CN106528774A - Method and apparatus for predicting distribution network project management trend - Google Patents
Method and apparatus for predicting distribution network project management trend Download PDFInfo
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Abstract
Embodiments of the present invention provide a method and an apparatus for predicting the distribution network project management trend, and belongs to the field of data processing. The method comprises: obtaining data of a plurality of projects stored in advance in a local database; drawing a scatter diagram based on the material amount and the capital amount; obtaining to-be-analyzed projects displayed on the scatter diagram based on the first preset rule; carrying out clustering operations on the to-be-analyzed projects according to a second preset rule so as to obtain a plurality of clusters; obtaining a standard feature map for each to-be-analyzed project in each cluster; based on the standard feature map, drawing history feature maps of the total quantities of the current material and capital of the to-be-analyzed projects with the same cluster; and obtaining predict feature maps of the projects within the same cluster based on the standard feature maps and the history feature maps. According to the method provided by the embodiments of the present invention, the standard feature map is obtained by obtaining the history feature map and then analyzing the history feature map, so that the future capital and material of other projects within the same cluster can be predicted, and human, material and financial resources can be effectively allocated by a power grid company.
Description
Technical field
The present invention relates to data processing field, in particular to a kind of distribution project management trend forecasting method and dress
Put.
Background technology
With going from strength to strength for electric power enterprise, distribution project management construction occupies critical role in current electric grid work.
But traditional project feasibility studies report only lays particular emphasis on the demonstration of the Necessity and feasibility of project, and to each intermediate item
There is certain empiricism in the index choosing of investment, as the undue expertise that relies on judges, thus easily ignore history
Other reliability accurately information, the association and resources flow prediction of the shortage to historical data such as data, causes the result predicted inclined
From reality.So that power grid enterprises cannot rational allocation human and material resources and financial resources so that the development of power grid enterprises is subject to tight
The obstruction of weight.Therefore, how evaluation to be managed to the investment of all kinds of finished items reasonably, and invest by finished item
Instruct the great difficult problem that Future Project construction and development are power grid enterprises' urgent need to resolve.
The content of the invention
The present invention provides a kind of distribution project management trend forecasting method and device, it is intended to improve the problems referred to above.
A kind of distribution project management trend forecasting method that the present invention is provided, methods described include：Acquisition is stored in advance in
Multiple project datas in local data base, each described project data include goods and materials amount and capital quantity；Based on the goods and materials amount
Scatter diagram is drawn with the capital quantity, each point on the scatter diagram characterizes a project, a project correspondence one
The individual project data；The project to be analyzed shown on the scatter diagram is obtained based on the first preset rules；Will be described to be analyzed
Project carries out cluster operation according to the second preset rules, obtains multiple cluster classes, and a cluster class is included described in one or more
Project to be analyzed；Obtain the standard feature figure of each project to be analyzed in each described cluster class, the standard feature figure
For representing the time schedule of a project to be analyzed and fund situation of change；Same cluster is drawn based on the standard feature figure
The history feature figure of the current material total and total amount of the fund of the project described to be analyzed in class, the history feature figure are used for table
Show the material total and the fund of project described to be analyzed in the same cluster class of the special time before current time node
Total amount；The predicted characteristics figure of the same cluster intermediate item is obtained based on the standard feature figure and the history feature figure.
A kind of distribution project management trend prediction device that the present invention is provided, described device include：First data acquisition list
Unit, prestores multiple project datas in the local database for obtaining, each described project data include goods and materials amount and
Capital quantity；First chart drawing unit, for drawing scatter diagram based on the goods and materials amount and the capital quantity, on the scatter diagram
Each point characterize a project, the project one project data of correspondence；Second data capture unit, is used for
The project to be analyzed shown on the scatter diagram is obtained based on the first preset rules；First data processing unit, for will be described
Project to be analyzed carries out cluster operation according to the second preset rules, obtains multiple cluster classes, and a cluster class includes one or many
The individual project to be analyzed；3rd data capture unit, for obtaining each the described project to be analyzed in each described cluster class
Standard feature figure, the standard feature figure is used to represent that time schedule and the fund of a project to be analyzed to change feelings
Condition；Second graph drawing unit, for being drawn with the current of the project described to be analyzed in cluster class based on the standard feature figure
The history feature figure of material total and total amount of the fund, the special time that the history feature figure is used for before representing current time node
Same cluster class in project described to be analyzed the material total and the total amount of the fund；4th data capture unit, is used for
The predicted characteristics figure of the same cluster intermediate item is obtained based on the standard feature figure and the history feature figure.
A kind of distribution project management trend forecasting method and device that the invention described above is provided, the method are treated point by obtaining
The history feature figure of analysis project, then the standard feature figure for obtaining each project to be analyzed is analyzed to the history feature figure,
So as to based on the standard feature figure be predicted in the future with the project to be analyzed with the sundry item of cluster class fund and thing
Money so that grid company can effectively allocate human and material resources and financial resources, and preferably Development Co., Ltd's business.
Description of the drawings
In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, below by to be used attached needed for embodiment
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, thus be not construed as it is right
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can be with according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 is the structured flowchart of electronic equipment provided in an embodiment of the present invention；
A kind of flow chart of distribution project management trend forecasting method that Fig. 2 is provided for first embodiment of the invention；
Scatter diagram in a kind of distribution project management trend forecasting method that Fig. 3 is provided for first embodiment of the invention；
Cluster Type of Collective in a kind of distribution project management trend forecasting method that Fig. 4 is provided for first embodiment of the invention
Figure；
A kind of flow chart of distribution project management trend forecasting method that Fig. 5 is provided for second embodiment of the invention；
A kind of structured flowchart of distribution project management trend prediction device that Fig. 6 is provided for third embodiment of the invention；
A kind of structured flowchart of distribution project management trend prediction device that Fig. 7 is provided for fourth embodiment of the invention.
Specific embodiment
To make purpose, technical scheme and the advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
The a part of embodiment of the present invention, rather than the embodiment of whole.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.Therefore,
The detailed description of the embodiments of the invention to providing in the accompanying drawings is not intended to limit the model of claimed invention below
Enclose, but be merely representative of the selected embodiment of the present invention.Based on the embodiment in the present invention, those of ordinary skill in the art are not having
There is the every other embodiment obtained under the premise of making creative work, belong to the scope of protection of the invention.
As shown in figure 1, for the structured flowchart of electronic equipment provided in an embodiment of the present invention.The electronic equipment 200 includes
Distribution project management trend prediction device, memory 201, storage control 202, processor 203, Peripheral Interface 204 and input
Output unit 205.
The memory 201, storage control 202, processor 203, Peripheral Interface 204, each yuan of input-output unit 205
Part is directly or indirectly electrically connected with each other, to realize the transmission or interaction of data.For example, these elements each other may be used
Realize being electrically connected with by one or more communication bus or holding wire.The distribution project management trend prediction device include to
During few one can be stored in the memory 201 in the form of software or firmware (firmware) or it is solidificated in the electronic equipment
Software function module in 200 operating system (operating system, OS).The processor 203 is used to perform storage
The executable module stored in device 201, such as software function module that described distribution project management trend prediction device includes or
Computer program.
Wherein, memory 201 may be, but not limited to, random access memory (Random Access Memory,
RAM), read-only storage (Read Only Memory, ROM), programmable read only memory (Programmable Read-
Only Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory,
EPROM), electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only Memory,
EEPROM) etc..
A kind of possibly IC chip of processor 203, the disposal ability with signal.Above-mentioned processor 203 can
Being general processor, including central processing unit (Central Processing Unit, abbreviation CPU), network processing unit
(Network Processor, abbreviation NP) etc.；Can also be digital signal processor (DSP), special IC (ASIC),
It is ready-made programmable gate array (FPGA) or other PLDs, discrete gate or transistor logic, discrete hard
Part component.Can realize or perform disclosed each method in the embodiment of the present invention, step and logic diagram.General processor
Can be microprocessor or the processor can also be any conventional processor etc..
Various input/output devices are coupled to processor 203 and memory 201 by the Peripheral Interface 204.At some
In embodiment, Peripheral Interface 204, processor 203 and storage control 202 can be realized in one single chip.Other one
In a little examples, they can be realized by independent chip respectively.
Input-output unit 205 is used to be supplied to user input data to realize interacting for user and the electronic equipment 200.
The input-output unit 205 may be, but not limited to, mouse and keyboard etc..
Fig. 2 is referred to, is a kind of flow process of distribution project management trend forecasting method that first embodiment of the invention is provided
Figure.Idiographic flow shown in Fig. 2 will be described in detail below.
Step S301, acquisition prestore multiple project datas in the local database.
Wherein, each described project data includes goods and materials amount and capital quantity.
Used as a kind of embodiment, acquisition prestores initial project data in the local database, based on data
Uniformity, integrality and available standards carry out data filtering process to the initial project data, the multiple institutes after being filtered
State project data.Wherein, initial project data refer to all items data being stored in database.The uniformity of data is referred to
Whether the data of zones of different storage are consistent.The integrality of data refers to the total amount of data.The available standards of data refer to for
Judge whether the initial project data can use, for example, the gross investment of initial project data is negative value, then by it is described can
Judge that the initial project data eliminate the initial project data for unavailable, that is, with standard.
As another embodiment, extract according to user's request and according to the important attribute of power business and prestore
Initial project data in the local database carry out data analysis, and the side such as the uniformity from data, integrality, availability
Face Develop Data quality evaluation, formulates data filtering rule according to assessment result, so as to carry out filtration treatment to data, is wrapped
The valid data collection of the project data containing data such as project funds, project goods and materials and project processes.Wherein, the important attribute
One or more data attributes in initial project data are referred to, the data attribute can affect initial project data institute right
The project answered, i.e., described data attribute play key effect in the project.
Step S302, draws scatter diagram based on the goods and materials amount and the capital quantity.
Wherein, with the goods and materials amount as transverse axis, the scatter diagram is drawn by the longitudinal axis of the capital quantity.By each item number
According to being plotted on the scatter diagram according to capital quantity and goods and materials amount, i.e., each point on described scatter diagram characterizes a project,
One project correspondence, one project data.As shown in figure 3, by multiple project datas according to goods and materials amount and gross investment point
Cloth on the scatter diagram, wherein, the gross investment be the capital quantity.
Step S303, obtains the project to be analyzed shown on the scatter diagram based on the first preset rules.
Wherein, obtain the project to be analyzed shown on the scatter diagram to refer to when the scatter diagram based on the first preset rules
The point of upper distribution is located at the goods and materials amount and is equal on the curve of the capital quantity place and when the point being distributed on the scatter diagram is leaned on
When the nearly goods and materials amount is equal to the capital quantity place curve, the project data represented by the point is obtained；By the item number
According to being labeled as project to be analyzed.
First preset rules refer to that setting goods and materials amount is equal to the curve that capital quantity is located, by judging on scatter diagram
Whether certain point is located on or near the curve.
Wherein, it is close to refer to that the point being distributed in around the curve is equal to or less than preset value to the distance of the curve.
For example, preset value is 2, i.e., when the distance of the point being distributed around the curve to the curve is less than or equal to 2, the point is as close
The point of the curve.As shown in figure 3, be that negative point is labeled as anomaly item point by gross investment on scatter diagram, when on scatter diagram
Point is equal on the curve of the capital quantity place and when the point being distributed on the scatter diagram is near the thing positioned at the goods and materials amount
When money amount is equal to the capital quantity place curve, the point is labeled as into the normal project to be analyzed of situation.In Fig. 3, the feelings
The normal most of project clusters of condition referred to multiple projects be located at the goods and materials amount be equal on the curve of the capital quantity place and
Capital quantity place curve is equal near the goods and materials amount.Wherein, will be far from the goods and materials amount to be located equal to the capital quantity
The point of curve, is labeled as the larger project of divorced value, allows the user to intuitively obtain useful information from the scatter diagram.
The project to be analyzed is carried out cluster operation according to the second preset rules by step S304, obtains multiple cluster classes.
Wherein, the project to be analyzed is carried out into cluster operation according to the second preset rules, obtains multiple cluster classes and refer to obtaining
Take the project to be analyzed corresponding project cycle, the project budget and item types；Will be the project cycle, the project pre-
Calculate and the item types are converted into numerical value and represent, cluster operation is carried out by K-means algorithms, obtain multiple cluster classes.
Second preset rules refer to K-means algorithms, i.e., described to carry out cluster operation according to the second preset rules and be
Refer to according to K-means algorithms to realize cluster operation.
As a kind of embodiment, by by each project to be analyzed corresponding project cycle, the project budget and project
Three attributes of type as three-dimensional coordinate point, i.e., by the project cycle, the project budget and the item types are turned
It is changed to numerical value to represent, so as to be used for representing a three-dimensional coordinate, K cluster center of mass point is randomly selected by K-means algorithms,
The project to be analyzed is measured to the distance of the center of mass point to the three-dimensional coordinate that remaining project to be analyzed is located, by obtaining
Distance results, the project of being analysed to is grouped in the class of the center of mass point nearest with center of mass point, recalculates obtained each
The center of mass point of individual class, is repeating following steps, step 1：Project to be analyzed passes through what is obtained to the distance of the center of mass point
Distance results, the project of being analysed to are grouped in the class of the center of mass point nearest with center of mass point, step 2：Recalculate what is obtained
The center of mass point of each class, until the center of mass point for reacquiring is equal with original center of mass point or is less than pre-set threshold value.As shown in figure 4,
By the project cycle, the project budget and the item types are converted into after numerical value represents, calculated based on K-means
Method is obtained and belongs to the project of same cluster class, judges each cluster class belonging to point by the point minute gray scale that shows on Fig. 4, will be grey
Degree identical point is judged to same cluster class, so as to each project is referred to affiliated cluster intuitively by the cluster Type of Collective figure
Class.
Step S305, obtains the standard feature figure of each project to be analyzed in each described cluster class.
Wherein, the standard feature figure for obtaining each project to be analyzed in each described cluster class refers to that acquisition is every
The characteristic pattern of each project to be analyzed in the individual cluster class；With the project cycle in project to be analyzed each described and item
The business of mesh budget expenditure time carries out process to the characteristic pattern based on K-means algorithms for the calculating factor and obtains the standard
Characteristic pattern.The project budget expenditure time refers to the time of the fund paid within the project cycle.
Wherein, the characteristic pattern referred to the capital quantity of each project to be analyzed as the longitudinal axis, with time schedule as transverse axis
Chart, for representing the fund of the project to be analyzed within the project cycle artificial situation.
Step S306, draws the current material total with the project described to be analyzed in cluster class based on the standard feature figure
With the history feature figure of total amount of the fund.
Wherein, the material total refers to the summation of the goods and materials of all items of same cluster class, and the total amount of the fund is in the same manner
Summation of the finger with the fund of all items of cluster class.The history feature figure is used to represent the project for having completed or current
The change of the project of hot work in progress is used before timing node material total and total amount of the fund with time schedule.
Used as a kind of embodiment, the goods and materials amount used on the same day by all items of same cluster class is added the thing for obtaining on the same day
Money total amount, the material total and time are marked out on the history feature figure comes, by all items of same cluster class on the same day
The capital quantity for being used is added the total amount of the fund for obtaining on the same day, by the total amount of the fund with the time in the history feature figure subscript
Outpour and, so as to obtain the time dependent history feature figure of material total, total amount of the fund.
Step S307, the prediction for obtaining the same cluster intermediate item based on the standard feature figure and the history feature figure are special
Levy figure.
By predicting the cluster class belonging to following all distribution projects, found in same cluster class according to the history feature figure for getting
Project standard feature figure, so as to the fund and time schedule change of the project according to represented by the standard feature figure is closed
System, is obtained the predicted characteristics figure with the project of cluster class with the project, is obtained by K-means algorithms based on the predicted characteristics figure
The prediction term purpose prediction standard characteristic pattern is taken, power grid enterprises can be enabled more preferable by the prediction standard characteristic pattern
Dispose available manpower, material resources and can show that following each timing node of distribution project, to goods and materials, the demand of fund, thus may be used
To predict goods and materials, use of funds peak period in advance, resource is allocated in advance for relevant departments foundation is provided.It is i.e. special by the prediction
Levy figure and can effectively predict capital quantity and goods and materials amount of the power grid enterprises in the range of overall region on following each time point,
So as to be controlled in advance so that the reasonable arrangement of human and material resources and fund, and then the electrical network that improves largely is looked forward to
The operating efficiency of industry.
Fig. 5 is referred to, is a kind of flow process of distribution project management trend forecasting method that second embodiment of the invention is provided
Figure.Idiographic flow shown in Fig. 5 will be described in detail below.
Step S401, acquisition prestore multiple project datas in the local database.
Step S402, draws scatter diagram based on the goods and materials amount and the capital quantity.
Step S403, obtains the project to be analyzed shown on the scatter diagram based on the first preset rules.
The project to be analyzed is carried out cluster operation according to the second preset rules by step S404, obtains multiple cluster classes.
Step S405, obtains the standard feature figure of each project to be analyzed in each described cluster class.
Step S406, draws the current material total with the project described to be analyzed in cluster class based on the standard feature figure
With the history feature figure of total amount of the fund.
Step S407, the prediction for obtaining the same cluster intermediate item based on the standard feature figure and the history feature figure are special
Levy figure.
The tool of step S401, step S402, step S403, step S404, step S405, step S406 and step S407
Body embodiment may be referred to the step of the correspondence in first embodiment, will not be described here.
Step S408, the capital quantity for showing is added obtains described on each the described predicted characteristics figure in the same cluster class
The following total amount of the fund of cluster class.
Wherein, the capital quantity for showing on described each described predicted characteristics figure by the same cluster class is added and refers to institute
State the capital quantity corresponding to the same time on predicted characteristics figure to be added, draw the future of the cluster class corresponding to the same time
Total amount of the fund.
Step S409, the goods and materials amount for showing is added obtains described on each the described predicted characteristics figure in the same cluster class
The following material total of cluster class.
Wherein, the goods and materials amount for showing on described each described predicted characteristics figure by the same cluster class is added and refers to institute
State the goods and materials amount corresponding to the same time on predicted characteristics figure to be added, draw the following thing of the cluster class corresponding to the same time
Money total amount.
Step S410, obtains future features figure with the time schedule as transverse axis and by the longitudinal axis of the capital quantity respectively,
The future features figure is used to represent the following total amount of the fund and the following material total.
The following material total for obtaining and following total amount of the fund are represented by the form of chart with the change of time schedule
Out, so as to obtain the future features figure, power grid enterprises can be caused total using following goods and materials by the future features figure
Measure feature, it can be deduced that following each timing node of distribution project is to goods and materials, the demand of fund, and then can predict thing in advance
Money, use of funds peak period, allocate resource in advance for relevant departments and provide foundation.
Fig. 6 is referred to, is a kind of structure of distribution project management trend prediction device that third embodiment of the invention is provided
Block diagram.Described device 500 includes the first data capture unit 501, the first chart drawing unit 502, the second data capture unit
503rd, the first data processing unit 504, the 3rd data capture unit 505, second graph drawing unit 506 and the 4th data acquisition
Unit 507.
First data capture unit 501, for obtaining the multiple project datas for prestoring in the local database, each
The project data includes goods and materials amount and capital quantity.
First data capture unit 501 is specifically for obtaining the initial term mesh number for prestoring in the local database
According to；Data filtering process is carried out to the initial project data based on the uniformity of data, integrality and available standards, was obtained
Multiple described project data after filter.
First chart drawing unit 502, for drawing scatter diagram, the scatterplot based on the goods and materials amount and the capital quantity
Each point on figure characterizes a project, one project data of a project correspondence.
Second data capture unit 503, for be analyzed based on what is shown on the first preset rules acquisition scatter diagram
Project.
Wherein, second data capture unit 503 is additionally operable to be located at the goods and materials when the point being distributed on the scatter diagram
Amount is equal on the curve of the capital quantity place and when the point being distributed on the scatter diagram is equal to the money near the goods and materials amount
During gold amount place curve, the project data represented by the point is obtained, the project data is labeled as into project to be analyzed.
First data processing unit 504, for the project to be analyzed is carried out cluster operation according to the second preset rules,
Multiple cluster classes are obtained, a cluster class includes one or more described projects to be analyzed.
Wherein, the first data processing unit 504 is specifically for obtaining the project to be analyzed corresponding project cycle, project
Budget and item types；The project cycle, the project budget and the item types are converted into numerical value to represent,
Cluster operation is carried out by K-means algorithms, multiple cluster classes are obtained.
3rd data capture unit 505, for obtaining the standard of each project to be analyzed in each described cluster class
Characteristic pattern, the standard feature figure are used for time schedule and the fund situation of change for representing a project to be analyzed.
Wherein, the 3rd data capture unit 505 is treated described in each in each described cluster class point specifically for obtaining
The characteristic pattern of analysis project；With the project cycle in project to be analyzed each described and the project budget expenditure time business as calculate because
Subbase carries out process in K-means algorithms and obtains the standard feature figure to the characteristic pattern.
Second graph drawing unit 506, for being drawn with the item described to be analyzed in cluster class based on the standard feature figure
The history feature figure of the current material total of purpose and total amount of the fund, before the history feature figure is used to represent current time node
The material total and the total amount of the fund of the project described to be analyzed in the same cluster class of special time.
4th data capture unit 507, for obtaining described same based on the standard feature figure and the history feature figure
The predicted characteristics figure of cluster intermediate item.
Fig. 7 is referred to, is a kind of structure of distribution project management trend prediction device that fourth embodiment of the invention is provided
Block diagram.Described device 600 includes the first data capture unit 601, the first chart drawing unit 602, the second data capture unit
603rd, the first data processing unit 604, the 3rd data capture unit 605, second graph drawing unit 606, the 4th data acquisition
Unit 607, the second data processing unit 608, the 3rd data processing unit 609 and the 5th data capture unit 610.
First data capture unit 601, for obtaining the multiple project datas for prestoring in the local database, each
The project data includes goods and materials amount and capital quantity.
First chart drawing unit 602, for drawing scatter diagram, the scatterplot based on the goods and materials amount and the capital quantity
Each point on figure characterizes a project, one project data of a project correspondence.
Second data capture unit 603, for be analyzed based on what is shown on the first preset rules acquisition scatter diagram
Project.
First data processing unit 604, for the project to be analyzed is carried out cluster operation according to the second preset rules,
Multiple cluster classes are obtained, a cluster class includes one or more described projects to be analyzed.
3rd data capture unit 605, for obtaining the standard of each project to be analyzed in each described cluster class
Characteristic pattern, the standard feature figure are used for time schedule and the fund situation of change for representing a project to be analyzed.
Second graph drawing unit 606, for being drawn with the item described to be analyzed in cluster class based on the standard feature figure
The history feature figure of the current material total of purpose and total amount of the fund, before the history feature figure is used to represent current time node
The material total and the total amount of the fund of the project described to be analyzed in the same cluster class of special time.
4th data capture unit 607, for obtaining described same based on the standard feature figure and the history feature figure
The predicted characteristics figure of cluster intermediate item.
Second data processing unit 608, for the money that will be shown on each the described predicted characteristics figure in the same cluster class
Gold amount is added the following total amount of the fund for obtaining the cluster class.
3rd data processing unit 609, for the thing that will be shown on each the described predicted characteristics figure in the same cluster class
Money amount is added the following material total for obtaining the cluster class.
5th data capture unit 610, for respectively with the time schedule as transverse axis and with the capital quantity as the longitudinal axis
Future features figure is obtained, the future features figure is used to represent the following total amount of the fund and the following material total.
In sum, the present invention provides a kind of distribution project management trend forecasting method and device, and the method is by obtaining
The history feature figure of project to be analyzed, then the standard feature for obtaining each project to be analyzed is analyzed to the history feature figure
Figure, so as to based on the standard feature figure be predicted in the future with the project to be analyzed with the fund of the sundry item of cluster class and
Goods and materials so that grid company can effectively allocate human and material resources and financial resources, and preferably Development Co., Ltd's business.
In several embodiments provided herein, it should be understood that disclosed apparatus and method, it is also possible to pass through
Other modes are realized.Device embodiment described above is only schematically, for example flow chart and block diagram in accompanying drawing
Show the device of multiple embodiments of the invention, the architectural framework in the cards of method and computer program product,
Function and operation.At this point, each square frame in flow chart or block diagram can represent the one of module, program segment or a code
Part, a part for the module, program segment or code are used to realize holding for the logic function for specifying comprising one or more
Row instruction.It should also be noted that at some as in the implementations replaced, the function of being marked in square frame can also be being different from
The order marked in accompanying drawing occurs.For example, two continuous square frames can essentially be performed substantially in parallel, and they are sometimes
Can perform in the opposite order, this is depending on involved function.It is also noted that every in block diagram and/or flow chart
The combination of individual square frame and block diagram and/or the square frame in flow chart, can use the special base for performing the function or action of regulation
Realize in the system of hardware, or can be realized with the combination of specialized hardware and computer instruction.
In addition, each functional module in each embodiment of the invention can integrate to form an independent portion
Divide, or modules individualism, it is also possible to which two or more modules are integrated to form an independent part.
If the function is realized using in the form of software function module and as independent production marketing or when using, can be with
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially in other words
The part contributed to prior art or the part of the technical scheme can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, is used including some instructions so that a computer equipment (can be individual
People's computer, server, or network equipment etc.) perform all or part of step of each embodiment methods described of the invention.
And aforesaid storage medium includes：USB flash disk, portable hard drive, read-only storage (ROM, Read-Only Memory), arbitrary access
Memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with the medium of store program codes.Need
It is noted that herein, such as first and second or the like relational terms are used merely to an entity or operation
Make a distinction with another entity or operation, and not necessarily require or imply these entities or exist between operating any this
Actual relation or order.And, term " including ", "comprising" or its any other variant are intended to nonexcludability
Comprising so that a series of process, method, article or equipment including key elements not only includes those key elements, but also wrapping
Other key elements being not expressly set out are included, or also includes intrinsic for this process, method, article or equipment wanting
Element.In the absence of more restrictions, the key element for being limited by sentence "including a ...", it is not excluded that wanting including described
The process of element, method, also there is other identical element in article or equipment.
The preferred embodiments of the present invention are the foregoing is only, the present invention is not limited to, for the skill of this area
For art personnel, the present invention can have various modifications and variations.It is all within the spirit and principles in the present invention, made any repair
Change, equivalent, improvement etc., should be included within the scope of the present invention.It should be noted that：Similar label and letter exist
Similar terms is represented in figure below, therefore, once being defined in a certain Xiang Yi accompanying drawing, then it is not required in subsequent accompanying drawing
Which is further defined and is explained.
Claims (10)
1. a kind of distribution project management trend forecasting method, it is characterised in that include：
Acquisition prestores multiple project datas in the local database, and each described project data includes goods and materials amount and fund
Amount；
Scatter diagram is drawn based on the goods and materials amount and the capital quantity, each point on the scatter diagram characterizes a project,
One project correspondence, one project data；
The project to be analyzed shown on the scatter diagram is obtained based on the first preset rules；
The project to be analyzed is carried out into cluster operation according to the second preset rules, multiple cluster classes, a cluster class bag is obtained
Include one or more described projects to be analyzed；
The standard feature figure of each project to be analyzed in each described cluster class is obtained, the standard feature figure is used to represent
The time schedule of one project to be analyzed and fund situation of change；
Current material total and total amount of the fund with the project described to be analyzed in cluster class is drawn based on the standard feature figure
History feature figure, described in the same cluster class that the history feature figure is used to represent the special time before current time node are treated point
The material total and the total amount of the fund of analysis project；
The predicted characteristics figure of the same cluster intermediate item is obtained based on the standard feature figure and the history feature figure.
2. method according to claim 1, it is characterised in that it is multiple that the acquisition prestores in the local database
The step of project data, includes：
Acquisition prestores initial project data in the local database；
Data filtering process is carried out to the initial project data based on the uniformity of data, integrality and available standards, is obtained
Multiple described project data after filtration.
3. method according to claim 1, it is characterised in that the standard feature figure with time schedule as transverse axis and with
Capital quantity is the longitudinal axis, and the history feature figure is with time schedule as transverse axis and with capital quantity as the longitudinal axis, described based on the mark
After the step of quasi- characteristic pattern obtains the predicted characteristics figure of the same cluster intermediate item with the history feature figure, also include：
The capital quantity shown on each described predicted characteristics figure in the same cluster class is added the following money for obtaining the cluster class
Golden total amount；
The goods and materials amount shown on each described predicted characteristics figure in the same cluster class is added the following thing for obtaining the cluster class
Money total amount；
Future features figure, the future features figure are obtained with the time schedule as transverse axis and by the longitudinal axis of the capital quantity respectively
For representing the following total amount of the fund and the following material total.
4. method according to claim 1, it is characterised in that first preset rules that are based on are obtained on the scatter diagram
The step of project to be analyzed for showing, includes：
It is equal on the curve of the capital quantity place and when described scattered when the point being distributed on the scatter diagram is located at the goods and materials amount
The point being distributed on point diagram near the goods and materials amount be equal to the capital quantity place curve when, obtain the item number represented by the point
According to；
The project data is labeled as into project to be analyzed.
5. method according to claim 1, it is characterised in that it is described by the project to be analyzed according to the second preset rules
Cluster operation is carried out, is included the step of obtain multiple cluster classes：
Obtain the project to be analyzed corresponding project cycle, the project budget and item types；
The project cycle, the project budget and the item types are converted into numerical value to represent, by K-means
Algorithm carries out cluster operation, obtains multiple cluster classes.
6. method according to claim 1, it is characterised in that treat described in each in the acquisition each described cluster class point
The step of standard feature figure of analysis project, includes：
Obtain the characteristic pattern of each project to be analyzed in each described cluster class；
K- is based on the business of the project cycle in project to be analyzed each described and project budget expenditure time to calculate the factor
Means algorithms carry out process and obtain the standard feature figure to the characteristic pattern.
7. a kind of distribution project management trend prediction device, it is characterised in that described device includes：
First data capture unit, for obtaining the multiple project datas for prestoring in the local database, each described item
Mesh number is according to including goods and materials amount and capital quantity；
First chart drawing unit, for drawing scatter diagram based on the goods and materials amount and the capital quantity, on the scatter diagram
Each point characterizes a project, one project data of a project correspondence；
Second data capture unit, for obtaining the project to be analyzed shown on the scatter diagram based on the first preset rules；
First data processing unit, for the project to be analyzed is carried out cluster operation according to the second preset rules, obtains many
Individual cluster class, a cluster class include one or more described projects to be analyzed；
3rd data capture unit, for obtaining the standard feature figure of each project to be analyzed in each described cluster class,
The standard feature figure is used for time schedule and the fund situation of change for representing a project to be analyzed；
Second graph drawing unit, for being drawn with the current of the project described to be analyzed in cluster class based on the standard feature figure
The history feature figure of material total and total amount of the fund, the special time that the history feature figure is used for before representing current time node
Same cluster class in project described to be analyzed the material total and the total amount of the fund；
4th data capture unit, for obtaining the same cluster intermediate item with the history feature figure based on the standard feature figure
Predicted characteristics figure.
8. device according to claim 7, it is characterised in that first data capture unit specifically for：
Acquisition prestores initial project data in the local database；
Data filtering process is carried out to the initial project data based on the uniformity of data, integrality and available standards, is obtained
Multiple described project data after filtration.
9. device according to claim 7, it is characterised in that the standard feature figure with time schedule as transverse axis and with
Capital quantity is the longitudinal axis, and with time schedule as transverse axis and with capital quantity as the longitudinal axis, the 4th data are obtained the history feature figure
After taking unit, also include：
Second data processing unit, the capital quantity for will show on each the described predicted characteristics figure in the same cluster class are added
Obtain the following total amount of the fund of the cluster class；
3rd data processing unit, the goods and materials amount for will show on each the described predicted characteristics figure in the same cluster class are added
Obtain the following material total of the cluster class；
5th data capture unit, for respectively with the time schedule as transverse axis and with the capital quantity as longitudinal axis acquisition future
Characteristic pattern, the future features figure are used to represent the following total amount of the fund and the following material total.
10. device according to claim 7, it is characterised in that second data capture unit is additionally operable to：
It is equal on the curve of the capital quantity place and when described scattered when the point being distributed on the scatter diagram is located at the goods and materials amount
The point being distributed on point diagram near the goods and materials amount be equal to the capital quantity place curve when, obtain the item number represented by the point
According to；
The project data is labeled as into project to be analyzed.
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| CN201610976648.1A CN106528774A (en) | 2016-11-07 | 2016-11-07 | Method and apparatus for predicting distribution network project management trend |
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| CN201610976648.1A CN106528774A (en) | 2016-11-07 | 2016-11-07 | Method and apparatus for predicting distribution network project management trend |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110147441A (en) * | 2019-04-03 | 2019-08-20 | 平安科技（深圳）有限公司 | Data integration display method and device, terminal equipment and medium |
| CN112950742A (en) * | 2021-01-26 | 2021-06-11 | 广西电网有限责任公司电力科学研究院 | Microgrid source-load comprehensive characteristic image construction method and device and storage medium |
| CN117151934A (en) * | 2023-10-30 | 2023-12-01 | 国网冀北电力有限公司 | Multi-dimensional cluster analysis method and device for uninterrupted operation project of power distribution network |
| CN117726304A (en) * | 2024-02-05 | 2024-03-19 | 天津航远信息技术有限公司 | Project progress prediction and project resource allocation recommendation method |
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2016
- 2016-11-07 CN CN201610976648.1A patent/CN106528774A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110147441A (en) * | 2019-04-03 | 2019-08-20 | 平安科技（深圳）有限公司 | Data integration display method and device, terminal equipment and medium |
| CN110147441B (en) * | 2019-04-03 | 2022-05-13 | 平安科技（深圳）有限公司 | Data integration display method and device, terminal equipment and medium |
| CN112950742A (en) * | 2021-01-26 | 2021-06-11 | 广西电网有限责任公司电力科学研究院 | Microgrid source-load comprehensive characteristic image construction method and device and storage medium |
| CN117151934A (en) * | 2023-10-30 | 2023-12-01 | 国网冀北电力有限公司 | Multi-dimensional cluster analysis method and device for uninterrupted operation project of power distribution network |
| CN117151934B (en) * | 2023-10-30 | 2024-01-30 | 国网冀北电力有限公司 | Multi-dimensional cluster analysis method and device for uninterrupted operation project of power distribution network |
| CN117726304A (en) * | 2024-02-05 | 2024-03-19 | 天津航远信息技术有限公司 | Project progress prediction and project resource allocation recommendation method |
| CN117726304B (en) * | 2024-02-05 | 2024-05-17 | 天津航远信息技术有限公司 | Project progress prediction and project resource allocation recommendation method |
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Application publication date: 20170322 |