CN113496391B - Project completion expense prediction method and device, terminal and storage medium - Google Patents

Project completion expense prediction method and device, terminal and storage medium Download PDF

Info

Publication number
CN113496391B
CN113496391B CN202110811644.9A CN202110811644A CN113496391B CN 113496391 B CN113496391 B CN 113496391B CN 202110811644 A CN202110811644 A CN 202110811644A CN 113496391 B CN113496391 B CN 113496391B
Authority
CN
China
Prior art keywords
cost
work package
work
cpi
acwp
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.)
Active
Application number
CN202110811644.9A
Other languages
Chinese (zh)
Other versions
CN113496391A (en
Inventor
纪璠
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Mountop Group Co ltd
Original Assignee
Mountop Group Co ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Mountop Group Co ltd filed Critical Mountop Group Co ltd
Priority to CN202110811644.9A priority Critical patent/CN113496391B/en
Publication of CN113496391A publication Critical patent/CN113496391A/en
Application granted granted Critical
Publication of CN113496391B publication Critical patent/CN113496391B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

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
    • G06Q10/10—Office automation; Time management
    • G06Q10/103—Workflow collaboration or project management
    • 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
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • 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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0206—Price or cost determination based on market factors

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Human Resources & Organizations (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Marketing (AREA)
  • Finance (AREA)
  • Accounting & Taxation (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • Data Mining & Analysis (AREA)
  • Game Theory and Decision Science (AREA)
  • Tourism & Hospitality (AREA)
  • Operations Research (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a project completion expense prediction method and device, a terminal and a storage medium, wherein the method comprises the following steps: according to the current process of each work package in the project, respectively determining a finished work package, an unexploited work package and an ongoing work package; the cost of the work package which is completed is calculated according to the actual cost, the cost of the work package which is not started to be performed is calculated according to the planned cost, and the cost of the work package which is performed is budgeted: the cost of the completed work packages, the cost of the work packages that did not begin to proceed, and the cost of the work packages that were proceeding are summarized. The invention calculates the on-going work package completion cost by using the work package process weighting prediction function, not only can predict the condition that the struggle check point is positioned at the stage of the work package just beginning and generate more accurate results, but also can predict the condition that the struggle check point is close to the planned completion time of the work package and generate more accurate results.

Description

Project completion expense prediction method and device, terminal and storage medium
Technical Field
The invention relates to the field of engineering project management, in particular to a project completion expense prediction method and device, a terminal and a storage medium.
Background
In struggle value analysis, predicting the cost of completing a project is a very important link. Because the struggle value method is not only a cost control mode for correcting the deviation of the cost or progress found by the struggle value check point, the concept of predicting the project completion expense is also embodied in an important prior control method. The prior control, the in-process control and the after-process control are all important constituent phases of cost control.
In the process of developing projects, many enterprises often pay more attention to in-process control and post-process control, and neglect the pre-process control relatively. However, the prediction cost is accurately controlled in advance, which is often as important as the in-process control and the post-process control, so that the quantitative management of the cost is facilitated, the implementation of the cost control of the whole process is facilitated, and the cost of the project is controlled more effectively.
The project Completion cost is predicted (ESTIMATE AT Completion, EAC) according to the struggle value method, and the following three methods are mainly available at present:
The first method assumes that the cost of the finished part of the project can represent the cost of the unfinished part of the project, and the unfinished part of the project is predicted according to the uniform cost execution index of the finished part, namely:
EAC＝ACWP+(BAC-BCWP)/CPI；
the second method assumes that the project incomplete part is predicted according to the project residual cost, and has the following prediction formula:
EAC＝ACWP+BAC-BCWP；
The third method is that the cost of the finished part of the project is insufficient to estimate the cost of the unfinished part of the project, and the cost of the unfinished part of the project is estimated again comprehensively, and the prediction formula is as follows:
Eac= ACWP + re-estimated remaining operating costs;
Where BAC is the total cost of project planning, ACWP is the actual cost of completed workload, BCWP is the budget cost of completed workload, and 1/CPI is the uniform cost performance index of the part already in progress.
Both the first and second methods are true under certain assumptions, which are not satisfied in many cases during actual project progress.
In view of the limitations of both assumptions, it has been analyzed that project completion cost predictions are strongly linked to ongoing work package cost predictions. For an ongoing work package, when the struggle check point is located at the beginning of the work package, the predicted completion cost of the work package can be used for predicting the completion cost, and when the struggle check point is close to the planned completion time of the ongoing work package, the predicted completion cost of the work package by using the calculated CPI is more accurate. And for work packages that have not yet been developed, it is more reasonable to make statistics with either a planned work budget fee or a planned engineering investment amount (Budgeted Cost for Work Performed, BCWS). Based on such a consideration, it is necessary to study a method capable of more reasonably predicting the completion costs as well as predicting the completion period of an ongoing work package.
Disclosure of Invention
The invention aims to: aiming at the defects of the existing project completion cost prediction method, the invention aims to provide a project completion cost prediction method, a project completion cost prediction device, a terminal and a storage medium, so that the completion cost can be predicted more reasonably.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
A project completion fee prediction method, the method comprising: according to the current process of each work package in the project, respectively determining a finished work package, an unexploited work package and an ongoing work package; the cost of the work package which is completed is calculated according to the actual cost, the cost of the work package which is not started to be performed is calculated according to the planned cost, and the cost of the work package which is performed is budgeted: summarizing the cost of the completed work packages, the cost of the work packages that are not started to be performed, and the cost of the work packages that are performed;
wherein the cost budget steps for an ongoing work package are as follows:
the following weighted prediction function is defined that considers the work package process:
w1(λ)＝e-αλ (1)
w2(λ)＝1/CPIi×(1-e-αλ) (2)
wa(λ)＝w1(λ)+w2(λ)＝e-αλ+1/CPIi×(1-e-αλ) (3)
Where λ=at i/BTi is the ratio of the number of days that the ith work package has started AT the time of the checkpoint to the number of days planned to finish, which is an amount reflecting the time course of the work package; AT i is the number of days the ith work package has started working AT the time of the checkpoint; BT i is the number of days the ith work package is planned to finish; alpha is a constant controlling the decay rate of the exponential function, CPI is a cost performance indicator, known as 1/CPI i＝ACWPi/BCWPi;
The following calculation equation is set forth for the projected completion cost of an ongoing single work package:
EACi＝ACWPi+(BACi-BCWPi)×wa(λ) (4)
Wherein ：wa(λ)＝e-αλ+1/CPIi×(1-e-αλ)＝e-αλ+ACWPi/BCWPi×(1-e-αλ), substitutes equation (3) into equation (4) to obtain the predicted work package completion cost as follows:
EACi＝ACWPi+(BACi-BCWPi)×(e-αλ+ACWPi/BCWPi×(1-e-αλ)) (5)
Where BAC i is the projected cost of work package i, ACWP i is the actual cost of work package i having performed the work load, BCWP i is the budget cost of work package i having completed the work load, and EAC i is the predicted completion cost of work package i.
Further, the value of the constant α controlling the decay rate of the exponential function is determined by the following requirements:
Let w 2(λ)＝0.99×1/CPIi, where the value of the weighted prediction function is almost equal to 1/CPI i, when λ is 0.99, there is:
1-e -αλ = 0.99, i.e.: e -0.99α = 0.01, solved: α= -ln (0.01)/0.99= 4.652.
An item completion fee prediction apparatus comprising:
the determining module is used for respectively determining the completed work packages, the work packages which do not start to be processed and the work packages which are in progress according to the current process of each work package in the project;
The budget module is used for calculating the cost of the finished work package according to the actual cost, calculating the cost of the work package which is not started to be performed according to the planned cost, and budgeting the cost of the work package which is performed:
and the summarizing module is used for summarizing the cost of the completed work package, the cost of the work package which is not started to be performed and the cost of the work package which is performed.
The cost budget steps for an ongoing work package are as follows:
the following weighted prediction function is defined that considers the work package process:
w1(λ)＝e-αλ (1)
w2(λ)＝1/CPIi×(1-e-αλ) (2)
wa(λ)＝w1(λ)+w2(λ)＝e-αλ+1/CPIi×(1-e-αλ) (3)
Where λ=at i/BTi is the ratio of the number of days that the ith work package has started AT the time of the checkpoint to the number of days planned to finish, which is an amount reflecting the time course of the work package; AT i is the number of days the ith work package has started working AT the time of the checkpoint; BT i is the number of days the ith work package is planned to finish; alpha is a constant controlling the decay rate of the exponential function, CPI is a cost performance indicator, known as 1/CPI i＝ACWPi/BCWPi;
The following calculation equation is set forth for the projected completion cost of an ongoing single work package:
EACi＝ACWPi+(BACi-BCWPi)×wa(λ) (4)
Wherein ：wa(λ)＝e-αλ+1/CPIi×(1-e-αλ)＝e-αλ+ACWPi/BCWPi×(1-e-αλ), substitutes equation (3) into equation (4) to obtain the predicted work package completion cost as follows:
EACi＝ACWPi+(BACi-BCWPi)×(e-αλ+ACWPi/BCWPi×(1-e-αλ)) (5)
Where BAC i is the projected cost of work package i, ACWP i is the actual cost of work package i having performed the work load, BCWP i is the budget cost of work package i having completed the work load, and EAC i is the predicted completion cost of work package i.
Further, the value of the constant α controlling the decay rate of the exponential function is determined by the following requirements:
Let w 2(λ)＝0.99×1/CPIi, where the value of the weighted prediction function is almost equal to 1/CPI i, when λ is 0.99, there is:
1-e -αλ = 0.99, i.e.: e -0.99α = 0.01, solved: α= -ln (0.01)/0.99= 4.652.
The terminal comprises a processor and a memory, wherein the memory stores instructions, and the processor executes the instructions to enable the terminal to execute the project completion expense prediction method.
A storage medium storing a computer program comprising program instructions which, when executed by a computer, cause the computer to perform the project completion expense prediction method described above.
The beneficial effects are that: compared with the current project completion expense prediction method, the work package process weighting prediction function is utilized to calculate the ongoing work package completion cost, so that not only can the current situation that the struggle value check point is positioned at the stage of the work package just beginning be predicted and a more accurate result can be generated, but also the current situation that the struggle value check point is close to the planned completion time of the work package can be predicted and a more accurate result can be generated.
Drawings
FIG. 1 is a flow chart of a method for predicting completion costs of the project of the present invention;
FIG. 2 is a graph of weighted prediction functions for a 1/CPI of 1;
FIG. 3 is a graph of weighted prediction functions for a 1/CPI of 0.8;
FIG. 4 is a graph of weighted prediction functions for a 1/CPI of 1.2;
FIG. 5 is a graph comparing the prediction results of the conventional prediction method and the process-weighted work pack completion cost prediction method of the present invention.
FIG. 6 is a schematic diagram of a device for predicting the completion expense of the project according to the present invention;
the specific embodiment is as follows:
the invention is further explained below with reference to the drawings.
As shown in fig. 1, a project completion fee prediction method of the present invention includes: according to the current process of each work package in the project, respectively determining a finished work package, an unexploited work package and an ongoing work package; calculating the cost of the finished work package according to the actual cost, calculating the cost of the work package which does not start to be performed according to the planned cost, and budgeting the cost of the work package which is performed; the cost of the completed work packages, the cost of the work packages that did not begin to proceed, and the cost of the work packages that were proceeding are summarized.
The cost budget steps for an ongoing work package are as follows:
the following weighted prediction function is defined that considers the work package process:
w1(λ)＝e-αλ (1)
w2(λ)＝1/CPIi×(1-e-αλ) (2)
w(λ)＝w1(λ)+w2(λ)＝e-αλ+1/CPIi×(1-e-αλ) (3)
Where λ=at i/BTi is the ratio of the number of days that the ith work package has started AT the time of the checkpoint to the number of days planned to finish, which is an amount reflecting the time course of the work package; AT i is the number of days the ith work package has started working AT the time of the checkpoint; BT i is the number of days the ith work package is planned to finish; alpha is a constant for controlling the decay rate of the exponential function, CPI is a cost performance index, meaning the ratio of earned value to actual cost value, is the ratio between the budget cost of the project having completed the workload and the actual cost of having completed the workload. The calculation formula is as follows: cpi= BCWP/ACWP, a concept in struggle value method. 1/CPI i＝ACWPi/BCWPi is known;
the alpha value is determined by the following requirements: i.e. lambda 0.99, let w 2(λ)＝0.99×1/CPIi, where the value of the weighted prediction function is almost equal to 1/CPI i. The method comprises the following steps: 1-e -αλ = 0.99, i.e.: e -0.99α = 0.01, solved: α= -ln (0.01)/0.99= 4.652.
Fig. 2 to 4 show the relationship between the ratio of the time at which the weighted prediction function actually starts working at the checkpoint to the planned time for 1/CPI values calculated at the checkpoint of 1, 0.8 and 1.2, respectively.
The following calculation equation is set forth for the projected completion cost of an ongoing single work package:
EACi＝ACWPi+(BACi-BCWPi)×wa(λ) (4)
Wherein ：wa(λ)＝e-αλ+1/CPIi×(1-e-αλ)＝e-αλ+ACWPi/BCWPi×(1-e-αλ), substitutes equation (3) into equation (4) to obtain the predicted work package completion cost as follows:
EACi＝ACWPi+(BACi-BCWPi)×(e-αλ+ACWPi/BCWPi×(1-e-αλ)) (5)
Equation (5) relates to the process of the work package, so it is called a process weighted prediction method of the work package completion cost, wherein BAC i is the planning cost of the work package i, ACWP i is the actual cost of the work package i for which the work has been performed, BCWP i is the budget cost of the work package i for which the work has been completed, EAC i is the predicted completion cost of the work package i;
taking a work package with a budget cost of 30 ten thousand yuan and planned to be completed for 30 days as an example, simulation comparison analysis is carried out. The total workload of the work package is to install 100 tons of equipment. The budgeted ton unit price is 30/100=0.3 ten thousand yuan/ton.
The following analysis and comparison is made with the existing method of predicting by the uniform cost performance index hypothesis (the existing first method) and the process weighted prediction method proposed herein, see table below and fig. 5.
Comparing results of existing method and process weighted prediction method
As can be seen from the above table and fig. 4, the new process weighted work pack cost prediction method presented herein outperforms the results presented by the existing prediction methods.
Aiming at the limitation of the existing project completion cost prediction method in the practical application of projects, the invention provides a new project completion cost prediction method, and the prediction of the project overall completion cost is carried out according to the following thought: the cost of the work package that has been completed is calculated according to the actual cost ACWP, the cost of the work package that has not been started is calculated according to the planned cost BCWS, and the work package completion cost prediction method given herein for the new process-weighted work package is used for the work package that is in progress. The new process weighting work package completion cost prediction method not only can predict the situation that the struggle value check point is located at the stage of the work package just beginning and generate more accurate results, but also can predict the situation that the struggle value check point is close to the planned completion time of the work package and generate more accurate results, and the total project completion cost is the sum of the three items. Namely:
Wherein: p+m+q=n, EAC is the total predicted cost of the project; ACWP i is the actual cost of the ith work package, EAC j is the predicted cost of the jth ongoing work package, and BCWS k is the budget cost of the kth not yet ongoing work package; p is the number of completed work packages, m is the number of work packages in progress, q is the number of work packages not yet in progress, and N is the total number of work packages for the project.
As shown in fig. 5, an item completion fee prediction apparatus of the present invention includes: the determining module is used for respectively determining the completed work packages, the work packages which do not start to be processed and the work packages which are in progress according to the current process of each work package in the project; the budget module is used for calculating the cost of the finished work package according to the actual cost, calculating the cost of the work package which is not started to be performed according to the planned cost, and budgeting the cost of the work package which is performed: and the summarizing module is used for summarizing the cost of the completed work package, the cost of the work package which is not started to be performed and the cost of the work package which is performed.
The cost budget steps for an ongoing work package are as follows:
the following weighted prediction function is defined that considers the work package process:
w1(λ)＝e-αλ (1)
w2(λ)＝1/CPIi×(1-e-αλ) (2)
wa(λ)＝w1(λ)+w2(λ)＝e-αλ+1/CPIi×(1-e-αλ) (3)
Where λ=at i/BTi is the ratio of the number of days that the ith work package has started AT the time of the checkpoint to the number of days planned to finish, which is an amount reflecting the time course of the work package; AT i is the number of days the ith work package has started working AT the time of the checkpoint; BT i is the number of days the ith work package is planned to finish; alpha is a constant controlling the decay rate of the exponential function, CPI is a cost performance indicator, known as 1/CPI i＝ACWPi/BCWPi;
The alpha value is determined by the following requirements: let w 2(λ)＝0.99×1/CPIi, where the value of the weighted prediction function is almost equal to 1/CPI i, when λ is 0.99, there is: 1-e -αλ = 0.99, i.e.: e -0.99α = 0.01, solved: α= -ln (0.01)/0.99= 4.652;
The following calculation equation is set forth for the projected completion cost of an ongoing single work package:
EACi＝ACWPi+(BACi-BCWPi)×wa(λ) (4)
Wherein ：wa(λ)＝e-αλ+1/CPIi×(1-e-αλ)＝e-αλ+ACWPi/BCWPi×(1-e-αλ), substitutes equation (3) into equation (4) to obtain the predicted work package completion cost as follows:
EACi＝ACWPi+(BACi-BCWPi)×(e-αλ+ACWPi/BCWPi×(1-e-αλ)) (5)
Where BAC i is the projected cost of work package i, ACWP i is the actual cost of work package i having performed the work load, BCWP i is the budget cost of work package i having completed the work load, and EAC i is the predicted completion cost of work package i.
The terminal of the invention comprises a processor and a memory, wherein the memory stores instructions, and the processor executes the instructions to enable the terminal to execute the project completion expense prediction method.
A storage medium storing a computer program comprising program instructions which, when executed by a computer, cause the computer to perform the project completion cost prediction method described above.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims (4)

1. A method of project completion expense prediction, the method comprising: according to the current process of each work package in the project, respectively determining a finished work package, an unexploited work package and an ongoing work package; the cost of the work package which is completed is calculated according to the actual cost, the cost of the work package which is not started to be performed is calculated according to the planned cost, and the cost of the work package which is performed is budgeted: summarizing the cost of the completed work packages, the cost of the work packages that are not started to be performed, and the cost of the work packages that are performed;
wherein the cost budget steps for an ongoing work package are as follows:
the following weighted prediction function is defined that considers the work package process:
w1(λ)＝e-αλ (1)
w2(λ)＝1/CPIi×(1-e-αλ) (2)
wa(λ)＝w1(λ)+w2(λ)＝e-αλ+1/CPIi×(1-e-αλ) (3)
Where λ=at i/BTi is the ratio of the number of days that the ith work package has started AT the time of the checkpoint to the number of days planned to finish, which is an amount reflecting the time course of the work package; AT i is the number of days the ith work package has started working AT the time of the checkpoint; BT i is the number of days the ith work package is planned to finish; alpha is a constant controlling the decay rate of the exponential function, CPI is a cost performance indicator, known as 1/CPI i＝ACWPi/BCWPi;
the value of the constant α controlling the decay rate of the exponential function is determined by the following requirements:
Let w 2(λ)＝0.99×1/CPIi, where the value of the weighted prediction function is almost equal to 1/CPI i, when λ is 0.99, there is:
1-e -αλ = 0.99, i.e.: e -0.99α = 0.01, solved: α= -ln (0.01)/0.99= 4.652;
The following calculation equation is set forth for the projected completion cost of an ongoing single work package:
EACi＝ACWPi+(BACi-BCWPi)×wa(λ) (4)
Wherein ：wa(λ)＝e-αλ+1/CPIi×(1-e-αλ)＝e-αλ+ACWPi/BCWPi×(1-e-αλ), substitutes equation (3) into equation (4) to obtain the predicted work package completion cost as follows:
EACi＝ACWPi+(BACi-BCWPi)×(e-αλ+ACWPi/BCWPi×(1-e-αλ)) (5)
Where BAC i is the projected cost of work package i, ACWP i is the actual cost of work package i having performed the work load, BCWP i is the budget cost of work package i having completed the work load, and EAC i is the predicted completion cost of work package i.
2. An apparatus for predicting a completion cost of an item, comprising:
the determining module is used for respectively determining the completed work packages, the work packages which do not start to be processed and the work packages which are in progress according to the current process of each work package in the project;
The budget module is used for calculating the cost of the finished work package according to the actual cost, calculating the cost of the work package which is not started to be performed according to the planned cost, and budgeting the cost of the work package which is performed:
The summarizing module is used for summarizing the cost of the completed work package, the cost of the work package which is not started to be performed and the cost of the work package which is performed;
The cost budget steps for an ongoing work package are as follows:
the following weighted prediction function is defined that considers the work package process:
w1(λ)＝e-αλ (1)
w2(λ)＝1/CPIi×(1-e-αλ) (2)
wa(λ)＝w1(λ)+w2(λ)＝e-αλ+1/CPIi×(1-e-αλ) (3)
Where λ=at i/BTi is the ratio of the number of days that the ith work package has started AT the time of the checkpoint to the number of days planned to finish, which is an amount reflecting the time course of the work package; AT i is the number of days the ith work package has started working AT the time of the checkpoint; BT i is the number of days the ith work package is planned to finish; alpha is a constant controlling the decay rate of the exponential function, CPI is a cost performance indicator, known as 1/CPI i＝ACWPi/BCWPi;
the value of the constant α controlling the decay rate of the exponential function is determined by the following requirements:
Let w 2(λ)＝0.99×1/CPIi, where the value of the weighted prediction function is almost equal to 1/CPI i, when λ is 0.99, there is:
1-e -αλ = 0.99, i.e.: e -0.99α = 0.01, solved: α= -ln (0.01)/0.99= 4.652;
The following calculation equation is set forth for the projected completion cost of an ongoing single work package:
EACi＝ACWPi+(BACi-BCWPi)×wa(λ) (4)
Wherein ：wa(λ)＝e-αλ+1/CPIi×(1-e-αλ)＝e-αλ+ACWPi/BCWPi×(1-e-αλ), substitutes equation (3) into equation (4) to obtain the predicted work package completion cost as follows:
EACi＝ACWPi+(BACi-BCWPi)×(e-αλ+ACWPi/BCWPi×(1-e-αλ)) (5)
Where BAC i is the projected cost of work package i, ACWP i is the actual cost of work package i having performed the work load, BCWP i is the budget cost of work package i having completed the work load, and EAC i is the predicted completion cost of work package i.
3. A terminal comprising a processor and a memory, the memory having instructions stored therein, which when executed by the processor, cause the terminal to perform the method of claim 1.
4. A storage medium storing a computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method of claim 1.
CN202110811644.9A 2021-07-19 2021-07-19 Project completion expense prediction method and device, terminal and storage medium Active CN113496391B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110811644.9A CN113496391B (en) 2021-07-19 2021-07-19 Project completion expense prediction method and device, terminal and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110811644.9A CN113496391B (en) 2021-07-19 2021-07-19 Project completion expense prediction method and device, terminal and storage medium

Publications (2)

Publication Number Publication Date
CN113496391A CN113496391A (en) 2021-10-12
CN113496391B true CN113496391B (en) 2024-05-28

Family

ID=77996551

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110811644.9A Active CN113496391B (en) 2021-07-19 2021-07-19 Project completion expense prediction method and device, terminal and storage medium

Country Status (1)

Country Link
CN (1) CN113496391B (en)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101529679B1 (en) * 2014-02-28 2015-06-18 연세대학교 산학협력단 Integrated co2-cost-schedule management system and method for building construction projects using the earned value management theory
CN105139159A (en) * 2015-10-12 2015-12-09 南京富士通南大软件技术有限公司 Project cost management and control method in power industry
CN108416477A (en) * 2018-03-15 2018-08-17 国家电网公司 It is a kind of that multi-dimensional optimization method is implemented based on the distribution network engineering for improving Earned Value

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101529679B1 (en) * 2014-02-28 2015-06-18 연세대학교 산학협력단 Integrated co2-cost-schedule management system and method for building construction projects using the earned value management theory
CN105139159A (en) * 2015-10-12 2015-12-09 南京富士通南大软件技术有限公司 Project cost management and control method in power industry
CN108416477A (en) * 2018-03-15 2018-08-17 国家电网公司 It is a kind of that multi-dimensional optimization method is implemented based on the distribution network engineering for improving Earned Value

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
挣值法在软件项目监理中的应用;蒋孝军;张守梅;秦升平;;信息技术与信息化;20130415(第02期);第99-101页 *

Also Published As

Publication number Publication date
CN113496391A (en) 2021-10-12

Similar Documents

Publication Publication Date Title
US20100180259A1 (en) Software Defect Forecasting System
JPH0789283B2 (en) Formula processing control system
CN111310998B (en) Method and device for generating critical path, electronic equipment and medium
CN113496391B (en) Project completion expense prediction method and device, terminal and storage medium
KR102108541B1 (en) Apparatus and method for managing counselor schedule
CN116957577A (en) Gas value estimation method, device, storage medium and equipment in transaction
Walter et al. Further analysis of a computing center environment
CN110377525B (en) Parallel program performance prediction system based on runtime characteristics and machine learning
Reinschmidt et al. Construction cash flow management system
JP7110624B2 (en) Operation planning method, operation planning device and program
CN109800975A (en) A kind of stock assessment method, apparatus, computer equipment and storage medium
CN113641674B (en) Self-adaptive global sequence number generation method and device
CN112564186B (en) Energy storage power and capacity planning method and system for assisting thermal power generating unit in deep peak shaving
Bogle et al. Stochastic optimization of water supply expansion
JP3206673B2 (en) Automatic control device for ozone generation
JP3612428B2 (en) Software reliability prediction method and apparatus and recording medium
Vestal On the accuracy of predicting rate monotonic scheduling performance
CN109140679B (en) A kind of permanent wind amount adjustment method, device and air-conditioning
RU210788U1 (en) A device for assessing the risk of implementing a program for the development of complex technical systems
Yasmin et al. Implementation of Critical Path Method and What If Analysis in Project Management Information System
CN116957618A (en) Thermal power unit carbon emission cost daily rolling prediction method
CN111697562B (en) SVM-based transient stability prevention control strategy generation method and device
CN116993386A (en) Quota design management method and system for constructional engineering
WO2023095191A1 (en) Information processing device, and computer-readable storage medium
JP3053482B2 (en) Method for controlling injection amount of aluminum compound in treatment of wastewater containing fluorine and aluminum and fluorine removing device

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