阅读说明：本技术 众包定价体系的评估方法、装置、设备及可读存储介质 (Appraisal procedure, device, equipment and the readable storage medium storing program for executing of crowdsourcing pricing structure ) 是由 胡龙 周康 刘江蓉 刘朔 杨华 高婧 任宏伟 范世纪 于 2019-09-04 设计创作，主要内容包括：本发明公开了一种众包定价体系的评估方法、装置、设备及可读存储介质,包括：从待评估众包定价体系中提取原始体系参数,根据所述原始体系参数建立初始群体集合；通过遗传算法对所述初始群体集合进行数据优化,获取新群体集合；根据所述新群体集合确定对应的适应度函数值；根据所述适应度函数值对所述待评估众包定价体系进行评估。通过上述方式,可以调整原有用户的众包价格,对新的用户点给出众包价格,并能根据实时完成的众包数据优化众包定价体系的参数,大大提高了任务完成率。(The invention discloses appraisal procedure, device, equipment and the readable storage medium storing program for executing of a kind of crowdsourcing pricing structure, comprising: extracts original system parameter from crowdsourcing pricing structure to be assessed, establishes initial population set according to the original system parameter；It is data-optimized to initial population set progress by genetic algorithm, obtain new group's set；Corresponding fitness function value is determined according to new group's set；The crowdsourcing pricing structure to be assessed is assessed according to the fitness function value.By the above-mentioned means, the crowdsourcing price of adjustable original user, provides crowdsourcing price to new user's point, and can substantially increase task completion rate according to the parameter for the data-optimized crowdsourcing pricing structure of crowdsourcing completed in real time.)

1. a kind of appraisal procedure of crowdsourcing pricing structure, which is characterized in that the described method includes:

Original system parameter is extracted from crowdsourcing pricing structure to be assessed, initial population collection is established according to the original system parameter It closes；

It is data-optimized to initial population set progress by genetic algorithm, obtain new group's set；

Corresponding fitness function value is determined according to new group's set；

The crowdsourcing pricing structure to be assessed is assessed according to the fitness function value.

2. the appraisal procedure of crowdsourcing pricing structure as described in claim 1, which is characterized in that it is described by genetic algorithm to institute It is data-optimized to state the progress of initial population set, before obtaining new group's set, the appraisal procedure of the crowdsourcing pricing structure is also wrapped It includes:

Corresponding initial fitness function value is obtained according to the original system parameter；

Select probability is obtained according to the initial fitness function value；

It is described to be calculated and obtained new parameter to the initial population set by genetic algorithm, it specifically includes:

According to default crossover probability, default mutation probability and the select probability by genetic algorithm, to the initial population Set progress is data-optimized, obtains new group's set.

3. the appraisal procedure of crowdsourcing pricing structure as claimed in claim 2, which is characterized in that the basis is default to intersect generally Rate, default mutation probability and the select probability pass through genetic algorithm, data-optimized to initial population set progress, obtain Qu Xin group set, specifically includes:

According to the default crossover probability, data-optimized, acquisition is carried out to the initial population set by the genetic algorithm Cross parameter；

According to the default mutation probability, data-optimized, acquisition is carried out to the initial population set by the genetic algorithm Mutation parameter；

According to the select probability, data-optimized, the new ginseng of acquisition is carried out to the initial population set by the genetic algorithm Number；

The cross parameter, the Mutation parameter and the new parameter group are combined into group set, and by the group Set is gathered as new group.

4. the appraisal procedure of crowdsourcing pricing structure as claimed in claim 3, which is characterized in that described according to the default intersection Probability, it is data-optimized to initial population set progress by the genetic algorithm, cross parameter is obtained, is specifically included:

The original system parameter is extracted from the initial population set according to the genetic algorithm, according to the default intersection Probability carries out crossover operation to the original system parameter, to obtain cross parameter.

5. the appraisal procedure of crowdsourcing pricing structure as claimed in claim 3, which is characterized in that general according to the default variation Rate, it is data-optimized to initial population set progress by the genetic algorithm, Mutation parameter is obtained, is specifically included:

The original system parameter is extracted from the initial population set according to the genetic algorithm, according to the default variation Probability carries out mutation operation to the original system parameter, to obtain Mutation parameter.

6. the appraisal procedure of crowdsourcing pricing structure as claimed in claim 3, which is characterized in that described general according to the selection Rate, it is data-optimized to initial population set progress by the genetic algorithm, new parameter is obtained, is specifically included:

The original system parameter is extracted from the initial population set by the genetic algorithm according to the select probability, Using the original system parameter of extraction as new parameter.

7. such as the appraisal procedure of crowdsourcing pricing structure according to any one of claims 1 to 6, which is characterized in that the basis The fitness function value assesses the crowdsourcing pricing structure to be assessed, specifically includes:

The fitness function value is compared with the initial fitness function value, according to comparison result to described to be assessed Crowdsourcing pricing structure is assessed.

8. a kind of assessment device of crowdsourcing pricing structure, which is characterized in that described device includes:

Module is obtained, for extracting original system parameter from crowdsourcing pricing structure to be assessed, according to the original system parameter Establish initial population set；

Optimization module, it is data-optimized to initial population set progress by genetic algorithm, obtain new group's set；

Computing module, for determining corresponding fitness function value according to new group's set；

Evaluation module, for being assessed according to the fitness function value the crowdsourcing pricing structure to be assessed.

9. a kind of assessment equipment of crowdsourcing pricing structure, which is characterized in that the equipment includes: memory, processor and storage On the memory and the appraisal procedure of crowdsourcing pricing structure that can run on the processor, the crowdsourcing pricing structure Appraisal procedure the step of being arranged for carrying out the appraisal procedure of the crowdsourcing pricing structure as described in any one of claims 1 to 7.

10. a kind of readable storage medium storing program for executing, which is characterized in that the readable storage medium storing program for executing is computer readable storage medium, described The appraisal procedure of crowdsourcing pricing structure, the appraisal procedure quilt of the crowdsourcing pricing structure are stored on computer readable storage medium The step of processor realizes the appraisal procedure of crowdsourcing pricing structure as described in any one of claim 1 to 7 when executing.

Technical field

The present invention relates to the evaluation areas of crowdsourcing pricing structure more particularly to a kind of appraisal procedure of crowdsourcing pricing structure, Device, equipment and readable storage medium storing program for executing.

Background technique

Crowdsourcing refers to the task that a company or mechanism are executed the past by employee, in freely voluntary form outside It wraps to the way of unspecific (and being usually large-scale) public volunteer.The task of crowdsourcing is usually to be undertaken by individual, If involving the need for the task of multiple person cooperational completion, it is also possible to occur in the form of the individual production by open source.

The assessment of crowdsourcing pricing structure mostly uses the data analysing method based on statistical thinking at present, and this method can pass through The information analysis of the price of crowdsourcing process and implementation finds crowdsourcing price rule, finds out the influence factor of price.This method Suitable for today's society economy, science and technology and cultural every field.But based on the data analysing method of statistical thinking without Method provides operable pricing system, and task completion rate is low, and crowdsourcing price can not be provided to new user's point, and use is not square Just.

Above content is only used to facilitate the understanding of the technical scheme, and is not represented and is recognized that above content is existing skill Art.

Summary of the invention

The main purpose of invention is the provision of the appraisal procedure of crowdsourcing pricing structure a kind of, device, equipment and readable deposits Storage media, it is intended to solve the high cost of the prior art and macrocyclic technical problem.

To achieve the above object, the present invention provides a kind of appraisal procedure of crowdsourcing pricing structure, the method includes with Lower step:

Original system parameter is extracted from crowdsourcing pricing structure to be assessed, initial population is established according to the original system parameter Body set；

It is data-optimized to initial population set progress by genetic algorithm, obtain new group's set；

Corresponding fitness function value is determined according to new group's set；

The crowdsourcing pricing structure to be assessed is assessed according to the fitness function value.

Preferably, described data-optimized to initial population set progress by genetic algorithm, obtain new group's set Before, the appraisal procedure of the crowdsourcing pricing structure further include:

Corresponding initial fitness function value is obtained according to the original system parameter；

Select probability is obtained according to the initial fitness function value；

It is described to be calculated and obtained new parameter to the initial population set by genetic algorithm, it specifically includes:

According to default crossover probability, default mutation probability and the select probability by genetic algorithm, to described initial Group's set progress is data-optimized, obtains new group's set.

Preferably, the default crossover probability of the basis, default mutation probability and the select probability pass through genetic algorithm, It is data-optimized to initial population set progress, new group's set is obtained, is specifically included:

It is data-optimized to initial population set progress by the genetic algorithm according to the default crossover probability, Obtain cross parameter；

It is data-optimized to initial population set progress by the genetic algorithm according to the default mutation probability, Obtain Mutation parameter；

According to the select probability, data-optimized, acquisition is carried out to the initial population set by the genetic algorithm New parameter；

The cross parameter, the Mutation parameter and the new parameter group are combined into group's set, and will be described Group's set is gathered as new group.

Preferably, described according to the default crossover probability, by the genetic algorithm to the initial population set into Row is data-optimized, obtains cross parameter, specifically includes:

The original system parameter is extracted from the initial population set according to the genetic algorithm, according to described default Crossover probability carries out crossover operation to the original system parameter, to obtain cross parameter.

Preferably, according to the default mutation probability, the initial population set is counted by the genetic algorithm According to optimization, Mutation parameter is obtained, is specifically included:

The original system parameter is extracted from the initial population set according to the genetic algorithm, according to described default Mutation probability carries out mutation operation to the original system parameter, to obtain Mutation parameter.

Preferably, described according to the select probability, the initial population set is counted by the genetic algorithm According to optimization, new parameter is obtained, is specifically included:

The original system is extracted from the initial population set by the genetic algorithm according to the select probability Parameter, using the original system parameter of extraction as new parameter.

Preferably, described that the crowdsourcing pricing structure to be assessed is assessed according to the fitness function value, specifically Include:

The fitness function value is compared with the initial fitness function value, according to comparison result to it is described to Assessment crowdsourcing pricing structure is assessed.

In addition, to achieve the above object, the present invention also proposes a kind of assessment device of crowdsourcing pricing structure, described device packet It includes:

Module is obtained, for extracting original system parameter from crowdsourcing pricing structure to be assessed, according to the original system Parameter establishes initial population set；

Optimization module, it is data-optimized for being carried out by genetic algorithm to the initial population set, obtain new group's collection It closes；

Computing module, for determining corresponding fitness function value according to new group's set；

Evaluation module, for being assessed according to the fitness function value the crowdsourcing pricing structure to be assessed.

In addition, to achieve the above object, the present invention also proposes a kind of assessment equipment of crowdsourcing pricing structure, the equipment packet It includes: memory, processor and being stored in the crowdsourcing pricing structure that can be run on the memory and on the processor Appraisal procedure, the appraisal procedure of the crowdsourcing pricing structure are arranged for carrying out the assessment side of crowdsourcing pricing structure as described above The step of method.

In addition, to achieve the above object, the present invention also proposes that a kind of readable storage medium storing program for executing, the readable storage medium storing program for executing are meter Calculation machine readable storage medium storing program for executing is stored with the appraisal procedure of crowdsourcing pricing structure, the crowd on the computer readable storage medium The appraisal procedure of packet pricing structure realizes the step of appraisal procedure of the crowdsourcing pricing structure when being executed by processor.

The invention discloses appraisal procedure, device, equipment and the readable storage medium storing program for executing of a kind of crowdsourcing pricing structure, comprising: Original system parameter is extracted from crowdsourcing pricing structure to be assessed, initial population set is established according to the original system parameter； It is data-optimized to initial population set progress by genetic algorithm, obtain new group's set；Gathered according to the new group Determine corresponding fitness function value；The crowdsourcing pricing structure to be assessed is assessed according to the fitness function value. By the above-mentioned means, the crowdsourcing price of adjustable original user, provides crowdsourcing price to new user's point, and can be according in real time The parameter of the data-optimized crowdsourcing pricing structure of the crowdsourcing of completion, substantially increases task completion rate.

Detailed description of the invention

Fig. 1 is the structure of the assessment equipment of the crowdsourcing pricing structure for the hardware running environment that the embodiment of the present invention is related to Schematic diagram；

Fig. 2 is the flow diagram of the appraisal procedure first embodiment of crowdsourcing pricing structure of the present invention；

Fig. 3 is the flow diagram of the appraisal procedure second embodiment of crowdsourcing pricing structure of the present invention；

Fig. 4 is the functional block diagram of the appraisal procedure first embodiment of crowdsourcing pricing structure of the present invention.

The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.

Specific embodiment

It should be appreciated that described herein, specific examples are only used to explain the present invention, is not intended to limit the present invention.

Referring to Fig.1, Fig. 1 is that the assessment of the crowdsourcing pricing structure for the hardware running environment that the embodiment of the present invention is related to is set Standby structural schematic diagram.

As shown in Figure 1, the assessment equipment of the crowdsourcing pricing structure may include: processor 1001, such as central processing unit (Central Processing Unit, CPU), communication bus 1002, user interface 1003, network interface 1004, memory 1005.Wherein, communication bus 1002 is for realizing the connection communication between these components.User interface 1003 may include display Shield (Display), input unit such as keyboard (Keyboard), optional user interface 1003 can also include that the wired of standard connects Mouth, wireless interface.Network interface 1004 optionally may include standard wireline interface and wireless interface (such as Wireless Fidelity (WIreless-FIdelity, WI-FI) interface).Memory 1005 can be the random access memory (Random of high speed Access Memory, RAM) memory, be also possible to stable nonvolatile memory (Non-Volatile Memory, ), such as magnetic disk storage NVM.Memory 1005 optionally can also be the storage device independently of aforementioned processor 1001.

The assessment of crowdsourcing pricing structure is set it will be understood by those skilled in the art that structure shown in Fig. 1 is not constituted Standby restriction may include perhaps combining certain components or different component layouts than illustrating more or fewer components.

As shown in Figure 1, as may include operating system, data storage mould in a kind of memory 1005 of storage medium Block, network communication module, Subscriber Interface Module SIM and crowdsourcing pricing structure appraisal procedure.

In the assessment equipment of crowdsourcing pricing structure shown in Fig. 1, network interface 1004 is mainly used for and network server Carry out data communication；User interface 1003 is mainly used for carrying out data interaction with user；The assessment of crowdsourcing pricing structure of the present invention Processor 1001, memory 1005 in equipment can be set in the assessment equipment of crowdsourcing pricing structure, the crowdsourcing price The assessment equipment of system calls the appraisal procedure of the crowdsourcing pricing structure stored in memory 1005 by processor 1001, and holds The appraisal procedure of row crowdsourcing pricing structure provided in an embodiment of the present invention.

The embodiment of the invention provides a kind of appraisal procedures of crowdsourcing pricing structure, are crowdsourcing of the present invention referring to Fig. 2, Fig. 2 The flow diagram of the appraisal procedure first embodiment of pricing structure.

In the present embodiment, the appraisal procedure of the crowdsourcing pricing structure the following steps are included:

Step S10: extracting original system parameter from crowdsourcing pricing structure to be assessed, is built according to the original system parameter Vertical initial population set.

It will be appreciated that the original system parameter extracted from the crowdsourcing pricing structure to be assessed refers to task Fix a price influential various dimensions factor, the various dimensions factor includes: price, participate in number, region total price etc., and it is described just Beginning group set is established by randomly selecting the original system parameter.

Step S20: it is data-optimized to initial population set progress by genetic algorithm, obtain new group's set.

It will be appreciated that the genetic algorithm is natural selection and the genetic mechanisms for simulating Darwinian evolutionism The computation model of biological evolution process is a kind of method by simulating natural evolution process searches optimal solution.Genetic algorithm is Since a population of the possible potential disaggregation of the problem that represents, and a population is then by the certain amount by gene coding Individual composition.Each individual is actually the entity that chromosome has feature.Main carriers of the chromosome as inhereditary material, The set of i.e. multiple genes, internal performance (i.e. genotype) is certain assortment of genes, it determines the outside of the shape of individual Performance, as dark hair is characterized in being determined by certain assortment of genes for controlling this feature in chromosome.Therefore, at the beginning Need to realize the mapping i.e. coding work from phenotype to genotype.Since the work for copying gene to encode is very complicated, we are past Toward being simplified, such as binary coding after population primary generates, according to the principle of the survival of the fittest and the survival of the fittest, is drilled by generation Change produces the approximate solution become better and better, in every generation, according to fitness size selection individual individual in Problem Areas, and by It is combined intersection and variation in the genetic operator of natural genetics, produces the population for representing new disaggregation.This process will The rear life for causing kind of images of a group of characters natural evolution the same is more adaptive to environment than former generation for population, the optimum individual warp in last reign of a dynasty population Decoding is crossed, can be used as problem approximate optimal solution.

However, it should be understood that in practical applications, genetic algorithm passes through the operations pair such as intersection, variation and duplication The progress of initial population set is data-optimized, obtains new group's set.In the present embodiment, genetic algorithm by intersect, variation and The operations such as duplication are data-optimized to the progress of initial population set respectively, to obtain new group's set.

Step S30: corresponding fitness function value is determined according to new group's set.

It should be noted that fitness function value is to describe the main indicator of individual performance according to suitable in genetic algorithm The size of response functional value, selects the superior and eliminates the inferior to individual.Fitness function value is the power for driving genetic algorithm.From biology Angle says that fitness is equivalent to the biological existence ability of " struggle for existence, the survival of the fittest ", has important meaning in genetic process Justice.The fitness of the objective function of optimization problem and individual is established into mapping relations, can be realized during Swarm Evolution pair The optimizing of optimization problem objective function.Fitness function is also referred to as evaluation function, is determined according to objective function for distinguishing group The standard of individual quality in body, always non-negative, the value for being intended to it in any case is the bigger the better.

However, it should be understood that the fitness function value is used for crowdsourcing pricing structure to be assessed in the present embodiment It is assessed, fitness function value is higher, then it represents that the crowdsourcing pricing structure evaluation to be assessed is better, for system parameter Speech, the fitness function value the high, indicates that the system parameter is higher to the fitness of the crowdsourcing pricing structure to be assessed, right The assessment of the crowdsourcing pricing structure to be assessed is more advantageous.

Step S40: the crowdsourcing pricing structure to be assessed is assessed according to the fitness function value.

The fitness function value is compared with the initial fitness function value, according to comparison result to it is described to Assessment crowdsourcing pricing structure is assessed.

The appraisal procedure of the crowdsourcing pricing structure provided in order to better understand the present invention, is specifically described below:

Step 1: the initial population S={ x that random foundation is made of n individual₁,x₂,...,x_n}；

Step 2: regulation pricing structure functionM is scale of fixing a price in original pricing structure Size, x_r={ a_r,b_r,...,d_r, a_r,b_r,...,d_rFor on the influential various dimensions factor of task price；

Step 3: definitionFor the price in original pricing structure, k is controllable parameter；Calculate it is each each and every one The fitness function value of bodyWherein

Step 4: setting crossover probability p_c=50%, mutation probability p_m=0.001 and select probability p_r；Wherein

Step 5: carrying out genetic probability generates new group:

1, intersect: two individual x are selected by roulette selection operating method_i、x_j, by individual x_iWith x_jIt is corresponding The various dimensions factor { a_i,b_i,...,d_i}、{a_j,b_j,...,d_jBe converted to binary system and encoded, and according to crossover probability p_cOne One it is corresponding crossover operation is carried out to it, two individuals of generation are then put into new group S^*In；

2, it makes a variation: by roulette selection operating method in new population S^*Select an individualAccording to mutation probability p_mIt carries out New individual is then inserted new group S if generating new individual by mutation operation^*In, it otherwise carries out in next step；

3, it replicates: defect individual is copied to by new group S by roulette selection operating method^*If meeting population scale, Then Population Regeneration S=S^*；

Step 6: the individual then termination algorithm if there is fitness value greater than 0.9, and as the more of pricing structure Dimensional parameter；Otherwise it is transferred to step 3.

It should be understood that the present invention assesses crowdsourcing pricing structure to realize by establishing innovation pricing model, The establishment process of innovation pricing model of the invention is as follows:

Establish objective functionConstraint condition is as follows:

In the establishment process of above-mentioned model, Max F is then to represent objective function, i.e., assesses crowdsourcing pricing structure The value exported afterwards,The price in original pricing structure is represented, k is controllable parameter, (t₁,t₂,L,t_m) this kind of parameter represents Impact factor in original pricing structure, m are the size of scale of fixing a price in original pricing structure, and x=(a, b, L, d) represents pair Task price it is influential to dimension factor, F >=0.9 represent model foundation finally, objective function desired value to be achieved.

It should be understood that having the above is only for example, not constituting any restriction to technical solution of the present invention In body application, those skilled in the art, which can according to need, to be configured, and the present invention is without limitation.

By foregoing description it is not difficult to find that the present embodiment extracts original system parameter from crowdsourcing pricing structure to be assessed, Initial population set is established according to the original system parameter；It is excellent that data are carried out to the initial population set by genetic algorithm Change, obtains new group's set；Corresponding fitness function value is determined according to new group's set；According to the fitness function Value assesses the crowdsourcing pricing structure to be assessed.By the above-mentioned means, the crowdsourcing price of adjustable original user, right New user's point provides crowdsourcing price, and can be according to the parameter for the data-optimized crowdsourcing pricing structure of crowdsourcing completed in real time, significantly Improve task completion rate.

With reference to Fig. 3, Fig. 3 is the flow diagram of the appraisal procedure second embodiment of crowdsourcing pricing structure of the present invention.

Based on above-mentioned first embodiment, the appraisal procedure of the present embodiment crowdsourcing pricing structure is after the step S20, also Include:

Step S301 carries out the initial population set by the genetic algorithm according to the default crossover probability It is data-optimized, obtain cross parameter.

It is understood that default crossover probability is that perhaps system is pre-set by user, for system parameter into The probability of row crossover operation, crossover operation are then the chromosome dyad being exchanged with each other between certain two individual with a certain probability, In In practical operation, it can be encoded with switching part.

Operating process in practical applications can be such that

Random pair is carried out to group first；

Next is randomly provided cross-point locations；

In the portion gene being exchanged with each other between pairing chromosome after rent；

For example, 4 individual needs now with number 1~4 carry out crossover operation, " 01 | 1101,11 | 1001,1010 | 11,1110 | 01 ", wherein " | " represents the position in crosspoint, pairing situation is that No. 1 individual and No. 2 individuals are matched, No. 3 Body and No. 4 individuals are matched, and the intersection finally obtained is as a result, it is 111101, No. 3 that No. 1 individual, which is 011001, No. 2 individuals, Body is that 101001, No. 4 individuals are 111011, if the more fitness of quantity are more with the height of the quantity representative fitness of " 1 " Height, then it can be seen that No. 2 individuals and No. 4 individual adaptation degrees that generate after crossover operation are higher than original individual.

Step S302 carries out the initial population set by the genetic algorithm according to the default mutation probability It is data-optimized, obtain Mutation parameter.

It is understood that mutation probability is equally that user or system are pre-set with crossover probability, for pair System parameter carries out the probability of mutation operation, mutation operation be genic value on some or certain some locus to individual by A certain lesser probability is changed, it is also a kind of operating method for generating new individual.

Operating process in practical applications can be such that

The genetic mutation position of each individual is determined first, following table show the change point position being randomly generated, wherein Digital representation change point setting changing at locus；

Then original genic value of change point is negated according to a certain probability.

Individual number	Intersect result	Change point	Make a variation result	Progeny population p
					1	011001	4	011101	011101
2	111101	5	111111	111111
					3	101001	2	111001	111001
4	111011	6	111010	111010

1 genes of individuals of table variation table

As can be seen from the above table, group is after a generation makes a variation, if counted with the height of the quantity representative fitness of " 1 " It is higher to measure more fitness, then it can be seen that generating individual adaptation degree after mutation operation is higher than original individual.

Step S303 carries out data to the initial population set by the genetic algorithm according to the select probability Optimization obtains new parameter.

It is understood that select probability is to be got by system according to the individual adaptation degree calculating under current environment, select Select operation (or for duplication operation) the higher individual of fitness in current group is genetic to by certain rule or model it is next For in group.Generally require the higher individual of fitness that there will be more chances to be genetic in next-generation group.

Operating process in practical applications can be such that

First calculate the fitness of all individuals in groupWherein

In above-mentioned formula, definitionFor the price in original pricing structure, k is controllable parameter；

Provide pricing structure functionM is the size of price scale in original pricing structure, x_r={ a_r,b_r,...,d_r, a_r,b_r,...,d_rFor on the influential various dimensions factor of task price；

Then select probability is calculatedIt is that each individual is genetic to the next generation Probability in group；

Each probability value forms a region, and the sum of whole probability values are 1；

The random number between one 0 to 1 is finally generated again, is appeared in which above-mentioned probability region according to the random number Determine the selected number of each individual, as shown in the table.

2 initial population of table selects table

As can be seen from the above table, Selecting operation can be selected just when higher individual inheritance into next-generation group.

By foregoing description it is not difficult to find that the present embodiment the present embodiment extracts initial body from crowdsourcing pricing structure to be assessed It is parameter, initial population set is established according to the original system parameter；By genetic algorithm to the initial population set into Row is data-optimized, obtains new group's set；Corresponding fitness function value is determined according to new group's set；According to described suitable Response functional value assesses the crowdsourcing pricing structure to be assessed.By the above-mentioned means, the crowd of adjustable original user Contract price lattice provide crowdsourcing price to new user's point, and can be according to the data-optimized crowdsourcing pricing structure of crowdsourcing completed in real time Parameter substantially increases task completion rate.

In addition, the embodiment of the present invention also proposes a kind of storage medium, crowdsourcing pricing structure is stored on the storage medium Appraisal procedure, the appraisal procedure of the crowdsourcing pricing structure realizes crowdsourcing price body as described above when being executed by processor The step of appraisal procedure of system.

Referring to the structural block diagram for the assessment device first embodiment that Fig. 4, Fig. 4 are crowdsourcing pricing structure of the present invention.

As shown in figure 4, the assessment device for the crowdsourcing pricing structure that the embodiment of the present invention proposes includes: to obtain module 10, excellent Change module 20, computing module 30, evaluation module 40.

Wherein, the acquisition module 10, for extracting original system parameter from crowdsourcing pricing structure to be assessed, according to institute It states original system parameter and establishes initial population set；

The optimization module 20, it is data-optimized for being carried out by genetic algorithm to the initial population set, it obtains new Group's set；

The computing module 30, for determining corresponding fitness function value according to new group's set；

The evaluation module 40, for being commented according to the fitness function value the crowdsourcing pricing structure to be assessed Estimate.

The present embodiment the present embodiment extracts original system parameter from crowdsourcing pricing structure to be assessed, according to the initial body It is that parameter establishes initial population set；It is data-optimized to initial population set progress by genetic algorithm, obtain new group Set；Corresponding fitness function value is determined according to new group's set；According to the fitness function value to described to be evaluated Estimate crowdsourcing pricing structure to be assessed.By the above-mentioned means, the crowdsourcing price of adjustable original user, gives new user's point Outstanding contract price lattice, and it is complete to substantially increase task according to the parameter for the data-optimized crowdsourcing pricing structure of crowdsourcing completed in real time At rate.

The other embodiments or specific implementation of the assessment device of crowdsourcing pricing structure of the present invention can refer to above-mentioned each side Method embodiment, details are not described herein again.

It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do There is also other identical elements in the process, method of element, article or system.

The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.

Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art The part contributed out can be embodied in the form of software products, which is stored in a storage medium In (such as read-only memory/random access memory, magnetic disk, CD), including some instructions are used so that a terminal device (can To be mobile phone, computer, server, air conditioner or the network equipment etc.) execute method described in each embodiment of the present invention.

The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills Art field, is included within the scope of the present invention.