User interface layout generation method and related equipment

Abstract

The invention provides a user interface layout generation method and related equipment, and relates to the technical field of user interface design. The method comprises the steps that a plurality of initial layouts are generated, each initial layout comprises a plurality of components, and each component has scores of multiple dimensions; according to the score of each component in the multiple dimensions and the weight corresponding to the multiple dimensions, determining the fitness score of each initial layout; processing the plurality of initial layouts according to the fitness score to obtain a plurality of candidate layouts; and determining a target layout according to the plurality of candidate layouts, and generating a user interface according to the target layout.

Description

Background Art

[0002] The smart editor has the advantages of high design efficiency, personalized design, diverse material library support, and real-time preview and adjustment functions when generating user interface layouts.

[0003] In the related art, the intelligent editor relies on fixed templates or simple rules to adjust the layout. However, the above method cannot optimize the user interface layout automatically and intelligently, and has poor adaptability. Summary of the invention

[0004] The present disclosure provides a user interface layout generation method and related devices, which at least to a certain extent overcome the problems in the related art that the user interface layout cannot be automatically optimized and has poor adaptability.

[0005] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0006] According to one aspect of the present disclosure, a method for generating a user interface layout is provided, comprising: generating multiple initial layouts, each of the initial layouts comprising multiple components, each of the components having scores in multiple dimensions; determining fitness scores of each of the initial layouts according to the scores of each component in the multiple dimensions and the weights corresponding to the multiple dimensions; processing the multiple initial layouts according to the fitness scores to obtain multiple candidate layouts; determining a target layout according to the multiple candidate layouts, and generating the user interface according to the target layout.

[0007] In one embodiment of the present disclosure, determining a target layout based on the multiple candidate layouts includes: determining a fitness score of each candidate layout based on components of each candidate layout and scores corresponding to the components in multiple dimensions; determining a dominance relationship of each candidate layout based on the fitness scores of each candidate layout; constructing a Pareto optimal solution set based on the dominance relationship of each candidate layout, wherein the Pareto optimal solution set includes all layouts of the multiple candidate layouts that are not dominated by other layouts; determining the target layout from the Pareto optimal solution set based on weights corresponding to the multiple dimensions, wherein the weights corresponding to the multiple dimensions are determined based on application scenarios or user needs.

[0008] In one embodiment of the present disclosure, the processing of the multiple initial layouts includes individual selection operations, crossover operations and mutation operations; wherein, the processing of the multiple initial layouts according to the fitness scores to obtain the multiple candidate layouts includes: performing individual selection operations according to the fitness scores of each of the initial layouts to determine multiple parent layouts, the individual selection probabilities of the parent layouts being greater than the initial layouts of a preset probability threshold, the individual selection probabilities of the parent layouts being obtained by the fitness scores of each of the initial layouts; performing crossover operations and / or mutation operations on the multiple parent layouts to obtain multiple child layouts; and obtaining the multiple candidate layouts according to the multiple parent layouts and the multiple child layouts.

[0009] In one embodiment of the present disclosure, after the multiple initial layouts are processed according to the fitness scores to obtain multiple candidate layouts, the method further includes: optimizing the multiple candidate layouts using a simulated annealing algorithm to obtain multiple optimized candidate layouts; determining the target layout according to the multiple candidate layouts includes: determining the target layout according to the multiple optimized candidate layouts.

[0010] In one embodiment of the present disclosure, the fitness score of each of the initial layouts is determined based on the scores of each component in multiple dimensions and the weights corresponding to the multiple dimensions, including: taking a weighted average of the scores of multiple components in each of the initial layouts in multiple dimensions to obtain the fitness score of the initial layout.

[0011] In one embodiment of the present disclosure, generating the user interface according to the target layout includes: obtaining user adjustment information of the target layout; generating the user interface according to attribute information of the target layout and the adjustment information, wherein the attribute information of the target layout includes at least one of position, size, style, and color of multiple components in the target layout.

[0012] According to another aspect of the present disclosure, there is provided a user interface layout generation device, comprising: a layout generation module, used to generate multiple initial layouts, each of the initial layouts comprising multiple components, each of the components having scores in multiple dimensions; a score determination module, used to determine the fitness scores of each of the initial layouts according to the scores of each of the components in multiple dimensions and the weights corresponding to the multiple dimensions; a set construction module, used to process the multiple initial layouts according to the fitness scores to obtain multiple candidate layouts; and a layout determination module, used to determine a target layout according to the multiple candidate layouts, and generate the user interface according to the target layout.

[0013] According to another aspect of the present disclosure, an electronic device is also provided, which includes: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the above-mentioned user interface layout generation methods by executing the executable instructions.

[0014] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for generating a user interface layout described above is implemented.

[0015] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the computer program implements any one of the above-mentioned methods for generating a user interface layout.

[0016] In an embodiment of the present disclosure, multiple initial layouts are generated, each initial layout includes multiple components, and each component has scores in multiple dimensions; the fitness scores of each initial layout are determined according to the scores of each component in the multiple dimensions and the weights corresponding to the multiple dimensions; the multiple initial layouts are processed according to the fitness scores to obtain multiple candidate layouts; the target layout is determined according to the multiple candidate layouts, and the user interface is generated according to the target layout. The present disclosure can realize dynamic optimization of the layout of the intelligent editor, and the adaptability of the page layout can be improved through multi-dimensional scoring.

[0017] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0019] Figure 1 A structural schematic diagram of an energy storage system using a method for generating a user interface layout in an embodiment of the present disclosure is shown.

[0020] Figure 2 A flow chart of a method for generating a user interface layout in an embodiment of the present disclosure is shown.

[0021] Figure 3 A flow chart of a method for determining a target layout in an embodiment of the present disclosure is shown.

[0022] Figure 4A flow chart of another target layout determination method in an embodiment of the present disclosure is shown.

[0023] Figure 5 A flow chart of another target layout determination method in an embodiment of the present disclosure is shown.

[0024] Figure 6 A flow chart of another method for generating a user interface layout in an embodiment of the present disclosure is shown.

[0025] Figure 7 A flow chart of another method for generating a user interface layout in an embodiment of the present disclosure is shown.

[0026] Figure 8 A schematic diagram of a user interface layout generating device in an embodiment of the present disclosure is shown.

[0027] Fig. 9 A structural block diagram of an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0028] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0029] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0030] In related technologies, smart editors usually rely on fixed templates or simple rules to adjust layouts. Most layouts require manual adjustment by users, and cannot automatically optimize the layout. There is a lack of automated and intelligent layout optimization solutions. When optimizing the layout, the main focus is on the aesthetics of the layout, resulting in a single optimization goal and insufficient responsiveness, making the layout less adaptable to different screen sizes and resolutions and unable to provide a consistent user experience.

[0031] In order to solve at least some of the above technical problems, the user interface layout generation method provided by the present disclosure generates multiple initial layouts, each initial layout includes multiple components, and each component has a score in multiple dimensions; determines the fitness score of each initial layout according to the score of each component in the multiple dimensions and the weights corresponding to the multiple dimensions; processes the multiple initial layouts according to the fitness score to obtain multiple candidate layouts; determines the target layout according to the multiple candidate layouts, and generates the user interface according to the target layout. The present disclosure can realize dynamic optimization of the layout of the intelligent editor, and can improve the adaptability of the page layout through multi-dimensional scoring.

[0032] The user interface layout generation method provided by the present disclosure can be applied to the layout optimization of the energy storage system configuration large-screen intelligent editor to generate the user interface. It can also be applied to other situations where the user interface layout is optimized through the intelligent editor.

[0033] The following describes in detail the user interface layout generation method provided by the present invention by taking the layout optimization method of the large-screen intelligent editor for energy storage system configuration as an example.

[0034] Since the energy people need is highly temporal and spatial, in order to rationally use energy and improve energy utilization, it is necessary to use a medium or device to store one form of energy in the same form or convert it into another form of energy, and then release it in a specific form based on future application needs. At present, the main way to generate green electricity is to develop green energy such as photovoltaics and wind power to replace fossil energy.

[0035] At present, the generation of green electricity generally relies on photovoltaics, wind power, and hydropower, etc. However, wind and solar energy generally have problems of strong intermittency and large volatility, which will cause instability in the power grid, insufficient electricity during peak hours, and too much electricity during valley hours. Unstable voltage will also cause damage to electricity. Therefore, insufficient electricity demand or insufficient grid acceptance capacity may cause the problem of "abandoning wind and solar power". To solve these problems, we must rely on energy storage. That is, converting electrical energy into other forms of energy through physical or chemical means and storing it, and converting energy into electrical energy and releasing it when needed. In simple terms, energy storage is like a large "power bank". When photovoltaic and wind energy are sufficient, electrical energy is stored and the stored electricity is released when needed.

[0036] Taking electrochemical energy storage as an example, the present disclosure provides an energy storage device, which has a group of chemical batteries in it. The chemical elements in the batteries are mainly used as energy storage media. The charging and discharging process is accompanied by chemical reactions or changes in the energy storage media. In simple terms, the electricity generated by wind and solar energy is stored in chemical batteries. When the use of external electricity reaches a peak, the stored electricity is released for use, or transferred to places where electricity is scarce for use.

[0037] At present, energy storage (i.e. energy storage) has a wide range of application scenarios, including energy storage on the power generation side, energy storage on the grid side, and energy storage on the power consumption side. The corresponding types of energy storage devices include:

[0038] (1) Large-scale energy storage power stations applied to wind power and photovoltaic power stations can help renewable energy generation meet grid connection requirements and improve the utilization rate of renewable energy. As a high-quality active / reactive regulating power source on the power supply side, energy storage power stations can achieve load matching of electric energy in time and space, enhance the ability to absorb renewable energy, reduce instantaneous power changes, reduce the impact on the power grid, improve the absorption of new energy generation, and are of great significance in power grid system backup, relieving peak load power supply pressure, and peak and frequency regulation.

[0039] (2) Energy storage containers used on the grid side mainly perform peak load regulation, frequency regulation, and grid congestion relief. They can achieve peak load shaving and valley filling of power loads, that is, charging the energy storage batteries when the power load is low and releasing the stored power during the peak load period, thereby achieving a balance between power production and consumption;

[0040] (3) Small energy storage cabinets used on the power consumption side, mainly for self-generation and self-use of electricity, peak-valley price difference arbitrage, capacity cost management and improving power supply reliability. According to different application scenarios, energy storage on the power consumption side can be divided into industrial and commercial energy storage cabinets, household energy storage devices, energy storage charging piles, etc., which are generally used in conjunction with distributed photovoltaics. Industrial and commercial users can use energy storage for valley-peak price difference arbitrage and capacity cost management. In the power market that implements peak-valley electricity prices, by charging the energy storage system at low electricity prices and discharging the energy storage system at high electricity prices, peak-valley electricity price difference arbitrage is achieved to reduce electricity costs. In addition, industrial enterprises that are subject to two-part electricity prices can use energy storage systems to store energy during low electricity consumption and discharge at peak loads, thereby reducing peak power and the maximum demand reported, and achieving the purpose of reducing capacity electricity charges. Household photovoltaic storage can improve the level of self-generation and self-use of electricity. Due to high electricity prices and poor power supply stability, the demand for household photovoltaic installations has been driven. Considering that photovoltaic power is generated during the day, and users generally have higher loads at night, energy storage can be configured to better utilize photovoltaic power, improve the level of self-generation and self-use, and reduce electricity costs. In addition, communication base stations, data centers and other fields need to configure energy storage for backup power.

[0041] See also Figure 1 , Figure 1 is a schematic diagram of the structure of an energy storage system according to an embodiment of the present disclosure, and Figure 1 The embodiment is described by taking the shared energy storage scenario on the generation / distribution side as an example, but the energy storage system 100 disclosed in the present invention is not limited to the energy storage scenario on the generation / distribution side.

[0042] The present disclosure provides an energy storage system, which includes: an energy storage device 110, a high-voltage cable 120, a first electric energy conversion device 130, and a second electric energy conversion device 140. In the case of power generation, the first electric energy conversion device 130 and the second electric energy conversion device 140 are used to convert other forms of energy into electric energy, which is connected to the high-voltage cable 120 and supplied to the power distribution network for use. When the power load is low and the first conversion device 130 and the second electric energy conversion device 140 generate excess power, the excess power is stored in the energy storage device 110, thereby reducing the wind and solar power abandonment rates and improving the problem of new energy power generation and consumption. When the power load is high, the power grid issues an instruction to transmit the power stored in the energy storage device 110 in conjunction with the high-voltage cable 120 in a grid-connected mode to the power consumption side, thereby providing peak load regulation, frequency regulation, standby and other services for the operation of the power grid, giving full play to the peak load regulation of the power grid, promoting peak load shaving and valley filling of the power grid, and alleviating the power supply pressure of the power grid.

[0043] Optionally, the first electric energy conversion device 130 and the second electric energy conversion device 140 can convert at least one of solar energy, light energy, wind energy, thermal energy, tidal energy, biomass energy and mechanical energy into electric energy.

[0044] The number of energy storage devices 110 can be multiple, and multiple energy storage devices 110 are connected in series or in parallel. Multiple energy storage devices 110 are supported and electrically connected by isolation plates (not shown). In this embodiment, "multiple" refers to two or more. An energy storage box can also be provided outside the energy storage device 110 to accommodate the energy storage device 110.

[0045] Optionally, the energy storage device 110 may include but is not limited to a battery cell, a battery balancing system, a battery pack, a battery system, etc. The actual application form of the energy storage device 110 provided in the embodiment of the present disclosure may be but is not limited to the listed products, and may also be other application forms. The embodiment of the present disclosure does not strictly limit the application form of the energy storage device 110. The embodiment of the present disclosure is only described by taking the energy storage device 110 as a battery cell as an example. When the energy storage device 110 is a battery cell, the energy storage device 110 may be at least one of a cylindrical battery, a square battery, etc.

[0046] In the energy storage system, large-screen monitoring can be used to summarize statistical data, display key data by category, implement an overview of operating information intentions, obtain time-sharing statistical revenue information, and optimize operating strategies.

[0047] In the monitoring screen of the energy storage system, the interface component is the basic element of the user interface, which is used for users to interact with the software or system. Various components can be designed to achieve corresponding functions. Components can include basic components, navigation components, input components, display components, feedback components, etc.

[0048] Among them, the basic components are the basic components of the view layer, which can include text Text, image Image, text input TextInput, button Button, loading progress LoadingProcess, etc. The Text component is used to display a piece of text information on the user interface, and can contain subcomponents Span; the Image component is used to render and display images, which can make the interface colorful; the TextInput component is used to input a single line of text and respond to input events; the Button component is used to respond to click operations and can contain subcomponents; the LoadingProcess component is used to display the loading progress.

[0049] Navigation components are used to guide users to browse and locate, helping users quickly find the information they need. Navigation components include navigation bars, tab bars, index bars, etc.

[0050] Input components are used for data input and support user selection and input operations, including radio buttons, check boxes, input boxes, etc.

[0051] Display components are used to display data content to help users understand information more clearly, including labels, lists, notification bars, etc.

[0052] Feedback components are used to provide feedback after user operations, informing users of operation results or page status, including Toast prompts, pop-up windows, etc.

[0053] In addition, user components can also be divided in other ways. For example, in QL Designer, eight types of interface visualization components are provided, namely: layout components, split components, button components, table item components, table item views, container components, input components, and display components. This disclosure does not make specific limitations on this.

[0054] Under the above system architecture, a method for generating a user interface layout is provided in an embodiment of the present disclosure, and the method can be executed by any electronic device with computing and processing capabilities, such as a user interface layout generating device, a server or a processor.

[0055] Figure 2 A flow chart of a method for generating a user interface layout in an embodiment of the present disclosure is shown as follows: Figure 2 As shown, the user interface layout generation method provided in the embodiment of the present disclosure includes the following steps:

[0056] S202: Generate multiple initial layouts, each initial layout includes multiple components, and each component has scores in multiple dimensions.

[0057] In one embodiment, the initial layout can be obtained by the user configuring corresponding values ​​for the attribute information of the components in each layout in the intelligent editor. Each initial layout can be composed of multiple components. For example, a layout includes a bar chart card, a carousel list card, etc. The position and attributes of the components are reasonably allocated according to the initial conditions to ensure the basic aesthetics and consistency of the initial layout. The attribute information of the component includes at least one of the position, size, style and color of the component. The relative position of the component in the layout can be determined through the attribute information of the component, and the attributes of the component itself can also be determined.

[0058] The component types and number of components in each initial layout can be determined according to actual needs. For example, the initial layout may include basic components, split components, button components, etc. The initial layout may also include basic components, input components, etc., and the present disclosure does not make specific limitations on this.

[0059] The above-mentioned multiple dimensions may include one or more of aesthetics, usability, and responsiveness. Each component has a score of multiple dimensions, including aesthetics, usability, responsiveness, and the like.

[0060] The aesthetic score of the component in the initial layout represents an initial aesthetic score of each component determined according to visual characteristics. Visual characteristics may include alignment, symmetry, color matching, etc. For example, a component that is centered and has consistent color and overall style has a higher aesthetic score.

[0061] The usability score of the component in the initial layout represents the initial usability score determined based on the ease of operation of the component and the friendliness of user interaction. For example, a button component placed in a position that is easy for users to click and has a clear label will have a high usability score.

[0062] The responsiveness score of a component in the initial layout represents the initial responsiveness score based on the component's adaptability to different devices and screen sizes. For example, a component that can maintain a good display effect on both mobile phones and desktop devices will have a high responsiveness score.

[0063] In one embodiment, the scoring method of the above-mentioned multiple dimensions can be determined according to the actual situation. For example, for the button component in the initial layout, the ratio between the area of ​​the button component and the screen area can be calculated, and the usability score can be determined according to the relationship between the ratio and the preset range. One preset range corresponds to one usability score; when the button component has a clear label, the usability score of the button component is 100 points, and when the button component has an unclear label or no label, the usability score of the button component is 50 points.

[0064] It should be noted that the above-mentioned method for determining the usability score is only an example provided to illustrate the calculation method, and it cannot be used as a limitation on the scope of protection of the present disclosure. The scoring method and scoring strategy for other dimensions can refer to the usability score without specific limitation.

[0065] S204: Determine the fitness scores of the initial layouts according to the scores of each component in multiple dimensions and the weights corresponding to the multiple dimensions.

[0066] In one embodiment, the weights corresponding to the multiple dimensions are determined according to the application scenario or user needs. The weights corresponding to the multiple dimensions will directly affect the fitness score of the target layout, and the values ​​of the weights corresponding to the multiple dimensions can be determined according to specific needs. For example, if the user is more concerned about aesthetics, the weight corresponding to aesthetics can be configured with a higher value, thereby selecting a layout with a higher aesthetic score in the candidate layout set. The sum of the weights corresponding to the multiple dimensions is 1.

[0067] In S204, the scores of multiple components in each initial layout in multiple dimensions may be weighted averaged to obtain the fitness score of the initial layout.

[0068] Assuming that there are n components in an initial layout, the aesthetic score of component i is recorded as The usability score is recorded as The adaptability score is recorded as The fitness score of this initial layout can be expressed as:

[0069]

[0070] Among them, α, β, γ are the weights of aesthetics, usability and responsiveness respectively, n is the total number of components in the initial layout, and F m 、F u 、F r These are the average scores of aesthetics, usability, and responsiveness for multiple components in the initial layout.

[0071] If an initial layout includes components A, B, and C, where component A Component B Component C According to formula 1, the responsiveness score of the layout can be obtained as:

[0072] When α=0.4, β=0.3, γ=0.3, F layout =0.4×85+0.3×89+0.3×86.3≈86.7.

[0073] S206: Process the multiple initial layouts according to the fitness scores to obtain multiple candidate layouts.

[0074] In one embodiment, multiple initial layouts may be adjusted using crossover operations, mutation operations, etc. according to the initial layouts and the corresponding fitness scores to generate new layouts, and the new layouts may be added to the candidate layout set as candidate layouts.

[0075] The candidate layout set may include multiple initial layouts generated in S202, and may also include new layouts generated by adjusting the initial layouts through crossover operations, mutation operations, etc.

[0076] It should be noted that after a new layout is generated through a crossover operation, a mutation operation, etc., the scores of each component in the new layout need to be adjusted, and the fitness score of the new layout needs to be recalculated based on the scores of the adjusted components.

[0077] The manner of adjusting the scores of the components in the new layout may be similar to the manner of determining the scores of the components in the initial layout in the aforementioned embodiment, and will not be described in detail here.

[0078] The number of candidate layouts in the candidate layout set can be determined according to actual conditions. It is worth noting that the process of generating a new layout can also be called an iterative process of the layout, with the goal of gradually increasing the fitness score of the layout.

[0079] S208: Determine a target layout according to the multiple candidate layouts, and generate a user interface according to the target layout.

[0080] In one embodiment, after multiple iterations, as the fitness score is optimized, a candidate layout that meets a preset condition may be selected from the candidate layout set as the target layout.

[0081] For example, the candidate layout with the highest fitness score in the candidate layout set is used as the target layout.

[0082] Alternatively, multiple candidate layouts in the candidate layout set may be sorted in descending order according to the fitness scores, and any one of the top m candidate layouts may be selected as the target layout, such as selecting a candidate layout in the top 5 as the target layout.

[0083] After the target layout is determined, the target layout is displayed on the terminal device used by the user to provide a user interface, thereby supporting the user's manual fine-tuning and real-time preview, providing an interactive interface to allow the user to adjust the layout according to their own preferences, and providing real-time feedback on the optimization results.

[0084] In an embodiment of the present disclosure, multiple initial layouts are generated, each initial layout includes multiple components, and each component has scores in multiple dimensions; the fitness scores of each initial layout are determined according to the scores of each component in the multiple dimensions and the weights corresponding to the multiple dimensions; the multiple initial layouts are processed according to the fitness scores to obtain multiple candidate layouts; the target layout is determined according to the multiple candidate layouts, and the user interface is generated according to the target layout. The present disclosure can realize dynamic optimization of the layout of the intelligent editor, and the adaptability of the page layout can be improved through multi-dimensional scoring.

[0085] Figure 3 A flow chart of a method for determining a target layout in an embodiment of the present disclosure is shown. Figure 3 As shown, in one embodiment, determining the target layout according to the multiple candidate layouts in S208 above includes:

[0086] S302, determining the fitness score of each candidate layout according to the components of each candidate layout and the scores of the components corresponding to multiple dimensions;

[0087] S304: Determine the target layout according to the fitness score of each candidate layout.

[0088] In one embodiment, the scores corresponding to the components in each candidate layout in multiple dimensions need to be re-determined, and the fitness scores of each candidate layout are calculated according to Formula 1. The calculation method of the fitness scores of each candidate layout is not repeated here.

[0089] It should be noted that when processing multiple initial layouts to generate candidate layouts, the attribute parameters of some components in the candidate layouts may change. In this case, it is necessary to re-evaluate the scores of multiple dimensions of the components with changed attributes. The evaluation method is the same as the evaluation method of the component scores in the initial layout.

[0090] In one embodiment, when the number of candidate layouts in the candidate layout set reaches a preset number, layout optimization is no longer performed, and a target layout is selected from the candidate layout set; or, when the number of candidate layouts in the candidate layout set reaches a preset number and the fitness score of the candidate layout exceeds a preset score, layout optimization is no longer performed, and a target layout is selected from the candidate layout set.

[0091] In the disclosed embodiments, a data basis is provided for layout optimization through multi-dimensional scoring and corresponding weights. By processing the initial layout to generate new candidate layouts, possible better layout combinations can be continuously explored, thereby screening the target layout that meets user needs from the candidate layout set and improving the efficiency of layout recommendation.

[0092] Figure 4 Another target layout determination method flow chart in the embodiment of the present disclosure is shown. Figure 3 Based on the embodiment, the above S304 is further refined into S3042 to limit the determination method of the target layout. Figure 4 As shown, in one embodiment, the above S304 determines the target layout according to the fitness score of each candidate layout, including:

[0093] S3042. Determine the candidate layout corresponding to the maximum fitness score as the target layout.

[0094] In one embodiment, n initial layouts can be generated, and the n initial layouts can be used to construct a candidate layout set, and the candidate layout set can record layout attribute information and corresponding fitness scores. When each new layout is generated, the fitness score of the new layout can be calculated, and the fitness score of the new layout can be compared with the fitness scores of each candidate layout in the candidate layout set. If the fitness score of the new layout is greater than the fitness score of the candidate layout, the attribute information and the corresponding fitness score of the new layout will replace the candidate layout with the smallest fitness score in the candidate layout set; if the fitness score of the new layout is less than the fitness score of the candidate layout, no replacement is required; when the fitness score of the new layout is equal to the fitness score of the candidate layout, the attribute information and the corresponding fitness score of the new layout can be added to the candidate layout set.

[0095] The multiple candidate layouts in the candidate layout set are sorted in descending order of fitness scores, and the candidate layout corresponding to the maximum fitness score is used as the target layout; the multiple candidate layouts can also be sorted in ascending order of fitness scores to determine the target layout.

[0096] In the disclosed embodiment, the selected target layout is the layout with the highest comprehensive fitness score, ensuring that the target layout not only performs well in one aspect but also achieves a balance in the overall score, meets the design goals, and improves the effectiveness of the layout recommendation.

[0097] Figure 5 A flow chart of another target layout determination method in an embodiment of the present disclosure is shown. Figure 3 Based on the embodiment, S304 is further refined into S3044-S3048 to define another way of determining the target layout. Figure 5 As shown, the above S304 determines the target layout according to the fitness score of each candidate layout, including:

[0098] S3044, determining the dominance relationship of each candidate layout according to the fitness score of each candidate layout;

[0099] S3046. Construct a Pareto optimal solution set according to the dominance relationship of each candidate layout, wherein the Pareto optimal solution set includes all layouts among the multiple candidate layouts that are not dominated by other layouts;

[0100] S3048. Determine the target layout from the Pareto optimal solution set according to the weights corresponding to the multiple dimensions.

[0101] A candidate layout set S is defined, and the candidate layout set S includes all possible layout solutions, such as the multiple candidate layouts in the aforementioned embodiment.

[0102] For a candidate layout x∈S, calculate the fitness score F of the candidate layout x layout (x):

[0103] F layout (x)=(F m (x),F u (x),F r (x)) (Formula 2)

[0104] Among them, F m (x),F u (x),F r (x) are the fitness scores of candidate layout x in the three dimensions of aesthetics, usability, and responsiveness.

[0105] According to the fitness score F of each candidate layout x layout (x) Determine the dominance relationship. For two candidate layouts x and y, if candidate layout x is better than candidate layout y in at least one scoring dimension and is not inferior to candidate layout y in all other dimensions, then candidate layout x is said to dominate candidate layout y.

[0106] Mathematically, the condition for candidate layout x to dominate candidate layout y is:

[0107]

[0108] in, It is a universal quantifier, which indicates the designation or description of all or any one of a class of things. It represents the existence of quantifiers, m, u, and r are the dimension indicators of aesthetics, usability, and responsiveness, respectively.

[0109] After determining the dominance relationship of the candidate layouts, construct the Pareto optimal solution set p optimal , where there is no dominance relationship between all candidate layouts in the Pareto optimal solution set. The Pareto optimal solution set can be expressed as in, The symbol does not exist.

[0110] A set of balanced solutions is formed in the Pareto optimal solution set, representing the optimal compromise layout scheme in different dimensions (such as aesthetics, usability, and responsiveness).

[0111] In the Pareto optimal solution set, select the candidate layout that meets the current demand weight. For example, select the candidate layout with the highest weight corresponding to multiple dimensions as the target layout; or select the candidate layout with the highest weight and the highest dimension score as the target layout.

[0112] For example, when the user wants to assign a higher weight to aesthetics, the layout with a higher aesthetics score in the candidate layout set is selected as the target layout.

[0113] Assume that in the following scenario, when performing smart editor layout optimization, 4 candidate layouts are obtained. Each candidate layout includes scores in three dimensions, namely aesthetics Fm, usability Fu, and responsiveness Fr. Among them, aesthetics measures the visual aesthetics of the candidate layout, usability measures the ease of use of the candidate layout, and responsiveness measures the adaptability of the candidate layout on different devices.

[0114] The scores of the four candidate layouts are as follows:

[0115] Candidate layout A: Fm(A)=85, Fu(A)=70, Fr(A)=80;

[0116] Candidate layout B: Fm(B)=80, Fu(B)=75, Fr(B)=70;

[0117] Candidate layout C: Fm(C)=90, Fu(C)=65, Fr(C)=75;

[0118] Candidate layout D: Fm(D)=70, Fu(D)=85, Fr(D)=85.

[0119] The dominance relationship between candidate layout A and other candidate layouts is as follows:

[0120] For candidate layout A and candidate layout B, in terms of aesthetics, Fm(A)>Fm(B), in terms of usability, Fu(A)<Fu(B), and in terms of responsiveness, Fr(A)>Fr(B). It can be seen that candidate layout A is better than candidate layout B in two dimensions (aesthetics and responsiveness), and slightly worse than candidate layout B in usability. Therefore, candidate layout A does not dominate candidate layout B, and candidate layout B does not dominate candidate layout A.

[0121] For candidate layout A and candidate layout C, in terms of aesthetics, Fm(A) < Fm(C), in terms of usability, Fu(A) > Fu(C), and in terms of responsiveness, Fr(A) > Fr(C). It can be seen that candidate layout A is superior to candidate layout C in two dimensions (usability and responsiveness), and is slightly inferior to candidate layout C in aesthetics. Therefore, candidate layout A does not dominate candidate layout C, and candidate layout C does not dominate candidate layout A.

[0122] For candidate layout A and candidate layout D, in terms of aesthetics, Fm(A)>Fm(D), in terms of usability, Fu(A)<Fu(D), and in terms of responsiveness, Fr(A)<Fr(D). It can be seen that candidate layout A is better than candidate layout D in terms of aesthetics, but slightly worse than candidate layout D in terms of usability and responsiveness. Therefore, candidate layout A does not dominate candidate layout D, and candidate layout D does not dominate candidate layout A.

[0123] Through the above comparison, we can draw the following conclusions: Candidate layout A is not dominated by other candidate layouts, nor does it dominate other candidate layouts; Candidate layout B is surpassed by some candidate layouts in some dimensions, but is not completely surpassed in all dimensions; Candidate layout C is not dominated by other candidate layouts, nor does it dominate other candidate layouts; Candidate layout D is not dominated by other candidate layouts, nor does it dominate other candidate layouts. Therefore, the Pareto optimal solution set contains candidate layouts A to D.

[0124] For candidate layout A: it is very aesthetically pleasing, has fair responsiveness, and is moderately easy to use, so it may be the best choice in some specific scenarios.

[0125] For candidate layout B: the usability is good, the responsiveness is average, and the aesthetics is slightly inferior, but it may be the best under a specific weight combination.

[0126] For candidate layout C: the aesthetics is very good, the responsiveness is fair, but the usability is relatively poor. It may be suitable for scenarios with extremely high requirements for aesthetics.

[0127] For candidate layout D: the usability and responsiveness scores are the highest, but the aesthetics are poor, which is suitable for scenarios that require high usability and responsiveness.

[0128] In actual intelligent editor layout optimization, it is often necessary to select the target layout from the Pareto optimal solution set according to specific needs. The combination, crossover and mutation operations of different layouts will generate a large number of candidate layouts. By scoring and comparing the candidate layouts, a Pareto optimal solution set is constructed, and then the target combination that meets the current needs is selected from a small number of candidate layouts in the Pareto optimal solution set.

[0129] For example, the candidate layout set includes 100 candidate layouts, of which 5 candidate layouts constitute a Pareto optimal solution set. These layouts have no obvious disadvantages in terms of aesthetics, usability, and responsiveness, and are suitable for being recommended to users as target layouts so that users can choose from the recommended target layouts.

[0130] In the disclosed embodiment, the dominance relationship of the candidate layouts is determined according to the fitness scores of the candidate layouts, and a Pareto optimal solution set is constructed, and the target layout is determined based on the Pareto optimal solution set, thereby improving the layout optimization efficiency.

[0131] Figure 6 Another method flow chart of generating a user interface layout in an embodiment of the present disclosure is shown. Figure 2 Based on the embodiment, S206 is further refined into S2062 to limit the construction method of the candidate layout set. Figure 6 As shown, the above S206 processes multiple initial layouts according to the fitness scores to obtain multiple candidate layouts, including:

[0132] S2062: Based on the fitness score, a preset optimization algorithm is used to process the multiple initial layouts to obtain multiple candidate layouts.

[0133] In one embodiment, a preset optimization algorithm is used to process the initial layout to obtain multiple candidate layouts. The preset optimization algorithm may include one or more of a genetic algorithm, a particle swarm optimization algorithm, an ant colony algorithm, an artificial neural network, and a Bayesian optimization algorithm.

[0134] The following description will be made by taking the preset optimization algorithm as a genetic algorithm as an example.

[0135] In one embodiment, the preset optimization algorithm includes a genetic algorithm, and the processing of the multiple initial layouts includes individual selection operations, crossover operations, and mutation operations. The above S2062 uses the preset optimization algorithm to process the multiple initial layouts based on the fitness score to obtain multiple candidate layouts, including:

[0136] An individual selection operation is performed according to the fitness score of each initial layout to determine multiple parent layouts, and the individual selection operation is used to screen a preset number of parent layouts whose selection probability is greater than a preset probability threshold from the multiple initial layouts, wherein the selection probability of the initial layout is obtained by the fitness score of each initial layout;

[0137] Perform crossover operations and / or mutation operations on multiple parent layouts to obtain multiple child layouts;

[0138] According to the multiple parent layouts and the multiple child layouts, multiple candidate layouts are obtained.

[0139] In the genetic algorithm, each layout (initial layout and candidate layout) is represented as a chromosome. The genes in the chromosome represent the specific properties of the component, which include position, size, style, color, etc.

[0140] Assume that the population size corresponding to the generated initial layout is N, and the length of each chromosome is L, that is, the generated initial population size is N=5, and each chromosome contains L=3 genes (or components). Each layout includes component type, position, size, and color attributes. The initial population example is as follows:

[0141] Initial layout 1: [(bar chart card, (10, 20), (100, 200), blue), (carousel list card, (120, 20), (100, 200), green), (bar chart card, (230, 20), (100, 200), blue)];

[0142] Initial layout 2: [(carousel list card, (10,240), (100,200), green), (bar chart card, (120,240), (100,200), blue), (carousel list card, (230,240), (100,200), green)].

[0143] The fitness scores of initial layout 1 and initial layout 2 are calculated by formula 2.

[0144] At least two initial layouts with high fitness scores are selected as parent layouts by using one of a roulette wheel selection method, a tournament selection method, or a ranking selection method.

[0145] For example, the roulette wheel selection method is used to determine the parent layout, and the selection probability P of selecting the i-th initial layout is calculated. i , expressed using Formula 4:

[0146]

[0147] Where Fi is the fitness score of the i-th initial layout, and N is the total number of initial layouts.

[0148] The above preset number and preset probability threshold can be determined according to actual conditions, and the present disclosure does not make specific limitations. For example, after calculating the selection probability of each initial layout, the selection probability of each layout is sorted in descending order, and the first five initial layouts with the largest selection probability are determined as the parent layout.

[0149] Table 1 shows the fitness scores of all initial layouts in the initial population and the calculated selection probabilities. The two initial layouts with the highest fitness scores can be selected as parent layouts.

[0150] Table 1

[0151] Initial layout 1 2 3 4 5 Fi 0.835 0.75 0.8 0.65 0.9 Pi 0.2 0.18 0.19 0.15 0.21

[0152] It can be seen from Table 1 that the initial layout 1 and the initial layout 5 have the highest fitness scores, and the initial layout 1 and the initial layout 5 can be used as parent layouts.

[0153] It should be noted that the number of parent layouts can be determined according to actual needs, and this disclosure does not make any specific limitation on this.

[0154] Perform crossover operations on multiple selected parent layouts to generate child layouts. The crossover operation can include single-point crossover and multi-point crossover.

[0155] For example, for a single-point crossover, the second gene position in the parental layout can be selected for crossover.

[0156] Parent layout 1 = [(bar chart card, (10, 20), (100, 200), blue), (carousel list card, (120, 20), (100, 200), green), (bar chart card, (230, 20), (100, 200), blue)];

[0157] Parent layout 2 = [(carousel list card, (10, 240), (100, 200), green), (bar chart card, (120, 240), (100, 200), blue), (carousel list card, (230, 240), (100, 200), green)].

[0158] The offspring layout after single-point crossover is:

[0159] Child layout 1: [(bar chart card, (10, 20), (100, 200), blue), (bar chart card, (120, 240), (100, 200), blue), (bar chart card, (230, 20), (100, 200), blue)];

[0160] Sub-layout 2: [(Carousel List Card, (10, 240), (100, 200), green), (Carousel List Card, (120, 20), (100, 200), green), (Carousel List Card, (230, 240), (100, 200), green)].

[0161] For the mutation operation, at least part of the parent layout and the child layout may be randomly mutated to increase the diversity of the population and avoid falling into a local optimum.

[0162] The mutation operation is used to randomly adjust the position or properties of some components.

[0163] The mutated component = the original component + Δ, where Δ is the mutation adjustment amount, which is a smaller random number.

[0164] Assume that the variation adjustment amount Δ is: position variation Δ=5.

[0165] Exemplarily, a mutation operation is performed on the child layout 1 to adjust the position of the first component to obtain the mutated layout:

[0166] Child layout 1: [(bar chart card, (10, 20), (100, 200), blue), (bar chart card, (120, 240), (100, 200), blue), (bar chart card, (230, 20), (100, 200), blue)];

[0167] Layout after mutation: [(bar chart card, (15, 25), (100, 200), blue), (bar chart card, (120, 240), (100, 200), blue), (bar chart card, (230, 20), (100, 200), blue)].

[0168] The mutation operation introduces subtle random changes that affect the fitness score of the layout. The mutation operation can be a random adjustment of the position, size, color and other attributes of the component, which may cause a shift in the aesthetics, usability and responsiveness scores.

[0169] The variation score offset formula is expressed in Formula 5:

[0170] ΔF layout =ΔF m α+ΔF u β+ΔF r γ (Formula 5)

[0171] Where, ΔF m , ΔF u , ΔF r They are the changes in the aesthetics, usability and responsiveness scores of the layout after mutation.

[0172] For example, the fitness score of the offspring layout 1 is 82. After the above offspring layout 1 mutates, the size of a component increases, resulting in a decrease of 1 point in aesthetics score, an increase of 0.5 points in usability score, and an unchanged responsiveness score. Then the fitness score of the offspring layout 1 after mutation changes to: ΔF layout = -0.25. Therefore, the fitness score of the mutated offspring layout 1 drops from 82 to 81.75.

[0173] It should be noted that the order of the crossover operation and the mutation operation, as well as the corresponding operation methods, etc. can be determined according to actual needs, and the present disclosure does not make specific limitations on this.

[0174] The multiple child layouts and the multiple parent layouts obtained through the crossover operation and the mutation operation are determined as multiple candidate layouts, and the multiple candidate layouts constitute a candidate layout set.

[0175] In the disclosed embodiments, the self-learning capability of preset optimization algorithms such as genetic algorithms is used to achieve dynamic optimization of intelligent layout, provide a layout solution that better meets user needs, and improve the accuracy and personalization of layout recommendations.

[0176] Figure 7 A flow chart of another method for generating a user interface layout according to an embodiment of the present disclosure is shown. Figure 6 Based on the embodiment, S2064 is added after S2062 to limit the way of optimizing the candidate layout set by the simulated annealing algorithm. Figure 7 As shown, after S2062, the method further includes:

[0177] S2064, optimizing the multiple candidate layouts using a simulated annealing algorithm to obtain multiple optimized candidate layouts;

[0178] The above S208 determines the target layout according to the multiple candidate layouts, including:

[0179] S2082: Determine a target layout according to the optimized multiple candidate layouts.

[0180] The simulated annealing algorithm can control the amplitude of the mutation operation by gradually lowering the "temperature" in multiple mutation operations to avoid falling into the local optimum. The acceptance probability in the simulated annealing algorithm is used to decide whether to accept the mutation result of the crossover to avoid falling into the local optimal solution.

[0181] Select a layout from the currently optimized population as the layout to be optimized, gradually lower the temperature and perform neighborhood search. The acceptance function is expressed as:

[0182]

[0183] Among them, ΔF is the difference in fitness scores between the current layout and the mutated layout, and T is the current temperature. The formula for gradually decreasing temperature is expressed as:

[0184] T new =δ×T old (Formula 7)

[0185] Wherein, δ is the cooling coefficient, 0.8≤δ≤0.99.

[0186] Assuming T = 0.5, the fitness score of the layout after mutation decreases by 1 point due to mutation, then the value of the acceptance function is:

[0187] Since P>1, even if the fitness score of the layout decreases after mutation, the population diversity can still be increased within the acceptable range of the mutation result.

[0188] The simulated annealing algorithm can gradually focus on a better layout solution while maintaining a certain degree of randomness, avoiding falling into local optimality.

[0189] In the disclosed embodiments, the self-learning capabilities of the genetic algorithm and the simulated annealing algorithm are combined to achieve dynamic optimization of the intelligent layout, provide a layout solution that better meets user needs, and improve the accuracy and personalization of layout recommendations.

[0190] In one embodiment, generating a user interface according to the target layout in S208 above includes: obtaining adjustment information of the target layout by the user; and generating a user interface according to the attribute information and adjustment information of the target layout.

[0191] In a feasible implementation, user input data is obtained, and the user input data may include attribute information of components in the initial layout, etc. The user input data is analyzed, the data type is identified, a chart recommendation is generated, and the optimal icon type is recommended to the user. The user selects a chart, and after the user confirms or adjusts the recommended chart, a chart is generated based on the component attribute information and other data adjusted by the user for the target layout or the data of the target layout confirmed by the user.

[0192] The attribute information of the target layout includes at least one of the position, size, style, and color of the multiple components in the target layout, and is used to determine the positions of the multiple components in the target layout, as well as the attributes of the multiple components themselves.

[0193] When generating a user interface, user data and model data can be synchronously stored in the database for subsequent calls.

[0194] In the embodiments of the present disclosure, the present disclosure can automatically adjust the layout and provide a user interface to support manual fine-tuning and real-time preview by users. An interactive interface is provided to allow users to adjust the layout according to their own preferences and provide real-time feedback on the optimization results, thereby improving the user experience. By introducing a real-time feedback mechanism, the user's evaluation of the layout is collected in real time to improve the recommendation effect.

[0195] Based on the same inventive concept, the present disclosure also provides a user interface layout generation device, as described in the following embodiments. Since the principle of solving the problem in the device embodiment is similar to that in the above method embodiment, the implementation of the device embodiment can refer to the implementation of the above method embodiment, and the repeated parts will not be repeated.

[0196] Figure 8A schematic diagram of a user interface layout generating device according to an embodiment of the present disclosure is shown. Figure 8 As shown, the apparatus includes a layout generating module 810 , a score determining module 820 , a set building module 830 and a layout determining module 840 .

[0197] The layout generation module 810 is used to generate multiple initial layouts, each initial layout includes multiple components, and each component has scores in multiple dimensions;

[0198] A score determination module 820, for determining the fitness score of each initial layout according to the scores of each component in multiple dimensions and the weights corresponding to the multiple dimensions;

[0199] A set construction module 830 is used to process the multiple initial layouts according to the fitness scores to obtain multiple candidate layouts;

[0200] The layout determination module 840 is used to determine a target layout according to a plurality of candidate layouts, and generate a user interface according to the target layout.

[0201] It should be noted that the above-mentioned layout generation module 810, score determination module 820, set construction module 830 and layout determination module 840 correspond to S202 to S208 in the method embodiment, and the examples and application scenarios implemented by the above-mentioned modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned method embodiment. It should be noted that the above-mentioned modules as part of the device can be executed in a computer system such as a set of computer executable instructions.

[0202] In one embodiment, the layout determination module 840 is used to determine the fitness score of each candidate layout based on the components of each candidate layout and the scores corresponding to the components in multiple dimensions; determine the dominance relationship of each candidate layout based on the fitness score of each candidate layout; construct a Pareto optimal solution set based on the dominance relationship of each candidate layout, wherein the Pareto optimal solution set includes all layouts in the multiple candidate layouts that are not dominated by other layouts; determine the target layout from the Pareto optimal solution set based on the weights corresponding to the multiple dimensions, wherein the weights corresponding to the multiple dimensions are determined according to the application scenario or user needs.

[0203] In one embodiment, the processing of the multiple initial layouts includes individual selection operations, crossover operations, and mutation operations; wherein the set construction module 830 is used to perform individual selection operations on the multiple initial layouts according to the fitness scores of the respective initial layouts to determine multiple parent layouts, the individual selection operation being used to screen a preset number of parent layouts whose selection probabilities are greater than a preset probability threshold from the multiple initial layouts, wherein the selection probability of the initial layouts is obtained by the fitness scores of the respective initial layouts; crossover operations and / or mutation operations are performed on the multiple parent layouts to obtain multiple child layouts; and multiple candidate layouts are obtained based on the multiple parent layouts and the multiple child layouts.

[0204] In one embodiment, the set construction module 830 is further used to optimize the candidate layout set using a simulated annealing algorithm to obtain multiple optimized candidate layouts after processing multiple initial layouts according to fitness scores. The layout determination module 840 is further used to determine the target layout based on the multiple optimized candidate layouts.

[0205] In one embodiment, the score determination module 820 is used to perform weighted averaging of scores of multiple components in each initial layout in multiple dimensions to obtain a fitness score of the initial layout.

[0206] In one embodiment, the layout determination module 840 is also used to obtain the user's adjustment information on the target layout; generate a user interface based on the attribute information and adjustment information of the target layout, and the attribute information of the target layout includes at least one of the position, size, style, and color of multiple components in the target layout.

[0207] In an embodiment of the present disclosure, multiple initial layouts are generated, each initial layout includes multiple components, and each component has scores in multiple dimensions; the fitness scores of each initial layout are determined according to the scores of each component in the multiple dimensions and the weights corresponding to the multiple dimensions; the multiple initial layouts are processed according to the fitness scores to obtain multiple candidate layouts; the target layout is determined according to the multiple candidate layouts, and the user interface is generated according to the target layout. The present disclosure can realize dynamic optimization of the layout of the intelligent editor, and the adaptability of the page layout can be improved through multi-dimensional scoring.

[0208] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0209] Refer to the following Fig. 9The electronic device 900 according to this embodiment of the present disclosure is described. Fig. 9 The electronic device 900 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0210] like Fig. 9 As shown, the electronic device 900 is in the form of a general computing device. The components of the electronic device 900 may include but are not limited to: at least one processing unit 910, at least one storage unit 920, and a bus 930 connecting different system components (including the storage unit 920 and the processing unit 910).

[0211] The storage unit stores a program code, and the program code can be executed by the processing unit 910, so that the processing unit 910 executes the steps described in the "Exemplary Method" section of this specification according to various exemplary embodiments of the present disclosure. For example, the processing unit 910 can execute the following steps of the above method embodiment: generate multiple initial layouts, each initial layout includes multiple components, and each component has scores in multiple dimensions; determine the fitness scores of each initial layout according to the scores of each component in multiple dimensions and the weights corresponding to the multiple dimensions; process the multiple initial layouts according to the fitness scores to obtain multiple candidate layouts; determine the target layout according to the multiple candidate layouts, and generate a user interface according to the target layout.

[0212] The storage unit 920 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 9201 and / or a cache storage unit 9202 , and may further include a read-only storage unit (ROM) 9203 .

[0213] The storage unit 920 may also include a program / utility 9204 having a set (at least one) of program modules 9205, such program modules 9205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0214] Bus 930 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0215] The electronic device 900 may also communicate with one or more external devices 940 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 900, and / or may communicate with any device that enables the electronic device 900 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 950. Furthermore, the electronic device 900 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 960. As shown, the network adapter 960 communicates with other modules of the electronic device 900 via a bus 930. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0216] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0217] In particular, according to an embodiment of the present disclosure, the process described in the above reference flow chart may be implemented as a computer program product, which includes: a computer program, which implements the above-mentioned battery cell capacity calibration method when executed by a processor.

[0218] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, which may be a readable signal medium or a readable storage medium. In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary implementations of the present disclosure described in the above “Exemplary Method” section of this specification.

[0219] More specific examples of computer-readable storage media in the present disclosure may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0220] In the present disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, wherein a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0221] Alternatively, the program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0222] In a specific implementation, the program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0223] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0224] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0225] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0226] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims

1. A method for generating a user interface layout, characterized in that: include: Generate multiple initial layouts, each of the initial layouts includes multiple components, and each of the components has scores in multiple dimensions; Determining the fitness score of each of the initial layouts according to the scores of each of the components in the multiple dimensions and the weights corresponding to the multiple dimensions; Processing the multiple initial layouts according to the fitness scores to obtain multiple candidate layouts; A target layout is determined according to the multiple candidate layouts, and the user interface is generated according to the target layout.

2. The method for generating a user interface layout according to claim 1, characterized in that: The determining a target layout according to the multiple candidate layouts includes: Determining the fitness scores of the candidate layouts according to the components of the candidate layouts and the scores of the components in multiple dimensions; Determining the dominance relationship of each candidate layout according to the fitness score of each candidate layout; Constructing a Pareto optimal solution set according to the dominance relationship of each candidate layout, wherein the Pareto optimal solution set includes all layouts among the multiple candidate layouts that are not dominated by other layouts; The target layout is determined from the Pareto optimal solution set according to the weights corresponding to the multiple dimensions, wherein the weights corresponding to the multiple dimensions are determined according to application scenarios or user needs.

3. The method for generating a user interface layout according to claim 1, characterized in that: The processing of the multiple initial layouts includes individual selection operation, crossover operation and mutation operation; The processing of the multiple initial layouts according to the fitness scores to obtain multiple candidate layouts includes: performing an individual selection operation on the multiple initial layouts according to the fitness scores of the respective initial layouts to determine multiple parent layouts, wherein the individual selection operation is used to screen a preset number of parent layouts having a selection probability greater than a preset probability threshold from the multiple initial layouts, wherein the selection probability of the initial layout is obtained according to the fitness scores of the respective initial layouts; Performing a crossover operation and / or a mutation operation on the multiple parent layouts to obtain multiple child layouts; The plurality of candidate layouts are obtained according to the plurality of parent layouts and the plurality of child layouts.

4. The method for generating a user interface layout according to claim 3, characterized in that: After the multiple initial layouts are processed according to the fitness scores to obtain multiple candidate layouts, the method further includes: Using a simulated annealing algorithm to optimize the multiple candidate layouts to obtain multiple optimized candidate layouts; The determining a target layout according to the multiple candidate layouts includes: The target layout is determined according to the optimized multiple candidate layouts.

5. The method for generating a user interface layout according to claim 1, characterized in that: Determining the fitness scores of the respective initial layouts according to the scores of each component in the multiple dimensions and the weights corresponding to the multiple dimensions includes: The scores of the multiple components in each of the initial layouts in multiple dimensions are weighted averaged to obtain a fitness score of the initial layout.

6. The method for generating a user interface layout according to claim 1, characterized in that: The generating the user interface according to the target layout includes: Obtaining adjustment information of the target layout by the user; The user interface is generated according to the attribute information of the target layout and the adjustment information, wherein the attribute information of the target layout includes at least one of the position, size, style, and color of multiple components in the target layout.

7. A user interface layout generating device, characterized in that: include: A layout generation module, used to generate multiple initial layouts, each of which includes multiple components, and each of which has scores in multiple dimensions; A score determination module, used to determine the fitness score of each of the initial layouts according to the scores of each of the components in multiple dimensions and the weights corresponding to the multiple dimensions; A set building module, used for processing the multiple initial layouts according to fitness scores to obtain multiple candidate layouts; The layout determination module is used to determine a target layout according to the multiple candidate layouts, and generate the user interface according to the target layout.

8. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to execute the user interface layout generating method according to any one of claims 1 to 6 by executing the executable instructions.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for generating a user interface layout according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product includes a computer program or computer instructions, and the computer program or the computer instructions are loaded and executed by a processor to enable a computer to implement the user interface layout generating method according to any one of claims 1 to 6.

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