CN114926032A - Modular assembly method and system for feed enterprise - Google Patents
Modular assembly method and system for feed enterprise Download PDFInfo
- Publication number
- CN114926032A CN114926032A CN202210572461.0A CN202210572461A CN114926032A CN 114926032 A CN114926032 A CN 114926032A CN 202210572461 A CN202210572461 A CN 202210572461A CN 114926032 A CN114926032 A CN 114926032A
- Authority
- CN
- China
- Prior art keywords
- information
- enterprise
- product
- operation range
- construction scale
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a modular assembly method and a modular assembly system for a feed enterprise, and relates to the technical field of industrial organization modularization. The technical problems that the acquisition mode of the modular assembly scheme in the prior art is incomplete in information acquisition and processing, the finally determined scheme environment integrating degree is not enough, and enterprise development is influenced to a certain degree are solved, and the purpose of acquiring the optimal scheme of corresponding modular assembly is achieved.
Description
Technical Field
The invention relates to the technical field of industrial organization modularization, in particular to a feed enterprise modularization assembling method and system.
Background
At present, the application of modularization in the aspect of building is more extensive, and through carrying out modularization assembly, the performance effect of each module has clear understanding, and a plurality of modules have all passed the pertinence test in the assembly process, also have corresponding concern in the fodder enterprise, but the acquisition method of its scheme has certain flaw, plays certain restrictive action to the development of enterprise.
The acquisition mode of the existing modular assembly scheme is incomplete in information acquisition and processing, so that the finally determined scheme environment is not in enough conformity, and the development of enterprises can be influenced to a certain extent.
Disclosure of Invention
The application provides a modular assembly method and a modular assembly system for a feed enterprise, which are used for solving the technical problems that the acquisition mode of the existing modular assembly scheme in the prior art is not complete enough in information acquisition and processing, so that the finally determined scheme environment fit degree is not enough, and the development of the enterprise is influenced to a certain degree.
In view of the above problems, the present application provides a modular assembly method and system for a feed enterprise.
In a first aspect, the present application provides a modular assembly method for a feed enterprise, the method comprising: acquiring enterprise operation range information; carrying out multi-dimensional characteristic analysis on the enterprise operation range information, and extracting product type information, product quantity information, product storage cost information and production risk information; acquiring a reference index of an operating range based on the product type information, the product quantity information, the product storage cost information and the production risk information; acquiring the enterprise assembly site selection area information; acquiring environmental characteristic information by collecting the information of the enterprise assembly site selection area and combining the environmental characteristic information with the product type information to obtain an environmental adaptation reference index; acquiring the information of the pre-construction scale of the enterprise; performing standard value correlation mapping on the pre-construction scale information to obtain pre-construction scale parameters; and performing distributed calculation according to the pre-construction scale parameter, the operation range reference index and the environment adaptation reference index to obtain a modular assembly scheme of the enterprise.
In a second aspect, the present application provides a modular assembly system for a feed enterprise, the system comprising: the information acquisition module is used for acquiring enterprise operation range information; the characteristic analysis module is used for carrying out multi-dimensional characteristic analysis on the enterprise operation range information and extracting product type information, product quantity information, product storage cost information and production risk information; the index acquisition module is used for acquiring an operation range reference index based on the product type information, the product quantity information, the product storage cost information and the production risk information; the regional information acquisition module is used for acquiring regional information of the enterprise assembly site selection; the characteristic acquisition module is used for acquiring environmental characteristics of the enterprise assembly site selection area information and combining the environmental characteristic information with the product type information to acquire an environmental adaptation reference index; the system comprises a pre-construction scale information acquisition module, a pre-construction scale information acquisition module and a pre-construction scale information acquisition module, wherein the pre-construction scale information acquisition module is used for acquiring pre-construction scale information of the enterprise; the information mapping module is used for carrying out standard value correlation mapping on the pre-construction scale information to obtain pre-construction scale parameters; and the index calculation module is used for performing distributed calculation according to the pre-construction scale parameter, the operation range reference index and the environment adaptation reference index to obtain a modular assembly scheme of the enterprise.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the feed enterprise modular assembly method and system provided by the embodiment of the application, firstly, enterprise operation range information is collected, multidimensional characteristic extraction and analysis are carried out, product type information, product quantity information, product storage cost information and production risk information are obtained, and operation range reference indexes are obtained on the basis of the product type information, the product quantity information, the product storage cost information and the production risk information; the method comprises the steps of collecting enterprise assembly site selection area information, collecting environmental characteristics of the enterprise assembly site selection area information, combining the environmental characteristics with the product type information, obtaining an environment adaptation reference index, obtaining enterprise pre-construction scale information, performing standard value association mapping on the pre-construction scale information to obtain a pre-construction scale parameter, performing distributed calculation according to the obtained pre-construction scale parameter, the operation range reference index and the environment adaptation reference index to obtain a modular assembly scheme of the enterprise, further performing feasibility analysis and evaluation on the scheme to determine the applicability of the scheme, and obtaining a final modular assembly scheme, and solves the technical problems that the collection and processing of information are incomplete in a modular assembly scheme obtaining mode in the prior art, so that the finally determined scheme has insufficient environmental conformity and can influence the development of the enterprise to a certain degree, to make the determination of the best modular assembly scheme.
Drawings
Fig. 1 is a schematic flow chart of a modular assembly method for a feed enterprise according to the present application;
fig. 2 is a schematic diagram illustrating a process of acquiring a reference index of a camping range in a modular assembly method for a feed enterprise according to the present application;
fig. 3 is a schematic view illustrating an environment adaptive reference index acquisition process in a modular assembly method for a feed enterprise according to the present application;
fig. 4 provides a schematic structural diagram of a modular assembly system of a feed enterprise.
Description of the reference numerals: the system comprises an information acquisition module a, a characteristic analysis module b, an index acquisition module c, an area information acquisition module d, a characteristic acquisition module e, a pre-construction scale information acquisition module f, an information mapping module g and an index calculation module h.
Detailed Description
The application provides a modular assembly method and a system for a feed enterprise, parameter analysis and calculation are carried out on an enterprise operation range reference index and an environment adaptation reference index to obtain a corresponding modular assembly method, feasibility evaluation is carried out on the method to determine a final modular assembly scheme of the enterprise, and the method and the system are used for solving the technical problem that information is collected and processed in an existing modular assembly scheme obtaining mode in the prior art, the finally determined scheme environment fit degree is not enough, and development of the enterprise can be influenced to a certain degree.
Example one
As shown in fig. 1, the present application provides a modular assembly method for a feed enterprise, the method comprising:
step S100: acquiring enterprise operation range information;
specifically, the feed enterprise modular assembly method comprises the steps of conducting enterprise site selection, enterprise operation range and enterprise scale analysis and determination, and further conducting enterprise modular assembly scheme determination on the basis of environment adaptation.
Step S200: performing multidimensional characteristic analysis on the enterprise operation range information, and extracting product type information, product quantity information, product storage cost information and production risk information;
specifically, based on the obtained operation range information, performing multi-dimension characteristic analysis on product types, product quantity, product storage cost and production risk, judging the included product types, obtaining corresponding product type information, for example, performing product type division according to the physical and chemical shape of feed, dividing the product types into coarse feed, green feed, fine feed and additive feed, further performing data acquisition on the production quantities of a plurality of products, classifying and summarizing the obtained product quantity information on the basis of the product type information, determining the material and property of the product according to different product types, further judging the most suitable storage mode of the product, for example, the chemical components contained in the product are easy to decompose to cause failure due to improper storage, and analyzing and calculating the corresponding storage cost based on the quantity information of each product, the method comprises the steps of obtaining product storage cost information, further obtaining information of production steps of a plurality of products, judging risks possibly existing in corresponding production processes, for example, risks of carrying non-pestiviruses exist in feed raw materials, and obtaining corresponding production risk information, wherein product type information, product quantity information, product storage cost information and production risk information of a plurality of products related to an enterprise are in one-to-one correspondence, and the obtained product type information, product quantity information, product storage cost information and production risk information are classified, integrated and stored, so that later extraction and calling are facilitated.
Step S300: acquiring an operation range reference index based on the product type information, the product quantity information, the product storage cost information and the production risk information;
specifically, the product type information, the product quantity information, the product storage cost information and the production risk information are collected and summarized, the operation range of the product is analyzed according to the corresponding product dimension, the application range corresponding to the product is judged, to determine the corresponding reference index, for example, the additive feed can be applied to a plurality of species of mammals, aquatic animals and the like, but different species have different requirements, and the additive feed is subjected to targeted and specific analysis to obtain the corresponding parameter index, and analyzing and determining various parameter indexes covered by the product type information, the product quantity information, the product storage cost information and the production risk information, further integrating the information, acquiring the operation range reference index, and providing theoretical support for determining a corresponding enterprise modular assembly scheme.
Step S400: acquiring the enterprise assembly site selection area information;
step S500: acquiring environmental characteristic information by collecting the information of the enterprise assembly site selection area and combining the environmental characteristic information with the product type information to obtain an environmental adaptation reference index;
specifically, information collection is carried out on the enterprise assembly site selection area, the site selection is used as a long-term fixed investment of an enterprise, corresponding change can be carried out on other factors to adapt based on the change of an external large environment, the site selection is difficult to change randomly, the area environment of the area determined by the site selection meets certain requirements, a certain promotion effect is played on the development of the enterprise, specific directions and places are further determined, for example, the difficulty degree of the area for collecting raw materials, whether the environment is suitable for the storage of products, whether the production process of the products is influenced, and the like, relevant collection is carried out on the area information of the site selection, and the optimized site selection is carried out based on information proofreading analysis so as to realize the long-term sustainable development of the enterprise.
Further, based on the obtained enterprise assembly site selection area information, extracting environment information, further judging corresponding environment characteristics, further specifically analyzing site selection positions, judging whether the surrounding environment of the site selection positions is suitable for production and storage of products according to related products of corresponding feed enterprises, analyzing corresponding altitude, temperature, humidity and ground surface information, judging whether the surrounding environment of the site selection positions is suitable for production and storage of the products or not, further judging whether the geographical positions of the site selection positions are susceptible to the influence of natural environment factors such as earthquakes, tsunamis and the like, determining the adaptation degree of the environment characteristic information and the product type information, and determining an environment adaptation reference index on the basis of the relative adaptation degree through further analysis, wherein the environment adaptation reference index refers to the optimal environment standard which is most suitable for the enterprises and relates to production and storage of the products, based on the determination of the environment adaptive reference index, corresponding enterprise site selection standards can be obtained so as to perform optimal site selection.
Step S600: acquiring the pre-construction scale information of the enterprise;
step S700: performing standard value correlation mapping on the pre-construction scale information to obtain pre-construction scale parameters;
specifically, pre-construction scale information of an enterprise is acquired, wherein the enterprise pre-construction scale information is corresponding idealized planning and construction information, the pre-construction scale information comprises construction scale information of a plurality of modules, for example, a production construction module, a product storage module, a defective secondary treatment module, a waste treatment module and the like, the modules are assembled in a corresponding idealized module assembly mode by extracting information of the plurality of construction modules, the corresponding construction scale is determined, the construction scale is extracted, the information comprises integral information and information corresponding to each module, information integration and summarization are further carried out, and the information is stored as the pre-construction scale information of the enterprise.
Further, based on a big data platform, information of corresponding enterprise construction standard scale is called, based on the acquired information of the pre-construction scale, comparing with the standard scale, further determining the corresponding association mapping relation, the standard scale can be expressed as 1, the pre-construction scale and the pre-construction scale are collated with a plurality of construction modules, for example, a production module on a pre-build scale is half the standard scale as compared to the standard scale, then, indicated as 0.5, the product storage module in the pre-build size is 3/4 in standard size, and then, the data integration is performed by using 0.75 to represent the data, and the corresponding multi-module data parameters are obtained by performing multi-module association mapping between the pre-construction scale information and the standard value, and are further stored as the pre-construction scale parameters, so that corresponding data information support is provided for the modular assembly scheme of the enterprise in the later period.
Step S800: and performing distributed calculation according to the pre-construction scale parameter, the operation range reference index and the environment adaptation reference index to obtain a modular assembly scheme of the enterprise.
Specifically, based on the acquired construction scale parameters, the operation range reference indexes and the environment adaptive reference indexes, the modular assembly scheme of the enterprise is determined through distributed computation, because the data volume covered by the parameter information is large, the centralized computation is complex and difficult, and needs strong computing power, the distributed computation is adopted, the parameters of a plurality of modules are computed through modularization to obtain the relative computation results of the modules, the results are integrated and summarized to determine a relatively reasonable modular assembly drawing, a BIM (building information modeling) model is constructed based on a modeling software platform, a proper modular assembly mode is intelligently selected for the structural characteristics and equipment characteristics of different positions, corresponding effect diagrams are generated based on model simulation, and the feasibility evaluation is further carried out on the assembly method, and if the assembly method is reasonable and has stronger feasibility, determining the assembly method as the modular assembly scheme of the enterprise.
Further, the step S200 of performing multidimensional feature analysis on the enterprise operation range information, and extracting product type information, product quantity information, product storage cost information, and production risk information further includes:
step S210: converting the enterprise operation range information into quantized feature vectors;
step S220: carrying out multi-dimensional feature extraction on the enterprise operation range information through feature vectors;
step S230: and acquiring the product type information, the product quantity information, the product storage cost information and the production risk information.
Specifically, information acquisition is carried out on the operation range of an enterprise, the operation range of the enterprise is further subjected to quantitative conversion, and the operation range is expressed by a characteristic vector, so that the information range is clearer. Based on the obtained information quantization feature vector, extracting vector information of product types, product quantity, product storage cost and product production risk, and obtaining corresponding multidimensional feature information, wherein the product type information refers to a plurality of different product types contained in the enterprise operation range, the corresponding product quantity is determined based on the plurality of product types, the corresponding vector information is extracted, further, aiming at the products of the same type and the corresponding product quantity, the vector information of the storage cost is extracted under the optimal storage condition, the storage cost vector information of a plurality of types of products is obtained, further, screening detection is carried out on the production risk in the production process of the plurality of products, the corresponding plurality of risk information is obtained, corresponding targeted operation can be carried out based on the information to carry out risk avoidance, and the obtained information is integrated and classified, and obtaining the product type information, the product quantity information, the product storage cost information and the production risk information, and providing a real-time data basis for obtaining the later-stage operation range reference index.
Further, as shown in fig. 2, the step S300 of obtaining the reference index of the operation range based on the product type information, the product quantity information, the product storage cost information, and the production risk information further includes:
step S310: performing radar feature analysis on the product type information, the product quantity information, the product storage cost information and the production risk information, and mapping the product type information into dimension quantity information;
step S320: mapping the product quantity information to dimension strength information;
step S330: mapping the product storage cost information into image granular sensing data information;
step S340: mapping the production risk information into image color data information;
step S350: obtaining an enterprise operation range radar matrix map based on the dimension intensity information, the image granular sensation data information, the image color data information and the dimension quantity information;
step S360: and performing correlation operation on the enterprise operation range radar matrix map to obtain an operation range reference index.
Specifically, based on the obtained product type information, product quantity information, product storage cost information and production risk information, accurate detection and positioning of corresponding features are carried out on the product type information, mapping analysis is carried out on the positioned related features, information mapping is further carried out on the obtained feature information, the product type information is mapped into dimension quantity information, wherein one product type corresponds to one dimension, multi-dimension quantity information is further obtained, the product quantity information is mapped into dimension strength information, the strength of the mapped dimension is judged according to the quantity of the same type of products, the more the quantity is, the stronger the corresponding dimension is, the product storage cost information is mapped into image granular sensation data information, the granular sensation refers to the saw-tooth shape represented by the unsmooth corresponding image display line, along with the increasing of the storage cost, and correspondingly enhancing the degree of the granular sensation of the image to express the product cost information, mapping the production risk information into image color data information, and carrying out multi-color gradient expression according to different covering colors of the corresponding images with different risk types, wherein the higher the risk intensity is, the darker the color of the image is, and further carrying out information integration to obtain the image color data information.
Further, the enterprise operation range radar matrix chart is drawn through the acquired dimension intensity information, the acquired image granular sensation data information, the acquired image color data information and the acquired dimension quantity information, the enterprise operation range radar matrix chart can clearly express relevant dimension information so as to facilitate extraction and analysis of the relevant information, relevance calculation of the expression information is performed on the basis of the enterprise operation range radar matrix chart, relevance between different information of the same dimension and relevance between different dimensions are determined, the operation range reference index is further determined, the operation range reference index refers to a plurality of limiting indexes for direction judgment of the operation range of the enterprise, and basis is provided for determination of subsequent schemes.
Further, the step S360 of calculating the radar matrix map of the enterprise operating range to obtain the reference index of the operating range further includes:
step S361: receiving image information of the enterprise operation range radar matrix diagram through an input layer;
step S362: performing multi-feature extraction on the image information of the radar matrix image through an input data extraction layer, and integrating an image color data set, an image granular sensation data set, dimension quantity information and dimension intensity information;
step S363: establishing a mapping relation between the image parameters and the index parameters;
step S364: and calculating the image color data set, the image granular sensation data set, the dimension quantity information and the dimension intensity information through the mapping relation to obtain the management range reference index.
Specifically, the radar matrix is subjected to correlation analysis operation through a multi-level network layer, firstly, image information is extracted and input from the enterprise operation range radar matrix based on an input layer to obtain related matrix information, further, data screening based on image color data information, image granular sensation data information, dimension quantity information and dimension intensity information is carried out on the image information of the radar matrix through a data extraction layer, the obtained multi-level characteristic data is classified and integrated, data information storage is further carried out to obtain a multi-level characteristic data set, further, a mapping relation between image parameters and index parameters is established, different image parameter data correspond to a certain index range, corresponding index parameters are synchronously changed according to gradual change of the image parameters, and the method is based on the obtained image color data set, And carrying out equal-proportion change on related parameter indexes by the image granular sensation data set, the dimension quantity information and the dimension strength information to obtain the operation range reference index, namely the corresponding index for expressing the applicability of the product, so that the enterprise operation range is further divided according to the operation range reference index.
Further, as shown in fig. 3, the step S500 of acquiring the environmental adaptation reference index by collecting the environmental characteristics of the enterprise assembly site selection area information and combining the environmental characteristic information with the product category information further includes:
step S510: acquiring longitude and latitude position characteristics, sea and land position characteristics and relative position characteristics according to the enterprise assembly site selection area information;
step S520: respectively calculating the adaptation degrees of the longitude and latitude position characteristics, the sea-land position characteristics and the relative position characteristics and the product category information;
step S530: and acquiring an environment adaptation reference index according to the longitude and latitude position characteristics, the sea and land position characteristics and the adaptation degree of the relative position characteristics and the product type information.
Specifically, by collecting the information of the enterprise assembly site selection area and further analyzing corresponding environmental characteristics, including the longitude and latitude position characteristics, the sea and land position characteristics and the relative position characteristics, the longitude and latitude position characteristics refer to the longitude and latitude absolute position of the area, the longitude and latitude coordinates are utilized to determine the only fixed point of the site selection area on the earth, the sea and land position determines whether the site selection area belongs to inland or coastal, is located on the east coast or the west coast of the continent, the weather difference of different positions and the traffic and foreign economy of different positions are different, the relative geographic position is set as a corresponding reference point, the selected position area is judged based on the determined reference point, on the basis, a plurality of product types related to the enterprise are analyzed one by one, and the obtained adaptation degree between the multistage environmental characteristics and different product types is judged, the suitability degree refers to the suitability degree of the site selection environmental characteristics for products related to a plurality of enterprises, whether the site selection environmental characteristics are suitable for production of corresponding products or not, the suitability degree information of the site selection environmental characteristics and the product type information is obtained, the multi-level environmental characteristic ratio corresponding to the product type information is determined, the obtained related information is subjected to union processing, further the total environmental characteristic suitability degree is carried out, the environmental adaptation reference index is further determined, and the enterprise sites are further screened based on the obtained environmental adaptation reference index so as to obtain the optimal position suitable for long-term sustainable development of the enterprises.
Further, the step S700 of performing standard value-related mapping on the pre-construction scale information to obtain a pre-construction scale parameter further includes:
step S710: obtaining preset standard construction scale information;
step S720: establishing association mapping between the pre-construction scale information and standard construction scale information;
step S730: and obtaining a pre-construction scale parameter through the correlation mapping.
Specifically, standard construction scale information is preset, wherein the standard scale information refers to information obtained by a big data platform, collecting construction scale information of enterprises of the same type, obtaining standard scale information which is collated with the pre-construction scale information, further carrying out association mapping on the pre-construction scale information and the standard construction scale confidence, the analysis expression of the pre-construction scale information may be performed based on the standard construction scale confidence, the degree of the pre-construction scale is determined, the standard scale information is expressed as 1, performing proofreading calculation of a plurality of construction modules on the pre-construction information, if a production module is half of the standard construction information, expressing the module by 0.5, performing one-to-one mapping to obtain a plurality of associated mapping parameters, and further performing data integration to obtain the pre-construction scale parameters, and storing the pre-construction scale parameters as a support basis of the enterprise modular assembly scheme.
Further, step S800 of the present application further includes:
step S810: carrying out feasibility evaluation on the obtained modular assembly scheme of the enterprise;
step S820: if the modular assembly scheme of the enterprise meets the preset requirement, assembling according to the modular assembly scheme of the enterprise;
step S830: and if the modular assembly scheme of the enterprise does not meet the preset requirements, stopping using the modular assembly scheme of the enterprise.
Specifically, distributed calculation is performed on the pre-construction scale parameter, the operation range reference index and the environment adaptation reference index, a corresponding module assembly mode is determined, feasibility evaluation is performed on the module assembly mode, whether the determined module assembly scheme has real operability and can meet a preset requirement is judged, if the obtained module assembly scheme meets the preset requirement, the module assembly scheme is determined to be a final enterprise modular assembly scheme, assembly is further performed on the basis of the enterprise modular assembly scheme, if the scheme does not meet the preset requirement, the scheme is stopped from being used, and the enterprise modular assembly scheme is determined again.
Example two
Based on the same inventive concept as the feed enterprise modular assembly method in the foregoing embodiment, as shown in fig. 4, the present application provides a feed enterprise modular assembly system, which includes:
the system comprises an information acquisition module a, a management server and a management server, wherein the information acquisition module a is used for acquiring enterprise management range information;
the characteristic analysis module b is used for carrying out multi-dimensional characteristic analysis on the enterprise operation range information and extracting product type information, product quantity information, product storage cost information and production risk information;
the index acquisition module c is used for acquiring an operation range reference index based on the product type information, the product quantity information, the product storage cost information and the production risk information;
the regional information acquisition module d is used for acquiring the regional information of the enterprise assembly site selection;
the characteristic acquisition module e is used for acquiring environmental characteristics of the enterprise assembly site selection area information and combining the environmental characteristic information with the product type information to acquire an environmental adaptation reference index;
the system comprises a pre-construction scale information acquisition module f, a pre-construction scale information acquisition module f and a pre-construction scale information acquisition module f, wherein the pre-construction scale information acquisition module f is used for acquiring pre-construction scale information of the enterprise;
the information mapping module g is used for performing standard value correlation mapping on the pre-construction scale information to obtain pre-construction scale parameters;
and the index calculation module h is used for performing distributed calculation according to the pre-construction scale parameter, the operation range reference index and the environment adaptation reference index to obtain a modular assembly scheme of the enterprise.
Further, the system further comprises:
the information quantization module is used for converting the enterprise operation range information into quantized characteristic vectors;
the characteristic extraction module is used for carrying out multi-dimensional characteristic extraction on the enterprise operation range information through a characteristic vector;
and the multi-dimensional characteristic information acquisition module is used for acquiring the product type information, the product quantity information, the product storage cost information and the production risk information.
Further, the system further comprises:
the category information mapping module is used for performing radar feature analysis on the product category information, the product quantity information, the product storage cost information and the production risk information and mapping the product category information into dimension quantity information;
a quantity information mapping module for mapping the product quantity information into dimension intensity information;
the storage cost information mapping module is used for mapping the product storage cost information into image granular sensation data information;
the production risk information mapping module is used for mapping the production risk information into image color data information;
the matrix map drawing module is used for obtaining an enterprise operation range radar matrix map based on the dimension intensity information, the image granular sensation data information, the image color data information and the dimension quantity information;
and the reference index acquisition module is used for performing correlation operation on the radar matrix map of the enterprise operating range to acquire an operating range reference index.
Further, the system further comprises:
the image information acquisition module is used for receiving the image information of the radar matrix map of the enterprise operation range through an input layer;
the image characteristic extraction module is used for performing multi-characteristic extraction on the image information of the radar matrix image through an input data extraction layer, and integrating an image color data set, an image granular sensation data set, dimension quantity information and dimension intensity information;
the parameter mapping construction module is used for establishing a mapping relation between the image parameters and the index parameters;
and the parameter operation module is used for operating the image color data set, the image granular sensation data set, the dimension quantity information and the dimension strength information through the mapping relation to obtain the operation range reference index.
Further, the system further comprises:
the position characteristic obtaining module is used for obtaining longitude and latitude position characteristics, sea and land position characteristics and relative position characteristics according to the enterprise assembly site selection area information;
the information adaptation degree matching module is used for respectively calculating the adaptation degrees of the longitude and latitude position characteristics, the sea-land position characteristics and the relative position characteristics and the product type information;
and the environment adaptation index acquisition module is used for acquiring an environment adaptation reference index according to the longitude and latitude position characteristics, the sea-land position characteristics and the adaptation degree of the relative position characteristics and the product type information.
Further, the system further comprises:
the standard scale information acquisition module is used for acquiring preset standard construction scale information;
the information mapping construction module is used for establishing the association mapping between the pre-construction scale information and the standard construction scale information;
and the pre-construction scale parameter acquisition module is used for acquiring a pre-construction scale parameter through the association mapping.
Further, the system further comprises:
a scenario evaluation module for performing feasibility evaluation on the obtained modular assembly scenario of the enterprise;
the scheme determining module is used for assembling according to the enterprise modular assembly scheme if the enterprise modular assembly scheme meets preset requirements;
and the scheme judging module is used for stopping using the enterprise modular assembly scheme if the scheme of the enterprise modular assembly scheme does not meet the preset requirement.
In the present specification, through the foregoing detailed description of the modular assembly method for a feed enterprise, it is clear to those skilled in the art that the modular assembly method and system for a feed enterprise in the present embodiment are disclosed.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A modular assembly method for a feed enterprise, the method comprising:
acquiring enterprise operation range information;
performing multidimensional characteristic analysis on the enterprise operation range information, and extracting product type information, product quantity information, product storage cost information and production risk information;
acquiring an operation range reference index based on the product type information, the product quantity information, the product storage cost information and the production risk information;
acquiring the enterprise assembly site selection area information;
acquiring environmental characteristic information by collecting the environmental characteristic information of the enterprise assembly site selection area and combining the environmental characteristic information with the product type information to obtain an environmental adaptation reference index;
acquiring the information of the pre-construction scale of the enterprise;
performing standard value correlation mapping on the pre-construction scale information to obtain pre-construction scale parameters;
and performing distributed calculation according to the pre-construction scale parameter, the operation range reference index and the environment adaptation reference index to obtain a modular assembly scheme of the enterprise.
2. The method of claim 1, wherein the performing multidimensional feature analysis on the enterprise operation range information to extract product type information, product quantity information, product storage cost information and production risk information comprises:
converting the enterprise operation range information into quantized feature vectors;
carrying out multi-dimensional feature extraction on the enterprise operation range information through feature vectors;
and acquiring the product type information, the product quantity information, the product storage cost information and the production risk information.
3. The method of claim 1, wherein obtaining an operation range reference index based on the product category information, the product quantity information, the product storage cost information, and the production risk information comprises:
performing radar feature analysis on the product type information, the product quantity information, the product storage cost information and the production risk information, and mapping the product type information into dimension quantity information;
mapping the product quantity information into dimension intensity information;
mapping the product storage cost information into image granular sensation data information;
mapping the production risk information into image color data information;
obtaining an enterprise operation range radar matrix map based on the dimension intensity information, the image granular sensation data information, the image color data information and the dimension quantity information;
and performing correlation operation on the enterprise operation range radar matrix map to obtain an operation range reference index.
4. The method of claim 3, wherein the operating the enterprise operation range radar matrix map to obtain an operation range reference index comprises:
receiving image information of the enterprise operation range radar matrix diagram through an input layer;
performing multi-feature extraction on the image information of the radar matrix image through an input data extraction layer, and integrating an image color data set, an image granular sensation data set, dimension quantity information and dimension intensity information;
establishing a mapping relation between the image parameters and the index parameters;
and calculating the image color data set, the image granular sensation data set, the dimension quantity information and the dimension strength information through the mapping relation to obtain the operation range reference index.
5. The method of claim 1, wherein the obtaining the environment adaptive reference index by combining the environment characteristic information with the product category information through environment characteristic collection of the enterprise assembly site selection area information comprises:
acquiring longitude and latitude position characteristics, sea and land position characteristics and relative position characteristics according to the enterprise assembly site selection area information;
respectively calculating the adaptation degrees of the longitude and latitude position characteristics, the sea-land position characteristics and the relative position characteristics and the product category information;
and acquiring an environment adaptation reference index according to the longitude and latitude position characteristics, the sea and land position characteristics and the adaptation degree of the relative position characteristics and the product type information.
6. The method according to claim 1, wherein the performing standard value-related mapping on the pre-construction scale information to obtain pre-construction scale parameters comprises:
obtaining preset standard construction scale information;
establishing an association mapping between the pre-construction scale information and standard construction scale information;
and obtaining a pre-construction scale parameter through the correlation mapping.
7. The method of claim 1, wherein the method further comprises:
carrying out feasibility evaluation on the obtained modular assembly scheme of the enterprise;
if the modular assembly scheme of the enterprise meets the preset requirement, assembling according to the modular assembly scheme of the enterprise;
and if the modular assembly scheme of the enterprise does not meet the preset requirements, stopping using the modular assembly scheme of the enterprise.
8. A modular assembly system for a feed enterprise, the system comprising:
the information acquisition module is used for acquiring enterprise operation range information;
the characteristic analysis module is used for carrying out multi-dimensional characteristic analysis on the enterprise operation range information and extracting product type information, product quantity information, product storage cost information and production risk information;
the index acquisition module is used for acquiring an operation range reference index based on the product type information, the product quantity information, the product storage cost information and the production risk information;
the regional information acquisition module is used for acquiring the regional information of the enterprise assembly site selection;
the characteristic acquisition module is used for acquiring environmental characteristics of the enterprise assembly site selection area information and combining the environmental characteristic information with the product type information to acquire an environmental adaptation reference index;
the system comprises a pre-construction scale information acquisition module, a pre-construction scale information acquisition module and a pre-construction scale information acquisition module, wherein the pre-construction scale information acquisition module is used for acquiring pre-construction scale information of the enterprise;
the information mapping module is used for carrying out standard value correlation mapping on the pre-construction scale information to obtain a pre-construction scale parameter;
and the index calculation module is used for performing distributed calculation according to the pre-construction scale parameter, the operation range reference index and the environment adaptation reference index to obtain a modular assembly scheme of the enterprise.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210572461.0A CN114926032B (en) | 2022-05-24 | 2022-05-24 | Modular assembly method and system for feed enterprises |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210572461.0A CN114926032B (en) | 2022-05-24 | 2022-05-24 | Modular assembly method and system for feed enterprises |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114926032A true CN114926032A (en) | 2022-08-19 |
| CN114926032B CN114926032B (en) | 2023-07-25 |
Family
ID=82811256
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210572461.0A Active CN114926032B (en) | 2022-05-24 | 2022-05-24 | Modular assembly method and system for feed enterprises |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114926032B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115328242A (en) * | 2022-10-11 | 2022-11-11 | 山东华邦农牧机械股份有限公司 | Culture environment intelligent regulation system based on remote control |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105956747A (en) * | 2016-04-22 | 2016-09-21 | 中南大学 | Corporate reputation evaluation visualization method |
| WO2019018315A1 (en) * | 2017-07-17 | 2019-01-24 | Kaarta, Inc. | Aligning measured signal data with slam localization data and uses thereof |
| US20200217666A1 (en) * | 2016-03-11 | 2020-07-09 | Kaarta, Inc. | Aligning measured signal data with slam localization data and uses thereof |
| CN113191681A (en) * | 2021-05-21 | 2021-07-30 | 中国工商银行股份有限公司 | Site selection method and device for network points, electronic equipment and readable storage medium |
| CN113240281A (en) * | 2021-05-14 | 2021-08-10 | 邓润阳 | Cloud storage and cloud logistics management method and system based on electronic commerce |
| CN113487246A (en) * | 2021-09-06 | 2021-10-08 | 南通高精数科机械有限公司 | Storage station site selection method and system based on artificial intelligence |
| CN114021873A (en) * | 2021-09-23 | 2022-02-08 | 上海仪电人工智能创新院有限公司 | Data index quantification method and intelligent park enterprise value evaluation system |
| CN114399625A (en) * | 2022-03-24 | 2022-04-26 | 北京闪马智建科技有限公司 | Position determination method and device, storage medium and electronic device |
-
2022
- 2022-05-24 CN CN202210572461.0A patent/CN114926032B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200217666A1 (en) * | 2016-03-11 | 2020-07-09 | Kaarta, Inc. | Aligning measured signal data with slam localization data and uses thereof |
| CN105956747A (en) * | 2016-04-22 | 2016-09-21 | 中南大学 | Corporate reputation evaluation visualization method |
| WO2019018315A1 (en) * | 2017-07-17 | 2019-01-24 | Kaarta, Inc. | Aligning measured signal data with slam localization data and uses thereof |
| CN113240281A (en) * | 2021-05-14 | 2021-08-10 | 邓润阳 | Cloud storage and cloud logistics management method and system based on electronic commerce |
| CN113191681A (en) * | 2021-05-21 | 2021-07-30 | 中国工商银行股份有限公司 | Site selection method and device for network points, electronic equipment and readable storage medium |
| CN113487246A (en) * | 2021-09-06 | 2021-10-08 | 南通高精数科机械有限公司 | Storage station site selection method and system based on artificial intelligence |
| CN114021873A (en) * | 2021-09-23 | 2022-02-08 | 上海仪电人工智能创新院有限公司 | Data index quantification method and intelligent park enterprise value evaluation system |
| CN114399625A (en) * | 2022-03-24 | 2022-04-26 | 北京闪马智建科技有限公司 | Position determination method and device, storage medium and electronic device |
Non-Patent Citations (5)
| Title |
|---|
| CÉDRIC LARDEUX: "Classification of Tropical Vegetation Using Multifrequency Partial SAR Polarimetry", 《IEEE GEOSCIENCE AND REMOTE SENSING LETTERS》, vol. 8, no. 1, pages 133, XP011340724, DOI: 10.1109/LGRS.2010.2053836 * |
| 孙国立: "探讨模块化装配生产在汽车总装生产工艺中的应用", 《时代汽车》, no. 06, pages 73 - 74 * |
| 王真真: "基于系统动力学生态城市建设评价方法研究 ————以天津市为例", 《中国优秀硕士学位论文全文数据库》, no. 07, pages 145 - 172 * |
| 马凤德: "先进复合材料在饲料机械领域的研发与发展方向", 《中小企业管理与科技(下旬刊)》, no. 06, pages 139 - 140 * |
| 黄会: "中马钦州产业园区建设绩效评估研究", 《中国优秀硕士学位论文全文数据库》, no. 01, pages 147 - 312 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115328242A (en) * | 2022-10-11 | 2022-11-11 | 山东华邦农牧机械股份有限公司 | Culture environment intelligent regulation system based on remote control |
| CN115328242B (en) * | 2022-10-11 | 2022-12-27 | 山东华邦农牧机械股份有限公司 | Culture environment intelligent regulation system based on remote control |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114926032B (en) | 2023-07-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108984803B (en) | Method and system for spatializing crop yield | |
| Fassnacht et al. | Remote sensing in forestry: current challenges, considerations and directions | |
| CN111738175A (en) | Agricultural drought monitoring system based on remote sensing image and convolutional neural network | |
| Solvin et al. | Use of UAV photogrammetric data in forest genetic trials: measuring tree height, growth, and phenology in Norway spruce (Picea abies L. Karst.) | |
| CN111667183A (en) | Method and system for monitoring cultivated land quality | |
| CN111563430A (en) | Public welfare forest land image intelligent identification method and system based on convolutional nerves | |
| CN114357563A (en) | Layout generation method and application of south-of-the-river private garden landscape | |
| CN111222539A (en) | Method for optimizing and expanding supervision classification samples based on multi-source multi-temporal remote sensing image | |
| CN115468917A (en) | Method and system for extracting crop information of farmland plot based on high-resolution remote sensing | |
| CN114926032A (en) | Modular assembly method and system for feed enterprise | |
| Chen et al. | Linear downscaling from MODIS to Landsat: connecting landscape composition with ecosystem functions | |
| WO2023007398A1 (en) | System and method for natural capital measurement | |
| CN117197668A (en) | Crop lodging level prediction method and system based on deep learning | |
| CN114166842A (en) | Town forest monitoring method based on cooperation of high-resolution remote sensing data and ground survey data | |
| CN116486282A (en) | Digital elevation model manufacturing method and system based on deep learning, electronic equipment and storage medium | |
| CN116822980A (en) | Base vector guided typical earth surface element intelligent monitoring method and system | |
| CN114842356B (en) | High-resolution earth surface type sample automatic generation method, system and equipment | |
| WO2023131949A1 (en) | A versatile crop yield estimator | |
| CN113610294A (en) | Color planning method, storage medium and device for medium and small cities | |
| CN115953685A (en) | Multi-layer multi-scale division agricultural greenhouse type information extraction method and system | |
| Van Niekerk | CLUES: A web-based land use expert system for the Western Cape | |
| Bao et al. | An automatic extraction method for individual tree crowns based on self-adaptive mutual information and tile computing | |
| Mellor et al. | Remote Sensing Victoria’s Public Land Forests—A Two Tiered Synoptic Approach | |
| Adesuyi | Automating land cover classification using time series NDVI: a case study in the berg river catchment area | |
| Zhai et al. | A new approach for mapping regional land cover and the application of this approach in Australia |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |