CN106327023A - Method and device for measuring transmission project man hour quota - Google Patents
Method and device for measuring transmission project man hour quota Download PDFInfo
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Abstract
The invention provides a method and a device for measuring a transmission project man hour quota. The method comprises steps: influencing factor historical sample data and man hour historical sample data of the transmission project are acquired; according to the particle swarm iteration times, an inertia weight, a learning factor, a particle speed and a swarm scale for the transmission project man hour, a transmission project man hour particle swarm model is built; a fruit fly optimization algorithm is adopted to carry out model parameter optimization on the transmission project man hour particle swarm model, and a fruit fly particle swarm model is obtained; according to the influencing factor historical sample data, the iteration times of the fruit fly particle swarm model, an inertia weight and the optimal value of a learning factor are determined, the weight and the threshold of a fruit fly particle swarm radial basis function neural network measurement model are determined, and the fruit fly particle swarm radial basis function neural network measurement model is built; and according to the man hour historical sample data and the fruit fly particle swarm radial basis function neural network measurement model, a transmission project man hour quota measurement result is generated. The measured transmission project man hour meets the practice of the transmission project.
Description
Technical field
The present invention relates to power transmission engineering technical field, in particular it relates to a kind of power transmission engineering time allowance assay method and
Device.
Background technology
In order to ensure the legal economic interests of each side in power transmission engineering, should calculate and develop scientific and reasonable and actual work
The engineering valuating basis that Cheng Chengben phase is agreed with.The subject matter of power transmission engineering time allowance assay method of the prior art is:
Norm Measure method falls behind, and rating level can not truly reflect that practical situation, major part engineering staff still use " experience estimation
Method " measure power transmission engineering man-hour, and not quality to human users, the flow process of operation, the rhythm of operation carries out the research of science
And assessment.
Time allowance measures conventional method at present substantially three kinds, i.e. experience estimation method, statistical analysis method and technology is surveyed
Determine method.
(1) experience estimation method
Experience estimation method is to be combined in one by quota management professional, engineers and technicians and veteran workman
Rise, according to individual or the practical experience of collective, through to design drawing and site operation situation analysis, understand construction technology, point
After the complexity of analysis construction organization and operational approach, by having an informal discussion, the method formulating quota is discussed.Experience estimation method is the easiest
OK, workload is little, and speed is fast, reduces and measures link, shortens the working time drafting quota.Its shortcoming is that degree of accuracy is poor,
Limited by assessment personnel's construction experience, the subjective one-sided phenomenon that assessment value is higher or on the low side is easily occurred.It is typically limited to only secondary
Want quota project or the estimation of quota provisional, disposable, and quota lacuna and when being eager to use, be difficult to computational engineering again
The fragmentary engineering of amount uses.
(2) statistical analysis method
Statistical analysis method is by similar projects in past construction or to produce the engineering consumption of like product, material consumption, machine
The statistics that tool machine-team consumes, it is considered to current construction technology, execution conditions, the changing factor of construction organization carry out statistical analysis
The method studying and defining quota.Statistical analysis method is simple, and workload is little.If the statistics relevant with construction production to the past
Data analyzed, arrange and just can calculate quota index.Its shortcoming is to adopt this method the rating level calculated
Inevitably affected by abnormal factor during in the past construction produces, and construction protocol, statistics accurate
The impact that degree is poor, makes the quota index distortion of measuring and calculating.Therefore, its scope of application be limited to some secondary quota project with
And some cannot be carried out the project of technical measurement on the spot.
(3) technical measurement method
Technical measurement method is according to the rational production technology of advanced person, operating procedure, the rational organization of labour and to give birth to normally
Product condition, carries out field observation, the workman of itemized record construction and the working time of machinery to the concrete activity in work progress
Consume, complete the quantity of product and relevant influence factor, the result of record is arranged, the shadow of objective analysis various factors
Ring, accept or reject accordingly, to obtain the method for expenditure of time amount in quota.Owing to technical measurement method is paid attention to construction technology tissue
Condition and the analysis of operational approach, therefore be easier to find expenditure of time unreasonable factor and various wasting phenomenon, and find out man-hour
The reason of loss.Recording, analyze, arrange on the basis of make the calculating of data have certain scientific basis, the skill of acquirement
Art measurement data the most more accuracy.Again owing to using relatively uniform assay method and criterion, therefore the data measured are relatively
Stable, the rating level between work post with work post compares balance.Therefore, use technical measurement method to formulate construction norm, its quota
Quality is of a relatively high.Its scope of application is relatively wide, either the main quota such as labor hour, material and mechanical one-shift project
Mensuration all can adopt this method.
Wherein, technical measurement method is divided into working-day realistic method, realistically recording method and horology three kinds.Part document is in technology
Proposing a kind of sampling survey method in algoscopy, its viewpoint is different with the viewpoint of working-day realistic method, and this method is thought
Working-day realistic method has its weak point in utilization, such as, have certain false in utilization of hour and the consumption observed
Time more, workload is big, costly.Sampling survey method is to use the Sampling in statistics to study people and the activity of machinery
Situation, the sample extracted can be operation teams and groups, it is also possible to be a workman or machinery is producing a certain product
Whole active procedure in time of being consumed of one of which activity, it is also possible to be each the movable time consumed, pass through
Observation repeatedly determines normality and the representativeness of result of activity.
Making a general survey of above-mentioned Norm Measure method, major part also rests on shallow hierarchy, or is algorithm answering at single aspect
With, or it is only applicable to the sweeping engineering field of history project data, the time allowance of " small sample " project data is measured
Method does not has further investigated, does not meets power transmission engineering actual, it is impossible to true reflection industry average level, it is impossible to adapt to current transmission of electricity
Engineering and the development of management mode.
Summary of the invention
Embodiments provide a kind of power transmission engineering time allowance assay method, in order to make the power transmission engineering work of mensuration
Shi Fuhe power transmission engineering is actual, and method includes:
Obtain factor of influence historical sample data and the historical sample data in man-hour of power transmission engineering；
The iterations of population, Inertia Weight, Studying factors, particle rapidity and population rule according to power transmission engineering man-hour
Mould, sets up the population model in power transmission engineering man-hour；
Employing fruit bat optimized algorithm carries out Model Parameter Optimization to the population model in power transmission engineering man-hour, obtains fruit bat grain
Subgroup model；
According to factor of influence historical sample data determine the iterations of fruit bat population model, Inertia Weight and study because of
The optimal value of son；
The optimal value of iterations, Inertia Weight and Studying factors according to fruit bat population model, determines fruit bat particle
The weights of group's radial base neural net rating model and threshold value, set up fruit bat population radially base nerve net according to weights and threshold value
Network rating model；
Historical sample data and fruit bat population radial base neural net rating model in man-hour according to power transmission engineering, generates
Power transmission engineering time allowance measurement result.
Wherein in a kind of embodiment, according to the iterations of population in power transmission engineering man-hour, Inertia Weight, study because of
Son, particle rapidity and population scale, set up the population model in power transmission engineering man-hour, including: initialize power transmission engineering man-hour
The iterations of population, Inertia Weight, Studying factors, particle rapidity and population scale.
Wherein in a kind of embodiment, the particle rapidity of the population initializing power transmission engineering man-hour includes: according to transmission of electricity
The iterations of the population of engineering manhour, Inertia Weight and Studying factors initialize the particle of the population in power transmission engineering man-hour
Speed.
Wherein in a kind of embodiment, the factor of influence historical sample data of power transmission engineering includes: construction weather, construction work
Skill, one of them or combination in any of construction experience.
Present invention also offers a kind of power transmission engineering time allowance determinator, device includes:
Data input module, for obtaining factor of influence historical sample data and the historical sample number in man-hour of power transmission engineering
According to；
Population model building module, for the iterations of population according to power transmission engineering man-hour, Inertia Weight,
Practise the factor, particle rapidity and population scale, set up the population model in power transmission engineering man-hour；
Optimize module, excellent for using fruit bat optimized algorithm that the population model in power transmission engineering man-hour is carried out model parameter
Change, obtain fruit bat population model；
Optimal value determines module, for determining the iteration time of fruit bat population model according to factor of influence historical sample data
Number, Inertia Weight and the optimal value of Studying factors；
Radial base neural net module, for according to iterations, Inertia Weight and the study of fruit bat population model because of
The optimal value of son, determines weights and the threshold value of fruit bat population radial base neural net rating model, builds according to weights and threshold value
Vertical fruit bat population radial base neural net rating model；
Measure module, for the historical sample data and fruit bat population radial base neural net in man-hour according to power transmission engineering
Rating model, generates power transmission engineering time allowance measurement result.
Wherein in a kind of embodiment, population model building module is additionally operable to: initialize the particle in power transmission engineering man-hour
Iterations, Inertia Weight, Studying factors, particle rapidity and the population scale of group.
Wherein in a kind of embodiment, the particle rapidity of the population initializing power transmission engineering man-hour includes: according to transmission of electricity
The iterations of the population of engineering manhour, Inertia Weight and Studying factors initialize the particle of the population in power transmission engineering man-hour
Speed.
Wherein in a kind of embodiment, the factor of influence historical sample data of power transmission engineering includes: construction weather, construction work
Skill, one of them or combination in any of construction experience.
The embodiment of the present invention by optimize the iterations of population in power transmission engineering man-hour, Inertia Weight, Studying factors,
Particle rapidity and population scale, obtain fruit bat population model；Fruit bat particle is determined further according to factor of influence historical sample data
The optimal value of the iterations of group model, Inertia Weight and Studying factors；Optimal value finally according to above-mentioned parameter determines fruit bat
The weights of population radial base neural net rating model and threshold value, and then set up fruit bat population radial base neural net mensuration
Model, is input to the historical sample data in man-hour of power transmission engineering fruit bat population radial base neural net rating model and can get
In power transmission engineering man-hour accurately, the power transmission engineering of mensuration is made to meet power transmission engineering reality man-hour.
For the above and other objects, features and advantages of the present invention can be become apparent, preferred embodiment cited below particularly,
And coordinate institute's accompanying drawings, it is described in detail below.
Accompanying drawing explanation
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
In having technology to describe, the required accompanying drawing used is briefly described, it should be apparent that, the accompanying drawing in describing below is only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, also may be used
To obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is a kind of power transmission engineering time allowance assay method flow chart that the embodiment of the present invention provides；
Fig. 2 is a kind of power transmission engineering time allowance assay device structures block diagram that the embodiment of the present invention provides；
Fig. 3 is that in the embodiment of the present invention, fruit bat population radial base neural net rating model builds flow chart.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Describe, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiments wholely.Based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under not making creative work premise
Embodiment, broadly falls into the scope of protection of the invention.
For adapting to the development of current power transmission engineering technology and management mode, existing time allowance assay method needs further
Improve, to this end, power transmission engineering is investigated further analysis by inventor, have studied current time allowance assay method, breach
The limitation of original time allowance assay method, uses and is suitable for power transmission engineering time allowance mensuration initial data " small sample " feature
Theory, construct a kind of new method model so that it is actual that rating level more conforms to power transmission engineering, true reflection industry is put down
All level, meets being actually needed of power transmission engineering construction, reaches valuation reasonable to engineering and the purpose of effective management and control.
A kind of power transmission engineering time allowance assay method flow chart that Fig. 1 provides for the embodiment of the present invention.As it is shown in figure 1,
Embodiments providing a kind of power transmission engineering time allowance assay method, method includes:
Step 101, it is thus achieved that the factor of influence historical sample data of power transmission engineering and historical sample data in man-hour；
Step 102, according to the iterations of population in power transmission engineering man-hour, Inertia Weight, Studying factors, particle rapidity
And population scale, set up the population model in power transmission engineering man-hour；
Step 103, employing fruit bat optimized algorithm carries out Model Parameter Optimization to the population model in power transmission engineering man-hour,
To fruit bat population model；
Step 104, determines the iterations of fruit bat population model, Inertia Weight according to factor of influence historical sample data
Optimal value with Studying factors；
Step 105, according to the optimal value of iterations, Inertia Weight and the Studying factors of fruit bat population model, determines
The weights of fruit bat population radial base neural net rating model and threshold value, set up fruit bat population radially according to weights and threshold value
Base neural net rating model；
Step 106, according to power transmission engineering man-hour historical sample data and fruit bat population radial base neural net measure
Model, generates power transmission engineering time allowance measurement result.
The Bring out Background of fruit bat population radial base neural net rating model in the embodiment of the present invention:
Radial base neural net shows many special in solving small sample, the non-linear and Machine Learning Problems of higher-dimension
Some advantages, but, the simple radial base neural net technology that relies on carries out Small Sample Database study and is still difficult to acquirement and stablizes good
Good learning effect.Along with radial basis neural network deepening continuously at engineer applied, himself also exposes some not
Evitable defect, the most prominent is choosing and optimization problem of model parameter, chose aspect in parameter in the past, and generally relied on
Specialist system or the blindly search etc. of setting initial value, will necessarily affect the precision of model, cause certain in reality application
Impact.It is not enough, and concrete manifestation is as follows:
1. weights W.Neutral net connects the initialization of weights W and has randomness, and it easily occurs that study convergence rate becomes
Slowly, it is absorbed in the problem such as local minimum, poor stability, thus affects predicting the outcome of neutral net, and along with input variable
Increase, the e-learning time also can increase severely, the most easily make it be absorbed in local optimum.
2. threshold value σ.The initialization of neutral net threshold value σ has randomness equally, threshold value excessive or too small all can because of cross learn
Practising or owing study makes the Generalization Capability of neutral net be deteriorated, thus have impact on the precision of prediction of neutral net.
How to choose rational parameter and become the problem in radial base neural net application process, be also application at present simultaneously
The emphasis of research.And the method for conventional cross validation tentative calculation, the most time-consumingly, and search purpose is unclear so that the wasting of resources, consumption
Time effort, it is impossible to effectively parameter is optimized.It is thus desirable to find a kind of new method, it is possible to radial direction base nerve net
That the parameter of network model is carried out is reasonable, optimize efficiently so that rating model is flexible, intelligent, more conforms to actual power transmission engineering work
Time Norm Measure demand.
Particle swarm optimization algorithm realizes simple, but to have local search ability weak for it, is easily absorbed in local best points, evolves
The late convergence scarce limit such as slowly.Restrain soon, to the features such as initial condition sensitivity, therefore this technology owing to fruit bat algorithm has
In fundamental particle colony optimization algorithm, introduce fruit bat algorithm, improve multiformity and the ergodic of particle search of population, improve
Particle swarm optimization algorithm breaks away from the ability of Local Extremum, improves convergence rate and the precision of fundamental particle colony optimization algorithm.
Based on this, this technology considers that using fruit bat particle swarm optimization algorithm to arrange the parameter in model is optimized.Fruit bat population
The basic thought of optimized algorithm: 1) use the position of fruit bat algorithm optimization particle and speed, neither change particle swarm optimization algorithm
The dom nature being had during initialization, can improve again the multiformity of population and the ergodic of particle search simultaneously, is producing
On the basis of raw a large amount of initial population, preferentially select initial population.2) optimal location searched with current whole population is
Basis produces new sequence, with the position of a particle in the optimal location replacement current particle group after fruit bat algorithm optimization.Draw
Enter fruit bat optimized algorithm, iteration produces many neighborhood points of local optimum, helps inert particle to flee from local minimum with this
Point, thus fast searching is to optimal solution.
In embodiment, factor of influence historical sample data and the history in man-hour of power transmission engineering can be obtained in several ways
Sample data.Such as, above-mentioned historical sample data is inputted by user or external equipment.External equipment can be memorizer or number
According to storehouse.The factor of influence historical sample data of power transmission engineering can include all shadows such as weather, construction technology, construction experience of constructing
Ring the influence factor in power transmission engineering man-hour.
The population model setting up power transmission engineering man-hour has various ways, such as, and can be according to the grain in power transmission engineering man-hour
The iterations of subgroup, Inertia Weight, Studying factors, particle rapidity and population scale, set up the population in power transmission engineering man-hour
Model, it is also possible to set up the population model in power transmission engineering man-hour according to other parameter of the population in power transmission engineering man-hour.?
Before setting up the population model in power transmission engineering man-hour, need first to initialize the population in power transmission engineering man-hour iterations,
Inertia Weight, Studying factors, particle rapidity and population scale.Wherein, the particle speed of the population in power transmission engineering man-hour is initialized
Degree includes: initialize power transmission engineering work according to the iterations of population, Inertia Weight and the Studying factors in power transmission engineering man-hour
Time the particle rapidity of population.When being embodied as, it is the iterations of population according to power transmission engineering man-hour, Inertia Weight
It is multiplied by corresponding coefficient, namely by the iterations of population, Inertia Weight and Studying factors normalizing with the magnitude of Studying factors
Being multiplied after change, corresponding coefficient is 1 again.
In embodiment, first use fruit bat optimized algorithm that the population model in power transmission engineering man-hour is carried out model parameter excellent
Change, obtain fruit bat population model, further according to factor of influence historical sample data determine fruit bat population model iterations,
Inertia Weight and the optimal value of Studying factors, the optimal value finally according to above-mentioned fruit bat population model parameter determines fruit bat particle
The weights of group's radial base neural net rating model and threshold value, and then set up fruit bat population radial base neural net mensuration mould
Type.The historical sample data in man-hour of power transmission engineering is input to the fruit bat population radially base set up by Matlab software programming
In neutral net rating model, power transmission engineering time allowance measurement result can be obtained.
Fig. 3 is that in the embodiment of the present invention, fruit bat population radial base neural net rating model builds flow chart, fruit bat grain
It is as follows that subgroup radial base neural net rating model builds flow process:
1. the scale of Initialize installation population, maximum allowable iterations L, Inertia Weight M, Studying factors D, initialization
The speed of each particle.It is noted that owing to optimizing L, M and D simultaneously, the value of 3 parameters is general not on the same order of magnitude,
Corresponding coefficient should be multiplied by when initializing particle rapidity.
2. particle position is initialized.Randomly generate each component values of 3-dimensional vector between 0-1, obtain N number of to
Amount is initial population, then by within each component carrier wave respectively to the span of L, M, D parameter, finally calculates population
Adaptive value, and from N number of initial population select preferable Q the solution of performance as initial solution, randomly generate N number of initial velocity.
If 3. particle fitness is better than individual extreme value, the adaptive value of population is set to new position.
4. particle fitness is better than global extremum, and global extremum is set to new position.
The speed of the most more new particle and position.
6. optimal location is carried out fruit bat optimization.Each feasible solution of variable experience is calculated its adaptive value, obtaining property
The feasible solution that energy is best.
7. the position of any one particle in current group is replaced by best feasible solution.
If 8. meeting maximum iteration time, then stopping search, global optimum position is parameter vector (L, M, D)；Otherwise,
Return the 3rd step.
9. for needing parameter W optimized and σ to build sample standard deviation square errorAs radially
The fitness function of base neural net model, the object function of the particle cluster algorithm after simultaneously it being optimized as fruit bat.Wherein,For the measured value of radial base neural net, y (i) is the actual value of radial base neural net, and N is radial base neural net
Sample size.
10., when the sample standard deviation square error minimum of radial base neural net, corresponding W and σ is optimized parameter, finally
Set up the fruit bat population radial base neural net rating model of fruit bat particle group optimizing.
Below in conjunction with specifically embodiment, the present invention is described in further details:
The Ji Bei Utilities Electric Co. 220kv time allowance in power transmission engineering budget stage is set up rating model by this project, needs to divide
Other to site transportation, earth and rock works, foundation engineering, tower engineering, stringing engineering, adnexa engineering, cable work and auxiliary work
Journey totally 8 specific item engineerings set up rating model, here as a example by earth and rock works, set up time allowance rating model.Due to soil
Stonework historical sample capacity is 19, here the population scale of population is set as 19, and maximum iteration time L is 1000,
Two parameters of M and D are used binary coding, and wherein the hunting zone of M is set to [0,100], and the hunting zone of D is set to
[0.1,100].The initial velocity of particle is 2.Meanwhile, according to the historical sample of input, the parameter of optimum is found.Final structure
Becoming input is 3 nodes, is output as 1 node, and hidden layer is the radial base neural net of 4 nodes.Input layer is connected weights with hidden layer
W1、W2And W3, output layer is connected weights W with hidden layer4With hidden layer weights σ1, σ2, σ3, σ4.By calculated optimized parameter
As shown in table 1:
Table 1 different parameters measurement result compares
Wherein, sample standard deviation square error With y (i) be respectively measure the time allowance value and
Actual hours nominally, the parameter in above-mentioned table 1 is at sample standard deviation square error eRMSETry to achieve in the case of minimum.
As can be seen from Table 1, W is worked as1=(0.3,0.1,0.6), W2=(0.3,0.2,0.5), W3=(0.3,0.3,0.4),
W4=(0.3,0.5,0.2), during (σ 1, σ 2, σ 3, σ 4)=(2,5,4,6), the power transmission engineering budget stage work that rating model draws
Time nominally minimum with the time allowance error in version power construction engineering in 2013 quota.Therefore, this project utilizes parameter W1
=(0.3,0.1,0.6), W2=(0.3,0.2,0.5), W3=(0.3,0.3,0.4), W4=(0.3,0.5,0.2), (σ 1, σ 2, σ
3, σ 4)=(2,5,4,6), set up power transmission engineering time allowance rating model based on fruit bat population radial base neural net.
When being embodied as, power transmission engineering can include site transportation, earth and rock works, foundation engineering, tower engineering, stringing
Engineering, adnexa engineering, cable work and ancillary works.Employing power transmission engineering time allowance assay method is presented herein below carry out determining man-hour
The sample checking that volume measures:
(1) site transportation
220kv power transmission engineering site transportation includes manpower transport, tractor transport, Automobile Transportation, Shipping and cableway
As a example by transporting five specific items, the most only the concrete frame transport specific item below Automobile Transportation, carry out time allowance mensuration.In conjunction with
15 Practical Project samples, fruit bat population radial base neural net rating model based on fruit bat particle group optimizing, uses
Matlab software programming, using 13 samples as learning sample, other 2 conduct measuring and calculating samples, gained time allowance mensuration is tested
Card result is as follows:
The stopwatch measurement result of table 2 Automobile Transportation concrete frame
| Within 500kg | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 0.1360 | 0.1260 | 7.35% |
| Technology of transmission of electricity work | 0.0150 | 0.0140 | 6.66% |
Wherein, learning sample is used for setting up fruit bat population radial base neural net rating model, and test sample is used for testing
The accuracy of card fruit bat population radial base neural net rating model.
(2) earth and rock works
220kv power transmission engineering earth and rock works includes repetition survey of existing rail way and Fen Keng；Electric rod pit, Ta Keng, bracing wire hole hand excavation
And backfill；Bracing wire hole machinery excavation and backfill, borehole basis excavation (or explosion), ground slot excavation (or explosion) and backfill, row
Seven specific items such as ditch excavation, spike and formation level excavation, the most only as a example by repetition survey of existing rail way and point hole mesh, carry out man-hour
Norm Measure.In conjunction with 15 Practical Project samples, fruit bat population radial base neural net based on fruit bat particle group optimizing is surveyed
Cover half type, uses Matlab software programming, using 13 samples as learning sample, other 2 as measuring and calculating samples, gained man-hour
Norm Measure the result is as follows:
Table 3 repetition survey of existing rail way and the stopwatch measurement result in point hole
| Straight line single pole | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 0.1080 | 0.1150 | 6.79% |
| Technology of transmission of electricity work | 0.1620 | 0.1510 | 6.48% |
(3) foundation engineering
220kv power transmission engineering foundation engineering includes prefabricated foundation, cast-in-place basis, Rock Bolt Foundation boring pouring, boring
13 specific items such as bored concrete pile foundation, root pile basis, prefabricated pile basis, steel pipe pile foundation, hand-dug pile foundation's retaining wall, this
In as a example by only commerical ready-mixed concrete below cast-in-place basis casts specific item, carry out time allowance mensuration.In conjunction with 15 Practical Projects
Sample, fruit bat population radial base neural net rating model based on fruit bat particle group optimizing, use Matlab software programming,
Using 13 samples as learning sample, other 2 conduct measuring and calculating samples, it is as follows that the gained time allowance measures the result:
The stopwatch measurement result that table 4 commerical ready-mixed concrete is cast
| Within 5 meters | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 0.9920 | 1.0550 | 6.35% |
| Technology of transmission of electricity work | 0.9920 | 1.0550 | 6.35% |
(4) tower engineering
220kv power transmission engineering tower engineering includes that concrete frame group is vertical, steel loop lap welding connects and cement pole binds, steel pipe pole group
Seven specific items such as vertical, tower erection, bracing wire make and install, shaft tower mopping and shaft tower will board installation, the most only with concrete frame
As a example by the vertical specific item of group, carry out time allowance mensuration.In conjunction with 15 Practical Project samples, fruit bat grain based on fruit bat particle group optimizing
Subgroup radial base neural net rating model, uses Matlab software programming, using 13 samples as learning sample, other 2
As measuring and calculating sample, it is as follows that the gained time allowance measures the result:
The stopwatch measurement result that table 5 concrete frame group is vertical
| Whole without sleeve | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 1.5830 | 1.4850 | 7.89% |
| Technology of transmission of electricity work | 2.3750 | 2.4950 | 5.05% |
(5) stringing engineering
220kv power transmission engineering stringing engineering includes that wire, lightning conducter typically set up；OPGW, wire, lightning conducter tension bracket
If；OPGW, wire, lightning conducter are crossed over and are set up；Special leap, live across eight specific items such as electric lines of force measure, the most only to lead
As a example by line, lightning conducter typically set up specific item, carry out time allowance mensuration.In conjunction with 15 Practical Project samples, based on fruit bat particle
The fruit bat population radial base neural net rating model that group optimizes, uses Matlab software programming, using 13 samples as
Practising sample, other 2 conduct measuring and calculating samples, it is as follows that the gained time allowance measures the result:
The stopwatch measurement result that table 6 wire, lightning conducter typically set up
| Within 35 kms | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 2.3400 | 2.1340 | 8.80% |
| Technology of transmission of electricity work | 5.4700 | 5.7810 | 5.68% |
(6) adnexa engineering
220kv power transmission engineering adnexa engineering includes strain insulator corner pole wire hanging wire and insulator chain installation, straight line pole
Insulator chain hangs nine specific items such as installation, hanging conductor clamp installation, grading ring, shading ring installation, the most only turns with strain insulator
As a example by angular pole tower wire hanging wire and insulator chain install specific item, carry out time allowance mensuration.In conjunction with 15 Practical Project samples, base
In the fruit bat population radial base neural net rating model of fruit bat particle group optimizing, use Matlab software programming, with 13
Sample is as learning sample, and samples are calculated in other 2 conducts, and it is as follows that the gained time allowance measures the result:
Table 7 strain insulator corner pole wire hanging wire and insulator chain installation work-hour measurement result
| 220kV single conductor | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 2.5920 | 2.3880 | 7.87% |
| Technology of transmission of electricity work | 14.6880 | 15.5710 | 6.01% |
(7) cable work
220kv power transmission engineering cable work includes cable duct, comb；Cable laying；Cable intermediate joint fabrication and installation；Electricity
Cable terminal fabrication and installation；Six specific items such as appurtenant work and cable routine test, the most only with the cable below cable duct, comb
As a example by ditch, groove, hole hand excavation and backfill specific item, carry out time allowance mensuration.In conjunction with 15 Practical Project samples, based on fruit bat
The fruit bat population radial base neural net rating model of particle group optimizing, uses Matlab software programming, makees with 13 samples
For learning sample, other 2 conduct measuring and calculating samples, it is as follows that the gained time allowance measures the result:
Table 8 cable duct, groove, hole hand excavation and the stopwatch measurement of backfill
| Within 2 cubic metres | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 0.2753 | 0.2893 | 5.08% |
| Technology of transmission of electricity work | 0.0145 | 0.0136 | 6.20% |
(8) ancillary works
220kv power transmission engineering ancillary works includes cableway terminal installation, construction road, three specific items such as fixes the sand, the most only with
As a example by roadbase specific item under construction road, carry out time allowance mensuration.In conjunction with 15 Practical Project samples, based on fruit bat grain
The fruit bat population radial base neural net rating model that subgroup optimizes, uses Matlab software programming, using 13 samples as
Learning sample, other 2 conduct measuring and calculating samples, it is as follows that the gained time allowance measures the result:
The stopwatch measurement of table 9 roadbase
| 15 centimetres of chunk stones | Middle Electricity Federation measured value (work day) | This model determination value (work day) | Deviation |
| Transmission of electricity unskilled labor | 0.0848 | 0.0911 | 7.43% |
| Technology of transmission of electricity work | 0.0094 | 0.0101 | 7.44% |
A kind of power transmission engineering time allowance assay device structures block diagram that Fig. 2 provides for the embodiment of the present invention.Such as Fig. 2 institute
Showing, present invention also offers a kind of power transmission engineering time allowance determinator, device includes:
Data input module 201, for obtaining factor of influence historical sample data and the historical sample in man-hour of power transmission engineering
Data；
Population model building module 202, for the iterations of population according to power transmission engineering man-hour, inertia power
Value, Studying factors, particle rapidity and population scale, set up the population model in power transmission engineering man-hour；
Optimize module 203, for using fruit bat optimized algorithm that the population model in power transmission engineering man-hour is carried out model ginseng
Number optimizes, and obtains fruit bat population model；
Optimal value determines module 204, for determining changing of fruit bat population model according to factor of influence historical sample data
The optimal value of generation number, Inertia Weight and Studying factors；
Radial base neural net module 205, for iterations, Inertia Weight and study according to fruit bat population model
The optimal value of the factor, determines weights and the threshold value of fruit bat population radial base neural net rating model, according to weights and threshold value
Set up fruit bat population radial base neural net rating model；
Measure module 206, for according to power transmission engineering man-hour historical sample data and fruit bat population radially base neural
Network rating model, generates power transmission engineering time allowance measurement result.
In embodiment, population model building module 202 is additionally operable to: initialize the iteration of the population in power transmission engineering man-hour
Number of times, Inertia Weight, Studying factors, particle rapidity and population scale.
In embodiment, the particle rapidity of the population initializing power transmission engineering man-hour includes: according to power transmission engineering man-hour
The iterations of population, Inertia Weight and Studying factors initialize the particle rapidity of the population in power transmission engineering man-hour.
In embodiment, the factor of influence historical sample data of power transmission engineering includes: construction weather, construction technology, construction warp
One of them or the combination in any tested.
In sum, the embodiment of the present invention by optimize the iterations of population in power transmission engineering man-hour, Inertia Weight,
Studying factors, particle rapidity and population scale, obtain fruit bat population model；Determine further according to factor of influence historical sample data
The optimal value of iterations, Inertia Weight and the Studying factors of fruit bat population model；Optimal value finally according to above-mentioned parameter
Determine weights and the threshold value of fruit bat population radial base neural net rating model, and then it is neural to set up fruit bat population radially base
Network rating model.The historical sample data in man-hour of power transmission engineering is input to fruit bat population radial base neural net and measures mould
Type can get power transmission engineering man-hour accurately, makes the power transmission engineering of mensuration meet power transmission engineering reality man-hour, truly reflects industry
Average level, adapts to the development of current power transmission engineering technology and management mode.
It is soft that method described in the embodiment of the present invention or the step of algorithm can be directly embedded into hardware, processor performs
Part module or the combination of both.Software module can be stored in RAM memory, flash memory, ROM memory, EPROM storage
Other any form of storage medium in device, eeprom memory, depositor, hard disk, moveable magnetic disc, CD-ROM or this area
In.Exemplarily, storage medium can be connected with processor, so that processor can read information from storage medium, and
Write information can be deposited to storage medium.Alternatively, storage medium can also be integrated in processor.Processor and storage medium can
To be arranged in ASIC, ASIC can be arranged in user terminal.Alternatively, processor and storage medium can also be arranged at use
In different parts in the terminal of family.
In one or more exemplary designs, the above-mentioned functions described by the embodiment of the present invention can be at hardware, soft
The combination in any of part, firmware or this three realizes.If realized in software, these functions can store and computer-readable
On medium, or it is transmitted on the medium of computer-readable with one or more instructions or code form.Computer readable medium includes electricity
Brain stores medium and is easy to so that allowing computer program transfer to the telecommunication media in other place from a place.Storage medium is permissible
It is that any general or special computer can be with the useable medium of access.Such as, such computer readable media can include but
It is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disc storage, disk storage or other magnetic storage device, or other
What may be used for carrying or storage can be by general or special computer or general or special handling with other with instruction or data structure
Device reads the medium of the program code of form.Additionally, any connection can be properly termed computer readable medium, example
As, if software is by coaxial cable, fiber optic cables, double from a web-site, server or other remote resource
Twisted wire, Digital Subscriber Line (DSL) or with the wireless way for transmittings such as the most infrared, wireless and microwave be also contained in defined
In computer readable medium.Described video disc (disk) and disk (disc) include Zip disk, radium-shine dish, CD, DVD, floppy disk
And Blu-ray Disc, disk is generally with magnetic duplication data, and video disc generally carries out optical reproduction data with laser.Combinations of the above
Can also be included in computer readable medium.
Particular embodiments described above, has been carried out the purpose of the present invention, technical scheme and beneficial effect the most in detail
Describe in detail bright, be it should be understood that the specific embodiment that the foregoing is only the present invention, the guarantor being not intended to limit the present invention
Protect scope, all within the spirit and principles in the present invention, any modification, equivalent substitution and improvement etc. done, should be included in this
Within the protection domain of invention.
Claims (8)
1. a power transmission engineering time allowance assay method, it is characterised in that including:
Obtain factor of influence historical sample data and the historical sample data in man-hour of power transmission engineering；
According to the iterations of population, Inertia Weight, Studying factors, particle rapidity and the population scale in power transmission engineering man-hour,
Set up the population model in power transmission engineering man-hour；
Employing fruit bat optimized algorithm carries out Model Parameter Optimization to the population model in power transmission engineering man-hour, obtains fruit bat population
Model；
According to described factor of influence historical sample data determine the iterations of fruit bat population model, Inertia Weight and study because of
The optimal value of son；
The optimal value of iterations, Inertia Weight and Studying factors according to described fruit bat population model, determines fruit bat particle
The weights of group's radial base neural net rating model and threshold value, set up fruit bat population radially base nerve net according to weights and threshold value
Network rating model；
Historical sample data and fruit bat population radial base neural net rating model in man-hour according to power transmission engineering, generates transmission of electricity
Engineering manhour Norm Measure result.
2. power transmission engineering time allowance assay method as claimed in claim 1, it is characterised in that according to power transmission engineering man-hour
The iterations of population, Inertia Weight, Studying factors, particle rapidity and population scale, set up the particle in power transmission engineering man-hour
Group model, including: initialize the iterations of population in power transmission engineering man-hour, Inertia Weight, Studying factors, particle rapidity and
Population scale.
3. power transmission engineering time allowance assay method as claimed in claim 2, it is characterised in that initialize power transmission engineering man-hour
The particle rapidity of population include: according to the iterations of population, Inertia Weight and the Studying factors in power transmission engineering man-hour
Initialize the particle rapidity of the population in power transmission engineering man-hour.
4. power transmission engineering time allowance assay method as claimed in claim 1, it is characterised in that the factor of influence of power transmission engineering
Historical sample data includes: construction weather, construction technology, one of them or combination in any of construction experience.
5. a power transmission engineering time allowance determinator, it is characterised in that including:
Data input module, for obtaining factor of influence historical sample data and the historical sample data in man-hour of power transmission engineering；
Population model building module, for according to the iterations of population in power transmission engineering man-hour, Inertia Weight, study because of
Son, particle rapidity and population scale, set up the population model in power transmission engineering man-hour；
Optimize module, for using fruit bat optimized algorithm that the population model in power transmission engineering man-hour is carried out Model Parameter Optimization,
Obtain fruit bat population model；
Optimal value determines module, for determining the iteration time of fruit bat population model according to described factor of influence historical sample data
Number, Inertia Weight and the optimal value of Studying factors；
Radial base neural net module, for according to iterations, Inertia Weight and the study of described fruit bat population model because of
The optimal value of son, determines weights and the threshold value of fruit bat population radial base neural net rating model, builds according to weights and threshold value
Vertical fruit bat population radial base neural net rating model；
Measure module, for according to power transmission engineering man-hour historical sample data and fruit bat population radial base neural net measure
Model, generates power transmission engineering time allowance measurement result.
6. power transmission engineering time allowance determinator as claimed in claim 5, it is characterised in that population model building module
It is additionally operable to: initialize the iterations of population, Inertia Weight, Studying factors, particle rapidity and the population in power transmission engineering man-hour
Scale.
7. power transmission engineering time allowance determinator as claimed in claim 6, it is characterised in that initialize power transmission engineering man-hour
The particle rapidity of population include: according to the iterations of population, Inertia Weight and the Studying factors in power transmission engineering man-hour
Initialize the particle rapidity of the population in power transmission engineering man-hour.
8. power transmission engineering time allowance determinator as claimed in claim 5, it is characterised in that the factor of influence of power transmission engineering
Historical sample data includes: construction weather, construction technology, one of them or combination in any of construction experience.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112949906A (en) * | 2021-02-04 | 2021-06-11 | 杭州品茗安控信息技术股份有限公司 | Matching method, device, equipment and storage medium for engineering cost quota conversion |
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| CN106845729A (en) * | 2017-02-15 | 2017-06-13 | 南京航空航天大学 | A kind of electronic product rack assembly work based on gray theory determines method |
| CN106932196A (en) * | 2017-03-10 | 2017-07-07 | 华北电力大学 | A kind of gear case of blower fault diagnosis model method for building up and device |
| CN107918824A (en) * | 2017-11-02 | 2018-04-17 | 中交第二公路工程局有限公司 | A kind of highway engineering construction Norm Measure method |
| CN107918824B (en) * | 2017-11-02 | 2022-03-08 | 中交第二公路工程局有限公司 | Method for determining construction quota of highway engineering |
| CN112949907A (en) * | 2021-02-04 | 2021-06-11 | 杭州品茗安控信息技术股份有限公司 | Quota matching method, device, equipment and storage medium for engineering cost |
| CN112949906A (en) * | 2021-02-04 | 2021-06-11 | 杭州品茗安控信息技术股份有限公司 | Matching method, device, equipment and storage medium for engineering cost quota conversion |
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| CN112949907B (en) * | 2021-02-04 | 2024-03-19 | 品茗科技股份有限公司 | Quota matching method, device and equipment for engineering cost and storage medium |
| CN116992770A (en) * | 2023-08-07 | 2023-11-03 | 中国铁建大桥工程局集团有限公司 | Wall protection control blasting method based on GOA-DBN neural network |
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Application publication date: 20170111 |