50 results about "Battlefield" patented technology

The invention relates to the technical field of informatization war, and particularly provides a big data analysis-based combat decision auxiliary system and method, and the system comprises a data collection module, a data preprocessing module, a multi-source intelligence fusion module, a situation prediction depth mining and analysis module, a military strength deployment module, and an auxiliary optimization module. The method comprises the following steps: S101, data acquisition, connection and preprocessing; s102, fusing multi-source intelligence to judge a target; s103, accurately analyzing and predicting the attempt of the enemy; s104, carrying out multi-dimensional association recommendation on the available strength; s105, assisting in optimizing a combat scheme; according to the scheme, how to apply a big data analysis technology is introduced in detail, a set of efficient and intelligent combat scheme generation system is constructed, and scientific and accurate tactical and strategic guidance is provided for military decision makers. According to the system, key technical links such as data acquisition, fusion, analysis, modeling and visualization are integrated so as to cope with a complex and dynamic battlefield environment, and maximization of combat effectiveness is achieved.

The invention discloses an unmanned combat equipment intelligent decision-making system based on reinforcement learning. The system comprises a task understanding module which analyzes a combat intention according to a task instruction, analyzes a battlefield situation according to battlefield information, forms a sub-first-level tactical task oriented to each agent, and transmits the sub-first-level tactical task to a scheme construction module; the scheme construction module is used for generating a plurality of feasible combat schemes according to each sub-first-level tactical task and transmitting the combat schemes to the task sequence generation module; the task sequence generation module is used for converting the combat scheme into task sequences corresponding to the intelligent agents and distributing the task sequences to the corresponding intelligent agents; and the agent control module is used for controlling the agents to execute combat tasks according to the distributed tasks, controlling the agents to sense battlefield information and feeding back the battlefield information to the task understanding module. The system collects and fuses battlefield situations obtained by equipment in the system in real time, and optimizes a decision process based on situation information so as to adapt to a complex and changeable battlefield environment.

The invention discloses an intelligent war game deduction method based on reinforcement learning, and the method comprises the steps: constructing a dynamic battlefield model: constructing an adjustable battlefield simulation platform, and defining the landform, resources and army distribution elements in a battlefield; a reinforcement learning strategy is generated and optimized, an intelligent strategy generation algorithm based on deep reinforcement learning is designed, and an efficient combat strategy is generated in multiple rounds of training by constructing a state space and an action space and combining a situation reward function; a double-agent chess playing training mechanism is introduced, black parties and white parties are modeled into reinforcement learning agents, red parties and blue parties are modeled into reinforcement learning agents, and a real battlefield game is simulated through multiple rounds of alternate training; result visualization deduction: a dynamic decision visualization function is provided, and battlefield situation, troop dynamics and a strategy execution process can be displayed in real time; according to the method, the problems of rule solidification, limited strategy generation capability, insufficient antagonism and the like in the prior art are solved.

The invention discloses a dynamic empowerment-based high-precision hexagonal grid long-range way-finding method in war chess, and particularly relates to the technical field of war chess deduction, comprising the following steps: matching regular hexagonal grids by using a Cube coordinate system, and obtaining battlefield dynamic change data of each regular hexagonal grid, respectively evaluating the threat degree and the obstacle degree of the regular hexagonal grid, and dividing nodes corresponding to the regular hexagonal grid into normal nodes and obstacle nodes based on an evaluation result; performing path weight adjustment on a path formed by two adjacent nodes, and searching an optimal path from a starting point to an end point according to a preset long-range path-finding algorithm; according to the method, the dynamic change data of the battlefield is collected in real time, and the threat index and the terrain arrival index of the node are dynamically adjusted, so that the path weight can reflect the change of the environment of the battlefield in time, the real-time performance and the dynamic adaptability of the path decision are improved, and the complicated and changeable battlefield environment is effectively coped with.

The invention provides a multi-agent decision-making method based on the combination of MAPPO and a hierarchical attention mechanism, and the method comprises the steps: inputting the observation state information of a current moment into a strategy network, which introduces a local attention mechanism, of each agent, and outputting a first action; second actions of other intelligent agents are combined to be input into the value network with the global attention mechanism introduced, and combined actions of the intelligent agents are output; the local attention mechanism of the strategy network can make the intelligent agents focus on key local information around the intelligent agents, the global attention mechanism of the value network can collectively collect the macroscopic situation of the whole battlefield, and the task value of each intelligent agent can be reasonably evaluated. When the situation of a battlefield is changed, dynamic adjustment can be rapidly made by means of the attention mechanism of the double view angles, and the MAPPO algorithm has the strengthening effect on agent cooperation, cooperates with the attention mechanism, dynamically weights according to task requirements and real-time situations, makes more optimized decisions and improves the success rate of combat.

The invention discloses a player character and BOSS battle real-time analysis method, system and device and a medium, and the method specifically comprises the steps: taking verification battle data as input, recognizing battlefield dynamic obstacles through an improved YOLOv5 model, and generating environment perception data through a three-dimensional space interpolation algorithm; constructing a dynamic attribute relation graph according to the environmental perception data and preset role state data, modeling a time-varying restriction relation between role skills by adopting a bidirectional graph attention network, and updating an edge weight matrix through a time sliding window mechanism; and inputting the dynamic attribute relation graph and player historical operation data into a reinforcement learning decision model together to generate a battle strategy tree, and dynamically adjusting the search depth of the battle strategy tree through a real-time calculated battle complexity index to generate an optimal battle strategy. The analysis efficiency and accuracy of player character battle BOSS are improved, players can be helped to quickly understand battle dynamics, and battle strategies and operation skills are improved.

The invention discloses a battlefield semantic situation rapid generation method based on image analysis, and belongs to the technical field of battlefield situation generation. The method comprises the following steps: dividing a battlefield area into a plurality of local battlefields; reconnaissance is carried out on each local battlefield area; generating a multi-source heterogeneous image database; performing time-space relationship unification on the multi-source heterogeneous image database; constructing a battlefield situation element composition system; constructing a battlefield situation element extraction technology system; carrying out adaptive extraction on battlefield situation elements; generating a local battlefield situation; a global battlefield situation is generated based on the local battlefield situation. The invention provides a battlefield situation element extraction framework based on deep learning, designs a battlefield situation generation method based on deep learning, and provides a conflict situation fusion method and a battlefield region division method based on an attention mechanism and a complete space-time relationship unification mode. A whole set of battlefield semantic situation adaptive generation method is constructed, and decision-making assistance can be provided for direct commanders and fighters.

The invention belongs to the technical field of wargame deduction, and discloses an emergency wargame deduction system capable of editing total elements. Comprising an operator editing subsystem, a decision table editing subsystem, a map editing subsystem, a chess editing subsystem, a scenario editing subsystem, a training organization subsystem, a deduction work subsystem, a guidance control subsystem, a deduction observation subsystem, a deduction replaying subsystem, a deduction engine subsystem and a system management subsystem. The system can meet the requirements of relevant professional operational scientific research activities on the sea. According to requirements, a deduction scenario is compiled, deduction conditions are set, and scientific research activities are carried out by selecting different weapons, combat deployment, combat actions, guarantee conditions, battlefield environments and the like and adopting a deduction-while-research or deduction playback mode. The war game system can be used as an explanation tool to provide an analysis and research environment, deduce and research are carried out on combat scenarios, classic combat examples and new combat styles and battlemen, and valuable reference data and experience are obtained.

A method of training an artificial intelligence (AI) system, comprising: (a) displaying an initial version of a battlefield environment visualization showing at least one asset and two or more threats; (b) receiving from a user a threat level for each of the two or more threats; (c) displaying a subsequent version of the battlefield environment visualization in which the two or more threats have a subsequent geospatial relationship with respect to the at least one asset; (d) receiving from the user an updated threat level for at least one of the two or more threats for the subsequent version of the battlefield environment visualization; and (e) reiterating steps c and d at least once to create a training data set of updated threat levels for changing subsequent geospatial relationships of threats relative to the at least one asset.

The present invention discloses a method and system for predicting health attrition based on the Lanchester equation, wherein the method includes introducing a time lag function and random white noise into the Lanchester equation to obtain a health attrition prediction model, wherein the time lag function is used to represent the time delay of troop reinforcement, and the random white noise is used to represent the uncontrollable factors affecting the development trend of the war; setting initial simulation parameters; performing numerical simulation on the health attrition prediction model based on the initial simulation parameters by simulation software, and obtaining a distribution curve of attrition of both sides of the war. The present invention can more effectively simulate the war process and show the evolution of the battlefield situation. The predicted results of attrition can reflect the uncertainty of the war to a certain extent, thereby effectively improving the accuracy of health attrition prediction.

Provided are an information processing method, apparatus and system, a server and a storage medium, which relates to the field of game technologies; during simulation of an injury and death process of soldiers of an army in a battlefield, an actual damage value of a current attack is first determined; then, an expected death quantity of soldiers of an attacked army is determined according to the actual damage value, and the expected death quantity is sent to a client, such that the client plays a death action corresponding to the expected death quantity. Influences of a soldier species and a surviving soldier quantity are considered when the actual damage value is determined, and influences of the soldier species are also considered when the expected death quantity is determined based on the actual damage value.

The invention relates to the technical field of signal processing, in particular to a signal recovery method and device based on signal noise and sparse characteristics. The method comprises the steps of providing an improved OMP algorithm based on signal noise and sparse characteristics to perform preliminary signal recovery by comprehensively analyzing the characteristics of mobility, sparse signal processing capability, communication distance and the like of nodes in an alley battle, optimizing a signal recovery result by using an L1 norm penalty term, providing a self-adaptive adjustment technology to adapt to battlefield situation changes, and improving the signal recovery efficiency. Rapid and accurate recovery of sparse signals is realized, the quality and reliability of wireless communication signals in an urban battlefield are improved, and stable and reliable support is provided for military communication.

The present application relates to the technical field of game artificial intelligence, and particularly relates to a global deployment decision method and device for virtual objects, equipment and medium, the method specifically comprises: determining a first virtual object set, establishing a battle database for each first virtual object in the first virtual object set, and giving a second virtual object the permission to access the battle database of each first virtual object; based on the battle database, the second virtual object respectively acquires the role data of each first virtual object, and then according to the battlefield element of the current battlefield and the role data of each first virtual object, determines a third virtual object set and the deployment arrangement of each third virtual object in the current battlefield in the third virtual object set. The present application makes global decision judgment such as pre-battle deployment, in-battle analysis and post-battle summary, so that each virtual object on the field can make the optimal action.

The present invention discloses a high-precision hexagon grid long-range pathfinding method based on dynamic weighting in war games, specifically relating to the technical field of war game deduction, and comprising the following steps: matching a regular hexagon grid by using a Cube coordinate system, and obtaining battlefield dynamic change data of each regular hexagon grid, respectively evaluating the threat level and obstacle level of the regular hexagon grid, and dividing the nodes corresponding to the regular hexagon grid into normal nodes and obstacle nodes based on the evaluation results; adjusting the path weight of the path formed by two adjacent nodes, and finding the optimal path from the starting point to the ending point according to a preset long-range pathfinding algorithm; by collecting battlefield dynamic change data in real time and dynamically adjusting the threat index and terrain accessibility index of the nodes, the present invention enables the path weight to timely reflect the changes in the battlefield environment, improves the real-time performance and dynamic adaptability of path decision-making, and effectively deals with complex and changeable battlefield environments.

The invention relates to a multi-attribute task scheduling method with timeliness guarantee and application thereof. The multi-attribute task scheduling method is applied to pervasive edge computing. A distributed computing power sensing mechanism is adopted, an IPv6 expansion header is designed, computing power sensing is achieved in a broadcast mode, and task equipment is generated to detect surrounding resources and load conditions; according to the method, battlefield tasks are subjected to multi-attribute tasks according to actual conditions, an unloading decision is made by comprehensively considering factors such as calculation, storage, transmission and load conditions by using multi-attribute decisions according to different task types, and a TOP3 pre-inquiry process is added. According to the multi-attribute task scheduling method with timeliness guarantee and reference thereof, resources in a battlefield environment are fully utilized, the load condition in a battlefield scene is optimized, stable task unloading is guaranteed, the deterministic time delay requirement of a time delay sensitive task is met, and the task completion rate is increased.

The present invention belongs to the technical field of environment construction, and provides a method and system for constructing a fine battlefield environment based on digital twins. The method includes: controlling each drone to transmit the field image data or three-dimensional terrain data of each sub-area of ​​the battlefield area according to a preset patrol strategy; constructing a digital twin sub-model corresponding to each sub-area according to the received field image data or three-dimensional terrain data, aligning the coordinates of each digital twin sub-model, and constructing a preliminary first digital twin model; evaluating the probability of destruction of the drones in each sub-area based on the first digital twin model, determining the prediction step size according to the destruction probability, and predicting an updated digital twin sub-model according to the digital twin sub-model corresponding to the sub-area; adding the updated digital twin sub-model to the first digital twin model to obtain an updated second digital twin model. The present invention realizes the rapid and refined construction of the battlefield environment.

The invention discloses a gear transmission type historical war deduction sand table control mechanism, and relates to the technical field of sand table control, the gear transmission type historical war deduction sand table control mechanism comprises a sand table mounting seat, control mechanisms, models, a glass plate and a projector, the top of the sand table mounting seat is slidably connected with twelve groups of control mechanisms, and the control mechanisms are arranged; a tooth-shaped structure is used for accurately transmitting power, the motion direction and speed of the model are controlled, stable and accurate movement and rotation of the model are guaranteed, and the reliability and simulation precision of deduction sand table operation are improved; a flag mechanism is arranged, and the flag state is rapidly switched during position attribution, tactical deployment change and attack and defense situation conversion, so that a deducer can clearly control the battlefield dynamic state, the deduction efficiency and the battlefield situation visualization degree are improved, and accurate and smooth deduction is guaranteed; the lifting mechanism is arranged, three-dimensional dynamic simulation of topographic relief and unit height is achieved through upward or downward movement of the model, plane deduction is expanded into three-dimensional battlefield reduction, and the authenticity and visualization degree of tactical deployment are improved.

The application discloses an event extraction method and system fusing a graph attention network and a QA extraction paradigm, and aims at historical combat texts including military events. Based on a graph attention network and a classification mechanism, the historical combat texts are preprocessed, trigger words are recognized, and event argument role extraction is carried out, so that the text is processed, the accuracy of event extraction is improved, and the extraction efficiency of key information is improved and the time of command decision is shortened in a complex and changeable battlefield environment.

The invention discloses a field operation energy scheduling system based on a Markov chain structure, and relates to the technical field of battlefield energy scheduling, and the field operation energy scheduling system comprises an intelligent prediction module, an energy aggregation module, an energy routing module, a control module, a communication and monitoring module and an energy management module. The system has the advantages that the energy demand, the weather condition and the equipment state on the battlefield are monitored and predicted in real time through the intelligent prediction module, accurate prediction is performed by using the Markov chain model, dynamic networking and rapid scheduling of power resources are realized, the flexibility of a battlefield power system is improved, and the power utilization rate of the battlefield power system is improved. The system can quickly adjust power output according to real-time conditions, meets complex and changeable battlefield requirements, realizes quick transmission and distribution of electric energy through flexible configuration of the energy routing module, and further improves the response speed of the system.

Provided are a computer program product, a game device, and a game management device, which improve convenience and interestingness of a game. A program capable of executing a fighting game between a player and a fighting player. A program for causing a computer to function as: a battlefield selection unit that selects a player's desired field from among a plurality of types of fields; a battlefield presentation unit that presents a battlefield to be used in the battle game; and a battle game execution means that arranges the game elements in the battle field and executes a battle game between the player and the battle player. The battlefield presentation means presents the player and the site selected by the battlefield player as a battlefield on the condition that the site selected by the player and the site selected by the battlefield player coincide with each other.

The invention provides an automatic situation plotting method and device and electronic equipment, and the method comprises the steps: carrying out the key information extraction of an initial combat plan text based on a large language model, obtaining the key combat information in the initial combat plan text, and carrying out the retrieval in a military mark library based on the key combat information, obtaining an initial military mark corresponding to the key battle information, and plotting the initial military mark in a military map to obtain an initial situation map of a battlefield; and performing key information extraction on the received battlefield real-time data, and updating the initial situation map based on the extracted real-time key information to obtain a real-time situation map of the battlefield. Based on the combination of the large language model and the military standard library, the whole process automation from the battle plan to the real-time situation icon drawing update is realized, the battlefield situation awareness efficiency and accuracy are obviously improved, and powerful support is provided for command decision making.

The application discloses a kind of based on key event detection's wargaming process key battle method mining method and device, comprising: the multi-resolution situation feature abstraction of the wargaming data collected, obtain the battlefield situation feature set of combat unit under uniform dimension;Known key event in wargaming data is extracted based on battlefield situation feature set using weak supervision self-training method, and specific key event set is obtained;Based on battlefield situation feature set and specific key event set, new key event in wargaming data is extracted using new key event identification method based on deep hidden layer feature, and new key event set is obtained by labeling new key event;Each key event in specific key event set and new key event set is combined according to time sequence relationship, forms multiple battle method set, completes key battle method mining.The present application improves the timeliness and accuracy of key battle method mining.

The invention relates to a terrain key point selection method based on deep learning, and the method comprises the steps: carrying out the preprocessing of battlefield environment data in a combat area, and obtaining a feature value matrix; inputting the characteristic value matrix into a pre-trained terrain key point selection model, and selecting to obtain terrain key points in the region; the terrain key point selection model selectively pays attention to and processes the most important part based on an attention mechanism, ignores irrelevant or secondary information, and then comprehensively measures interrelation of terrain elements in a battlefield environment through a convolutional neural network to realize selection of terrain key points. The terrain key point selection method designed by the invention is not only high in accuracy and simple in structure, but also has the advantages of good mobility, few parameters and low calculation complexity, and has relatively high practical application value.

The present application belongs to the field of military simulation technology, and specifically discloses a battle example data conversion method, system and program product for war game deduction, which realizes the automatic conversion from multi-source heterogeneous battle example data to standardized and executable war game deduction plan through data preprocessing and element sequence extraction on the multi-source heterogeneous battle example data, and then script generation using the extracted element sequence, thereby improving the battle example data conversion efficiency and the intelligent level of war game deduction; through the fusion and conflict resolution of multi-source elements, high-precision element extraction can be realized, the accuracy of element extraction is ensured, and the battle game deduction example data conversion demand of complex battlefield scenes can be supported; and through the automatic battle example data conversion processing, manual intervention can be reduced, the efficiency and quality of battle example data conversion are improved, and the present application is suitable for large-scale battle example library.

The invention provides a method and system for mapping a battle environment through cooperation of an unmanned aerial vehicle and a robot, and relates to the technical field of military monitoring. A battlefield surface layer is obtained by calling a first graphic processing component according to a spherical radius and a rendering material; acquiring latitude and longitude data of each battlefield in the battlefield surface layer, and performing data format standardization; a geometric type component is called, the longitude and latitude data after format standardization is preprocessed to obtain a polygon data set, and one polygon data represents the longitude and latitude data of one battlefield; a projection conversion assembly is called, and two-dimensional graph contours and the like of all battlefields are obtained according to latitude and longitude conversion of the polygon data set; the state and the spatial distribution condition of the weapons are displayed in a three-dimensional mode through a digital visualization means, a digital display mode is provided for management of the weapons in the battle environment, and a battle environment visual system is promoted to have higher standardization and specialization.

A method of training an artificial intelligence (AI) system, comprising: (a) displaying an initial version of a battlefield environment visualization showing at least one asset and two or more threats; (b) receiving from a user a threat level for each of the two or more threats; (c) displaying a subsequent version of the battlefield environment visualization in which the two or more threats have a subsequent geospatial relationship with respect to the at least one asset; (d) receiving from the user an updated threat level for at least one of the two or more threats for the subsequent version of the battlefield environment visualization; and (e) reiterating steps c and d at least once to create a training data set of updated threat levels for changing subsequent geospatial relationships of threats relative to the at least one asset.

The invention provides a war display method and device, electronic equipment and a storage medium, and relates to the technical field of games. The method can comprise the steps that in response to a war report playback operation, attribute information of all virtual objects in a target historical combat round is obtained, and the attribute information comprises identifiers of all the virtual objects, three-dimensional coordinates of all the virtual objects in a combat scene and attack parameters of all the virtual objects; and according to the attribute information of each virtual object in the target historical combat round, displaying a three-dimensional combat interface, and displaying a three-dimensional fight scene of at least part of the target virtual objects in the target historical combat round on the three-dimensional combat interface. According to the embodiment of the invention, the three-dimensional fighting scene of at least part of the target virtual object in the target historical combat round can be displayed through the three-dimensional combat interface, so that the battlefield situation awareness of players is improved through the three-dimensional fighting scene, and the players can carry out three-dimensional strategy analysis and accumulate combat experience based on the three-dimensional fighting scene.

The present invention discloses a war game deduction and confrontation system for logistics support, which relates to the technical field of logistics support. The technical key points are as follows: It includes a map unit, an operator unit, a weapon system, a behavior system, and a deduction system; the operator unit includes logistics operators and combat operators; the behavior system includes a strike behavior unit, a logistics behavior unit, and other behavior units; the deduction system includes a deployment phase unit and a plan execution phase unit; the deduction rules of the deduction system include line-of-sight rules, reconnaissance rules, mobility rules, aircraft takeoff and landing rules, strike rules, battle damage rules, military transportation rules, fuel rules, military supplies rules, medical service rules, camp material rules, command post rules, and victory and defeat adjudication rules; the present invention facilitates the derivation of war game rules through long-term battlefield experience summary and formula deduction, quantitatively analyzes each part of the battlefield environment into parameters, and gives meaning to the values of various operators on the computer war game screen, making the conclusions obtained from war game deduction more in line with the actual battlefield.

The invention discloses a land battle scene data set generation method and device based on a Unity engine, and the method comprises the steps: S1, building at least one virtual local land battle battlefield environment in the Unity engine based on the Unity engine; s2, in each virtual local land battle battlefield environment, setting of a preset actual combat scene is completed, multiple preset target parameters are correspondingly set, and the multiple target parameters at least comprise environment parameters, equipment parameters and camera shooting parameters; and S3, controlling the Unity engine to run a preset actual combat scene, and generating an environment reconstruction data set. On the premise that a scene and an equipment model with relatively high authenticity can be obtained, the method has the advantages that a large amount of image data which can be used for training a neural network can be generated in a virtual land battlefield environment; the difficulty of acquiring land battlefield data in reality and the huge workload of marking massive image data are avoided, so that the efficiency of training related neural networks is improved.