Resource allocation method and system for virtual game scene

Abstract

The invention discloses a resource allocation method and system for a virtual game scene, and relates to the technical field of resource allocation and data processing. According to the method, the player behavior data and the resource configuration data are regularly collected and encrypted, so that the security and privacy of data processing are ensured, the association model between the resource configuration and the game indexes is established by utilizing the data and combining the preset revenue and fairness indexes, and the model can predict the influence of the resource configuration on the game indexes, so that the user experience is improved. According to the technical scheme, the putting strategy of the resources and props in the game is optimized through the data analysis and machine learning technology, so that the preset fairness and profit conditions are met, the rationality of resource allocation is improved, and the fairness of game experience is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of resource configuration and data processing, and in particular to a resource configuration method and system for a virtual game scene. Background Art

[0002] In virtual games, the reasonable allocation of virtual resources and the placement of virtual props are important factors affecting the player's gaming experience and game revenue. The existing technology lacks a reasonable strategy to ensure fairness and profitability when allocating virtual resources. At the same time, the efficiency is low when generating and moving virtual props, which affects the user experience. Summary of the invention

[0003] The purpose of the present invention is to provide a resource allocation method and system for a virtual game scene, which solves the fairness and profitability issues of resource and prop placement in virtual games through refined data analysis and real-time adjustment of resource allocation strategies, optimizes usage efficiency, and enhances player experience.

[0004] The purpose of the present invention can be achieved through the following technical solutions: The present application provides a method for configuring resources of a virtual game scene, comprising the following steps: Regularly collect resource configuration data and player behavior data in virtual games, encrypt the collected data, and then transmit it to the data processing platform for pre-processing and storage; Analyze and obtain the preset conditions that the profitability index and fairness index of the virtual game need to meet based on the encrypted data, and then determine the amount of virtual resources in the task-based game strategy in the virtual game; According to the amount of investment, virtual resources are invested in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions; In the virtual scene, by responding to the player's two-dimensional map opening instruction, a two-dimensional map corresponding to the virtual scene is displayed; by responding to the player's target virtual prop generation instruction, the first position set by the player in the two-dimensional map and the type of the target virtual prop are determined; During the process of allocating virtual resources and delivering virtual props, the allocation strategy is adjusted in real time, and then invalid resources and props are delivered to players who have met the conditions, so as to optimize the efficiency of resource and prop usage; By collecting all player behavior data, generating a player behavior data set based on the behavior data, and combining the information on the types and quantities of configured resources and the types and quantities of delivered props, a player resource satisfaction list is obtained; Use decision tree algorithms to build models, set resource and item delivery thresholds, and use supervised machine learning models to determine whether to stop delivering resources and items to specific players; Based on the player's resource prop demand labels and the quantity obtained, the gradient boosting decision tree GBDT algorithm is used to predict and optimize the delivery of resource props. Then, a time series prediction model is established to predict the consumption trend of resources and props and adjust the delivery strategy. The isolation forest algorithm is used to eliminate abnormal player data, determine the resource prop delivery list, and perform actual resource and prop delivery operations according to the preset virtual currency threshold and exchange rules.

[0005] Furthermore, resource configuration data and player behavior data in virtual games are collected regularly, the collected data is encrypted, and then transmitted to the data processing platform for preprocessing and storage, specifically including: According to a preset time interval, the virtual game data collection program is periodically triggered to collect resource configuration data and player behavior data in the virtual game, and the collected resource configuration data and player behavior data are encrypted using an asymmetric encryption algorithm to obtain encrypted data; The encrypted resource configuration data and player behavior data are transmitted to the data processing platform through a secure channel. In the data processing platform, the encrypted data is decrypted using a decryption algorithm that matches the encryption algorithm to obtain the original resource configuration data and player behavior data; The decrypted resource configuration data and player behavior data are preprocessed by data cleaning and data conversion to obtain standardized data. The preprocessed resource configuration data and player behavior data are persistently stored by using distributed storage technology.

[0006] Further, after determining the amount of virtual resources to be put into the task-based game strategy in the virtual game according to the resource configuration data and the preset indicator conditions, the following steps are specifically included: Obtain multi-dimensional indicator data related to profitability and fairness in virtual games, and determine whether the current indicators meet the preset conditions based on the preset profitability and fairness target thresholds; Through machine learning algorithms, historical resource allocation data and corresponding profitability and fairness index data are trained to establish a correlation model between resource allocation and indicators. Based on the current resource allocation situation, the corresponding profitability and fairness index values ​​are predicted. When the predicted index value does not meet the preset conditions, the resource allocation plan is iteratively optimized through the optimization algorithm to obtain the optimized resource allocation plan; According to the optimized resource allocation plan, determine the delivery amount and allocation ratio of each type of virtual resources in different task-based game strategies, and make dynamic adjustments based on feedback data; then build a life cycle management mechanism for virtual resources to dynamically adjust the resource generation speed and recycling mechanism.

[0007] Furthermore, according to the amount of investment, virtual resources are invested in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions, including: Obtain historical data of task-based games, determine target optimization values ​​of profitability and fairness indicators based on preset conditions, and use machine learning algorithms to establish a correlation model between virtual resource delivery and profitability and fairness indicators; Through the association model, the changes in profitability indicators and fairness indicators under different virtual resource delivery amounts are predicted. When the predicted indicator changes meet the preset conditions, the corresponding virtual resource delivery amounts are output as candidate optimization values. The amount of delivery after comprehensive evaluation is selected from the candidate optimization values ​​as the basis for adjusting the game strategy, and then the optimized virtual resource delivery amount is applied to the task-based game, and resource allocation is dynamically adjusted to make the game's profitability and fairness indicators meet the expected requirements.

[0008] Further, by responding to the player's two-dimensional map opening instruction, a two-dimensional map corresponding to the virtual scene is displayed; by responding to the player's target virtual prop generation instruction, the first position set by the player in the two-dimensional map and the type of the target virtual prop are determined, specifically including: According to the player's map instruction, the scene map of the current virtual scene pre-established in the storage device is obtained. When there is no scene map of the virtual scene, the construction process is triggered to establish a two-dimensional top view according to the scene model; by obtaining the player's position, the player's three-dimensional coordinate information is calculated through the spatial coordinate system of the game engine and mapped to the scene map to form corresponding points; According to the attribute data of each game object on the scene map, the updated marked scene is obtained after data labeling, and the multi-scale edge detection algorithm is applied to the marked scene; the obtained marked scene is divided into several regions using the region growing algorithm, and then the relationship between the regions is determined, and the regional skeleton is extracted by the skeleton extraction algorithm, based on the obtained spatial geometric structure; Obtain the target item generation instruction of the player, extract the item type data and the first position information from the target item generation instruction to obtain the item data determined by the user, the first position information includes the two-dimensional coordinate information of the first position, according to the two-dimensional coordinate information of the first position, through the layout relationship database of the indoor scene, call the kd tree neighbor search algorithm to query the space unit close to the first position to obtain the second position of the three-dimensional coordinate system, and determine the third position and the direction of the item in the three-dimensional space; In the game engine, an instantiation model of a target virtual prop is loaded into a virtual scene according to the item data and a third position, and the item type determines the shape information and interaction information of the item instantiation.

[0009] Furthermore, it also includes: determining a second position in the virtual scene based on the first position; generating and displaying a target virtual prop at the second position according to the prop type; and displaying a moving animation of the target virtual prop moving from the second position to a third position.

[0010] Further, based on the first position, determining a second position in the virtual scene; generating and displaying a target virtual prop at the second position according to the prop type; and displaying a moving animation of the target virtual prop moving from the second position to a third position, specifically including: According to the first position information, using a spatial relationship mapping algorithm, the three-dimensional coordinates of the second position are determined and calibrated in a pre-established three-dimensional virtual scene space coordinate system; Get the 3D model data of the preset target props, find the corresponding data using the hash table structure according to the prop type attributes and the corresponding category information, read into the 3D model, and render the target props; After the rendering is completed, the target virtual props and other objects in the scene are synthesized into a unified image level, and the rendering result is combined with the pre-calculated ambient lighting data to a two-dimensional display plane; Calculate and record the position data in the two-dimensional image space according to the spatial information of the target virtual prop, generate a smooth moving trajectory in the three-dimensional space by using the continuous space cubic Bezier curve algorithm through the image position data, and form an image-level display effect in the two-dimensional space through the image position data; Then, the coordinates of the third position of the spatial movement are obtained according to the coordinate parameters determined by the spatial cubic Bezier curve algorithm, by collecting the average grayscale value L0 in the unit volume of the third position and the average grayscale value L1 in the unit volume of the target virtual prop; The two sets of grayscale value sets are processed using the mean standard deviation normalization method to obtain a final data difference greater than the grayscale threshold. When the difference result is greater than the grayscale threshold, a pre-judgment is made and the rendering output color value is changed; The color information of the third position is changed according to the calculation result, and the three-dimensional spatial position of the target virtual prop in each frame is updated according to the three-dimensional movement trajectory function. The rendering interface is continuously called through the image position data to obtain the updated two-dimensional display position of the target virtual prop.

[0011] Furthermore, after optimizing the efficiency of resource and item usage, it also includes: regularly evaluating configuration effects, continuously optimizing strategies, and achieving an efficient balance between resource allocation and item usage.

[0012] Furthermore, real-time data on resource allocation and prop usage is obtained, and a comprehensive analysis is performed to obtain key indicators. The effectiveness of the current resource allocation strategy is judged based on preset evaluation rules and thresholds. If the expected goal is not achieved, the strategy optimization process is triggered. Heuristic algorithms and reinforcement learning algorithms are used to find the optimal combination of resource allocation and prop usage in massive historical data to form candidate optimization strategies.

[0013] The present invention provides a resource configuration system for a virtual game scene, which is used to implement a resource configuration method for a virtual game scene, including: The data collection and processing module regularly collects resource configuration data and player behavior data in virtual games, encrypts the collected data, and then transmits it to the data processing platform for preprocessing and storage; An indicator determination module, which obtains the preset conditions that the profitability indicator and fairness indicator of the virtual game need to meet; The virtual resource configuration module determines the amount of virtual resources to be placed in the task-based game strategy in the virtual game according to the resource configuration data and preset index conditions; and according to the amount of placement, places virtual resources in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions; A virtual scene and prop generation module displays a two-dimensional map in the virtual scene, and displays a two-dimensional map corresponding to the virtual scene by responding to the player's two-dimensional map opening instruction; responding to the player's target virtual prop generation instruction, and determining the first position set by the player in the two-dimensional map and the type of the target virtual prop; Wherein, based on the first position, determining a second position in the virtual scene; generating and displaying a target virtual prop at the second position according to the prop type; and displaying a moving animation of the target virtual prop moving from the second position to the third position; Integrate the optimization and control modules to adjust the configuration strategy in real time during the process of virtual resource configuration and virtual prop delivery; then stop delivering invalid resources and props to players who have met the conditions, optimize the efficiency of resource and prop use, and regularly evaluate the configuration effect to continuously optimize the strategy.

[0014] The beneficial effects of the present invention are: The present invention effectively solves the fairness and profitability issues of resource allocation in virtual games through refined resource allocation and item placement strategies. By regularly collecting and encrypting player behavior data and resource allocation data, the security and privacy of data processing are ensured. Using these data, combined with preset profitability and fairness indicators, a correlation model between resource allocation and game indicators is established. The model can predict the impact of resource allocation on game indicators, and optimize the in-game resource and item placement strategy through data analysis and machine learning technology to meet the preset fairness and profitability conditions. In this way, not only the rationality of resource allocation is improved, but also the fairness of game experience and the economic benefits of game operators are ensured. By real-time monitoring and adjusting resource allocation strategies, the efficiency of resource and item usage is optimized, and the user experience is improved. According to the resource satisfaction of the players, decision trees and supervised machine learning models are used to set the delivery threshold and decide whether to stop delivering resources and items to specific players. At the same time, the GBDT algorithm and time series prediction model are used to predict the consumption trend of resources and items, dynamically adjust the delivery strategy, and eliminate abnormal data through the isolation forest algorithm to ensure the accuracy of resource delivery. Finally, according to the preset virtual currency threshold and exchange rules, the actual resource and item delivery operation is performed, thereby solving the problem of low efficiency in generating and moving virtual items mentioned in the background technology and improving the efficiency and effect of virtual item delivery. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] For better understanding and implementation, the technical solution of the present application is described in detail below with reference to the accompanying drawings.

[0016] Figure 1 A flowchart of a resource configuration method for a virtual game scene provided in Example 1 of the present application; Figure 2 A schematic diagram of a flow chart of encrypting, preprocessing and storing collected data in a resource configuration method for a virtual game scene provided in Example 1 of the present application; Figure 3 A structural diagram of a resource configuration system for a virtual game scene provided in Example 2 of the present application. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects taken by the present invention to achieve the predetermined invention purpose, exemplary embodiments will be described in detail here, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are only examples of methods and systems consistent with some aspects of the present application as detailed in the attached claims.

[0018] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0019] The specific implementation methods, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0020] Example 1 See also Figure 1-Figure 2 This embodiment provides a method for configuring resources of a virtual game scene, comprising the following steps: S1. Regularly collect resource configuration data and player behavior data in virtual games, encrypt the collected data, and then transmit it to the data processing platform for preprocessing and storage; Furthermore, resource configuration data and player behavior data in virtual games are collected regularly, the collected data is encrypted, and then transmitted to the data processing platform for preprocessing and storage, specifically including: S11. According to a preset time interval, the virtual game data collection program is periodically triggered to collect resource configuration data and player behavior data in the virtual game, and the collected resource configuration data and player behavior data are encrypted using an asymmetric encryption algorithm, such as an RSA algorithm, to obtain encrypted data; S12, transmitting the encrypted resource configuration data and player behavior data to the data processing platform through a secure channel, and decrypting the encrypted data in the data processing platform using a decryption algorithm matching the encryption algorithm to obtain the original resource configuration data and player behavior data; S13. Preprocess the decrypted resource configuration data and player behavior data using methods such as data cleaning and data conversion to obtain standardized data. Use distributed storage technology to persistently store the preprocessed resource configuration data and player behavior data for subsequent data analysis and mining.

[0021] Specifically, by regularly collecting resource configuration and player behavior data, using asymmetric encryption algorithms (such as RSA) to ensure the security of data transmission, and then decrypting, cleaning, converting and standardizing the data on the data processing platform, the pre-processed data is finally persisted through distributed storage technology for effective data analysis and mining, thereby improving data security, availability and processing efficiency.

[0022] S2. Analyze and obtain the preset conditions that the profitability index and fairness index of the virtual game need to meet based on the encrypted data; determine the amount of virtual resources in the task-based game strategy in the virtual game based on the resource allocation data and the preset index conditions; Further, after determining the amount of virtual resources to be put into the task-based game strategy in the virtual game, it specifically includes: Obtain multi-dimensional indicator data related to profitability and fairness in virtual games, including user activity, payment rate, resource consumption rate, etc., and determine whether the current indicator meets the preset conditions based on the preset profitability and fairness target thresholds; Through machine learning algorithms, historical resource allocation data and corresponding profitability and fairness index data are trained to establish a correlation model between resource allocation and indicators. Based on the current resource allocation situation, the corresponding profitability and fairness index values ​​are predicted. When the predicted index value does not meet the preset conditions, the resource allocation plan is iteratively optimized through the optimization algorithm. While meeting the profitability and fairness indicators, the game balance and user experience are taken into consideration to obtain the optimized resource allocation plan. Based on the optimized resource allocation plan, determine the delivery and allocation ratio of each type of virtual resources in different task-based game strategies, compare the effects of different configuration plans through AB testing and other methods, and make dynamic adjustments based on feedback data.

[0023] Build a lifecycle management mechanism for virtual resources, dynamically adjust the resource generation speed and recycling mechanism based on factors such as resource scarcity and consumption rate, and ensure the sustainability and balance of resources; Design diverse task-based game strategies and gameplay to guide users to obtain and consume virtual resources in different ways, increase user participation and activity, and avoid excessively affecting the fairness of the game; establish a transaction and circulation mechanism for virtual resources, allowing users to exchange and transfer resources within a reasonable range, improve resource liquidity and utilization, and set appropriate transaction taxes and restrictions to prevent problems such as resource monopoly and inflation.

[0024] Specifically, by analyzing multi-dimensional indicator data, using machine learning algorithms to establish and optimize resource allocation models, dynamically adjusting resource delivery and allocation ratios, and building resource lifecycle management mechanisms and diversified game strategies, we aim to achieve a balance between game profitability, fairness and user experience, while improving the sustainability of resources and the activity of the game, avoiding resource monopoly and inflation problems, and thus improving the overall economic benefits of the game and player satisfaction.

[0025] S3. According to the delivery amount, virtual resources are delivered in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions; Furthermore, according to the amount of investment, virtual resources are invested in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions, including: Obtain historical data of task-based games, including game attribute data such as virtual resource delivery, profitability indicators, and fairness indicators; According to the preset conditions, the target optimization values ​​of the profitability index and the fairness index are determined, and a machine learning algorithm, such as reinforcement learning, is used to establish a correlation model between the virtual resource delivery amount and the profitability index and the fairness index; Through this association model, the changes in profitability and fairness indicators under different virtual resource delivery amounts are predicted. When the predicted indicator changes meet the preset conditions, the corresponding virtual resource delivery amounts are output as candidate optimization values. The amount of virtual resources with the best comprehensive evaluation effect is selected from the candidate optimization values ​​as the basis for adjusting the game strategy. The optimized amount of virtual resource delivery is then applied to the task-based game, and resource allocation is dynamically adjusted to ensure that the game's profitability and fairness indicators meet the expected requirements.

[0026] Specifically, machine learning algorithms, especially reinforcement learning, are used to establish a correlation model between the amount of virtual resources put into use and the profitability and fairness indicators of the game. By predicting and optimizing the changes in indicators under different puts, the resource allocation strategy is dynamically adjusted to ensure that the profitability and fairness indicators of the game meet the expected requirements, thereby optimizing the allocation of resources within the game and improving resource utilization efficiency and game balance.

[0027] S4, in the virtual scene, by responding to the player's two-dimensional map opening instruction, displaying the two-dimensional map corresponding to the virtual scene; by responding to the player's target virtual prop generation instruction, determining the first position set by the player in the two-dimensional map and the type of the target virtual prop; Further, by responding to the player's two-dimensional map opening instruction, a two-dimensional map corresponding to the virtual scene is displayed; by responding to the player's target virtual prop generation instruction, the first position set by the player in the two-dimensional map and the type of the target virtual prop are determined, specifically including: According to the player's map instruction, the scene map of the current virtual scene pre-established in the storage device is obtained. When there is no scene map of the virtual scene, the construction process is triggered to establish a two-dimensional top view according to the scene model; by obtaining the player's position, the player's three-dimensional coordinate information is calculated through the spatial coordinate system of the game engine and mapped to the scene map to form corresponding points; According to the attribute data of each game object on the scene map, the updated marked scene is obtained after data labeling, and the multi-scale edge detection algorithm is applied to the marked scene; the obtained marked scene is divided into several regions using the region growing algorithm, and then the relationship between the regions is determined, and the regional skeleton is extracted by the skeleton extraction algorithm, based on the obtained spatial geometric structure; Obtain the target item generation instruction of the player, extract the item type data and the first position information from the target item generation instruction to obtain the item data determined by the user, the first position information includes the two-dimensional coordinate information of the first position, according to the two-dimensional coordinate information of the first position, through the layout relationship database of the indoor scene, call the kd tree neighbor search algorithm to query the space unit closest to the first position to obtain the second position of the three-dimensional coordinate system, and determine the third position and the object orientation in the three-dimensional space; In the game engine, an instantiation model of a target virtual prop is loaded into a virtual scene according to the item data and a third position, and the item type determines the shape information and interaction information of the item instantiation.

[0028] Furthermore, it also includes: determining a second position in the virtual scene based on the first position; generating and displaying a target virtual prop at the second position according to the prop type; and displaying a moving animation of the target virtual prop moving from the second position to a third position.

[0029] Further, based on the first position, determining a second position in the virtual scene; generating and displaying a target virtual prop at the second position according to the prop type; and displaying a moving animation of the target virtual prop moving from the second position to a third position, specifically including: According to the first position information, using a spatial relationship mapping algorithm, the three-dimensional coordinates of the second position are determined and calibrated in a pre-established three-dimensional virtual scene space coordinate system; Get the 3D model data of the preset target props, find the corresponding data using the hash table structure according to the prop type attributes and the corresponding category information, read into the 3D model, and render the target props; After the rendering is completed, the target virtual props and other objects in the scene are synthesized into a unified image level, and the rendering result is combined with the pre-calculated ambient lighting data to a two-dimensional display plane; Generate a random number r again. When the random number r conforms to the gamma distribution, add a new object to the three-dimensional scene and calculate its visibility according to the calculation result. Among them, the gamma distribution is a continuous probability distribution in statistics, which contains two parameters: shape and scale. The probability density function of the gamma distribution is: ,in and are the two parameters of the gamma distribution, is the gamma function, which is used to represent the shape parameter of the gamma distribution, represents the value of a random variable, which is a non-negative real number. .

[0030] Get the size A1 of the rendered object and the average value A2 of the curvature k of each point on the object contour, and make a prediction based on A1 and A2; Calculate and record the position data in the two-dimensional image space according to the spatial information of the target virtual prop, generate a smooth moving trajectory in the three-dimensional space by using the continuous space cubic Bezier curve algorithm through the image position data, and form an image-level display effect in the two-dimensional space through the image position data; Then, the coordinates of the third position of the spatial movement are obtained according to the coordinate parameters determined by the spatial cubic Bezier curve algorithm, by collecting the average grayscale value L0 in the unit volume of the third position and the average grayscale value L1 in the unit volume of the target virtual prop; The two sets of grayscale value sets are processed using the mean standard deviation normalization method to obtain a final data difference greater than the grayscale threshold A. When the difference result is greater than the grayscale threshold A, a pre-judgment is made and the rendering output color value is changed to ensure that the spatial information is not distorted when it is synthesized into the image; Generate a random number again. If it conforms to the exponential distribution, change the color information of the third position according to the calculation result. According to the three-dimensional movement trajectory function, update the three-dimensional spatial position of the target virtual prop in each frame. Through the image position data, continuously call the rendering interface to obtain the updated two-dimensional display position of the target virtual prop, and construct the target virtual prop movement process on the two-dimensional plane to form a complete moving animation effect.

[0031] Specifically, users can adjust different angles of observation in three-dimensional space, determine the angle with the three-dimensional coordinate system according to different observation angles, change the angle parameters according to the spatial coordinate mapping transformation relationship of the three-dimensional coordinate system, and use the machine learning spatial object interpolation model to train the interpolation network to obtain a transition interpolation image sequence with a smooth predicted viewing angle.

[0032] Specifically, by responding to player instructions, it can obtain and display two-dimensional maps, determine the position and prop type set by the player, and accurately generate and position virtual props in the virtual scene. By using spatial coordinate systems, data labeling, multi-scale edge detection, region growing algorithms, skeleton extraction and other technologies, the system can create and render three-dimensional models of props, and use continuous space cubic Bezier curve algorithms to generate smooth movement trajectories of props. In addition, random numbers are generated through gamma distribution and exponential distribution to increase the dynamics and realism of the scene, ultimately achieving realistic moving animation effects of props on a two-dimensional plane, while allowing users to observe three-dimensional space from different angles, enhancing the interactivity and visual experience of the game.

[0033] S5. During the process of virtual resource allocation and virtual item delivery, adjust the allocation strategy in real time to ensure the rational use of resources, and then stop delivering invalid resources and items to players who have met the conditions, so as to optimize the efficiency of resource and item use; Furthermore, in the process of virtual resource allocation and virtual item delivery, the allocation strategy is adjusted in real time to ensure the rational use of resources, and then the invalid resources and items are stopped from being delivered to players who have met the conditions, so as to optimize the efficiency of resource and item use, including: Collect all player behavior data, generate a player behavior data set based on the behavior data, combine the information on the types and quantities of configured resources, and the types and quantities of delivered props, and obtain the satisfied player data and unsatisfied player data corresponding to the player data set through processing. The unsatisfied player data includes the corresponding unsatisfied player list, and obtain the player resource satisfied list; Use decision tree algorithm to build a model, set resource props delivery threshold according to player behavior data and game process data in the player resource satisfaction list, game resource threshold parameter includes numerical variable A and categorical variable B, game props threshold parameter includes numerical variable and categorical variable, set game resource numerical variable and game props numerical variable as delivery stop parameter, and obtain the list that meets the delivery stop parameter by combining the stop parameter; By judging the delivery stop parameters, when a player reaches the stop parameters, the supervised machine learning model is used to make the next judgment for the player to determine whether to stop delivering resources and props to him. The delivery content parameters include numerical variables and categorical variables to obtain the player's resource prop demand label.

[0034] Compare the number of resources and props obtained by the player, combine the player resource and prop demand labels obtained in the previous process, use the gradient boosting decision tree (GBDT) algorithm to train to obtain the delivery prediction value, build a classifier for accurate delivery of resources and props content, and then obtain player data below the set threshold as the data to be delivered, and get the recommended delivery content and recommended quantity.

[0035] By building a time series prediction model based on existing player behavior patterns and delivery data, we can predict the consumption trend of resources and props in a short time range, and then formulate adjustment plans based on the changing trends. We set the plan modification frequency to N, and use the series composed of historical observation results of past values ​​to construct a time series model through processing, and derive the predicted delivery modification plan, obtain real-time monitoring data, and get immediate modification content.

[0036] By adjusting the instant modification content and combining it with the recommended delivery content, if the types of resources and props exceed the set number of types, the player's historical satisfaction data will be obtained, and the isolated forest algorithm will be used for training based on the player's historical data to determine whether it is abnormal player data, eliminate abnormal players, and then determine the final resource prop delivery list.

[0037] Get the resource and item data in the final list, perform actual delivery operations, use the preset virtual currency quantity threshold to determine the relationship between the resource value and the preset virtual currency quantity threshold, and set a resource delivery ratio P1 for the value greater than the currency threshold to perform resource conversion, use the preset exchange rules to determine the relationship between resources and items, determine the item conversion rules, P1, the preset exchange rule parameters include numerical variables and categorical variables, and obtain the resource and item delivery execution strategy based on the converted data.

[0038] Furthermore, after optimizing the efficiency of resource and item usage, it also includes: regularly evaluating configuration effects, continuously optimizing strategies, and achieving an efficient balance between resource allocation and item usage.

[0039] Furthermore, real-time data on resource allocation and item usage is obtained and comprehensively analyzed to obtain key indicators such as resource utilization and item usage efficiency. The effectiveness of the current resource allocation strategy is judged based on preset evaluation rules and thresholds. If the expected goal is not achieved, the strategy optimization process is triggered. Heuristic algorithms and reinforcement learning algorithms are used to find the optimal combination of resource allocation and item usage in massive historical data to form candidate optimization strategies.

[0040] Specifically, by real-time collection and analysis of player behavior data, dynamic adjustment of resource allocation strategies, precise delivery of resources and props, and optimization of resource utilization efficiency, it also uses advanced technical means such as supervised machine learning models, gradient boosting decision tree (GBDT) algorithms, time series prediction models, and isolation forest algorithms to predict consumption trends, eliminate abnormal data, and continuously optimize delivery strategies according to preset rules to achieve an efficient balance between resource allocation and prop usage, thereby significantly improving the gaming experience and the economic benefits of game operators.

[0041] By integrating virtual resource allocation and virtual item placement optimization technology, the rational utilization rate of virtual resources and the efficiency of virtual item use are significantly improved. Through big data analysis and real-time adjustment of strategies, the profitability and fairness of the game are ensured, resource waste is reduced, the player's gaming experience and the operating efficiency of the entire system are improved, and the user's various behaviors in the game are better managed and controlled, ensuring the healthy development of the game.

[0042] Example 2 See also Figure 3 This embodiment provides a resource configuration system for a virtual game scene, which is used to implement a resource configuration method for a virtual game scene, including: The data collection and processing module regularly collects resource configuration data and player behavior data in virtual games, encrypts the collected data, and then transmits it to the data processing platform for preprocessing and storage; An indicator determination module, which obtains the preset conditions that the profitability indicator and fairness indicator of the virtual game need to meet; The virtual resource configuration module determines the amount of virtual resources to be placed in the task-based game strategy in the virtual game according to the resource configuration data and preset index conditions; and according to the amount of placement, places virtual resources in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions; A virtual scene and prop generation module displays a two-dimensional map in the virtual scene, and displays a two-dimensional map corresponding to the virtual scene by responding to the player's two-dimensional map opening instruction; responding to the player's target virtual prop generation instruction, and determining the first position set by the player in the two-dimensional map and the type of the target virtual prop; Wherein, based on the first position, determining a second position in the virtual scene; generating and displaying a target virtual prop at the second position according to the prop type; and displaying a moving animation of the target virtual prop moving from the second position to the third position; Integrate optimization and control modules to adjust configuration strategies in real time during virtual resource configuration and virtual item delivery to ensure rational use of resources; stop delivering invalid resources and items to players who have met the conditions to optimize the efficiency of resource and item use; regularly evaluate configuration effects, continuously optimize strategies, and achieve an efficient balance between resource allocation and item use.

[0043] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A resource configuration method for a virtual game scene, characterized in that: The steps include: Regularly collect resource configuration data and player behavior data in virtual games, encrypt the collected data, and then transmit it to the data processing platform for pre-processing and storage; Analyze and obtain the preset conditions that the profitability index and fairness index of the virtual game need to meet based on the encrypted data, and then determine the amount of virtual resources in the task-based game strategy in the virtual game; According to the amount of investment, virtual resources are invested in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions; In the virtual scene, by responding to the player's two-dimensional map opening instruction, a two-dimensional map corresponding to the virtual scene is displayed; by responding to the player's target virtual prop generation instruction, the first position set by the player in the two-dimensional map and the type of the target virtual prop are determined; During the process of allocating virtual resources and delivering virtual props, the allocation strategy is adjusted in real time, and then invalid resources and props are delivered to players who have met the conditions, so as to optimize the efficiency of resource and prop usage; By collecting all player behavior data, generating a player behavior data set based on the behavior data, and combining the information on the types and quantities of configured resources and the types and quantities of delivered props, a player resource satisfaction list is obtained; Use decision tree algorithms to build models, set resource and item delivery thresholds, and use supervised machine learning models to determine whether to stop delivering resources and items to specific players; Based on the player's resource prop demand labels and the quantity obtained, the gradient boosting decision tree GBDT algorithm is used to predict and optimize the release of resource props, and then a time series prediction model is established to predict the consumption trend of resources and props to adjust the release strategy. The isolation forest algorithm is used to eliminate abnormal player data, determine the resource prop release list, and perform actual resource and prop release operations according to the preset virtual currency threshold and exchange rules; After optimizing the efficiency of resource and item usage, it also includes: regularly evaluating configuration effects and continuously optimizing strategies. By obtaining real-time data on resource configuration and item usage, a comprehensive analysis is performed to obtain key indicators. According to preset evaluation rules and thresholds, the effectiveness of the current resource configuration strategy is judged. When the expected goal is not achieved, the strategy optimization process is triggered. Heuristic algorithms and reinforcement learning algorithms are used to find combinations of resource configuration and item usage in massive historical data to form candidate optimization strategies.

2. The resource configuration method of a virtual game scene according to claim 1, characterized in that: Regularly collect resource configuration data and player behavior data in virtual games, encrypt the collected data, and then transmit it to the data processing platform for pre-processing and storage, including: According to a preset time interval, the virtual game data collection program is periodically triggered to collect resource configuration data and player behavior data in the virtual game, and the collected resource configuration data and player behavior data are encrypted using an asymmetric encryption algorithm to obtain encrypted data; The encrypted resource configuration data and player behavior data are transmitted to the data processing platform through a secure channel. In the data processing platform, the encrypted data is decrypted using a decryption algorithm that matches the encryption algorithm to obtain the original resource configuration data and player behavior data; The decrypted resource configuration data and player behavior data are preprocessed by data cleaning and data conversion to obtain standardized data. The preprocessed resource configuration data and player behavior data are persistently stored by using distributed storage technology.

3. The resource configuration method of a virtual game scene according to claim 1, characterized in that: After determining the amount of virtual resources in the virtual game in the task-based game strategy, including: Obtain multi-dimensional indicator data related to profitability and fairness in virtual games, and determine whether the current indicators meet the preset conditions based on the preset profitability and fairness target thresholds; Through machine learning algorithms, historical resource allocation data and corresponding profitability and fairness index data are trained to establish a correlation model between resource allocation and indicators. Based on the current resource allocation situation, the corresponding profitability and fairness index values ​​are predicted. When the predicted index value does not meet the preset conditions, the resource allocation plan is iteratively optimized through the optimization algorithm to obtain the optimized resource allocation plan; According to the optimized resource allocation plan, determine the delivery amount and allocation ratio of each type of virtual resources in different task-based game strategies, and make dynamic adjustments based on feedback data; then build a life cycle management mechanism for virtual resources to dynamically adjust the resource generation speed and recycling mechanism.

4. The resource configuration method of a virtual game scene according to claim 1, characterized in that: According to the amount of investment, virtual resources are invested in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions, including: Obtain historical data of task-based games, determine target optimization values ​​of profitability and fairness indicators based on preset conditions, and use machine learning algorithms to establish a correlation model between virtual resource delivery and profitability and fairness indicators; Through the association model, the changes in profitability indicators and fairness indicators under different virtual resource delivery amounts are predicted. When the predicted indicator changes meet the preset conditions, the corresponding virtual resource delivery amounts are output as candidate optimization values. The amount of delivery after comprehensive evaluation is selected from the candidate optimization values ​​as the basis for adjusting the game strategy, and then the optimized virtual resource delivery amount is applied to the task-based game, and resource allocation is dynamically adjusted to make the game's profitability and fairness indicators meet the expected requirements.

5. The resource configuration method of a virtual game scene according to claim 1, characterized in that: By responding to the player's two-dimensional map opening instruction, a two-dimensional map corresponding to the virtual scene is displayed; By responding to the target virtual prop generation instruction of the player, determining the first position set by the player in the two-dimensional map and the type of the target virtual prop, specifically including: According to the player's map instruction, the scene map of the current virtual scene pre-established in the storage device is obtained. When there is no scene map of the virtual scene, the construction process is triggered to establish a two-dimensional top view according to the scene model; by obtaining the player's position, the player's three-dimensional coordinate information is calculated through the spatial coordinate system of the game engine and mapped to the scene map to form corresponding points; According to the attribute data of each game object on the scene map, the updated marked scene is obtained after data labeling, and the multi-scale edge detection algorithm is applied to the marked scene; the obtained marked scene is divided into several regions using the region growing algorithm, and then the relationship between the regions is determined, and the regional skeleton is extracted by the skeleton extraction algorithm, based on the obtained spatial geometric structure; Obtain the target item generation instruction of the player, extract the item type data and the first position information from the target item generation instruction to obtain the item data determined by the user, the first position information includes the two-dimensional coordinate information of the first position, according to the two-dimensional coordinate information of the first position, through the layout relationship database of the indoor scene, call the kd tree neighbor search algorithm to query the space unit close to the first position to obtain the second position of the three-dimensional coordinate system, and determine the third position and the direction of the item in the three-dimensional space; In the game engine, an instantiation model of a target virtual prop is loaded into a virtual scene according to the item data and a third position, and the item type determines the shape information and interaction information of the item instantiation.

6. The resource configuration method of a virtual game scene according to claim 1, characterized in that: Also includes: Based on the first position, determining a second position in the virtual scene; generating and displaying a target virtual prop at the second position according to the prop type; By displaying a moving animation of the target virtual prop moving from the second position to the third position.

7. The resource configuration method of a virtual game scene according to claim 6, characterized in that: Based on the first position, determining a second position in the virtual scene; generating and displaying a target virtual prop at the second position according to the prop type; By displaying a moving animation of the target virtual prop moving from the second position to the third position, including: According to the first position information, using a spatial relationship mapping algorithm, the three-dimensional coordinates of the second position are determined and calibrated in a pre-established three-dimensional virtual scene space coordinate system; Get the 3D model data of the preset target props, find the corresponding data using the hash table structure according to the prop type attributes and the corresponding category information, read into the 3D model, and render the target props; After the rendering is completed, the target virtual props and other objects in the scene are synthesized into a unified image level, and the rendering result is combined with the pre-calculated ambient lighting data to a two-dimensional display plane; According to the spatial information of the target virtual prop, the position data in the two-dimensional image space is calculated and recorded. Through the image position data, a smooth moving trajectory is generated in the three-dimensional space using the continuous space cubic Bezier curve algorithm. Through the image position data, an image-level display effect is formed in the two-dimensional space.

8. The resource configuration method of a virtual game scene according to claim 7, characterized in that: The coordinates of the third position of the spatial movement are obtained according to the coordinate parameters determined by the spatial cubic Bezier curve algorithm, by collecting the average gray value L0 in the unit volume of the third position and the average gray value L1 in the unit volume of the target virtual prop; The two sets of grayscale value sets are processed using the mean standard deviation normalization method to obtain data with a difference greater than the grayscale threshold. When the difference result is greater than the grayscale threshold, a pre-judgment is made and the rendering output color value is changed; The color information of the third position is changed according to the calculation result, and the three-dimensional spatial position of the target virtual prop in each frame is updated according to the three-dimensional movement trajectory function. The rendering interface is continuously called through the image position data to obtain the updated two-dimensional display position of the target virtual prop.

9. A resource configuration system for a virtual game scene, used to implement a resource configuration method for a virtual game scene as claimed in any one of claims 1 to 8, characterized in that: include: The data collection and processing module regularly collects resource configuration data and player behavior data in virtual games, encrypts the collected data, and then transmits it to the data processing platform for preprocessing and storage; An indicator determination module, which obtains the preset conditions that the profitability indicator and fairness indicator of the virtual game need to meet; The virtual resource configuration module determines the amount of virtual resources to be placed in the task-based game strategy in the virtual game according to the resource configuration data and preset index conditions; and according to the amount of placement, places virtual resources in the task-based game strategy so that the profitability index and fairness index of the virtual game meet the preset conditions; A virtual scene and prop generation module displays a two-dimensional map in the virtual scene, and displays a two-dimensional map corresponding to the virtual scene by responding to the player's two-dimensional map opening instruction; responding to the player's target virtual prop generation instruction, and determining the first position set by the player in the two-dimensional map and the type of the target virtual prop; Wherein, based on the first position, a second position in the virtual scene is determined; and according to the type of the prop, a target virtual prop is generated and displayed at the second position; Displaying a moving animation of the target virtual prop moving from the second position to the third position; Integrate the optimization and control modules to adjust the configuration strategy in real time during the process of virtual resource configuration and virtual prop delivery; then stop delivering invalid resources and props to players who have met the conditions, optimize the efficiency of resource and prop use, and regularly evaluate the configuration effect to continuously optimize the strategy.

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