem model, generate an interaction network diagram within the science park, and determine the potential impact value of each resident enterprise through the interaction network diagram; Determine the science park development index based on the potential value of each enterprise and the potential impact value, and determine the science park contribution factor of the science park development index to generate a science park operation and management report.

[0155] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a LAN (local area network) or WAN (wide area network)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0156] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of devices, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based device that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0157] The modules described in the embodiments of this disclosure can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0158] The computer-readable storage medium provided in this application stores computer-readable program instructions for executing the aforementioned CIM-based science park management method, aiming to solve the technical problems of low matching degree between enterprises to be introduced and enterprises already in operation in science parks, as well as low operational services and efficiency in science parks. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the CIM-based science park management method provided in the above embodiments, and will not be repeated here.

[0159] Example 7

[0160] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the CIM-based science park management method described above.

[0161] The computer program product provided in this application aims to solve the technical problems of low matching between enterprises to be introduced and those already in operation in science parks, as well as low operational service and efficiency in science parks. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the CIM-based science park management method provided in the above embodiments, and will not be repeated here.

[0162] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A CIM-based management method for science and technology parks, characterized in that, The CIM-based science park management method includes: The CIM module is invoked to construct a science park ecosystem model of the science park by using the enterprise operation information of each enterprise in the science park, the surrounding environment information of the science park, and the planning information within the science park. By using the aforementioned science and technology park ecosystem model, a preset potential prediction model is invoked to predict the development potential of each of the resident enterprises, thereby obtaining the enterprise potential value corresponding to each of the resident enterprises. By using the science park ecosystem model, the interaction information between the resident enterprises is obtained, an interaction network diagram within the science park is generated, and the potential impact value of each resident enterprise is determined by the interaction network diagram. The science park development index is determined by the potential value of each enterprise and the potential impact value of each enterprise, and the science park contribution factor of the science park development index is determined to generate the science park operation and management report.

2. The CIM-based science park management method as described in claim 1, characterized in that, The enterprise operation information includes the enterprise's development stage, enterprise type, related information, and enterprise structure; The step of predicting the development potential of each resident enterprise by calling a preset potential prediction model through the science park ecosystem model, and obtaining the enterprise potential label corresponding to each resident enterprise, includes: For any of the aforementioned resident enterprises, the enterprise development stage, enterprise type, enterprise association information, and enterprise structure of the resident enterprise are obtained through the science and technology park ecosystem model; The preset potential prediction model is determined based on the enterprise type; The preset potential prediction model predicts the first potential of the resident enterprises based on the enterprise development stage and the enterprise structure, and predicts the second potential of the resident enterprises based on the enterprise association information. The enterprise potential value is obtained by combining the first potential and the second potential.

3. The CIM-based science park management method as described in claim 1, characterized in that, The step of obtaining the interaction information between the resident enterprises through the science park ecosystem model and generating the interaction network diagram within the science park includes: The science park ecosystem model is used to determine the enterprise distribution map of each enterprise in the science park and to obtain the interaction information between each enterprise. The interaction data between each of the listed companies is obtained from the interaction information, and the interaction data carries the information exchanged between the listed companies. Based on the interaction data between the two parties, an interaction channel is established between the resident enterprises in the enterprise distribution visualization, and the interaction data between the two parties is marked on the interaction channel between each pair of resident enterprises to generate the interaction network diagram.

4. The CIM-based science park management method as described in claim 3, characterized in that, The interactive network diagram includes target interactive enterprises, and the target interactive enterprises are marked with target interactive channels on the interactive network diagram; The steps of determining the potential impact value of each of the resident enterprises through the interactive network diagram include: Obtain all target interaction channels of the target interactive enterprise from the interaction network diagram, and determine the target channel value factor of each target interaction channel based on the two-way interaction data on each target interaction channel. Based on the channel direction of each target interaction channel, the target interaction channels are classified into altruistic interaction channels and self-interested interaction channels. The potential altruistic value is determined based on the number of altruistic interaction channels of the target interactive enterprise and the altruistic channel value factor of each altruistic interaction channel. The potential value of self-interest is determined based on the number of self-interested interaction channels of the target interactive enterprise and the self-interested channel value factor of each self-interested interaction channel. By combining the altruistic potential value and the self-interested potential value, the potential impact value is obtained.

5. The CIM-based science park management method as described in claim 4, characterized in that, The interaction data between the two parties includes interaction frequency and interaction feedback data; The step of determining the target channel value factor for each target interaction channel based on the interaction data between the two parties on each target interaction channel includes: For any of the target interaction channels, acquire the interaction data between the two parties in the target interaction channel; The interaction frequency and the interaction feedback data are determined from the interaction data between the two parties, wherein the interaction feedback data includes supply feedback data and receive feedback data; The intrinsic value of supply resources and the transformation value of supply resources are determined from the supply feedback data, and the ratio of the transformation value of supply resources to the intrinsic value of supply resources is used as the supply value factor. The received resource intrinsic value and received resource conversion value are determined from the received feedback data, and the ratio of the received resource conversion value to the received resource intrinsic value is used as the received value factor. By aggregating the supply value factor and the receiving value factor, a feedback value factor is obtained; The target channel value factor is obtained by weighted summation of the interaction frequency and the feedback value factor.

6. The CIM-based science park management method as described in claim 1, characterized in that, The steps for determining the science park development index based on the potential value of each enterprise and the potential impact value of each enterprise include: The enterprise potential value and potential impact value of the same resident enterprise are combined to obtain the overall enterprise value of each resident enterprise. Based on the enterprise type of each enterprise, the enterprises in the science and technology park are classified into enterprise category clusters. The overall value of each enterprise in the enterprise category cluster is aggregated to obtain the category cluster value of each enterprise category cluster; The combined value of each of the aforementioned cluster categories will be used as the development index of the science and technology park.

7. The CIM-based science park management method as described in claim 6, characterized in that, The steps for determining the science park contribution factor of the science park development index include: Based on the overall value of each of the resident enterprises, target positive enterprises with a value greater than or equal to a preset positive contribution threshold are selected from among the resident enterprises. The contribution factor of the science park is determined from the target enterprise operation information of the target positive enterprise.

8. A CIM-based technology park management device, characterized in that, The CIM-based science park management device includes: The construction module is invoked to call the CIM module to construct a science and technology park ecosystem model based on the enterprise operation information of each enterprise in the science and technology park, the surrounding environment information of the science and technology park, and the planning information within the science and technology park. The potential value determination module is used to predict the development potential of each of the resident enterprises by calling a preset potential prediction model through the science park ecosystem model, and to obtain the enterprise potential value corresponding to each of the resident enterprises. The potential value impact module is used to obtain the interaction information between the resident enterprises through the science park ecosystem model, generate an interaction network diagram within the science park, and determine the potential impact value of each resident enterprise through the interaction network diagram. The Science and Technology Park Development Index Determination Module is used to determine the Science and Technology Park Development Index of the Science and Technology Park through the potential value of each enterprise and the potential impact value of each enterprise, and to determine the Science and Technology Park Contribution Factor of the Science and Technology Park Development Index, so as to generate a Science and Technology Park Operation and Management Report.

9. A device, characterized in that, The device includes: At least one processor, the device being an electronic device; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the steps of the CIM-based science park management method according to any one of claims 1 to 7.

10. A medium, characterized in that, The medium is a computer-readable storage medium, on which a program for implementing a CIM-based science park management method is stored. The program for implementing the CIM-based science park management method is executed by a processor to implement the steps of the CIM-based science park management method as described in any one of claims 1 to 7.

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