CN116663854A - Resource scheduling management method, system and storage medium based on intelligent park - Google Patents
Resource scheduling management method, system and storage medium based on intelligent park Download PDFInfo
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Abstract
The invention discloses a resource scheduling management method and system based on an intelligent park, which relate to the technical field of intelligent parks and comprise the following steps: acquiring overlooking image data of a park through a high-altitude image acquisition device; determining an optimal layout point position of a resource providing point in the park based on overlooking image data of the park; distributing resource providing points based on the optimal distribution points of the resource providing points in the park; fitting and calculating the real-time resource demand quantity of each resource demand point; acquiring the number of resource storage in each resource providing point; planning an optimal resource scheduling scheme; and carrying out resource scheduling allocation according to the optimal resource scheduling scheme. The invention has the advantages that: the intelligent analysis planning of the internal optimal resource scheduling scheme of the park is carried out based on the operation data of the park, so that the internal resource allocation cost of the park can be effectively reduced, the intelligent allocation of the internal resources of the park is realized, and the internal management efficiency of the park is improved.
Description
Technical Field
The invention relates to the technical field of intelligent parks, in particular to a resource scheduling management method, a resource scheduling management system and a storage medium based on an intelligent park.
Background
The intelligent park is an intelligent management system established on the basis of park informatization construction, helps the park establish a unified in-pair external service operation platform, improves park service efficiency, promotes offices and living standards of parks to resident enterprises, enables end users to enjoy various convenience and efficiently utilizes energy. And (3) network connection is carried out on each data acquisition point and each equipment control point through the Internet of things technology, and the campus management system stores, analyzes and judges the data by utilizing cloud computing, big data and Internet technology, so as to intelligently allocate resources. Therefore, the problems that information connection among modules of the conventional park management system is not feasible, resources cannot be allocated in a centralized manner, personnel management efficiency is low and the like are solved.
In the operation process of the intelligent park, how to arrange the optimized resource providing point position in the park and how to realize the optimized resource scheduling in the park are technical problems to be solved in the field, and based on the technical problems, the scheme provides a resource scheduling management method, a system and a storage medium based on the intelligent park.
Disclosure of Invention
In order to solve the technical problems, the technical scheme is to provide a resource scheduling management method, a system and a storage medium based on an intelligent park, calculate and determine the optimal layout point of the resource providing point in the park based on the actual topography state of the park, and intelligently analyze and plan the optimal resource scheduling scheme in the park based on the operation data of the park, so that the cost of the allocation of the resources in the park can be effectively reduced, the intelligent allocation of the resources in the park is realized, and the management efficiency in the park is improved.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a resource scheduling management method based on an intelligent park comprises the following steps:
acquiring overlooking image data of a park through a high-altitude image acquisition device;
determining an optimal layout point position of a resource providing point in the park based on overlooking image data of the park;
distributing resource providing points based on the optimal distribution points of the resource providing points in the park;
fitting and calculating the real-time resource demand quantity of each resource demand point based on park operation history data;
acquiring the number of resource storage in each resource providing point;
planning an optimal resource scheduling scheme based on the resource storage quantity in each resource providing point and the real-time resource demand quantity of each resource demand point;
and carrying out resource scheduling allocation according to the optimal resource scheduling scheme.
Preferably, the determining the optimal layout point of the resources providing point in the campus based on the status of the campus specifically includes:
establishing a park terrain simulation model based on the overlooking image data of the park;
setting a plurality of resource demand nodes in a park terrain simulation model based on the actual positions of the resource demand points in the park;
determining a plurality of positions capable of arranging resource providing points based on a park environment, and setting a plurality of resource providing point arranging points in a park terrain simulation model based on the positions capable of arranging the resource providing points;
determining the layout quantity of the resource providing points;
combining a plurality of resource providing point arrangement point groups based on the resource providing point arrangement point positions according to the arrangement quantity of the resource providing points;
setting resource providing point nodes in a park terrain simulation model based on each resource providing point setting point group, and establishing scheduling connection lines between the resource providing point nodes and resource demand nodes to obtain a plurality of scheduling mesh diagrams;
calculating a resource scheduling consumption index of each scheduling mesh map;
and screening a dispatching mesh map with the lowest resource dispatching consumption index, and using a resource providing point set corresponding to the dispatching mesh map as a layout position of the resource providing point.
Preferably, the establishing a scheduling connection line between the resource providing point node and the resource demand node specifically includes:
establishing a scheduling connection line between a resource demand node and each resource providing point node, and obtaining a plurality of scheduling connection lines to be verified, which correspond to the resource demand node;
determining a scheduling difficulty coefficient of each area of the park based on the actual terrain state of the interior of the park, and dividing the interior of the park into a plurality of areas with different scheduling difficulty levels;
calculating the scheduling difficulty index of each scheduling line to be verified through a scheduling difficulty index calculation formula based on the length of the scheduling line to be verified in each area with different scheduling difficulty levels and the scheduling difficulty coefficient of each area;
screening out to-be-verified scheduling connection lines with minimum scheduling difficulty indexes from a plurality of to-be-verified scheduling connection lines corresponding to the resource demand nodes, and taking the to-be-verified scheduling connection lines with minimum scheduling difficulty indexes as scheduling connection lines corresponding to the resource demand nodes;
the scheduling difficulty index calculation formula is as follows:
wherein d is a scheduling difficulty index, m is the total number of areas with different scheduling difficulty levels,a scheduling difficulty coefficient for the region of the jth scheduling difficulty level,>and the length of the scheduling connection line to be verified in the region of the j-th scheduling difficulty level is determined.
Preferably, the calculating the resource scheduling consumption index of each scheduling mesh map specifically includes:
determining a scheduling frequency weight value of each scheduling connection line based on the actual resource demand condition of each resource demand point, wherein the larger the scheduling frequency weight value is, the higher the scheduling frequency of the resource along the scheduling connection line is;
calculating a resource scheduling consumption index of the scheduling mesh map through a consumption index calculation formula based on the degree difficulty index of the scheduling connection line of each scheduling mesh map and the degree difficulty index scheduling frequency weight value of the scheduling connection line of each scheduling connection line;
the consumption index calculation formula is as follows:
in the method, in the process of the invention,resource scheduling cost index for scheduling mesh map, < +.>To schedule the total number of scheduled links in the mesh map,for the scheduling frequency weight value of the ith scheduling link in the scheduling mesh map,/for the scheduling frequency weight value of the ith scheduling link in the scheduling mesh map>And the scheduling difficulty index is the scheduling difficulty index of the ith scheduling connection line in the scheduling mesh map.
Preferably, the calculating the real-time resource demand number of each resource demand point based on the park operation history data specifically includes:
establishing a regression model of the resource demand quantity of each resource demand point with respect to time based on the resource demand historical quantity of each resource demand point in park operation, wherein the regression model is a linear regression model or a nonlinear regression model;
and predicting the resource demand quantity of each resource demand point in the next time period based on a regression model of the resource demand quantity of each resource demand point with respect to time, wherein the resource demand quantity is used as the real-time resource demand quantity of the resource demand point.
Preferably, the planning the optimal resource scheduling scheme based on the number of resource storages in each resource providing point and the number of real-time resource demands of each resource demand point specifically includes:
judging whether the resource storage quantity in the resource providing point can meet the real-time resource demand quantity of all the resource demand points or not based on the real-time resource demand quantity of the resource demand points and the resource storage quantity in the resource providing point, if so, taking the real-time resource demand quantity of each resource demand point as the real-time resource allocation quantity of each resource demand point, and if not, intelligently calculating the real-time resource allocation quantity of each resource demand point according to the scheduling priority of each resource demand point;
generating a plurality of resource scheduling schemes according to the condition of meeting the scheduling allocation condition, and calculating the implementation difficulty index of each resource scheduling scheme;
screening out a resource scheduling scheme with the lowest implementation difficulty index as an optimal resource scheduling scheme;
the scheduling allocation conditional expression specifically includes:
in the method, in the process of the invention,resource amount scheduled to the kth resource demand point for the kth resource providing point, +.>Real-time resource allocation quantity for the first resource demand point,/->Providing the number of resource stores of the point for the kth resource, for>Providing a total number of point-out scheduled resource demand points for a kth resource, +.>A total number of resource providing points for providing resources to the first resource demand point;
the calculation formula of the implementation difficulty index is as follows:
in the method, in the process of the invention,for implementing the difficulty index of resource scheduling scheme, +.>For the total number of resource demand points, +.>And providing a scheduling difficulty index of a scheduling connection line between the point and the point of the first resource demand for the kth resource.
Preferably, the intelligent calculating the real-time resource allocation number of each resource demand point according to the scheduling priority of each resource demand point specifically includes:
establishing a change function of a demand priority value and the resource allocation quantity for each resource demand point according to the resource demand condition of each resource demand point;
establishing a comprehensive resource allocation evaluation function and resource allocation conditions, and calculating the resource allocation quantity of each resource demand point when the comprehensive resource allocation evaluation function takes the maximum value under the resource allocation conditions to serve as the real-time resource allocation quantity of each resource demand point;
the comprehensive evaluation function expression of the resource allocation is as follows:
comprehensive evaluation function for resource allocationIn the numerical expression, the number of the words,allocating comprehensive evaluation functions for resources>Resource allocation quantity for the first resource demand point,/->A change function of the first resource demand point demand priority value and the resource allocation quantity;
the expression of the resource allocation condition is:
in the expression of the resource allocation condition,real-time resource demand quantity for the first resource demand point,/->The total number of resource stores within a point is provided for all resources.
Further, a resource scheduling management system based on an intelligent park is provided, which is used for implementing the resource scheduling management method based on the intelligent park, and the resource scheduling management system based on the intelligent park includes:
the high-altitude image acquisition device is used for acquiring overlooking image data of a park;
the point position layout module is in communication connection with the high-altitude image acquisition device in a wired or wireless mode and is used for determining the optimal layout point position of the resource providing point in the park based on the overlooking image data of the park;
the resource allocation module is electrically connected with the point position layout module and is used for planning an optimal resource scheduling scheme based on the number of resource storage in each resource providing point and the number of real-time resource requirements of each resource requirement point.
Optionally, the point location layout module is internally integrated with:
the modeling unit is used for automatically or manually establishing a park terrain simulation model based on the park overlooking image data;
the resource point location unit is used for setting a plurality of resource demand nodes in the campus topography simulation model based on the actual positions of the resource demand points in the campus;
the point position combining unit is used for combining a plurality of resource providing point arrangement point groups based on the resource providing point arrangement points according to the arrangement quantity of the resource providing points;
the networking unit is used for setting resource providing point nodes in the campus topography simulation model based on each resource providing point setting point group, establishing scheduling connection lines between the resource providing point nodes and resource demand nodes, and obtaining a plurality of scheduling mesh diagrams;
the computing unit is used for computing the resource scheduling consumption index of each scheduling mesh map;
the screening unit is used for screening a scheduling mesh map with the lowest resource scheduling consumption index, and setting a point group with the resource providing point corresponding to the scheduling mesh map as the setting position of the resource providing point;
the resource allocation module is internally integrated with:
the demand prediction unit is used for carrying out fitting calculation on the real-time resource demand quantity of each resource demand point based on park operation historical data;
the data acquisition unit is used for acquiring the resource storage quantity in each resource providing point;
and the allocation planning unit is used for planning an optimal resource scheduling scheme based on the resource storage quantity in each resource providing point and the real-time resource demand quantity of each resource demand point.
Still further, a computer-readable storage medium having a computer-readable program stored thereon, which when called performs the intelligent park-based resource scheduling management method as described above, is also provided.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a resource scheduling management scheme based on an intelligent park, which is characterized in that a park terrain simulation model is built based on a park terrain environment, the position of each resource consumption point is determined based on the park terrain simulation model, the optimal layout point position of a resource supply point is comprehensively calculated by combining a resource scheduling difficulty coefficient caused by the park terrain based on the position and the resource consumption condition of the resource consumption point, and the optimal layout position of the resource supply point can be intelligently planned in the park, so that the minimum operation cost of resource allocation is ensured, and the efficient operation of the intelligent park is realized;
according to the method, the real-time resource demand quantity of each resource demand point is calculated through fitting based on the park operation historical data, resources are comprehensively distributed to the resource consumption points in the park according to the total storage quantity of the resources in the park, meanwhile, an internal resource scheduling scheme is planned according to the scheduling difficulty gap of each scheduling route caused by the topography in the park, optimal resource distribution is achieved when park resource distribution is guaranteed, and operation in an optimal state in the park is guaranteed.
Drawings
FIG. 1 is a flow chart of a resource scheduling management method based on an intelligent park according to the scheme;
FIG. 2 is a flow chart of a method for determining an optimal layout point of a resource providing point in a park in the present solution;
FIG. 3 is a flow chart of a method of establishing a scheduling connection between a resource providing point node and a resource requiring node in the present solution;
FIG. 4 is a flowchart of a method for calculating a resource scheduling cost index of a scheduling mesh map in the present solution;
FIG. 5 is a flow chart of a method for calculating the real-time resource demand number of each resource demand point by fitting in the present solution;
FIG. 6 is a flow chart of a method of planning an optimal resource scheduling scheme in the present scheme;
FIG. 7 is a flow chart of a method for calculating the real-time resource allocation quantity of each resource demand point in the present solution;
fig. 8 is a block diagram of a resource scheduling management system based on an intelligent park according to the present disclosure.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art.
Referring to fig. 1, a resource scheduling management method based on an intelligent park includes:
acquiring overlooking image data of a park through a high-altitude image acquisition device;
determining an optimal layout point position of a resource providing point in the park based on overlooking image data of the park;
distributing resource providing points based on the optimal distribution points of the resource providing points in the park;
fitting and calculating the real-time resource demand quantity of each resource demand point based on park operation history data;
acquiring the number of resource storage in each resource providing point;
planning an optimal resource scheduling scheme based on the resource storage quantity in each resource providing point and the real-time resource demand quantity of each resource demand point;
and carrying out resource scheduling allocation according to the optimal resource scheduling scheme.
Referring to fig. 2, determining an optimal layout point for a resource providing point in a campus based on a status of the campus specifically includes:
establishing a park terrain simulation model based on the overlooking image data of the park;
setting a plurality of resource demand nodes in a park terrain simulation model based on the actual positions of the resource demand points in the park;
determining a plurality of positions capable of arranging resource providing points based on a park environment, and setting a plurality of resource providing point arranging points in a park terrain simulation model based on the positions capable of arranging the resource providing points;
determining the layout quantity of the resource providing points;
combining a plurality of resource providing point arrangement point groups based on the resource providing point arrangement point positions according to the arrangement quantity of the resource providing points;
setting resource providing point nodes in a park terrain simulation model based on each resource providing point setting point group, and establishing scheduling connection lines between the resource providing point nodes and resource demand nodes to obtain a plurality of scheduling mesh diagrams;
calculating a resource scheduling consumption index of each scheduling mesh map;
and screening a dispatching mesh map with the lowest resource dispatching consumption index, and using a resource providing point set corresponding to the dispatching mesh map as a layout position of the resource providing point.
Establishing a park terrain simulation model based on a park terrain environment, determining the position of each resource consumption point based on the park terrain simulation model, comprehensively calculating the optimal layout point position of the resource supply point by combining the resource scheduling difficulty coefficient caused by the park terrain based on the position and the resource consumption condition of the resource consumption point, and intelligently planning the optimal layout position of the resource supply point in the park in the mode, so that the operation cost of resource allocation is ensured to be minimized, and further the efficient operation of an intelligent park is realized;
it can be understood that the resources can be material resources such as emergency materials and equipment scheduling, and for different resource types, the resource providing points are different, and the parameters required to be referred to are different when determining the scheduling connection line and the resource scheduling consumption index;
for material resources such as emergency material and equipment scheduling, the resource providing point is a storage warehouse, the scheduling connection line is a material transportation route between the storage warehouse and the resource consumption point, and the resource scheduling consumption index is mainly referred to the difficulty in using transportation equipment caused by the road state of each section of route in the material transportation route.
Referring to fig. 3, establishing a scheduling connection between a resource providing node and a resource requiring node specifically includes:
establishing a scheduling connection line between a resource demand node and each resource providing point node, and obtaining a plurality of scheduling connection lines to be verified, which correspond to the resource demand node;
determining a scheduling difficulty coefficient of each area of the park based on the actual terrain state of the interior of the park, and dividing the interior of the park into a plurality of areas with different scheduling difficulty levels;
calculating the scheduling difficulty index of each scheduling line to be verified through a scheduling difficulty index calculation formula based on the length of the scheduling line to be verified in each area with different scheduling difficulty levels and the scheduling difficulty coefficient of each area;
screening out to-be-verified scheduling connection lines with minimum scheduling difficulty indexes from a plurality of to-be-verified scheduling connection lines corresponding to the resource demand nodes, and taking the to-be-verified scheduling connection lines with minimum scheduling difficulty indexes as scheduling connection lines corresponding to the resource demand nodes;
the scheduling difficulty index calculation formula is as follows:
wherein d is a scheduling difficulty index, m is the total number of areas with different scheduling difficulty levels,a scheduling difficulty coefficient for the region of the jth scheduling difficulty level,>and the length of the scheduling connection line to be verified in the region of the j-th scheduling difficulty level is determined.
Dividing the interior of the park into a plurality of areas with different scheduling difficulty levels according to the actual state of the interior of the park, wherein the dividing standard can be adjusted according to the type of resources, for example, for the material resources, the dividing standard is the road width of each area, and the applicable transportation instrument scale is adopted;
the length of each section of to-be-verified scheduling connection line in each difficult area is calculated, the scheduling difficulty index of each section of to-be-verified scheduling connection line is comprehensively calculated, the larger the scheduling difficulty index is, the larger the cost and the consumption caused by resource scheduling according to the route are represented, the resource providing point corresponding to the scheduling connection line is the optimal resource providing point of the resource demand node by screening out the to-be-verified scheduling connection line with the lowest scheduling difficulty index, and in the normal operation process in the later stage, the optimal resource providing point is the main point for resource allocation to the resource providing point, and according to the to-be-verified scheduling connection line, the resource scheduling consumption of the resource demand node in the operation process of a park can be truly reflected by taking the to-be-verified scheduling connection line as the scheduling connection line corresponding to the resource demand node.
Referring to fig. 4, calculating the resource scheduling consumption index of each scheduling mesh map specifically includes:
determining a scheduling frequency weight value of each scheduling connection line based on the actual resource demand condition of each resource demand point, wherein the larger the scheduling frequency weight value is, the higher the scheduling frequency of the resource along the scheduling connection line is;
calculating a resource scheduling consumption index of the scheduling mesh map through a consumption index calculation formula based on the degree difficulty index of the scheduling connection line of each scheduling mesh map and the degree difficulty index scheduling frequency weight value of the scheduling connection line of each scheduling connection line;
the consumption index calculation formula is as follows:
in the method, in the process of the invention,resource scheduling cost index for scheduling mesh map, < +.>To schedule the total number of scheduled links in the mesh map,for the scheduling frequency weight value of the ith scheduling link in the scheduling mesh map,/for the scheduling frequency weight value of the ith scheduling link in the scheduling mesh map>And the scheduling difficulty index is the scheduling difficulty index of the ith scheduling connection line in the scheduling mesh map.
The sum of the resource scheduling consumption of each resource demand node in the whole park and the frequency of the resource scheduling is calculated to be used as a resource scheduling consumption index of the whole scheduling network graph, and the larger the index is, the larger the resource scheduling consumption of the scheduling network graph is, and the higher the operation cost is.
Referring to fig. 5, performing fitting calculation on the real-time resource demand number of each resource demand point based on park operation history data specifically includes:
establishing a regression model of the resource demand quantity of each resource demand point with respect to time based on the resource demand historical quantity of each resource demand point in park operation, wherein the regression model is a linear regression model or a nonlinear regression model;
and predicting the resource demand quantity of each resource demand point in the next time period based on a regression model of the resource demand quantity of each resource demand point with respect to time, wherein the resource demand quantity is used as the real-time resource demand quantity of the resource demand point.
Referring to fig. 6, the planning of the optimal resource scheduling scheme based on the number of resource storage in each resource providing point and the number of real-time resource demand in each resource demand point specifically includes:
judging whether the resource storage quantity in the resource providing point can meet the real-time resource demand quantity of all the resource demand points or not based on the real-time resource demand quantity of the resource demand points and the resource storage quantity in the resource providing point, if so, taking the real-time resource demand quantity of each resource demand point as the real-time resource allocation quantity of each resource demand point, and if not, intelligently calculating the real-time resource allocation quantity of each resource demand point according to the scheduling priority of each resource demand point;
generating a plurality of resource scheduling schemes according to the condition of meeting the scheduling allocation condition, and calculating the implementation difficulty index of each resource scheduling scheme;
screening out a resource scheduling scheme with the lowest implementation difficulty index as an optimal resource scheduling scheme;
the scheduling allocation conditional expression specifically includes:
in the method, in the process of the invention,resource amount scheduled to the kth resource demand point for the kth resource providing point, +.>Real-time resource allocation quantity for the first resource demand point,/->Providing the number of resource stores of the point for the kth resource, for>Providing a total number of point-out scheduled resource demand points for a kth resource, +.>A total number of resource providing points for providing resources to the first resource demand point;
the calculation formula of the implementation difficulty index is as follows:
in the method, in the process of the invention,for implementing the difficulty index of resource scheduling scheme, +.>For the total number of resource demand points, +.>And providing a scheduling difficulty index of a scheduling connection line between the point and the point of the first resource demand for the kth resource.
In the operation of the park, when the storage quantity of the resources in all the resource providing points in the park is larger than the real-time resource demand quantity of all the resource demand points, the required resources can be fully allocated to each resource demand point, and when the storage quantity of the resources in all the resource providing points in the park is larger than the real-time resource demand quantity of all the resource demand points
And comprehensively calculating implementation difficulty indexes of each resource scheduling scheme based on the implementation difficulty of scheduling routes between each resource demand point and each resource supply point in the park, wherein the indexes are combined with the scheduling difficulty indexes of the resource scheduling connection lines and the resource scheduling quantity to perform comprehensive calculation, and the larger the indexes are, the greater the implementation difficulty in the actual running process of the resource scheduling scheme is represented.
Referring to fig. 7, performing intelligent calculation on the real-time resource allocation number of each resource demand point according to the scheduling priority of each resource demand point specifically includes:
establishing a change function of a demand priority value and the resource allocation quantity for each resource demand point according to the resource demand condition of each resource demand point;
establishing a comprehensive resource allocation evaluation function and resource allocation conditions, and calculating the resource allocation quantity of each resource demand point when the comprehensive resource allocation evaluation function takes the maximum value under the resource allocation conditions to serve as the real-time resource allocation quantity of each resource demand point;
the comprehensive evaluation function expression of the resource allocation is as follows:
in the expression of the comprehensive evaluation function of the resource allocation,allocating comprehensive evaluation functions for resources>Resource allocation quantity for the first resource demand point,/->A change function of the first resource demand point demand priority value and the resource allocation quantity;
the expression of the resource allocation condition is:
in the expression of the resource allocation condition,real-time resource demand quantity for the first resource demand point,/->The total number of resource stores within a point is provided for all resources.
The method comprises the steps of combining the resource demand conditions of resource demand points, establishing a change function of a demand priority value and a resource allocation quantity, wherein the resource demand priority value of each resource demand point is reduced along with the increase of the quantity of resources allocated to each resource demand point under the normal condition, and comprehensively screening the resource allocation quantity of each resource demand point corresponding to the maximum integral total value of the change function of each demand priority value and the resource allocation quantity, so that a park can keep optimal operation according to the current resource state.
Referring to fig. 8, further, based on the same inventive concept as the resource scheduling management method based on the smart park, the present disclosure further provides a resource scheduling management system based on the smart park, including:
the high-altitude image acquisition device is used for acquiring overlooking image data of the park;
the point position layout module is in communication connection with the high-altitude image acquisition device in a wired or wireless mode and is used for determining the optimal layout point position of the resource providing point in the park based on overlooking image data of the park;
the resource allocation module is electrically connected with the point position layout module and is used for planning an optimal resource scheduling scheme based on the number of resource storage in each resource providing point and the number of real-time resource requirements of each resource requirement point.
The point position layout module is internally integrated with:
the modeling unit is used for automatically or manually establishing a park terrain simulation model based on the park overlooking image data;
the resource point location unit is used for setting a plurality of resource demand nodes in the campus topography simulation model based on the actual positions of the resource demand points in the campus;
the point position combining unit is used for combining a plurality of resource providing point arrangement point groups based on the resource providing point arrangement points according to the arrangement quantity of the resource providing points;
the networking unit is used for setting resource providing point nodes in the campus topography simulation model based on each resource providing point setting point group, establishing scheduling connection lines between the resource providing point nodes and resource demand nodes, and obtaining a plurality of scheduling mesh diagrams;
the computing unit is used for computing the resource scheduling consumption index of each scheduling mesh map;
the screening unit is used for screening the scheduling mesh map with the lowest resource scheduling consumption index, and the resource providing point corresponding to the scheduling mesh map is used as the layout position of the resource providing point.
The resource allocation module is internally integrated with:
the demand prediction unit is used for carrying out fitting calculation on the real-time resource demand quantity of each resource demand point based on park operation historical data;
the data acquisition unit is used for acquiring the resource storage quantity in each resource providing point;
and the allocation planning unit is used for planning an optimal resource scheduling scheme based on the resource storage quantity in each resource providing point and the real-time resource demand quantity of each resource demand point.
The resource scheduling management system based on the intelligent park comprises the following working processes:
step one: the high-altitude image acquisition device acquires overlooking image data of a park;
step two: the modeling unit automatically or manually establishes a park terrain simulation model based on the park overlooking image data;
step three: the resource point location unit sets a plurality of resource demand nodes in a park terrain simulation model based on the actual positions of the resource demand points in the park;
step four: the point position combining unit combines a plurality of resource providing point arrangement point groups based on the resource providing point arrangement points according to the arrangement quantity of the resource providing points;
step five: the networking unit sets resource providing point nodes in a park terrain simulation model based on each resource providing point setting point group, establishes scheduling connection lines between the resource providing point nodes and resource demand nodes, and obtains a plurality of scheduling mesh diagrams;
step six: the calculation unit calculates the resource scheduling consumption index of each scheduling mesh map;
step seven: the screening unit is used for screening a dispatching mesh map with the lowest resource dispatching consumption index, and setting a point group by using the resource providing points corresponding to the dispatching mesh map as the setting positions of the resource providing points;
step eight: the demand prediction unit performs fitting calculation on the real-time resource demand quantity of each resource demand point based on park operation historical data;
step nine: the data acquisition unit acquires the resource storage quantity in each resource providing point;
step ten: the allocation planning unit plans an optimal resource scheduling scheme based on the resource storage quantity in each resource providing point and the real-time resource demand quantity of each resource demand point.
Still further, the present invention also provides a computer readable storage medium having a computer readable program stored thereon, the computer readable program when invoked performing the intelligent park-based resource scheduling management method as described above;
it is understood that the computer readable storage medium may be a magnetic medium, e.g., floppy disk, hard disk, tape; optical media such as DVD; or a semiconductor medium such as a solid state disk SolidStateDisk, SSD, etc.
In summary, the invention has the advantages that: the intelligent analysis planning of the internal optimal resource scheduling scheme of the park is carried out based on the operation data of the park, so that the internal resource allocation cost of the park can be effectively reduced, the intelligent allocation of the internal resources of the park is realized, and the internal management efficiency of the park is improved.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The resource scheduling management method based on the intelligent park is characterized by comprising the following steps of:
acquiring overlooking image data of a park through a high-altitude image acquisition device;
determining an optimal layout point position of a resource providing point in the park based on overlooking image data of the park;
distributing resource providing points based on the optimal distribution points of the resource providing points in the park;
fitting and calculating the real-time resource demand quantity of each resource demand point based on park operation history data;
acquiring the number of resource storage in each resource providing point;
planning an optimal resource scheduling scheme based on the resource storage quantity in each resource providing point and the real-time resource demand quantity of each resource demand point;
and carrying out resource scheduling allocation according to the optimal resource scheduling scheme.
2. The resource scheduling management method based on the intelligent campus as claimed in claim 1, wherein the determining the optimal layout point of the resources providing point in the intelligent campus based on the status of the intelligent campus specifically comprises:
establishing a park terrain simulation model based on the overlooking image data of the park;
setting a plurality of resource demand nodes in a park terrain simulation model based on the actual positions of the resource demand points in the park;
determining a plurality of positions capable of arranging resource providing points based on a park environment, and setting a plurality of resource providing point arranging points in a park terrain simulation model based on the positions capable of arranging the resource providing points;
determining the layout quantity of the resource providing points;
combining a plurality of resource providing point arrangement point groups based on the resource providing point arrangement point positions according to the arrangement quantity of the resource providing points;
setting resource providing point nodes in a park terrain simulation model based on each resource providing point setting point group, and establishing scheduling connection lines between the resource providing point nodes and resource demand nodes to obtain a plurality of scheduling mesh diagrams;
calculating a resource scheduling consumption index of each scheduling mesh map;
and screening a dispatching mesh map with the lowest resource dispatching consumption index, and using a resource providing point set corresponding to the dispatching mesh map as a layout position of the resource providing point.
3. The method for resource scheduling management based on intelligent park according to claim 2, wherein the establishing a scheduling connection between the resource providing node and the resource demand node specifically comprises:
establishing a scheduling connection line between a resource demand node and each resource providing point node, and obtaining a plurality of scheduling connection lines to be verified, which correspond to the resource demand node;
determining a scheduling difficulty coefficient of each area of the park based on the actual terrain state of the interior of the park, and dividing the interior of the park into a plurality of areas with different scheduling difficulty levels;
calculating the scheduling difficulty index of each scheduling line to be verified through a scheduling difficulty index calculation formula based on the length of the scheduling line to be verified in each area with different scheduling difficulty levels and the scheduling difficulty coefficient of each area;
screening out to-be-verified scheduling connection lines with minimum scheduling difficulty indexes from a plurality of to-be-verified scheduling connection lines corresponding to the resource demand nodes, and taking the to-be-verified scheduling connection lines with minimum scheduling difficulty indexes as scheduling connection lines corresponding to the resource demand nodes;
the scheduling difficulty index calculation formula is as follows:
wherein d is a scheduling difficulty index, m is the total number of areas with different scheduling difficulty levels,a scheduling difficulty coefficient for the region of the jth scheduling difficulty level,>and the length of the scheduling connection line to be verified in the region of the j-th scheduling difficulty level is determined.
4. The resource scheduling management method based on the intelligent park according to claim 3, wherein the calculating the resource scheduling consumption index of each scheduling network map specifically includes:
determining a scheduling frequency weight value of each scheduling connection line based on the actual resource demand condition of each resource demand point, wherein the larger the scheduling frequency weight value is, the higher the scheduling frequency of the resource along the scheduling connection line is;
calculating a resource scheduling consumption index of the scheduling mesh map through a consumption index calculation formula based on the degree difficulty index of the scheduling connection line of each scheduling mesh map and the degree difficulty index scheduling frequency weight value of the scheduling connection line of each scheduling connection line;
the consumption index calculation formula is as follows:
in the method, in the process of the invention,resource scheduling cost index for scheduling mesh map, < +.>For scheduling total number of scheduling links in the mesh map, < >>For the scheduling frequency weight value of the ith scheduling link in the scheduling mesh map,/for the scheduling frequency weight value of the ith scheduling link in the scheduling mesh map>And the scheduling difficulty index is the scheduling difficulty index of the ith scheduling connection line in the scheduling mesh map.
5. The resource scheduling management method based on the intelligent park according to claim 4, wherein the performing fitting calculation on the real-time resource demand number of each resource demand point based on the park operation history data specifically comprises:
establishing a regression model of the resource demand quantity of each resource demand point with respect to time based on the resource demand historical quantity of each resource demand point in park operation, wherein the regression model is a linear regression model or a nonlinear regression model;
and predicting the resource demand quantity of each resource demand point in the next time period based on a regression model of the resource demand quantity of each resource demand point with respect to time, wherein the resource demand quantity is used as the real-time resource demand quantity of the resource demand point.
6. The resource scheduling management method based on the intelligent park according to claim 5, wherein the planning the optimal resource scheduling scheme based on the number of resource storages in each resource providing point and the number of real-time resource demands in each resource demand point specifically comprises:
judging whether the resource storage quantity in the resource providing point can meet the real-time resource demand quantity of all the resource demand points or not based on the real-time resource demand quantity of the resource demand points and the resource storage quantity in the resource providing point, if so, taking the real-time resource demand quantity of each resource demand point as the real-time resource allocation quantity of each resource demand point, and if not, intelligently calculating the real-time resource allocation quantity of each resource demand point according to the scheduling priority of each resource demand point;
generating a plurality of resource scheduling schemes according to the condition of meeting the scheduling allocation condition, and calculating the implementation difficulty index of each resource scheduling scheme;
screening out a resource scheduling scheme with the lowest implementation difficulty index as an optimal resource scheduling scheme;
the scheduling allocation conditional expression specifically includes:
in the method, in the process of the invention,resource amount scheduled to the kth resource demand point for the kth resource providing point, +.>Real-time resource allocation quantity for the first resource demand point,/->Providing the number of resource stores of the point for the kth resource, for>Providing points for kth resourcesTotal number of resource demand points scheduled outwards, +.>A total number of resource providing points for providing resources to the first resource demand point;
the calculation formula of the implementation difficulty index is as follows:
in the method, in the process of the invention,for implementing the difficulty index of resource scheduling scheme, +.>For the total number of resource demand points, +.>And providing a scheduling difficulty index of a scheduling connection line between the point and the point of the first resource demand for the kth resource.
7. The resource scheduling management method based on the intelligent park according to claim 6, wherein the intelligent calculation of the real-time resource allocation number of each resource demand point according to the scheduling priority of each resource demand point specifically comprises:
establishing a change function of a demand priority value and the resource allocation quantity for each resource demand point according to the resource demand condition of each resource demand point;
establishing a comprehensive resource allocation evaluation function and resource allocation conditions, and calculating the resource allocation quantity of each resource demand point when the comprehensive resource allocation evaluation function takes the maximum value under the resource allocation conditions to serve as the real-time resource allocation quantity of each resource demand point;
the comprehensive evaluation function expression of the resource allocation is as follows:
in the expression of the comprehensive evaluation function of the resource allocation,the comprehensive evaluation function is allocated for the resources,resource allocation quantity for the first resource demand point,/->A change function of the first resource demand point demand priority value and the resource allocation quantity;
the expression of the resource allocation condition is:
in the expression of the resource allocation condition,real-time resource demand quantity for the first resource demand point,/->The total number of resource stores within a point is provided for all resources.
8. A smart campus-based resource scheduling management system for implementing the smart campus-based resource scheduling management method as claimed in any one of claims 1 to 7, comprising:
the high-altitude image acquisition device is used for acquiring overlooking image data of a park;
the point position layout module is in communication connection with the high-altitude image acquisition device in a wired or wireless mode and is used for determining the optimal layout point position of the resource providing point in the park based on the overlooking image data of the park;
the resource allocation module is electrically connected with the point position layout module and is used for planning an optimal resource scheduling scheme based on the number of resource storage in each resource providing point and the number of real-time resource requirements of each resource requirement point.
9. The intelligent park-based resource scheduling management system of claim 8, wherein the point location layout module is internally integrated with:
the modeling unit is used for automatically or manually establishing a park terrain simulation model based on the park overlooking image data;
the resource point location unit is used for setting a plurality of resource demand nodes in the campus topography simulation model based on the actual positions of the resource demand points in the campus;
the point position combining unit is used for combining a plurality of resource providing point arrangement point groups based on the resource providing point arrangement points according to the arrangement quantity of the resource providing points;
the networking unit is used for setting resource providing point nodes in the campus topography simulation model based on each resource providing point setting point group, establishing scheduling connection lines between the resource providing point nodes and resource demand nodes, and obtaining a plurality of scheduling mesh diagrams;
the computing unit is used for computing the resource scheduling consumption index of each scheduling mesh map;
the screening unit is used for screening a scheduling mesh map with the lowest resource scheduling consumption index, and setting a point group with the resource providing point corresponding to the scheduling mesh map as the setting position of the resource providing point;
the resource allocation module is internally integrated with:
the demand prediction unit is used for carrying out fitting calculation on the real-time resource demand quantity of each resource demand point based on park operation historical data;
the data acquisition unit is used for acquiring the resource storage quantity in each resource providing point;
and the allocation planning unit is used for planning an optimal resource scheduling scheme based on the resource storage quantity in each resource providing point and the real-time resource demand quantity of each resource demand point.
10. A computer-readable storage medium having a computer-readable program stored thereon, wherein the computer-readable storage medium when called performs the intelligent park-based resource scheduling management method of any one of claims 1-7.
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