Position selection method, apparatus, device, medium, and computer program product

Abstract

The application provides a position selection method, device, equipment, medium and computer program product. The method comprises: obtaining input factors corresponding to each candidate position, and actual parameters and preset parameters corresponding to the input factors; determining membership functions corresponding to the input factors according to the actual parameters and the preset parameters, and calculating the membership of the input factors according to the membership functions; inputting the membership of the input factors into a preset fuzzy controller to obtain evaluation values of each candidate position, and determining a selectable position in each candidate position according to the evaluation values. The application makes quantitative analysis on multiple input factors affecting the selected position, and finally determines a unique selectable position, which has high universality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quantitative analysis, in particular to a position selection method, device, equipment, medium and computer program product. BACKGROUND

[0002] In the existing task analysis, multiple different influence factors exist, which jointly affect the actual analysis result of the task. In the existing evaluation analysis method, only a single factor affecting the analysis result is analyzed, and the influence degree of the single factor is represented by a non-automatic change weight. For task analysis involving multiple factors, only qualitative analysis is involved, and quantitative analysis is not involved, which has low universality. SUMMARY

[0003] The present application provides a position selection method, device, equipment, storage medium and computer program product to solve the technical problem of low universality of existing task analysis.

[0004] The present application provides a position selection method, comprising:

[0005] Obtaining an input factor corresponding to each candidate position, and an actual parameter and a preset parameter corresponding to the input factor;

[0006] According to the actual parameter and the preset parameter, determining a membership function corresponding to the input factor, and calculating the membership of the input factor according to the membership function;

[0007] Inputting the membership of the input factor into a preset fuzzy controller to obtain an evaluation value of each candidate position, and determining a selectable position in each candidate position according to the evaluation value.

[0008] According to the position selection method provided by the present application, the step of determining the membership function corresponding to the input factor according to the actual parameter and the preset parameter comprises:

[0009] In the case where the input factor is the length of sunlight, the actual parameter comprises an actual illumination time, and the preset parameter comprises a preset simulation time length, a first coefficient and a second coefficient, wherein the first coefficient and the second coefficient are determined according to the observed load photoelectric conversion efficiency of each candidate position and the tolerance of the load to the light illumination factor;

[0010] According to the actual illumination time, the preset simulation time length, the first coefficient and the second coefficient, the membership function corresponding to the length of sunlight is determined as Wherein, y 2iis a membership function corresponding to the sunlight duration, T is the preset simulation time length, a is the first coefficient, b is the second coefficient, t s is the actual illumination time.

[0011] According to the position selection method provided by the application, the step of determining the membership function corresponding to the input factor according to the actual parameter and the preset parameter further comprises:

[0012] In the case that the input factor is the lunar surface terrain slope, the actual parameter comprises the actual lunar surface slope, and the preset parameter comprises a preset maximum slope;

[0013] According to the actual lunar surface slope and the preset maximum slope, the membership function corresponding to the lunar surface terrain slope is determined as wherein, y 1i is the membership function corresponding to the lunar surface terrain slope, S i is the actual lunar surface slope, S max is the preset maximum slope.

[0014] According to the position selection method provided by the application, the step of determining the membership function corresponding to the input factor according to the actual parameter and the preset parameter further comprises:

[0015] In the case that the input factor is the earth disc visibility, the actual parameter comprises the actual earth disc visibility time, and the preset parameter comprises a third coefficient and the preset simulation time length;

[0016] According to the actual earth disc visibility time, the third coefficient and the preset simulation time length, the membership function corresponding to the earth disc visibility is determined as wherein, y 3i is the membership function corresponding to the earth disc visibility, t e is the actual earth disc visibility time, β is the third coefficient, and T is the preset simulation time length.

[0017] According to the position selection method provided by the application, the step of calculating the membership degree of the input factor according to the membership function further comprises:

[0018] obtaining a fuzzy rule corresponding to the input factor;

[0019] The step of inputting the membership degree of the input factor into a preset fuzzy controller to obtain evaluation values of each of the candidate positions and determining a selectable position in each of the candidate positions according to the evaluation values further comprises:

[0020] input the membership degree of the input factor into a preset fuzzy controller determined by the fuzzy rule, and calculate an evaluation value of each of the candidate positions according to the membership degree and the fuzzy rule;

[0021] determine a selectable position from the candidate positions according to a preset screening ratio and the evaluation value.

[0022] According to the position selection method provided by the application, the step of calculating the evaluation value of each of the candidate positions according to the membership degree and the fuzzy rule comprises:

[0023] According to the fuzzy rule corresponding to the input factor, the membership degree of the input factor is calculated to obtain an evaluation coefficient corresponding to the input factor.

[0024] The evaluation value of each of the candidate positions is calculated according to the evaluation coefficient.

[0025] The application further provides a position selection device, comprising:

[0026] a parameter acquisition module, configured to acquire input factors corresponding to each of the candidate positions, and actual parameters and preset parameters corresponding to the input factors;

[0027] a membership degree calculation module, configured to determine a membership degree function corresponding to the input factor according to the actual parameters and the preset parameters, and calculate the membership degree of the input factor according to the membership degree function;

[0028] a position selection module, configured to input the membership degree of the input factor into a preset fuzzy controller to obtain the evaluation value of each of the candidate positions, and determine a selectable position from the candidate positions according to the evaluation value.

[0029] The application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the position selection method as described above when executing the program.

[0030] The application further provides a non-transitory computer readable storage medium, which stores a computer program executable on a processor to implement the position selection method as described above.

[0031] The application further provides a computer program product, comprising a computer program executable on a processor to implement the position selection method as described above.

[0032] The location selection method, apparatus, device, storage medium, and computer program product provided by this invention acquire multiple input factors corresponding to each candidate location, as well as actual parameters and preset parameters corresponding to each input factor. Then, based on the actual parameters and preset parameters, a membership function corresponding to each input factor is determined. The actual parameters and preset parameters are input into the membership function to calculate the membership degree of each input factor. Finally, the membership degree of each input factor corresponding to each candidate location is input into a preset fuzzy controller to obtain an evaluation value for each candidate location. Based on the evaluation value of each candidate location, the final selectable location is determined. By performing quantitative analysis on multiple input factors affecting the selection of the location, a unique selectable location is ultimately determined, exhibiting high universality. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 This is one of the flowcharts illustrating the location selection method provided by the present invention;

[0035] Figure 2 This is the second flowchart illustrating the location selection method provided by the present invention;

[0036] Figure 3 This is a schematic diagram of the position selection device provided by the present invention;

[0037] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0039] The following is combined Figures 1-4 The location selection method of the present invention is described.

[0040] Please refer to Figure 1 The present invention provides a location selection method, comprising:

[0041] Step S100, obtaining input factors corresponding to each candidate position, and actual parameters and preset parameters corresponding to the input factors;

[0042] Specifically, for the task analysis problem of multiple influence factors and absolute output (i.e. output of a single result), the position selection method disclosed in the embodiment solves the above problem by a quantitative analysis method. The following content takes the analysis task of selecting the most suitable position point for building an observation station on the lunar surface as an example, and takes the sunlight duration, lunar terrain slope and earth disc visibility as influence factors (i.e. input factors in the embodiment) and the most suitable position point for building an observation station as an absolute output. In the task analysis of selecting the most suitable position point for building an observation station on the lunar surface, there are multiple candidate positions, and each candidate position has multiple input factors. By analyzing these input factors, one or more most suitable position points for building an observation station are determined from the candidate positions. The actual parameters in the embodiment refer to the actual data of the candidate positions, for example, the actual terrain slope of the candidate positions. The preset parameters in the embodiment refer to threshold data that affect the construction of the observation station, for example, the maximum slope on which the observation station can be built.

[0043] Step S200, determining a membership function corresponding to the input factor according to the actual parameter and the preset parameter, and calculating the membership of the input factor according to the membership function;

[0044] The embodiment introduces the concept of membership function, wherein the membership function refers to: if there is a number A(x) [0, 1] corresponding to any element x in the domain of discourse (i.e. the scope of the study) U, A is called a fuzzy set on U, and A(x) is called the membership of x to A. When x changes in U, A(x) is a function, called the membership function of A. If the membership A(x) is closer to 1, it indicates that x belongs to A to a higher degree, and vice versa. If A(x) is closer to 0, it indicates that x belongs to A to a lower degree. The membership function A(x) with a value in the interval [0, 1] is used to represent the degree of x belonging to A.

[0045] According to the actual parameter and the preset parameter, the membership function corresponding to the input factor is determined. Taking the input factor of sunlight duration as an example, in the case of the input factor being sunlight duration, the actual parameter includes the actual illumination time of the selected position, the preset parameter includes the preset simulation time length T, the coefficient a and the coefficient b, wherein the value range of the coefficient a is [0, 1], the coefficient a is a coefficient related to T, the value range of the coefficient b is [0, a], the coefficient b represents the coefficient that makes b.T equal to the optimal illumination time relative to T, and the coefficients a and b are determined according to the observed photoelectric conversion efficiency of the load of each selected position and the observed tolerance degree of the load of each selected position to the illumination influencing factor. The membership function corresponding to the sunlight duration is Wherein, t s is the actual illumination time of the selected position. After the actual parameter and the preset parameter are obtained, the actual parameter and the preset parameter are input into the membership function corresponding to the sunlight duration, so that the membership of the sunlight duration can be calculated. As can be seen from the above formula, the value range of the membership of the sunlight duration is [0, 1].

[0046] In step S300, the membership of the input factor is input into the preset fuzzy controller to obtain the evaluation value of each selected position, and the selected position in each selected position is determined according to the evaluation value.

[0047] Specifically, after the membership of each input factor is calculated according to the membership function corresponding to each input factor, the membership of each input factor is input into the preset fuzzy controller, so that the evaluation value of each selected position can be obtained, wherein each input factor has multiple rules to describe the appropriate degree of the input factor alone to the position selection. Assuming that each input factor has four rules (HA, IA, LA and IC) to describe the appropriate degree of the input factor alone to the position selection, which respectively represent that the selected position is very suitable as a selection point, the selected position is suitable as a selection point, the selected position can be as a selection point, and the selected position is not suitable as a selection point. For the input factor u1, the four rules are HA1, IA1, LA1 and IC1; for the input factor u2, the four rules are HA2, IA2, LA2 and IC2; for the input factor u3, the four rules are HA3, IA3, LA3 and IC3. When the input factor u3 is IC3, LA3, IA3 and HA3 respectively, the overall fuzzy rule table of u1, u2 and u3 is as follows.

[0048]

[0049] Table 1. Fuzzy rule table when the input factor u3 is IC3

[0050]

[0051] Table 2. Fuzzy rule table when input factor u3 is LA3

[0052]

[0053] Table 3. Fuzzy rule table when input factor u3 is IA3

[0054]

[0055] Table 4. Fuzzy rule table when input factor u3 is HA3

[0056] After the membership degrees of the sunlight duration, the lunar surface terrain slope and the earth disc visibility are calculated, the evaluation values of the candidate positions are calculated, and finally the final selectable position is determined according to the evaluation values of the candidate positions, as shown in the following Table 5. The evaluation value of the candidate position with the serial number 1 is 0.803, which is the highest among the three candidate positions.

[0057]

[0058] Table 5

[0059] It can be understood that for a candidate position, if y 1i = 0, y 2i = 0, and y 3i = 0, the evaluation value is zero, indicating that the candidate position is not suitable as a station site.

[0060] In this embodiment, by obtaining a plurality of input factors corresponding to each candidate position, and actual parameters and preset parameters corresponding to each input factor, the membership degree function corresponding to each input factor is determined according to the actual parameters and the preset parameters corresponding to each input factor, the actual parameters and the preset parameters are input into the membership degree function, the membership degree corresponding to each input factor is calculated, and finally the membership degree of each input factor corresponding to each candidate position is input into the preset fuzzy controller to obtain the evaluation value of each candidate position. The final selectable position is determined based on the evaluation value of each candidate position. Through quantitative analysis of a plurality of input factors affecting the selection of the position, the only selectable position is finally determined, which has high universality.

[0061] In one embodiment, the position selection method provided by the embodiment of the present application can further include:

[0062] In step S210a, when the input factor is the sunlight duration, the actual parameter includes an actual illumination time, and the preset parameter includes a preset simulation time length, a first coefficient and a second coefficient, wherein the first coefficient and the second coefficient are determined according to the photoelectric conversion efficiency of the load observed at each of the candidate positions and the tolerance of the load to the illumination influencing factor;

[0063] In step S220b, according to the actual illumination time, the preset simulation time length, the first coefficient and the second coefficient, the membership function corresponding to the sunlight duration is determined as

[0064] wherein y 2i is the membership function corresponding to the sunlight duration, T is the preset simulation time length, a is the first coefficient, b is the second coefficient, and t s is the actual illumination time.

[0065] Specifically, when the input factor is the sunlight duration, the actual parameter includes the actual illumination time of the candidate position, and the preset parameter includes the preset simulation time length T, the coefficient a (i.e., the first coefficient in this embodiment) and the coefficient b (i.e., the second coefficient in this embodiment), wherein the value range of the coefficient a is [0, 1], the coefficient a is a coefficient related to T, the value range of the coefficient b is [0, a], the coefficient b represents a coefficient that makes b.T equal to the optimal illumination time relative to T, and the coefficient a and the coefficient b are determined according to the photoelectric conversion efficiency of the load observed at each of the candidate positions and the tolerance of the load to the illumination influencing factor observed at each of the candidate positions. The membership function corresponding to the sunlight duration is wherein t s is the actual illumination time of the candidate position. After the actual parameter and the preset parameter are obtained, the actual parameter and the preset parameter are input into the membership function corresponding to the sunlight duration, so that the membership of the sunlight duration can be calculated. As can be seen from the above formula, the value range of the membership of the sunlight duration is [0, 1].

[0066] This embodiment determines the membership function corresponding to the sunlight duration through the actual parameter and the preset parameter corresponding to the sunlight duration, and finally determines the only selectable position through quantitative analysis of multiple input factors affecting the selection position, which has high universality.

[0067] In one embodiment, the position selection method provided by the embodiment of the present application can further include:

[0068] In step S210c, when the input factor is the lunar surface terrain slope, the actual parameter includes an actual lunar surface slope, and the preset parameter includes a preset maximum slope.

[0069] Step S220d: Based on the actual slope of the lunar surface and the preset maximum slope, determine the membership function corresponding to the lunar surface terrain slope. Among them, y 1i S is the membership function corresponding to the slope of the lunar surface terrain. i S represents the actual slope of the lunar surface. max The preset maximum slope.

[0070] Specifically, when the input factor is lunar surface slope, the actual parameters include the actual slope of the lunar surface at the candidate location, and the preset parameters include the preset maximum slope that can be used to establish an observation station (i.e., the preset maximum slope in this embodiment). The membership function corresponding to the lunar surface slope is: Among them, the actual slope S of the lunar surface i The range of values ​​for is [0, S]. max The closer the actual slope of the lunar surface is to 0, the more suitable the location is as an observation station. Here, the membership function of the lunar surface slope is a function in the range [0, S]. max The curve shows a monotonically decreasing trend within the interval.

[0071] This embodiment determines the membership function corresponding to the lunar surface slope by using actual parameters and preset parameters. By performing quantitative analysis on multiple input factors that affect the selection of the location, a unique selectable location is finally determined, which has high universality.

[0072] In one embodiment, the location selection method provided in this application may further include:

[0073] Step S210e: When the input factor is the line-of-sight of the Earth disk, the actual parameters include the actual line-of-sight time of the Earth disk, and the preset parameters include the third coefficient and the preset simulation time length.

[0074] Step S210f: Based on the actual line-of-sight time of the Earth disk, the third coefficient, and the preset simulation time length, determine the membership function corresponding to the line-of-sight of the Earth disk. Among them, y 3i Let t be the membership function corresponding to the line-of-sight of the Earth disk. e β is the actual line-of-sight time of the Earth disk, β is the third coefficient, and T is the preset simulation time length.

[0075] Specifically, when the input factor is the line-of-sight of the Earth disk, the actual parameters include the actual line-of-sight time of the Earth disk, and the preset parameters include the coefficient β and the preset simulation time length. The membership function corresponding to the line-of-sight of the Earth disk is: Among them, t eis the actual time of the Earth disc, and β is a time coefficient (i.e., the third coefficient in the embodiment), and the value of β·T is the same as the time of the Earth disc without considering the lunar surface terrain. When the lunar surface terrain is not considered, the selected position on the moon has the maximum time of the Earth disc. Therefore, the membership function of the Earth disc is monotonically increasing in the interval [0, β·T].

[0076] The embodiment determines the membership function of the Earth disc by using the actual parameters and the preset parameters of the Earth disc, and determines the only selected position by quantitatively analyzing the multiple input factors affecting the selected position, which has high universality.

[0077] Please refer to Figure 2 In an embodiment, the position selection method provided by the embodiment can further include:

[0078] In step S230, the fuzzy rule corresponding to the input factor is obtained.

[0079] The steps of step S300 further include:

[0080] In step S310, the membership of the input factor is input into the preset fuzzy controller determined by the fuzzy rule, and the evaluation value of each selected position is calculated according to the membership and the fuzzy rule.

[0081] In step S320, the selected position is determined according to the preset screening ratio and the evaluation value.

[0082] Specifically, each input factor has multiple rules (i.e., the fuzzy rule corresponding to the input factor in the embodiment) to describe the appropriate degree of the input factor alone to the position selection. According to the above Tables 1 to 4, the appropriate degree of each rule describing the input factor alone to the position selection is different. The membership of the input factor is input into the preset fuzzy controller determined by the fuzzy rule, and the evaluation value of each selected position is calculated according to the membership and the fuzzy rule. The preset fuzzy controller disclosed in the embodiment uses Mamdani reasoning method to obtain the only absolute output (i.e., the evaluation value of the selected position in the embodiment). It can be understood that the selection of the position can not be unique. A certain number (calculated according to the preset screening ratio in the embodiment) of selected positions are selected from the evaluation values of the multiple selected positions. As shown in Table 5 above, one of the three selected positions is selected as the selected position. Therefore, the position corresponding to the maximum evaluation value is the final selected position.

[0083] The embodiment calculates the evaluation values of the candidate positions by fuzzy rules, determines the only selectable position by quantitatively analyzing the multiple input factors affecting the selectable position, and has high universality.

[0084] In one embodiment, the position selection method provided by the embodiment further includes the following steps.

[0085] In step S311, the membership degree of the input factor is calculated according to the fuzzy rule corresponding to the input factor, to obtain an evaluation coefficient corresponding to the input factor.

[0086] In step S312, the evaluation values of the candidate positions are calculated according to the evaluation coefficients.

[0087] Specifically, the membership degree of the input factor is calculated according to the fuzzy rule corresponding to the input factor, to obtain an evaluation coefficient corresponding to the input factor. The evaluation coefficient in the embodiment reflects the influence of the membership degree on the evaluation value, which is similar to the concept of weight. As can be known from the above embodiment, the evaluation coefficient in the embodiment reflects the influence degree of each input factor on the final selectable position. Specifically, after obtaining the membership degree corresponding to each input factor, the membership degree corresponding to each input factor is calculated through the evaluation coefficient corresponding to each input factor, to finally obtain the evaluation values of the candidate positions.

[0088] The embodiment calculates the evaluation values of the candidate positions by the evaluation coefficients, determines the only selectable position by quantitatively analyzing the multiple input factors affecting the selectable position, and has high universality.

[0089] The position selection device provided by the embodiment is described below. The position selection device described below can be correspondingly referred to the position selection method described above.

[0090] Please refer to Figure 3 The embodiment further provides a position selection device, which includes the following.

[0091] The parameter acquisition module 301 is configured to acquire the input factors corresponding to the candidate positions, and the actual parameters and preset parameters corresponding to the input factors.

[0092] The membership degree calculation module 302 is configured to determine the membership degree function corresponding to the input factor according to the actual parameters and the preset parameters, and calculate the membership degree of the input factor according to the membership degree function.

[0093] The position selection module 303 is configured to input the membership degree of the input factor into a preset fuzzy controller, to obtain the evaluation values of the candidate positions, and determine the selectable position in the candidate positions according to the evaluation values.

[0094] The membership calculation module comprises:

[0095] The first parameter determination unit is configured to, when the input factor is the sunlight duration, the actual parameter comprises an actual illumination time, and the preset parameter comprises a preset simulation time length, a first coefficient and a second coefficient, wherein the first coefficient and the second coefficient are determined according to the photoelectric conversion efficiency of the load observed at each of the candidate positions and the tolerance of the load to the illumination influencing factor.

[0096] The first membership function determination unit is configured to determine, according to the actual illumination time, the preset simulation time length, the first coefficient and the second coefficient, a membership function corresponding to the sunlight duration as

[0097] wherein y 2i is the membership function corresponding to the sunlight duration, T is the preset simulation time length, a is the first coefficient, b is the second coefficient, and t s is the actual illumination time.

[0098] The membership calculation module further comprises:

[0099] The second parameter determination unit is configured to, when the input factor is the lunar surface terrain slope, the actual parameter comprises an actual lunar surface slope, and the preset parameter comprises a preset maximum slope.

[0100] The second membership function determination unit is configured to determine, according to the actual lunar surface slope and the preset maximum slope, a membership function corresponding to the lunar surface terrain slope as wherein y 1i is the membership function corresponding to the lunar surface terrain slope, S i is the actual lunar surface slope, and S max is the preset maximum slope.

[0101] The membership calculation module further comprises:

[0102] The third parameter determination unit is configured to, when the input factor is the earth disc visibility, the actual parameter comprises an actual earth disc visibility time, and the preset parameter comprises a third coefficient and the preset simulation time length.

[0103] The third membership function determination unit is configured to determine, according to the actual earth disc visibility time, the third coefficient and the preset simulation time length, a membership function corresponding to the earth disc visibility as

[0104] wherein y3i is a corresponding membership function of the earth disc, t e is an actual visibility time of the earth disc, β is the third coefficient, and T is the preset simulation time length.

[0105] The position selection device further includes:

[0106] The fuzzy rule acquisition module is configured to acquire fuzzy rules corresponding to the input factors.

[0107] The position selection module further includes:

[0108] The first evaluation value calculation unit is configured to input the membership of the input factors into a preset fuzzy controller determined by the fuzzy rules, and calculate evaluation values of the candidate positions according to the membership and the fuzzy rules.

[0109] The optional position determination unit is configured to determine optional positions in the candidate positions according to a preset screening ratio and the evaluation values.

[0110] The position selection module includes:

[0111] The evaluation coefficient calculation unit is configured to calculate the membership of the input factors according to the fuzzy rules corresponding to the input factors, and obtain evaluation coefficients corresponding to the input factors.

[0112] The second evaluation value calculation unit is configured to calculate evaluation values of the candidate positions according to the evaluation coefficients.

[0113] Figure 4 An example of an entity structure diagram of an electronic device is shown in FIG. 1. Figure 4 As shown in FIG. 1, the electronic device can include a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 can communicate with each other through the communications bus 440. The processor 410 can invoke a logical instruction in the memory 430 to execute a position selection method, which includes acquiring input factors corresponding to candidate positions, and actual parameters and preset parameters corresponding to the input factors; determining a membership function corresponding to the input factors according to the actual parameters and the preset parameters, and calculating a membership of the input factors according to the membership function; inputting the membership of the input factors into a preset fuzzy controller to obtain evaluation values of the candidate positions, and determining optional positions in the candidate positions according to the evaluation values.

[0114] In addition, the logic instructions in the memory 430 described above can be implemented in the form of software function units and sold or used as independent products, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0115] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to execute the position selection method provided by the above-mentioned methods. The method comprises: obtaining input factors corresponding to each candidate position, and actual parameters and preset parameters corresponding to the input factors; determining membership functions corresponding to the input factors according to the actual parameters and the preset parameters, and calculating the membership degrees of the input factors according to the membership functions; inputting the membership degrees of the input factors into a preset fuzzy controller to obtain evaluation values of each candidate position, and determining a selectable position in each candidate position according to the evaluation values.

[0116] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to execute the position selection method provided by the above-mentioned methods. The method comprises: obtaining input factors corresponding to each candidate position, and actual parameters and preset parameters corresponding to the input factors; determining membership functions corresponding to the input factors according to the actual parameters and the preset parameters, and calculating the membership degrees of the input factors according to the membership functions; inputting the membership degrees of the input factors into a preset fuzzy controller to obtain evaluation values of each candidate position, and determining a selectable position in each candidate position according to the evaluation values.

[0117] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0118] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and necessary universal hardware platforms, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of software products, and the computer software products can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and include a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0119] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A position selection method characterized by, The method comprises the steps of: obtaining input factors corresponding to each candidate position, and actual parameters and preset parameters corresponding to the input factors; determining membership functions corresponding to the input factors according to the actual parameters and the preset parameters, and calculating the membership of the input factors according to the membership functions; inputting the membership of the input factors into a preset fuzzy controller to obtain evaluation values of each candidate position, and determining a selectable position in each candidate position according to the evaluation values; the step of determining the membership functions corresponding to the input factors according to the actual parameters and the preset parameters comprises: in the case that the input factor is the length of sunlight, the actual parameter comprises an actual illumination time, and the preset parameter comprises a preset simulation time length, a first coefficient and a second coefficient, wherein the first coefficient and the second coefficient are determined according to the observation of the load photoelectric conversion efficiency of each candidate position and the tolerance of the load to the illumination influencing factor; determining the membership function corresponding to the length of sunlight according to the actual illumination time, the preset simulation time length, the first coefficient and the second coefficient wherein, is a membership function corresponding to the sunlight illumination time length, is the preset simulation time length, is the first coefficient, is the second coefficient, is the actual illumination time; the step of determining the membership functions corresponding to the input factors according to the actual parameters and the preset parameters further comprises: in the case that the input factor is the lunar surface terrain slope, the actual parameter comprises an actual lunar surface slope, and the preset parameter comprises a preset maximum slope; According to the actual slope of the lunar surface and the preset maximum slope, a membership function corresponding to the topographic slope of the lunar surface is determined as wherein, is the membership function corresponding to the topographic slope of the lunar surface, is the actual slope of the lunar surface, is the preset maximum slope.

2. The position selection method according to claim 1, characterized by, the step of determining the membership functions corresponding to the input factors according to the actual parameters and the preset parameters further comprises: in the case that the input factor is the earth disc visibility, the actual parameter comprises an actual earth disc visibility time, and the preset parameter comprises a third coefficient and the preset simulation time length; determining the membership function corresponding to the earth disc visibility according to the actual earth disc visibility time, the third coefficient and the preset simulation time length wherein, is the membership function corresponding to the earth disc visibility, is the actual visibility time of the earth disc, is the third coefficient, is the preset simulation time length.

3. The position selection method of claim 1, wherein the step of calculating the membership of the input factors according to the membership functions comprises: obtaining fuzzy rules corresponding to the input factors; the step of inputting the membership of the input factors into a preset fuzzy controller to obtain evaluation values of each candidate position, and determining a selectable position in each candidate position according to the evaluation values comprises: inputting the membership of the input factors into a preset fuzzy controller determined by the fuzzy rules, and calculating the evaluation values of each candidate position according to the membership and the fuzzy rules; determining a selectable position in each candidate position according to a preset screening ratio and the evaluation values.

4. The position selection method according to claim 3, characterized by, the step of calculating the evaluation values of each candidate position according to the membership and the fuzzy rules comprises: calculating the membership of the input factors according to the fuzzy rules corresponding to the input factors to obtain evaluation coefficients corresponding to the input factors; calculating the evaluation values of each candidate position according to the evaluation coefficients.

5. A position selection device, characterized by The method comprises the steps of: a parameter acquisition module for obtaining input factors corresponding to each candidate position, and actual parameters and preset parameters corresponding to the input factors; a membership degree calculation module, configured to determine a membership degree function corresponding to the input factor according to the actual parameter and the preset parameter, and calculate the membership degree of the input factor according to the membership degree function; a position selection module, configured to input the membership degree of the input factor into a preset fuzzy controller to obtain an evaluation value of each of the candidate positions, and determine a selectable position in each of the candidate positions according to the evaluation value; the step of determining the membership degree function corresponding to the input factor according to the actual parameter and the preset parameter comprises: in a case where the input factor is a sunlight duration, the actual parameter comprises an actual illumination time, and the preset parameter comprises a preset simulation time length, a first coefficient and a second coefficient, wherein the first coefficient and the second coefficient are determined according to an observation of a photoelectric conversion efficiency of a load of each of the candidate positions and a tolerance degree of the load to an illumination influencing factor; a membership degree function corresponding to the sunlight duration is determined according to the actual illumination time, the preset simulation time length, the first coefficient and the second coefficient, and the membership degree function is wherein, is the membership function corresponding to the sunlight illumination time length, is the preset simulation time length, is the first coefficient, is the second coefficient, is the actual illumination time; the step of determining the membership degree function corresponding to the input factor according to the actual parameter and the preset parameter further comprises: in a case where the input factor is a lunar surface terrain slope, the actual parameter comprises an actual lunar surface slope, and the preset parameter comprises a preset maximum slope; According to the actual slope of the lunar surface and the preset maximum slope, a membership function corresponding to the topographic slope of the lunar surface is determined as wherein, is the membership function corresponding to the topographic slope of the lunar surface, is the actual slope of the lunar surface, is the preset maximum slope.

6. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, the processor implements the position selection method according to any one of claims 1 to 4 when executing the program.

7. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, the computer program implements the position selection method according to any one of claims 1 to 4 when executed by the processor.

8. A computer program product comprising a computer program, characterized in that, the computer program implements the position selection method according to any one of claims 1 to 4 when executed by the processor.

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