Nuclear power icon similarity evaluation method and device, electronic equipment and storage medium

Abstract

The invention is suitable for the field of nuclear power, and provides a nuclear power icon similarity evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining nuclear power icons needing similarity evaluation; determining similarity codes of the nuclear power icons according to the plurality of similarity attributes; a plurality of groups of icon schemes are designed by using similarity coding, the design basis of each group of icon schemes is a single similarity attribute, and the icon schemes comprise a plurality of icon schemes with different similarities; obtaining quantized data of each icon scheme in the initial group, wherein the quantized data is used for representing the search performance of the corresponding icon scheme in the target search experiment; and repeating the following process until a stop condition is met: combining the icon scheme corresponding to the maximum quantized data obtained in the previous round of experiment with a group of icon schemes selected in the current round, and then carrying out a target search experiment to obtain quantized data of each icon scheme, the groups selected in each round being different.

Description

Technical Field

[0001] The present application belongs to the field of nuclear power, and in particular, relates to a method and device for evaluating the similarity of nuclear power symbols, an electronic device, and a computer-readable storage medium. Background Art

[0002] The monitoring system of a nuclear power plant is different from a general industrial system. The overall data volume is huge and varied, but the information elements are mainly in certain data types and presentation forms. At the same time, in order to convey information to operators faster and more effectively, the interface information is more centralized and complex. This results in little visual difference between different interfaces, with convergent similarity characteristics.

[0003] As an information-integrated combination, icons are the main target in the operator's visual search task. Improving the recognizability of icons is crucial to the efficiency of visual search. Nuclear power icons have specific semantics, but due to related functions, similar structures, and similar usage scenarios, icons that appear in the same interface are visually similar. On the one hand, such similarity is necessary, which can make nuclear power icons have a unified style as a whole, thereby improving cognitive coordination; but on the other hand, too high a similarity of icons is not conducive to the operator's rapid recognition of their meaning, which may lead to cognitive bias, delayed operation, or even erroneous operation. It can be seen that the reasonable design of nuclear power icon similarity is still a problem to be solved. Summary of the invention

[0004] The embodiments of the present application provide a method and device for evaluating the similarity of nuclear power symbols, an electronic device, and a computer-readable storage medium, which can solve the problem of reasonable design of the similarity of nuclear power symbols in related technologies that still needs to be solved.

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating the similarity of nuclear power symbols, the method comprising: obtaining a nuclear power symbol that requires similarity evaluation; determining a similarity code of the nuclear power symbol based on multiple similarity attributes; using the similarity code to design multiple groups of symbol schemes, each group of symbol schemes being designed based on a single similarity attribute and including multiple symbol schemes with different similarities; obtaining quantitative data of each symbol scheme in the initial group, the quantitative data being used to represent the search performance of the corresponding symbol scheme in a target search experiment; repeating the following process until a stopping condition is met: combining the symbol scheme corresponding to the largest quantitative data obtained in the previous round of experiments with a group of symbol schemes selected in the current round, and then conducting a target search experiment to obtain quantitative data of each symbol scheme therein, with a different group selected in each round.

[0006] In the second aspect, an embodiment of the present application provides a similarity evaluation device for nuclear power symbols, which includes: a determination module, used to determine the similarity coding of the nuclear power symbol based on multiple similarity attributes; a design module, used to design multiple groups of symbol schemes using similarity coding, the design basis of each group of symbol schemes is a single similarity attribute, and includes multiple symbol schemes with different similarities; an initialization module, used to obtain quantitative data of each symbol scheme in the initial group, and the quantitative data is used to represent the search performance of the corresponding symbol scheme in the target search experiment; an iteration module, used to repeat the following process until the stopping condition is met: the symbol scheme corresponding to the largest quantitative data obtained in the previous round of experiments is combined with a group of symbol schemes selected in the current round to perform a target search experiment, and the quantitative data of each symbol scheme therein is obtained, and the group selected in each round is different.

[0007] In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the method described in the first aspect when executing the computer program.

[0008] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, which implements the method described in the first aspect when executed by a processor.

[0009] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the method described in the first aspect above.

[0010] Compared with the prior art, the embodiments of the present application have the following beneficial effects: by obtaining nuclear power symbols that need similarity evaluation; determining the similarity coding of nuclear power symbols according to multiple similarity attributes; using similarity coding to design multiple groups of symbol schemes, each group of symbol schemes is designed based on a single similarity attribute and includes multiple symbol schemes with different similarities; obtaining quantitative data of each symbol scheme in the initial group, the quantitative data is used to represent the search performance of the corresponding symbol scheme in the target search experiment; repeating the following process until the stop condition is met: combining the symbol scheme corresponding to the largest quantitative data obtained in the previous round of experiments with a group of symbol schemes selected in the current round to conduct a target search experiment, and obtaining the quantitative data of each symbol scheme therein, and the groups selected in each round are different. The embodiments of the present application propose similarity coding of symbols, so that the similarity of symbols can be quantitatively evaluated from multiple different dimensions, and cyclic experiments are carried out with the goal of optimizing the search performance represented by quantitative data, and similarity attributes are determined one by one to obtain the final symbol scheme, so as to strike a balance between the high similarity of symbols being unfavorable for operators to quickly identify their meanings and the low similarity of symbols affecting the efficiency of operators' search and recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1 is a structural schematic diagram of an electronic device provided by an embodiment of the present application;

[0013] Figure 2 It is a flowchart of a method for similarity evaluation of nuclear power symbols provided in one embodiment of the present application;

[0014] Figure 3 It is a structural schematic diagram of a similarity assessment device for nuclear power symbols provided in one embodiment of the present application. DETAILED DESCRIPTION

[0015] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0016] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0017] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0018] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0019] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0020] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0021] The method provided in the embodiments of the present application can be applied to electronic devices, including but not limited to servers, server clusters, mobile phones, tablet computers, laptop computers, desktop computers, personal digital assistants, wearable devices and other electronic devices with computing functions. The embodiments of the present application do not impose any restrictions on the specific types of electronic devices.

[0022] Figure 1 FIG. 1 is a block diagram showing a partial structure of an electronic device provided by an embodiment of the present application. Figure 1 , the electronic device includes: a processor 10, a memory 20, a bus 30, an input device 40, an output device 50 and a communication device 60. The processor 10 and the memory 20 are connected to each other through the bus 30, and the input device 40, the output device 50 and the communication device 60 are also connected to the bus 30. Those skilled in the art can understand that Figure 1 The structure of the electronic device shown in the figure does not constitute a limitation of the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0023] Combine the following Figure 1 A detailed introduction to the various components of electronic equipment:

[0024] The processor 10 is the control center of the electronic device, and can run the program stored in the memory 20 to perform various functions and process data. The processor 10 can be a central processing unit (CPU), and the processor 10 can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In some embodiments, the processor 10 may include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0025] The memory 20 is used to store an operating system, an application program, a boot loader, data, and other programs, such as program codes of computer programs. The memory 20 can also be used to temporarily store data required for executing the program and generated. The memory 20 may include a high-speed random access memory, and may also include a non-volatile memory, such as a flash memory, a hard disk, a multimedia card, a card-type memory, etc. The memory 20 may include a storage unit disposed inside the electronic device, such as a hard disk of the electronic device, and / or a removable external storage unit, such as a mobile hard disk, a USB flash drive, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, etc.

[0026] The input device 40 may include at least one of a keyboard, a mouse, a touch panel, a joystick, etc., and is used to collect user input operations to generate corresponding operation instructions.

[0027] The output device 50 is used to output information to be provided to the user. The output device 50 generally includes a display, and optionally, a liquid crystal display (LCD), an organic light-emitting diode (OLED), etc. can be used. In addition, the output device can further include a speaker.

[0028] The communication device 60 may include a modem, a network card, etc., for establishing a network connection with other electronic devices and communicating with each other.

[0029] The method provided by the embodiment of the present application can be implemented as a computer software program. For example, the embodiment of the present application provides a computer program product, which includes a computer program carried on a computer readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 60, and / or installed from a removable external storage unit. When the computer program is executed by the processor 10, the various functions defined in the method provided by the embodiment of the present application are implemented.

[0030] Figure 2 A schematic flowchart of a method for evaluating the similarity of nuclear power symbols provided in an embodiment of the present application is shown. As an example but not a limitation, the method can be applied to the above-mentioned electronic devices.

[0031] S1: Obtain the nuclear power symbol that needs similarity evaluation.

[0032] S2: Determine the similarity coding of the nuclear power symbol based on multiple similarity attributes.

[0033] By analyzing the presentation form and application characteristics of nuclear power symbols, we can make cognitive interpretations that cause similarity deviations based on the two parts of "information perception" and "information processing" in the operator's visual search cognition, and determine multiple similarity categories of nuclear power symbols based on cognitive interpretations, which can specifically include perceptual similarity, semantic similarity, and memory similarity. The similarity of symbols described by perceptual similarity in the operator's information perception is mainly determined based on the overall appearance characteristics of the symbols. Semantic similarity describes the similarity of the symbol's own semantics in the operator's information processing, which is mainly determined based on the symbol's semantics. Memory similarity describes the similarity of the operator's memory of the use of symbols, which is mainly determined based on the frequency of use of the symbols.

[0034] After determining the similarity categories, the similarity categories can be mapped to at least one similarity attribute to obtain multiple similarity attributes. There may be at least one attribute that affects the similarity of each category. At least one similarity attribute with influence is selected for each similarity category. This process can be called mapping the similarity category to the similarity attribute. Generally speaking, attributes that have a large impact on the similarity category are preferentially selected as similarity attributes. If the number of attributes supports it, the specific number of similarity attributes corresponding to each similarity category can be 2-3, and more or fewer similarity attributes can be selected according to the actual situation, and there is no limitation here.

[0035] For example, the attributes of the perception class may include shape (the shape of the outer contour of the symbol), direction (the direction of the object represented by the foreground part of the symbol), background color, foreground color, etc., among which shape and direction have a greater impact on the overall similarity, and shape and direction are selected as the perception similarity attributes. The attributes of the semantic class may include semantic objects, semantic themes, semantic scenes, etc., among which semantic objects and semantic themes have a greater impact on the overall similarity, and semantic objects and semantic themes are selected as semantic similarity attributes. The attributes of the memory class include frequency of use, which is used as a memory similarity attribute. After summarization, the similarity attributes of the symbol include shape, direction, semantic object, semantic themes, and frequency of use.

[0036] Each similarity attribute can be described by at least two possible values. The actual value of each similarity attribute of each symbol is fixed. By combining the values ​​of all similarity attributes of a symbol, the similarity code of the symbol can be obtained. The number of values ​​and specific limitations of each similarity attribute can be determined according to actual needs, and are not limited here. For example, at least one threshold value can be set for the frequency of use according to needs, thereby dividing at least two intervals, and different intervals correspond to different values ​​of the frequency of use.

[0037] Continuing with the above example, possible values ​​of shape include circle, square, and rounded square; possible values ​​of direction include up, down, left, and right; possible values ​​of semantic object include component and instruction; possible values ​​of semantic subject include system A and system B; possible values ​​of frequency of use include low frequency (less than a set threshold) and high frequency (greater than or equal to a set threshold).

[0038] The similarity code can be represented by the actual value of the similarity attribute itself. For example, the similarity code of a certain symbol can be square-upward-component-system A-high frequency; or, the possible values ​​of each similarity attribute can be mapped to numbers. For example, the aforementioned square-upward-component-system A-high frequency can be mapped to 1-0-0-0-1. The similarity code obtained in this way is in digital format to facilitate subsequent similarity calculation.

[0039] S3: Design multiple sets of icon schemes using similarity encoding.

[0040] Each set of symbol schemes is designed based on a single similarity attribute, hereinafter referred to as the primary attribute. Each set of symbol schemes includes multiple symbol schemes with different similarities. The similarity here refers to the similarity obtained by evaluating the primary attribute. There is no restriction on the specific values ​​of other similarity attributes except the primary attribute. For example, they can be set to fixed values ​​to reduce interference with the primary attribute.

[0041] Each symbol scheme includes multiple nuclear power symbols in the operation interface of the nuclear power plant monitoring system. By counting the differences in the main attributes of these nuclear power symbols, the similarity of the symbol scheme can be obtained. The similarity can be represented by a specific scoring value, or at least two intervals can be divided by at least one threshold, and these intervals are used to represent the similarity, for example, three intervals of low similarity, medium similarity and high similarity can be divided by two thresholds. For example, for similarity coding in digital format, the variance / standard deviation of the main attributes of these nuclear power symbols can be calculated, and then the similarity can be determined based on the variance / standard deviation. The variance / standard deviation is negatively correlated with the similarity.

[0042] S4: Obtain quantitative data of each symbol scheme in the initial group.

[0043] The quantitative data of the symbol scheme can be obtained through the target search experiment. The quantitative data is used to represent the search performance of the corresponding symbol scheme in the target search experiment. Specifically, for the current symbol scheme, invite the operator to conduct multiple target search experiments. Each experiment gives a search target, and the number of targets can be 1 or more than 1. The operator's behavioral indicators for searching for the target in the current symbol scheme are recorded, such as the search time, whether the search result is correct, etc. The statistical data of the target search experiment of the current symbol scheme is calculated based on the behavioral indicators of multiple experiments. For example, the average search time is calculated as the reaction time, the accuracy of the search is calculated, and the quantitative data of the current symbol scheme is calculated using the accuracy and / or reaction time of the target search experiment.

[0044] The goal of this embodiment is to optimize the design of the symbol scheme and determine the symbol scheme that is ultimately used. In this process, a cyclic experiment is performed with the goal of optimizing search performance. The initial group is a group selected from the multiple groups of symbol schemes designed above as the starting point of the cyclic experiment. The specific selection method can be determined based on actual needs.

[0045] Optionally, a group of icon schemes are randomly selected as an initial group to conduct a target search experiment, and quantitative data of each icon scheme is obtained.

[0046] Optionally, a target search experiment is conducted on each group of symbol schemes designed above to obtain quantitative data of each group. The initial group is determined based on the difference between the maximum value and the second largest value of the quantitative data (hereinafter referred to as the difference value) and / or the maximum value of the quantitative data. When the initial group is determined based on the difference value, a group of symbol schemes with the largest difference value is preferentially selected as the initial group; when the initial group is determined based on the maximum value of the quantitative data, a group of symbol schemes with the largest maximum value of the quantitative data is preferentially selected as the initial group; when the initial group is determined based on the difference value and the maximum value of the quantitative data, the weighted sum of the two can be calculated, and a group of symbol schemes with the largest weighted sum can be selected as the initial group.

[0047] S5: Combining the symbol scheme corresponding to the maximum quantitative data obtained in the previous round of experiments with a group of symbol schemes selected in the current round, and then conducting a target search experiment to obtain the quantitative data of each symbol scheme.

[0048] There is no restriction on the method of selecting groups in each round, for example, random selection can be used. The completion of a round of experiments means that the main attributes of the groups selected in this round of experiments are determined, and more specifically, the similarity of the main attributes is determined. Different groups are selected in each round, which means that different similarity attributes are determined in each round.

[0049] In the similarity encoding of a group of symbol schemes selected in the current round, the similarity attributes determined in the previous round are modified according to the symbol scheme corresponding to the maximum quantitative data obtained in the previous round of experiments, and the combined symbol scheme is used as the symbol scheme of the current round. Then, a target search experiment is performed on the symbol scheme of the current round to obtain the quantitative data of each symbol scheme.

[0050] Still continuing with the above example, the main attribute of the initial group is shape. After the target search experiment, the symbol scheme with the largest quantitative data is the symbol scheme with medium similarity. The first round of experiments is completed, and it is determined that the similarity corresponding to the similarity attribute of shape should be medium similarity. Then enter the second round of experiments. The main attribute selected from the multiple groups of symbol schemes obtained in S3 is a group of semantic objects. The shape attribute in this group of symbol schemes is modified according to the symbol scheme with medium similarity corresponding to the shape in the initial group. The symbol schemes for the second round of experiments are obtained. The target search experiment is carried out on these symbol schemes to obtain the quantitative data of each symbol scheme. It is determined that the symbol scheme with the largest quantitative data is the symbol scheme with low similarity. The second round of experiments is completed, and it is determined that the similarity corresponding to the similarity attribute of semantic objects should be low similarity. Then we enter the third round of experiments. In this round, we select a group of symbol schemes with the main attribute of direction from the multiple groups of symbol schemes obtained in S3. We modify the shape and semantic object attributes in this group of symbol schemes according to the symbol schemes with low similarity corresponding to the semantic object attributes in the symbol schemes of the second round of experiments, and obtain the symbol schemes of the third round of experiments. We conduct target search experiments on these symbol schemes, obtain the quantitative data of each symbol scheme, determine that the symbol scheme with the largest quantitative data is the symbol scheme with high similarity, and complete the third round of experiments. We determine that the similarity corresponding to the similarity attribute of direction should be high. By analogy, we can get the specific process of subsequent experiments.

[0051] It can be seen that the symbol scheme used in the first round of experiments comes from the multiple sets of symbol schemes obtained in S3. As the iteration process proceeds, the symbol schemes used in subsequent rounds of experiments may be different from those obtained in S3. The goal of each round of experiments is to maximize the quantitative data and determine the best similarity design scheme for the main attribute selected in this round based on the best similarity design scheme of the previously determined similarity attribute.

[0052] S6: Determine whether the stopping condition is met based on the quantized data of the current round.

[0053] Specifically, the stop condition may include that the difference between the quantized data obtained in the current round is less than a first preset value, the difference between the maximum quantized data obtained in the current round and the maximum quantized data obtained in the previous round is less than a second preset value, and at least one of all similarity attributes has been determined.

[0054] The difference between the quantized data obtained in the current round can be the difference between the maximum quantized data obtained in the current round and the second largest quantized data, or the difference between the maximum quantized data obtained in the current round and the minimum quantized data, or the difference between the maximum quantized data obtained in the current round and the average quantized data, etc., and there is no limitation here.

[0055] The first two stopping conditions correspond to the situation that the improvement of the quantitative data within / between rounds is no longer obvious, and continuing the experiment will not significantly optimize the quantitative data. Even if all similarity attributes have not been traversed, the loop experiment can be ended.

[0056] If there is more than one stop condition, the combination of different stop conditions can be AND or OR.

[0057] If not satisfied, jump to S5, if satisfied, jump to S7.

[0058] S7: Taking the icon scheme corresponding to the largest quantized data in the current group as the final icon scheme.

[0059] Through the implementation of this embodiment, similarity coding of icons is proposed, so that the similarity of icons can be quantitatively evaluated from multiple different dimensions, and cyclic experiments are carried out with the goal of optimizing the search performance represented by quantitative data. The similarity attributes are determined one by one to obtain the final icon scheme, thereby achieving a balance between too high icon similarity, which is not conducive to the operator's rapid identification of its meaning, and too low icon similarity, which affects the operator's search and identification efficiency.

[0060] Figure 3 A schematic structural diagram of a nuclear power symbol similarity assessment device provided in one embodiment of the present application is shown, the device comprising an acquisition module 11, a determination module 12, a design module 13, an initialization module 14 and an iteration module 15.

[0061] The acquisition module 11 is used to acquire the nuclear power symbol that needs similarity evaluation.

[0062] The determination module 12 is used to determine the similarity code of the nuclear power symbol according to multiple similarity attributes.

[0063] The design module 13 is used to design multiple groups of icon schemes using similarity coding, wherein each group of icon schemes is designed based on a single similarity attribute and includes multiple icon schemes with different similarities.

[0064] The initialization module 14 is used to obtain quantitative data of each symbol solution in the initial group, and the quantitative data is used to represent the search performance of the corresponding symbol solution in the target search experiment.

[0065] Iteration module 15 is used to repeat the following process until the stopping condition is met: the symbol scheme corresponding to the maximum quantization data obtained in the previous round of experiments is combined with a group of symbol schemes selected in the current round to perform a target search experiment to obtain the quantization data of each symbol scheme, and the group selected in each round is different.

[0066] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / modules / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0067] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0068] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0069] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0070] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera / electronic device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0071] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0072] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0073] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0074] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0075] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A similarity evaluation method for nuclear power symbols, characterized in that: The method comprises: Obtaining nuclear power symbols requiring similarity evaluation; Determining a similarity code of the nuclear power symbol according to a plurality of similarity attributes; Using the similarity coding to design multiple groups of icon schemes, each group of the icon schemes is designed based on a single similarity attribute and includes multiple icon schemes with different similarities; Acquire quantitative data of each of the icon schemes in the initial group, wherein the quantitative data is used to represent the search performance of the corresponding icon scheme in the target search experiment; Repeat the following process until the stopping condition is met: combine the icon scheme corresponding to the largest quantized data obtained in the previous round of experiments with a group of icon schemes selected in the current round to conduct a target search experiment to obtain the quantized data of each icon scheme, with a different group selected in each round.

2. The method according to claim 1, characterized in that The combining of the icon scheme corresponding to the largest quantized data obtained in the previous round of experiments with a group of icon schemes selected in the current round includes: In the similarity coding of the group of icon schemes selected in the current round, the similarity attribute determined in the previous round of experiments is modified according to the icon scheme corresponding to the maximum quantized data obtained in the previous round of experiments.

3. The method according to claim 1, characterized in that The stop conditions include: The difference between the quantized data obtained in the current round is less than a first preset value, the difference between the maximum quantized data obtained in the current round and the maximum quantized data obtained in the previous round is less than a second preset value, and at least one of all the similarity attributes has been determined.

4. The method according to claim 1, characterized in that The step of obtaining the quantitative data of each of the icon schemes in the initial group comprises: A group of the icon schemes is randomly selected as the initial group to perform the target search experiment, and quantitative data of each of the icon schemes is obtained.

5. The method according to claim 1, characterized in that The step of obtaining the quantitative data of each of the icon schemes in the initial group comprises: Performing the target search experiment on each group of the icon schemes to obtain the quantitative data of each group; The initial group is determined according to a difference between a maximum value and a second maximum value of the quantized data and / or a maximum value of the quantized data.

6. The method according to any one of claims 1 to 5, characterized in that: Before determining the similarity code of the nuclear power symbol according to a plurality of similarity attributes, the method further includes: determining a plurality of similarity categories of the nuclear power symbol; The similarity categories are respectively mapped to at least one of the similarity attributes to obtain the multiple similarity attributes.

7. The method according to claim 6, characterized in that The similarity categories include perceptual similarity, semantic similarity, and memory similarity.

8. The method according to any one of claims 1 to 5, characterized in that: The quantitative data is calculated using the accuracy and / or reaction time of the target search experiment.

9. A similarity evaluation device for nuclear power symbols, characterized in that: The device comprises: An acquisition module, used for acquiring nuclear power symbols requiring similarity evaluation; A determination module, used for determining the similarity code of the nuclear power symbol according to a plurality of similarity attributes; A design module, used for designing multiple groups of icon schemes using the similarity code, wherein each group of icon schemes is designed based on a single similarity attribute and includes multiple icon schemes with different similarities; An initialization module, used for obtaining quantitative data of each of the icon schemes in the initial group, wherein the quantitative data is used for representing the search performance of the corresponding icon scheme in the target search experiment; The iterative module is used to repeat the following process until the stopping condition is met: the symbol scheme corresponding to the largest quantitative data obtained in the previous round of experiments is combined with a group of symbol schemes selected in the current round to conduct a target search experiment to obtain the quantitative data of each symbol scheme, and the group selected in each round is different.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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