CN117575370B - Project recommendation method and device based on park material flow - Google Patents
Project recommendation method and device based on park material flow Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention provides a project recommending method and device based on a park material flow, which relate to the technical field of park material flow analysis and comprise the following steps: adding each material flow data corresponding to each enterprise in the current park according to the industry to which each enterprise belongs to obtain first park index current state data; according to project construction scenes of the current park, determining second park index current data, wherein the second park index current data is respectively influenced by material flow data of industries to which each enterprise belongs and is correspondingly and finely classified by material flow data of each industry; and predicting an increment space of each material flow data corresponding to refined classification in each industry of the current park based on a preset index target of each material flow data and current state data of a second park index in the current park, and determining a project recommendation combination of the current park by taking the increment space as an error limit value so as to solve the technical problem that various material flows contained in the park cannot be analyzed.
Description
Technical Field
The invention relates to the technical field of campus material flow analysis, in particular to a project recommendation method and device based on a campus material flow.
Background
The recycling transformation of the park refers to the overall measure of optimizing and upgrading the industrial park according to the principles of reducing the recycling economy, reusing and recycling, and the systematic analysis of sources, sinks and paths of material flows of a specific industrial park within a certain time range is a main process of park material flow analysis.
The current main adoption is that the material flow analysis method is used for tracking and calculating the directions of the materials in the whole process flow, and carrying out value evaluation on the materials from the molecular layer to the material flow in the whole process flow, the technical method for carrying out item selection based on the material flow analysis of the park is very limited in research, and all the material flows in the park cannot be analyzed.
Disclosure of Invention
The invention aims to provide a project recommending method and device based on a park material flow, which are used for relieving the technical problem that various material flows included in the park cannot be analyzed.
In a first aspect, an embodiment of the present invention provides a method for recommending items based on a campus stream, including:
adding each material flow data corresponding to each enterprise in the current park according to the industry to which each enterprise belongs to obtain first park index current state data; the first park index current state data comprises refinement classifications corresponding to each material flow data in each industry; the material streams include energy streams, carbon streams, water streams, and waste streams;
According to the project construction scene of the current park, determining second park index current data according to influences on material flow data of industries to which each enterprise belongs and influences on corresponding refinement classification of each material flow data of each industry;
and predicting an increment space of each material flow data corresponding to refined classification in each industry of the current park based on a preset index target of each material flow data in the current park and the current state data of the second park, and determining a project recommendation combination of the current park by taking the increment space as an error limit value.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where the step of adding each material flow data corresponding to each enterprise according to an industry to which each enterprise belongs to obtain first campus index current status data includes:
determining the total energy consumption of each industry in the current park based on the sum of the total energy consumption of each type of clean energy and the total energy consumption of each type of non-clean energy in the industry to which each enterprise belongs;
determining current state data of indexes of a first park according to the total energy consumption amount of each industry in the current park; wherein the first campus index current status data includes a sum of a total consumption of each type of clean energy in each industry and a total consumption of each type of non-clean energy in each industry.
With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the step of adding each material flow data corresponding to each enterprise according to an industry to which each enterprise belongs to obtain first campus index current status data includes:
determining a total carbon emission for each industry in the current campus based on a sum of the total carbon emission for each type of clean energy and the total carbon emission for each type of non-clean energy for each industry to which each enterprise belongs;
determining first park index current state data according to the total carbon emission amount of each industry in the current park; wherein the first campus index current status data includes a sum of a total amount of carbon emissions of each type of clean energy in each industry and a total amount of carbon emissions of each type of non-clean energy in each industry.
With reference to the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the step of adding each material flow data corresponding to each enterprise according to an industry to which each enterprise belongs to obtain first campus index current status data includes:
determining a water resource source of each industry in the current park based on the summation of the water consumption of circulating water and the new water consumption of the industries of each enterprise;
Determining current status data of indexes of a first park according to water resource sources of each industry in the current park; the first park index current state data is used for representing water resource going of each industry in the current park, and comprises addition of circulating water consumption under each industry, water consumption reserved in process links under each industry, sewage discharge amount under each industry and water consumption.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the step of adding each material flow data corresponding to each enterprise according to an industry to which each enterprise belongs to obtain first campus index current status data includes:
determining the total amount of waste produced by each industry in the current park based on the total amount of waste produced by each industry to which each enterprise belongs;
determining current status data of indexes of a first park according to the total amount of production waste of each industry in the current park; wherein the first campus index presence data includes a sum of an amount of waste of each industry entering a first cycle of the enterprise, an amount of waste of each industry entering a second cycle of the campus, an amount of waste of each industry entering a third cycle of the society, and an amount of waste disposed of by each industry.
With reference to the first aspect, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where, according to a project construction scenario of the current campus, the step of determining second-campus index current status data includes the steps of:
determining a first influence quantity of the project construction scene on the material flow data of each industry to which each enterprise belongs and a second influence quantity of the project construction scene on each material flow data of each industry in a corresponding refined classification according to target project data corresponding to the project construction scene of the current park;
and updating the first park index current state data based on the first influence quantity and the second influence quantity to obtain second park index current state data.
With reference to the first aspect, the embodiment of the present invention provides a sixth possible implementation manner of the first aspect, wherein the step of predicting, based on a preset target for each material flow data in the current campus and the second-campus target current data, an increment space of a refinement class corresponding to each material flow data in each industry of the current campus, and determining, with the increment space as an error limit value, a project recommendation combination of the current campus includes:
Predicting an increment space of each material flow data corresponding to refined classification under each industry of the current park based on a difference value between a preset index target of each material flow data in the current park and the current data of the second park index;
determining the increment space of the refinement classification corresponding to each material flow data of the current park according to the product of the increment space distribution coefficient of the refinement classification corresponding to each material flow data of each industry and the increment space of the refinement classification corresponding to each material flow data of each industry of the current park;
and determining project recommendation combinations meeting the condition requirements in the current park by taking the increment space of the refinement classification corresponding to each material flow data in each industry of the current park and the increment space of the refinement classification corresponding to each material flow data in the current park as constraint conditions of standard error limit values.
In a second aspect, an embodiment of the present invention further provides a project recommendation device based on a campus stream, including:
the first determining module sums the data of each material flow corresponding to each enterprise in the current park according to the industry to which each enterprise belongs to obtain current data of indexes of the first park; the first park index current state data comprises refinement classifications corresponding to each material flow data in each industry; the material streams include energy streams, carbon streams, water streams, and waste streams;
The second determining module is used for determining second park index current data according to the project construction scene of the current park, wherein the second determining module is used for determining the influence on the material flow data of the industries to which each enterprise belongs and the influence on the corresponding refined classification of each material flow data of each industry;
and the recommending module predicts an increment space corresponding to refined classification of each material flow data in each industry of the current park based on a preset index target of each material flow data in the current park and the current state data of the second park, and determines project recommending combination of the current park by taking the increment space as an error limit value.
In a third aspect, an embodiment provides an electronic device, including a memory, a processor, where the memory stores a computer program executable on the processor, and where the processor implements the steps of the method according to any of the foregoing embodiments when the computer program is executed.
In a fourth aspect, embodiments provide a machine-readable storage medium storing machine-executable instructions that, when invoked and executed by a processor, cause the processor to implement the steps of the method of any of the preceding embodiments.
The embodiment of the invention provides a project recommending method and device based on park material flow, which are used for acquiring refined classification corresponding to each material flow data in each industry of a current park, determining the influence on the material flow according to project construction scenes in the park, updating current park index current data, predicting increment space of the refined classification corresponding to each material flow data in each industry of the current park based on the updated park index current data and a preset index target, further determining project recommending combination meeting the requirement of the increment space, and ensuring that more accurate project recommending based on various material flow analysis results in the park is realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an off-grid dispatching method for an industrial park, which is provided by the embodiment of the invention;
FIG. 2 is a flow chart of a material flow risk plan provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of a system for analyzing mass flow in a campus according to an embodiment of the present invention;
FIG. 4 is a flowchart of a method for recommending items based on a campus stream according to an embodiment of the present invention;
fig. 5 is a schematic functional block diagram of a project recommendation device based on campus material flow according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a hardware architecture of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The implementation of the prior art mainly comprises the following two steps, namely, establishing an industrial production flow model according to the transmission of the material flow of the industrial park, and providing an off-grid dispatching method of the industrial park on the premise of considering the uncertainty of the power failure time length, as shown in figure 1; in the industrial solid waste comprehensive utilization industry, dynamic element material flow prediction is performed by adopting a static migration rule based on the material flow analysis result of an industrial park, key flow element flow mass flow is predicted, risk factors are calculated, and a risk plan is given, as shown in fig. 2.
At the data analysis level, the existing industrial park material flow analysis technology mainly focuses on the analysis of solids, liquids, heavy metal elements and fuels, does not carry out comprehensive analysis on all material flows of the industrial park, does not play a substantial role in optimizing and pushing the park development at the analysis result application level, and the project is used as an important part of the operation development of the industrial park, and can efficiently integrate resources only by selecting projects suitable for the industrial park, so that the mutual win-win of the projects and the park is realized.
Based on the above, the project recommending method and device based on the park material flows provided by the embodiment of the invention can analyze various material flows included in the park and apply the project recommending method and device based on the comprehensive park material flow analysis result to obtain a more accurate project recommending result of the park.
For the understanding of this embodiment, first, an item selection system architecture based on campus material flow analysis according to an embodiment of the present invention is described, as shown in fig. 3:
the system comprises a system database, a data input module, a material flow analysis module and a project scheme selection module.
The system database contains basic data required for performing the analysis, the basic data including at least index current data of the campus, material flow data of the campus, and project data of the enterprise. The index current state data comprise on-board industrial increment value, construction land area, construction output rate, total energy consumption, clean energy consumption proportion, carbon dioxide emission of unit industrial increment value, total water resource consumption, repeated water consumption of industrial enterprises with more than one scale, comprehensive utilization of general industrial solid waste and other optional park index data; other optional park index data include total energy consumption of unit industrial increment value, total water resource consumption of unit industrial increment value, and the like; the material flow data comprise the industries of all regular enterprises in the park, the industrial increment value, the input amount of main resources (water resources and energy sources), the discharge amount of waste (industrial wastewater and general industrial solid waste), the cyclic utilization amount (water resource cyclic utilization amount and general industrial solid waste cyclic utilization amount); the project data of the campus enterprise comprises project categories, planned construction periods, resource consumption and expected benefits of all project types, project categories, construction periods, resource consumption and running benefits of the constructed/built projects, which are available to the system.
The data input module sets a target condition for park development required by material flow analysis and a tolerable error limit; the relevant input data of the data input module is used for calculation of the material flow analysis module; the target conditions include campus index target data and industry growth target data.
The material flow analysis module is used for executing a material flow analysis algorithm and carrying out operation analysis on the input related data. The operation of the related data relates to four types of energy source flow, carbon flow, water resource flow and waste flow, and each type of material flow needs to be subjected to operation analysis operation in three stages of current situation analysis, existing newly built project scene analysis and recommended project combination prediction scene analysis to obtain recommended project combination.
The project scheme selection module is used for further comparing and screening recommended project combinations provided by the material flow analysis to obtain project combinations meeting the overall development goal of the park, and outputting project scheme reports.
The following describes in detail a method for recommending projects using the above-mentioned campus flow analysis architecture, namely a method for recommending projects based on a campus flow, which mainly includes the following steps, as shown in fig. 4:
And step S102, adding each material flow data corresponding to each enterprise in the current park according to the industry to which each enterprise belongs to obtain first park index current state data.
The first park index current state data comprises refinement classification corresponding to each material flow data in each industry; the material streams include energy streams, carbon streams, water streams, and waste streams; for example, each industry energy source corresponds to a variety of energy classifications.
And step S104, determining second park index current data according to project construction scenes of the current park, wherein the second park index current data are respectively determined according to influences on material flow data of industries to which each enterprise belongs and influences on corresponding refinement classification of each material flow data under each industry.
Here, project construction scenarios may be understood as the engineering project set to be constructed, being constructed and/or newly established existing in the campus; the inventor researches and discovers that in order to ensure the accuracy of the recommendation of the campus project, the influence of the material flow of the project needs to be considered in the future.
And S106, predicting an increment space of each material flow data corresponding to refined classification in each industry of the current park based on the preset index target of each material flow data and the current data of the second park index in the current park, and determining the project recommendation combination of the current park by taking the increment space as an error limit value.
According to the current status data of the index of the park, an increment space corresponding to the refined classification of each material flow data in each industry can be predicted, and project recommendation combinations which can meet the material flow data requirements are determined based on the increment space.
In a preferred embodiment of practical application, the refined classification corresponding to each material flow data in each industry of the current park is obtained, the influence on the material flow is determined according to project construction scenes in the park, the current park index current state data is updated, each of the current park is predicted based on the updated park index current state data and a preset index target, the increment space of the refined classification corresponding to each material flow data in the industry is further determined, and then project recommendation combination meeting the requirement of the increment space is determined, so that more accurate project recommendation can be realized based on various material flow analysis results in the park.
Before step S102, in order to ensure that the application of the embodiment of the present invention is more complete, the method further includes:
step 1.1), configuring a system database, and importing basic data required for performing material flow analysis into the system database.
Step 1.2), a preset index target and an industry growth target of a park aiming at each material flow data in the current park are obtained.
Here, a park index target is provided, necessary park index targets are input, and the system calculates remaining index targets from the relation between indexes and stores the calculated remaining index targets in a database. Industry growth goals are also provided and stored in a database.
Among the necessary campus index targets are: the industrial increment value, the construction land area, the total energy consumption, the carbon dioxide emission, the total water resource consumption, the repeated water utilization rate of industrial enterprises with the above scale, the comprehensive utilization amount of general industrial solid waste and the comprehensive utilization rate of general industrial solid waste are increased. Industry growth targets are on-board industry increase value-to-ratio targets for each industry in the campus.
In practical application, step S102 summarizes the enterprise material flow data into industry material flow data, and performs a correlation operation on the industry material flow data and the campus index current status data, so as to construct an "index-material flow" correlation equation model, and further implement a campus material flow current status analysis according to the campus index current status data and the campus material flow data; for different substance flow data types, a corresponding index-substance flow correlation equation model is built, specifically as follows:
for energy sources:
Wherein,for the total energy consumption of each industry at present +.>For the current i-type clean energy consumption total amount of the j-th industry +.>Is the total consumption amount of i' type unclean energy in the j industry at present>Is the total consumption amount of various energy varieties at present>For the current consumption total amount of the i-th clean energy in the j-th industry, +.>For the current consumption total amount of i' type unclean energy in j industry, ++>For the i-th clean energy coal index, all energy units are calculated according to the standard coal,/-for the clean energy coal index>For the i' type unclean energy index coal coefficient, all energy units are counted according to the index coal, < >>For the total amount of i-th clean energy consumption, < >>Is the total consumption amount of i' type unclean energy,iin order to clean the quantity of energy varieties,i=1,2,3，……，n，i'is the quantity of non-clean energy varieties,i'=1,2,3，……，n'，jfor the number of industries to be used,j=1,2,3，……，m，/>specific gravity is consumed for clean energy.
It should be noted that, based on the total consumption amount of clean energy of each type in the industry to which each enterprise belongsAnd total consumption of non-clean energy of each type->Determining the total energy consumption per industry in the current campus +.>The method comprises the steps of carrying out a first treatment on the surface of the Here, based onAccording to the energy consumption total amount of each industry in the current park, determining the current status data of the index of the first park +. >The method comprises the steps of carrying out a first treatment on the surface of the Wherein the first campus index current status data comprises the consumption total amount of each type of clean energy in each industry>And the total consumption of each type of non-clean energy source in each industry>Is added to the sum of (3).
For carbon flow:
wherein,for the total carbon emission of each industry at present +.>Is the total carbon emission amount of various energy varieties at present, < >>Carbon emission coefficient for i-th clean energy, +.>The carbon emission coefficient of the i 'type non-clean energy is i the number of clean energy varieties, i=1, 2,3, … …, n, i' the number of non-clean energy varieties, i '=1, 2,3, … …, n', j the industry number, j=1, 2,3, … …, m.
It should be noted that, based on the sum of the total carbon emission of each type of clean energy and the total carbon emission of each type of non-clean energy in the industries to which each enterprise belongs, the total carbon emission of each industry in the current park is determinedThe method comprises the steps of carrying out a first treatment on the surface of the Based on->Determining first campus index present data based on the total carbon emissions of each industry in the current campus +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the current situation of the index of the first parkThe data includes the sum of the total amount of carbon emissions per industry for each type of clean energy source and the total amount of carbon emissions per industry for each type of non-clean energy source.
For water flow:
Wherein,is a water resource source of various industries, and is divided into circulating water and fresh water, and is prepared from the following materials (by weight portion)>Is->Circulating water consumption of individual industries,/->Is->New water consumption of individual industries is summarized from enterprise data>For the water resource of each industry ∈>Is->The water content of the individual industry, which remains in the process step, < >>Is->The sewage discharge of individual industries is summarized by enterprise data to obtain +.>Is->Water consumption of individual industries, < >>Is->Personal industry->Sub-circulation water consumption is obtained by summarizing enterprise data>Is->The water consumption coefficient of each industry is obtained by summarizing enterprise data>Is->Water usage in individual industries.
It will be appreciated that the water resource source for each industry in the current campus is determined based on the sum of the water usage of the circulating water and the new water usage of the industry to which each enterprise belongsThe method comprises the steps of carrying out a first treatment on the surface of the According to->Can determine the first campus index present data based on the water resource source of each industry in the current campus +.>The method comprises the steps of carrying out a first treatment on the surface of the The first park index current state data is used for representing water resource going of each industry in the current park, and comprises the sum of circulating water consumption in each industry, process link reserved water consumption in each industry, sewage discharge amount in each industry and water consumption.
For waste streams:
wherein,for the total amount of waste production of each industry->Is->The production waste of individual industries is summarized by enterprise data to obtain +.>Treatment amount for various wastes>Is->The waste amount of the individual industries entering the enterprise small circulation is obtained by the enterprise data summarization,is->The amount of waste circulated by the individual industry into the campus is summarized from the enterprise data, +.>Is->The waste amount of the individual industries entering the social major cycle is obtained by summarizing enterprise data, and the individual industries are in the form of +.>Is->The amount of waste treated by individual industry processes, obtained by summarizing enterprise data,/->Is used for comprehensively utilizing various wastes.
It should be noted that, based on the total amount of waste produced in the industry to which each enterprise belongs, the total amount of waste produced in each industry in the current park is determinedThe method comprises the steps of carrying out a first treatment on the surface of the According to->Can determine the first campus index present data based on the total amount of production waste per industry in the present campus>The method comprises the steps of carrying out a first treatment on the surface of the Wherein the first campus index presence data includes a sum of an amount of waste of each industry entering a first cycle of the enterprise, an amount of waste of each industry entering a second cycle of the campus, an amount of waste of each industry entering a third cycle of the society, and an amount of waste disposed of by each industry process.
Based on the foregoing embodiment, the existing new project scenario material flow analysis is performed according to the determined new project data in the campus material flow data and the project data, to obtain the material flow data and the campus index data in the scenario, and the "index-material flow" correlation equation model constructed in the foregoing embodiment step is updated, specifically, step S104 includes:
Step 2.1), according to target project data corresponding to project construction scenes of the current park, determining first influence amounts of the project construction scenes on material flow data of industries to which each enterprise belongs respectively and second influence amounts of the project construction scenes on refinement classification corresponding to each material flow data of each industry.
And 2.2) updating the first park index current state data based on the first influence quantity and the second influence quantity to obtain second park index current state data.
Introducing a newly built project scene, namely considering the project influence which is explicitly built or under construction, and adding the energy consumption caused by the project on both sides of a current equation in different varieties and industries to obtain a second equation relation; wherein for the energy source stream:
wherein,for the total energy consumption of each industry of newly-built projects, < + >>For the total consumption amount of various energy varieties of new projects, < > for new projects>For the total consumption amount of the i-th clean energy in the newly-built project of the j-th industry,/the total consumption amount of the i-th clean energy is->For the total consumption amount of i' type non-clean energy in the newly-built project of the j industry, the method comprises the steps of ++>For the consumption total amount of new projects of the ith clean energy source in the jth industry, ++>And (3) the total consumption of new projects in the j industry for the i' type non-clean energy.
For carbon flow:
wherein,for the total carbon emission of each industry of new projects, < +.>The total carbon emission amount of each industry of the newly-built project.
For water flow:
wherein,water resource sources of newly added items are determined for various industries,/->Is->The individual industry has determined the circulating water usage of the newly added project,/-for>Is->The individual industry has determined the new water usage of the newly added item,/->The water resource of the newly added project is determined to go to +.>Is->The individual industries have determined the sewage discharge of the newly added project,/-for>Is->The individual industry has determined that the newly added project remains the water quantity in the process link, < >>Is->The individual industry has determined the water consumption of the newly added project, < >>Is->The individual industry has determined the new project +.>Water consumption of secondary circulation>Is->The individual industry has determined the water loss factor of the newly added item,/->Is->The individual industry has determined the total water usage of the newly added project.
For waste streams:
wherein,the total amount of production waste of new projects is determined for each industry,/->Is->The individual industry has established the production waste of new projects,/->Treatment capacity for various kinds of waste for which newly created project has been determined, < > for>Is->The individual industry has determined the amount of waste of new projects into the enterprise's small loop,/- >Is->The individual industry has determined the amount of waste recycled into the campus for new projects +.>Is->The individual industry has established new constructionThe amount of waste of the project into the social major cycle, +.>Is->The individual industry has determined the amount of waste treated by the new project,/-for>The comprehensive utilization amount of various wastes for the established new projects is determined.
In some embodiments, step S106 calls an "index-material flow" association model under the existing newly-built project scenario according to the campus index target data and the industry growth target data, predicts industry material flow data, i.e. incremental space, for a period of time in the future, obtains input resource allowance data and output benefit demand data of each industry according to the current industry material flow data, determines recommended project combinations capable of meeting the requirements under tolerable error limits, and can obtain a plurality of recommended project combination schemes and corresponding "index-material flow" association models thereof.
Step 3.1), predicting the increment space of each material flow data corresponding to the refined classification in each industry of the current park based on the difference value of the preset index target of each material flow data and the current state data of the second park.
And 3.2) determining the increment space of the refinement classification corresponding to each material flow data of the current park according to the product of the increment space distribution coefficient of the refinement classification corresponding to each material flow data of each industry and the increment space of the refinement classification corresponding to each material flow data of the current park.
Step 3.3), determining project recommendation combinations meeting the condition requirements in the current park by taking the increment space of the refinement classification corresponding to each material flow data in each industry of the current park and the increment space of the refinement classification corresponding to each material flow data in the current park as constraint conditions of standard error limit values.
Illustratively, for the energy source stream:
/>
wherein the method comprises the steps of，T E For the purpose of consuming an incremental space for energy,total energy consumption specified for the target, +.>For the energy increment space of the j-th industry, < >>And (5) distributing coefficients for the energy increment space of the j-th industry.
Under the t project combination scheme, the total energy consumption of each industry cannot exceed the energy increment space corresponding to the industry; the total energy consumption under the current situation, the newly-built project and the t-th project combination scheme cannot exceed the total energy consumption specified by the index target; the specific gravity of the clean energy consumption must not be lower than the limit value requirement, namely:
Wherein,total energy consumption for the t-th item combination scheme,/->Is the total consumption amount of the i-th clean energy source in the j-th industry project in the t-th project combination scheme,/for the j-th industry project>The energy consumption total amount of the i' th type of non-clean energy consumption in the jth industry project in the jth project combination scheme, E is the current situation, the new project and the energy consumption total amount under the jth project combination scheme,for the allowable error limit +.>For the allowable error limit +.>In order to allow for the margin of error,lfor clean energy consumption specific gravity limit value +.>The total energy consumption under the finally determined project combination scheme is calculated.
For carbon flow:
wherein, E for carbon emission increment space, +.>Carbon emissions prescribed for the target +.>Incremental space for carbon emissions for the j-th industry, +.>And (5) distributing coefficients for the carbon emission increment space of the j-th industry.
Under the t project combination scheme, the carbon emission of each industry cannot exceed the corresponding carbon emission increment space of the industry; the carbon emission under the current situation, the newly built project and the t project combination scheme cannot exceed the carbon emission specified by the index target, namely:
wherein,for the carbon emission under the t item combination scheme, C is the current situation, the newly built item and the carbon emission under the t item combination scheme, +. >For the allowable error limit +.>For the allowable error limit +.>Total carbon emissions for the final project plan.
For water flow:
wherein,T W in order to increase the space with fresh water,the total amount of fresh water prescribed for the target, owner input, < ->Incremental space for new water for the j-th industry,>and (5) distributing the coefficients for the new water increment space of the j-th industry.
Wherein,for reuse water rate limit->For new water under the combination scheme of the t item of the j-th industry, +.>To allow error limit +.>To allow error limit +.>To allow error limit +.>For new water under the combination scheme of item t,/water consumption>Is the circulating water consumption under the t-th project combination scheme.
For waste streams:
/>
wherein,T D an incremental space is created for the waste,input of owner for comprehensive utilization of various wastes specified in the index target>Increment space for waste production of jth industry,/->Incremental space allocation coefficients are generated for waste of the jth industry.
Wherein,waste yield for the t-th project regimen, < ->Is the production waste of the jth industry under the project scheme of the jth,for the comprehensive utilization amount of wastes of the jth industry under the project scheme of the t th project, +. >For the comprehensive utilization amount of various wastes under the t-th project scheme, < > the method>For the allowable error limit +.>For the allowable error limit +.>For the allowable error limit +.>For waste recycling rate limit, < >>Comprehensive recycling rate of wastes for recommended project scheme, </i >>The comprehensive recycling amount of the waste is recommended to project scheme.
It should be noted that, the energy consumption target (and the clean energy ratio requirement) determined by the upper planning or the related management requirement is used as the upper limit of the total energy consumption of the enterprise in the energy source analysis in the future, and a difference value, that is, the energy consumption increment space (and the increment space of each energy variety obtained according to the clean energy ratio requirement) in the next several years can be obtained by calculating the current situation of the energy consumption target and the total energy consumption. At this time, an error limit is regulated by the increment space, then projects are matched from a project library, and the increment space is filled according to the requirements of index targets and the consumption of different energy varieties required by the projects and different industries to which the projects belong. So that the several items with the established equations in step S106 are the item combinations obtained by screening, more than one item combinations may be needed for further sorting.
On the basis of the embodiment, the recommended project combination subjected to the material flow analysis can meet the resource environment constraint under the existing data scene, further judge the meeting of the industrial index of the recommended project combination scene according to the economic index requirements such as the industrial increment value, the construction output rate and the like, screen the recommended project scheme meeting the integral development target of the park, and arrange the recommended project schemes according to the index expression descending order if a plurality of project combinations exist. And outputting a project scheme report, and ending the flow.
According to the embodiment of the invention, the index-material flow correlation model is constructed through experience data, so that the general garden index target can be disassembled into the resource input constraint and the output benefit requirement of the industry level, more specific and accurate project recommendation is realized, and a result-oriented feedback can be used for helping a garden manager to set the garden index target more reasonably so as to improve the fine management level of the garden.
As shown in fig. 5, an embodiment of the present invention provides a project recommendation device based on campus material flows, including:
the first determining module sums the data of each material flow corresponding to each enterprise in the current park according to the industry to which each enterprise belongs to obtain current data of indexes of the first park; the first park index current state data comprises refinement classifications corresponding to each material flow data in each industry; the material streams include energy streams, carbon streams, water streams, and waste streams;
the second determining module is used for determining second park index current data according to the project construction scene of the current park, wherein the second determining module is used for determining the influence on the material flow data of the industries to which each enterprise belongs and the influence on the corresponding refined classification of each material flow data of each industry;
And the recommending module predicts an increment space corresponding to refined classification of each material flow data in each industry of the current park based on a preset index target of each material flow data in the current park and the current state data of the second park, and determines project recommending combination of the current park by taking the increment space as an error limit value.
In some embodiments, the first determining module is further specifically configured to determine a total energy consumption amount of each industry in the current campus based on a sum of a total energy consumption amount of each type of clean energy and a total energy consumption amount of each type of non-clean energy in the industry to which each enterprise belongs; determining current state data of indexes of a first park according to the total energy consumption amount of each industry in the current park; wherein the first campus index current status data includes a sum of a total consumption of each type of clean energy in each industry and a total consumption of each type of non-clean energy in each industry.
In some embodiments, the first determining module is further specifically configured to determine a total carbon emission amount for each industry in the current campus based on a sum of a total carbon emission amount for each type of clean energy source and a total carbon emission amount for each type of non-clean energy source in the industry to which each enterprise belongs; determining first park index current state data according to the total carbon emission amount of each industry in the current park; wherein the first campus index current status data includes a sum of a total amount of carbon emissions of each type of clean energy in each industry and a total amount of carbon emissions of each type of non-clean energy in each industry.
In some embodiments, the first determining module is further specifically configured to determine a water resource source of each industry in the current campus based on a sum of a circulating water usage amount and a new water usage amount of the industry to which each enterprise belongs; determining current status data of indexes of a first park according to water resource sources of each industry in the current park; the first park index current state data is used for representing water resource going of each industry in the current park, and comprises addition of circulating water consumption under each industry, water consumption reserved in process links under each industry, sewage discharge amount under each industry and water consumption.
In some embodiments, the first determining module is further specifically configured to determine a total amount of production waste for each industry in the current campus based on a total amount of production waste for each industry to which each enterprise belongs; determining current status data of indexes of a first park according to the total amount of production waste of each industry in the current park; wherein the first campus index presence data includes a sum of an amount of waste of each industry entering a first cycle of the enterprise, an amount of waste of each industry entering a second cycle of the campus, an amount of waste of each industry entering a third cycle of the society, and an amount of waste disposed of by each industry.
In some embodiments, the second determining module is further specifically configured to determine, according to target project data corresponding to a project construction scenario of the current campus, a first influence amount of the project construction scenario on material flow data of industries to which each enterprise belongs, and a second influence amount of each material flow data of each industry corresponds to a refinement classification; and updating the first park index current state data based on the first influence quantity and the second influence quantity to obtain second park index current state data.
In some embodiments, the recommendation module is further specifically configured to predict an incremental space of the current campus corresponding to the refined classification of each material flow data in each industry based on a difference between a preset index target for each material flow data in the current campus and the current status data of the second campus index;
determining the increment space of the refinement classification corresponding to each material flow data of the current park according to the product of the increment space distribution coefficient of the refinement classification corresponding to each material flow data of each industry and the increment space of the refinement classification corresponding to each material flow data of each industry of the current park; and determining project recommendation combinations meeting the condition requirements in the current park by taking the increment space of the refinement classification corresponding to each material flow data in each industry of the current park and the increment space of the refinement classification corresponding to each material flow data in the current park as constraint conditions of standard error limit values.
In the embodiment of the present invention, the electronic device may be, but is not limited to, a personal computer (PersonalComputer, PC), a notebook computer, a monitoring device, a server, or other computer devices with analysis and processing capabilities.
As an exemplary embodiment, referring to fig. 6, an electronic device 110 includes a communication interface 111, a processor 112, a memory 113, and a bus 114, the processor 112, the communication interface 111, and the memory 113 being connected by the bus 114; the memory 113 is used for storing a computer program supporting the processor 112 to execute the method, and the processor 112 is configured to execute the program stored in the memory 113.
The machine-readable storage medium referred to herein may be any electronic, magnetic, optical, or other physical storage device that can contain or store information, such as executable instructions, data, or the like. For example, a machine-readable storage medium may be: RAM (random access memory), volatile memory, non-volatile memory, flash memory, a storage drive (e.g., hard drive), any type of storage disk (e.g., optical disk, dvd, etc.), or a similar storage medium, or a combination thereof.
The non-volatile medium may be a non-volatile memory, a flash memory, a storage drive (e.g., hard drive), any type of storage disk (e.g., optical disk, dvd, etc.), or a similar non-volatile storage medium, or a combination thereof.
It can be understood that the specific operation method of each functional module in this embodiment may refer to the detailed description of the corresponding steps in the above method embodiment, and the detailed description is not repeated here.
The computer readable storage medium provided by the embodiments of the present invention stores a computer program, where the computer program code may implement the method described in any of the foregoing embodiments when executed, and the specific implementation may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In addition, in the description of embodiments of the present invention, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (8)
1. A method of item recommendation based on a campus stream, comprising:
adding each material flow data corresponding to each enterprise in the current park according to the industry to which each enterprise belongs to obtain first park index current state data; the first park index current state data comprises refinement classifications corresponding to each material flow data in each industry; the material streams include energy streams, carbon streams, water streams, and waste streams;
according to the project construction scene of the current park, determining second park index current data according to influences on material flow data of industries to which each enterprise belongs and influences on corresponding refinement classification of each material flow data of each industry; the project construction scene is a project to be built matching, a project under construction matching and/or a newly built project matching existing in the current park;
predicting an increment space of each material flow data corresponding to refined classification in each industry of the current park based on a preset index target of each material flow data in the current park and the current state data of the second park, and determining a project recommendation combination of the current park by taking the increment space as an error limit value;
According to the project construction scenario of the current campus, determining second-campus index current status data according to the influence on the material flow data of the industries to which each enterprise belongs and the influence on the corresponding refinement classification of each material flow data of each industry, wherein the method comprises the following steps:
determining a first influence quantity of the project construction scene on the material flow data of each industry to which each enterprise belongs and a second influence quantity of the project construction scene on each material flow data of each industry in a corresponding refined classification according to target project data corresponding to the project construction scene of the current park;
updating the first campus index current status data based on the first influence quantity and the second influence quantity to obtain second campus index current status data;
predicting an increment space of each material flow data corresponding to refined classification in each industry of the current park based on a preset index target of each material flow data and the second park index current data in the current park, and determining a project recommendation combination of the current park by taking the increment space as an error limit value, wherein the step comprises the following steps:
predicting an increment space of each material flow data corresponding to refined classification under each industry of the current park based on a difference value between a preset index target of each material flow data in the current park and the current data of the second park index;
Determining the increment space of the refinement classification corresponding to each material flow data of the current park according to the product of the increment space distribution coefficient of the refinement classification corresponding to each material flow data of each industry and the increment space of the refinement classification corresponding to each material flow data of each industry of the current park;
and determining project recommendation combinations meeting the condition requirements in the current park by taking the increment space of the refinement classification corresponding to each material flow data in each industry of the current park and the increment space of the refinement classification corresponding to each material flow data in the current park as constraint conditions of standard error limit values.
2. The method of claim 1, wherein the step of summing each material flow data corresponding to each business according to the industry to which each business belongs to obtain first campus index presence data comprises:
determining the total energy consumption of each industry in the current park based on the sum of the total energy consumption of each type of clean energy and the total energy consumption of each type of non-clean energy in the industry to which each enterprise belongs;
determining current state data of indexes of a first park according to the total energy consumption amount of each industry in the current park; wherein the first campus index current status data includes a sum of a total consumption of each type of clean energy in each industry and a total consumption of each type of non-clean energy in each industry.
3. The method of claim 1, wherein the step of summing each material flow data corresponding to each business according to the industry to which each business belongs to obtain first campus index presence data comprises:
determining a total carbon emission for each industry in the current campus based on a sum of the total carbon emission for each type of clean energy and the total carbon emission for each type of non-clean energy for each industry to which each enterprise belongs;
determining first park index current state data according to the total carbon emission amount of each industry in the current park; wherein the first campus index current status data includes a sum of a total amount of carbon emissions of each type of clean energy in each industry and a total amount of carbon emissions of each type of non-clean energy in each industry.
4. The method of claim 1, wherein the step of summing each material flow data corresponding to each business according to the industry to which each business belongs to obtain first campus index presence data comprises:
determining a water resource source of each industry in the current park based on the summation of the water consumption of circulating water and the new water consumption of the industries of each enterprise;
determining current status data of indexes of a first park according to water resource sources of each industry in the current park; the first park index current state data is used for representing water resource going of each industry in the current park, and comprises addition of circulating water consumption under each industry, water consumption reserved in process links under each industry, sewage discharge amount under each industry and water consumption.
5. The method of claim 1, wherein the step of summing each material flow data corresponding to each business according to the industry to which each business belongs to obtain first campus index presence data comprises:
determining the total amount of waste produced by each industry in the current park based on the total amount of waste produced by each industry to which each enterprise belongs;
determining current status data of indexes of a first park according to the total amount of production waste of each industry in the current park; wherein the first campus index presence data includes a sum of an amount of waste of each industry entering a first cycle of the enterprise, an amount of waste of each industry entering a second cycle of the campus, an amount of waste of each industry entering a third cycle of the society, and an amount of waste disposed of by each industry.
6. A campus-based stream project recommendation device, comprising:
the first determining module sums the data of each material flow corresponding to each enterprise in the current park according to the industry to which each enterprise belongs to obtain current data of indexes of the first park; the first park index current state data comprises refinement classifications corresponding to each material flow data in each industry; the material streams include energy streams, carbon streams, water streams, and waste streams;
The second determining module is used for determining second park index current data according to the project construction scene of the current park, wherein the second determining module is used for determining the influence on the material flow data of the industries to which each enterprise belongs and the influence on the corresponding refined classification of each material flow data of each industry; the project construction scene is a project to be built matching, a project under construction matching and/or a newly built project matching existing in the current park;
the recommending module predicts an increment space of each material flow data corresponding to refined classification in each industry of the current park based on a preset index target of each material flow data and the current status data of the second park, and determines project recommending combination of the current park by taking the increment space as an error limit value;
the second determining module is further used for determining a first influence quantity of the project construction scene on the material flow data of the industries to which each enterprise belongs respectively and a second influence quantity of the refined classification on each material flow data of each industry according to the target project data corresponding to the project construction scene of the current park; updating the first campus index current status data based on the first influence quantity and the second influence quantity to obtain second campus index current status data;
The recommendation module is further used for predicting an increment space of the refined classification corresponding to each material flow data in each industry of the current park based on the difference value of the preset index target of each material flow data in the current park and the current situation data of the second park index; determining the increment space of the refinement classification corresponding to each material flow data of the current park according to the product of the increment space distribution coefficient of the refinement classification corresponding to each material flow data of each industry and the increment space of the refinement classification corresponding to each material flow data of each industry of the current park; and determining project recommendation combinations meeting the condition requirements in the current park by taking the increment space of the refinement classification corresponding to each material flow data in each industry of the current park and the increment space of the refinement classification corresponding to each material flow data in the current park as constraint conditions of standard error limit values.
7. An electronic device comprising a memory, a processor and a program stored on the memory and capable of running on the processor, the processor implementing the method of any one of claims 1 to 5 when executing the program.
8. A computer readable storage medium, characterized in that the computer program is stored in the readable storage medium, which computer program, when executed, implements the method of any of claims 1-5.
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