138results about How to "Reduce resource requirements" patented technology

The invention discloses a method for analyzing a matching degree between a demand and an output result based on text semantics. The method comprises the following steps: step 1, labeling a data set; step 2, technical document preprocessing; 3, training and predicting a single-parameter model; 4, integrating prediction results of the multi-parameter model; the method has the beneficial effects thatthe method is simple; deep learning and the NLP technology are applied to the field of project association degree calculation of enterprise project management for the first time. Calculating an association matching degree between the two projects according to project requirements and result description; the associated project positioning difficulty is effectively reduced; meanwhile, the demand side can be helped to quickly and efficiently locate high-quality projects adapting to the demand of the demand side; time and resource investment for achievement screening and matching are greatly reduced, the association matching degree between projects is calculated by means of text data of existing project achievement technical documents and project declaration guidelines, and then large enterprises are assisted in screening high-quality projects with the high matching degree in the project bidding and tendering link.

The invention relates to the technical field of multi-agent systems, and discloses a multi-agent and multi-mode alignment interaction method and system for a review scene, and the method comprises the steps: mapping real-time multi-mode data into a local belief vector through a heterogeneous agent cluster, and calculating the spatial divergence to determine a global cognitive entropy; interaction time sequence gating logic based on entropy flow differential is established, and active alignment is triggered when the global cognitive entropy is larger than a convergence threshold value and a first-order derivative is smaller than a damping threshold value; according to the method, through entropy flow differential control and an active semantic disturbance closed loop, decision oscillation of the multi-agent system in the non-cooperative environment is eliminated, and the reliability of the multi-agent system in the non-cooperative environment is improved. Mathematical convergence of the belief state in an adversarial disguise scene is realized, and the system identification precision in a complex interactive game is improved.

The invention provides a multi-process-mode intelligent switching method and system for vehicle-mounted sludge treatment, and the method comprises the steps: carrying out the time-space alignment and standardization of multi-dimensional sensing data such as sludge characteristics, environmental parameters and equipment states, carrying out the real-time reasoning of a process switching critical value through combining with a lightweight incremental regression model, generating a self-adaptive threshold value band with a confidence interval, and carrying out the real-time reasoning of the process switching critical value. Dynamic monitoring and mode switching pre-judgment of actual operation parameters are realized; in the switching process, a weighted fusion progressive transition control strategy is adopted, the transfer rate is adaptively adjusted according to real-time feedback, the operation stability is guaranteed, and the intelligence, reliability and switching smoothness of process switching of the vehicle-mounted sludge treatment system are remarkably improved.

The application provides a logistics transportation management method and system based on artificial intelligence, relates to the field of logistics transportation, and solves the technical problems that the prior art is difficult to balance real-time performance, distribution feasibility and resource utilization efficiency in the sudden interruption scene of a logistics vehicle, resulting in slow scheduling response, frequent secondary conflicts or failure of high-value order fulfillment. The method comprises the following steps: obtaining a set of orders to be delivered by a target vehicle at present and real-time position information; based on a preset hard constraint condition, screening candidate vehicles and constructing a task migration feasibility graph; inputting the task migration feasibility graph into a pre-trained lightweight graph neural network model to output the compatibility scores of each candidate vehicle for each order to be delivered in the order set; based on the compatibility scores, evaluating the urgency of the order to be delivered; and based on the urgency of the order to be delivered, updating the delivery task scheme of each candidate vehicle. The application is used in the process of logistics transportation.

The application relates to the technical field of network resource management and the technical field of reinforcement learning, and discloses a spectrum decision method, device and equipment based on a double-graph structure and reconstruction cost, which comprises the following steps: inputting original state data of low-altitude intelligent networking into an actor network of a reinforcement learning architecture, generating a predicted spectrum decision scheme of the low-altitude intelligent networking through the actor network, and obtaining an expected reward value output by a critic network based on the original state data and the predicted spectrum decision scheme; determining a trained actor network based on the expected reward value and an actual reward value; and generating a target spectrum decision scheme of the low-altitude intelligent networking based on a current double-graph structure and the trained actor network. The application can improve the generation efficiency of the target spectrum decision scheme of the low-altitude intelligent networking.

This invention discloses a device for recycling and reusing leather processing waste, belonging to the field of leather processing waste treatment technology. The device includes a frame, on which are mounted a feeding hopper, a dual-shaft crushing mechanism, a negative pressure adsorption chamber, and a dust recovery assembly. The dual-shaft crushing mechanism includes a crushing shaft with anti-entanglement blades, an elastic scraper ring, and a reciprocating feeding rod, with a pull-out screen below. The negative pressure adsorption chamber is connected to the dual-shaft crushing mechanism via a connecting duct. The dust recovery assembly includes a cyclone separator, a filter cartridge, and a dust collection box connected in sequence. A compression chamber with an automatic top-loading plate is located below the dust collection box. This invention effectively solves the problem of waste entanglement and blockage through the synergistic action of the anti-entanglement blades, the elastic scraper ring, and the feeding rod; negative pressure adsorption combined with cyclone separation and filtration improves recycling efficiency and reduces dust pollution; the automatic top-loading and shaping of the compression chamber facilitates transportation and reuse. It has the advantages of high automation, high recycling efficiency, and good environmental performance.

The application belongs to the technical field of advertisement pushing, and discloses an advertisement intelligent putting system and method based on specific user driving: demand expressions voluntarily submitted by users are collected, characteristic elements of each expression item are extracted, and a demand expression characteristic set is obtained; multi-layer condition discrimination is performed on the demand expression characteristic set, and uncoordinated expression items are removed, so that a preliminary putting demand set is obtained; situation derivation enhancement is performed, so that a complete putting demand set is obtained; core expression item data of adjacent demand sequences are extracted, and sequence mapping and fusion processing are performed, so that a persistent preference guidance group is obtained; peripheral expression item data is extracted, and an instant change coordination group is constructed; the peripheral expression items in the complete putting demand set are matched and adjusted, so that an adaptive putting advertisement set is obtained; and the precision marketing efficiency of advertisement intelligent putting is greatly improved.

The application discloses a kind of current transformer wire breakage fault positioning processing method and system, method includes: in protection device, additional redundant current transformer;With current mutation variable, real-time calculation N line and current amplitude and N line and current mutation variable amplitude;Set criterion, judge N line and current amplitude whether greater than flow threshold value, identify whether the stable CT wire breakage occurs outside protection device;And, judge N line and current mutation variable amplitude whether greater than mutation variable threshold, identify whether the intermittent CT wire breakage occurs outside protection device;According to the discrimination condition of conventional differential protection CT wire breakage, and in combination with criterion distinguishes wire breakage position, again in combination with three-phase CT sampling balance and distinguish result, determine the phase of specific CT wire breakage and position.The application has less demand to hardware resource, can distinguish whether CT wire breakage occurs in device CT primary side or secondary side, and according to fault position, provide corresponding processing mode.Improves the reliability of differential protection.

This application provides a resource planning method, apparatus, electronic device, medium, and program product, which can be applied to the fields of cloud computing technology and artificial intelligence technology. The method includes: acquiring resource observation information and knowledge representation information of a target sub-institution, wherein the knowledge representation information is information generated or provided by multiple teacher models constructed by multiple sub-institutions based on local resource usage history information, and the knowledge representation information includes model parameters and / or soft labels; determining teacher knowledge suitable for the target sub-institution based on the resource observation information and knowledge representation information; training or updating the student model of the target sub-institution based on the teacher knowledge to obtain a resource prediction model; obtaining resource usage prediction results based on the resource observation information and resource prediction model; and generating resource planning suggestions based on the resource usage prediction results.

This application belongs to the field of chemical equipment maintenance management technology, specifically providing a predictive maintenance management system for the entire lifecycle of chemical equipment. It mainly includes: a data standardization module: acquiring at least three operating parameters of the target chemical equipment within a first time period, standardizing these parameters to obtain standardized operating parameter data; and a coupling analysis module: based on the standardized operating parameter data, analyzing the dynamic coupling relationship between multiple operating parameters, and calculating the real-time correlation coefficient between parameter pairs to form a real-time correlation matrix. This application effectively solves the problem in existing technologies where maintenance methods struggle to identify early potential problems from subtle changes in parameter correlations. It achieves dynamic and accurate assessment of equipment health status, provides a comprehensive basis for maintenance decisions, reduces resource waste and failure risks, and improves the adaptability of the maintenance system.

This disclosure provides a data processing method, apparatus, and computer device based on butterfly networks, relating to the fields of artificial intelligence and hardware acceleration technology. The solution is as follows: In a switchable data processing architecture including an inverse butterfly network, a preprocessing module, a post-processing module, and a control signal generation module, when switching to aggregation operation, the preprocessing module inputs the first input data into the inverse butterfly network, the control signal generation module outputs the first control signal to complete data processing, and the post-processing module directly outputs the aggregation result. When switching to distribution operation, the preprocessing module performs input position mapping and filling on the second input data to obtain the third input data, the control signal generation module outputs the adapted second control signal to complete data processing, and the post-processing module performs rearrangement on the intermediate results to output the distribution result. This reduces hardware resource consumption, lowers control complexity and processing latency, and improves the hardware deployment adaptability of neural network sparse computing while ensuring functional integrity.

The application discloses a spherical decoding detection method and device, electronic equipment and a readable storage medium, and belongs to the technical field of wireless communication. The application obtains a Q matrix and an R matrix by performing orthogonal triangular QR decomposition on a channel response matrix, wherein each column in the Q matrix is arranged according to the size of channel energy; determines a target equalization signal according to the Q matrix and the R matrix; performs an ML path search process according to the target equalization signal to select N branches with minimum metrics as survivor paths; performs ML complement path search on the survivor paths to obtain ML complement paths; takes the survivor paths with minimum metrics as ML paths, and obtains the likelihood ratio information of each bit of each symbol at each layer according to the ML paths and the ML complement paths. The application can reduce the operation complexity of the spherical decoding algorithm while maintaining the decoding detection performance.

The invention belongs to the technical field of deep space exploration, and particularly relates to a multispectral image displacement depth adaptive mapping method and system based on radiometric calibration, and the method comprises the steps: obtaining original black field data with the input bit depth being N and original flat field data with the input bit depth being N; after bad pixels are shielded according to the original black field data and the original flat field data, row offset and row response are calculated; sequentially determining a global scale according to the row offset and the row response, calculating an integration slope, and generating a lookup table according to the integration slope; and acquiring real-time monitoring input, reading the M-bit output value corresponding to the real-time monitoring input according to the lookup table, and correcting and updating the lookup table according to the M-bit output value. Based on a parameterized calculation process (derivation from row bias and row response to a global scale and an integrated slope), different input bit depth and output bit depth requirements can be met by modifying input parameters, inherent limitation caused by hard coding is avoided, and the configurability of cross-platform tasks is improved.

This invention relates to the field of image generation technology, and more particularly to a method for generating bird's-eye view images of reservoir landscapes based on a Stable Diffusion large model. The method includes the following steps: preprocessing acquired reservoir landscape images and semantically annotating them based on water conservancy terminology to construct an image-text pairing dataset; training a pre-trained Stable Diffusion model, incorporating LoRA adaptation parameters into its UNet attention layer, using the image-text pairing dataset to generate a target feature image; and updating the LoRA adaptation parameters based on the difference between the target feature image and the reservoir landscape image to obtain a LoRA model for the reservoir landscape bird's-eye view image. This invention achieves structurally controllable and semantically consistent reservoir landscape generation by fusing structural reference constraints and semantically weighted alignment and introducing LoRA modulation.

The utility model relates to the technical field of petroleum pipeline valve bodies, and discloses a petroleum pipeline valve body convenient to maintain, which comprises a valve body and a rotary handle mechanism, a first connecting flange is fixedly mounted on one side of the valve body, a second connecting flange is fixedly mounted on the other side of the valve body, and a connecting mechanism is fixedly mounted on the upper surface of the valve body. A mounting mechanism is fixedly mounted on the outer surface of the rotary handle mechanism, and the connecting mechanism is connected with the mounting mechanism. Through the arrangement of the connecting mechanism and the mounting mechanism, the situation that the rotating handle mechanism can be detached from the upper surface of the valve body for maintenance only by detaching a plurality of bolts is avoided, and the maintenance efficiency is improved.

The utility model discloses a modularized buoyancy tank platform for water operation, which comprises a buoyancy tank module and a connecting component, a plurality of connecting grooves are arranged along the peripheral side wall of the buoyancy tank module, and the connecting grooves extend from the top of the buoyancy tank module to the bottom of the buoyancy tank module; the connecting assemblies can be inserted into the two opposite connecting grooves in the vertical direction. The connecting assembly comprises a first locking piece and a second locking piece, the first locking piece is located at the bottom of the second locking piece, the second locking piece comprises a connecting block, an opening assembly and a clamping assembly, a containing cavity is formed in the connecting block, the opening assembly is arranged in the containing cavity in the vertical direction, and the clamping assembly is arranged in the containing cavity in the horizontal direction; the opening assembly is located at the top of the clamping assembly. When the modular buoyancy tank platform is assembled, the purpose of connecting the buoyancy tank modules is achieved by inserting the connecting assemblies into the opposite connecting grooves of the adjacent buoyancy tank modules, when the modular buoyancy tank platform is disassembled and assembled, the connecting assemblies are taken out of the connecting grooves after the fastening connection between the connecting assemblies and the connecting grooves is removed, and the disassembling and assembling efficiency of the modular buoyancy tank platform is improved.

The invention discloses a modularized split type intelligent water surface monitoring and processing system and method. Comprising a mobile monitoring unit, a control center and a processing unit, the mobile monitoring unit is used for carrying out hydrological monitoring on a predetermined water area in real time and transmitting the monitoring combination back to the control center; the mobile processing unit is used for receiving the control signal to maintain a predetermined water area; and the control center is used for outputting a control signal according to a monitoring result of the mobile monitoring unit to control the appointed processing unit to go to a preset water area for processing. According to the invention, through the split and modular design of the sensor and the processing equipment, configuration as required and flexible assembly are realized. The same set of system infrastructure can be quickly adapted to multiple scenes such as lake blue-green algae emergency treatment, channel oil stain cleaning, park garbage salvage, wetland water quality dynamic monitoring, drowning personnel rescue and the like by replacing different sensors and processing modules, and the application range of the system is greatly expanded.

This application relates to the field of vehicle-related technology, and discloses a method, apparatus, equipment, and vehicle for vibration modal analysis of a vehicle spoiler. The Z-axis dimension of the target portion in the X-direction cross-section of the spoiler is smaller than the Z-axis dimensions of its two side portions. The method includes: substituting the free end overhang length, intermediate cavity height, elastic modulus, and material density of the spoiler into a preset simplified estimation formula for calculation, and outputting a first-order vibration modal estimation value; the intermediate cavity height is the Z-direction cross-sectional height at the narrowest cavity of the spoiler; the preset simplified estimation formula satisfies that: the square of the first-order vibration modal estimation value is directly proportional to the product of the elastic modulus and the square of the intermediate cavity height, and inversely proportional to the product of the material density and the fourth power of the free end overhang length; based on the first-order vibration modal estimation value, the vibration modal analysis result of the spoiler is determined. Applying the technical solution of this application can solve the problems of high analysis resource consumption, low efficiency, and high cost currently existing.

The application discloses a tunnel construction process automatic monitoring method, and belongs to the technical field of tunnel engineering construction monitoring. The method comprises the following steps: step 1, automatic monitoring equipment is arranged at key positions of a tunnel opening area, an advanced support section, an excavation face, an initial support structure, a waterproof layer construction area and a secondary lining structure; step 2, each automatic monitoring equipment is started, and monitoring data is collected at a preset sampling frequency; step 3, after receiving the monitoring data, a central monitoring platform uses a big data analysis algorithm to deeply process the monitoring data; and step 4, the central monitoring platform feeds back monitoring results and early warning information after analysis to a tunnel construction control system in real time. The application realizes real-time data acquisition and analysis through 5G technology, especially the UWB positioning system collects data once per second, realizes instant acquisition and analysis of monitoring data, and compared with traditional manual monitoring, the data update frequency is improved by tens of times, and abnormal conditions in the construction process can be found in time.

The invention relates to the technical field of composite material structural members, in particular to a design and construction method for recycling GFRP rib concrete beams of retired fan blades. A recycled GFRP (glass fiber reinforced plastic) reinforced concrete beam for retired fan blades comprises a concrete beam body, the bar framework is arranged in the concrete beam body and comprises at least two GFRP longitudinal stress bars arranged in the length direction of the concrete beam body and GFRP stirrups fixedly connected with the GFRP longitudinal stress bars and arranged in the length direction of the concrete beam body at intervals; wherein the GFRP longitudinal stress bars and the GFRP stirrups are all made of waste fan blade composite materials through mechanical recovery. The mechanically recycled GFRP rib material is used for replacing a traditional steel bar to serve as a stress bar of a concrete beam body, the environment pressure brought by large-scale composite material waste can be effectively relieved through recycling of the retired fan blade, conversion from a retired material of new energy equipment to a structural engineering material is achieved, and development of low-carbon circular economy is promoted.

The present application relates to the technical field of vehicle-mounted power supply, and particularly relates to a vehicle-mounted power supply module with intelligent adaptation and regulation module, which comprises a vehicle-mounted power supply module and an external assembly shell, the external assembly shell is composed of a plurality of sub-assembly shells, the vehicle-mounted power supply module is installed in the sub-assembly shell, and the sub-assembly shell comprises a bottom main receiving seat, an electrically-controlled external closing cover and an intelligent regulation assembly installed in the bottom main receiving seat. The vehicle-mounted power supply module with intelligent adaptation and regulation module adopts a modularized external assembly shell, cooperates with a clamped vehicle-mounted power supply module mounting structure, replaces a traditional glue bonding and multi-bolt fixing mode, realizes quick disassembly and assembly of the power supply module, does not need special tools, improves production and assembly efficiency and post-maintenance convenience, and avoids damage to the module in the disassembly and assembly process.

This invention discloses a RISC-V-based method for autonomous pedestrian localization, comprising the following steps: acquiring three-dimensional pedestrian motion data from accelerometer and gyroscope sensors; calculating attitude angles and transforming these angles from the carrier coordinate system to the navigation coordinate system using a coordinate transformation matrix; performing inertial navigation fundamental calculations based on the pedestrian motion data, attitude angles, and coordinate transformation matrix to determine the pedestrian's current attitude, velocity, and position; performing zero-velocity detection based on a neural network to determine if the pedestrian's current state is at a zero-velocity point; if so, proceeding to the next step; otherwise, returning to the first step; updating the pedestrian's current attitude, position, and velocity using a Kalman filter (EKF); and completing autonomous pedestrian localization based on the updated attitude, position, and velocity. This invention reduces noise errors, computational load, and processor execution time and resources, and exhibits good portability.

This invention proposes a key detection circuit and a key detection method. The circuit includes: a first key detection module, comprising m pull-up / pull-down branches and one pull-down branch, with the m pull-up / pull-down branches connected in parallel. Each pull-up / pull-down branch has an input / output interface, and the input / output interface is connected to the pull-down button in the pull-down branch via a series-connected first diode; and a second key detection module, comprising N key detection units, each key detection unit being connected to one of the q input / output interfaces in the first key detection module via q input / output terminals, with each key detection unit having a different connection method to the first key detection module. This key detection circuit allows for the connection of multiple buttons, diodes, and pull-up resistors with fewer input / output ports, thereby improving the efficiency of input / output port utilization, reducing the resource requirements of the processor's input / output ports, and lowering the overall cost.

The utility model discloses an end plate processing positioning jig, which relates to the technical field of positioning jigs and comprises a base, a sucker plate is fixedly connected onto the base, and the edge of the sucker plate is provided with a clearance portion corresponding to a workpiece processing track. A floating positioning pin and a positioning clamping block are arranged on the two adjacent sides of the suction cup plate respectively, the floating positioning pin is driven by a driving mechanism to ascend and descend, the positioning clamping block is fixedly connected with the base, a movable clamping block is arranged on the side, away from the positioning clamping block, of the suction cup plate, and the movable clamping block and the positioning clamping block are matched to be used for clamping a workpiece. According to the end plate machining and positioning jig, occupied machine resources and manpower resources are reduced, and the labor intensity is lowered; cutter machining cannot be interfered, and jig damage is avoided; and multiple positioning structures are arranged for co-positioning, so that the positioning effect is good.

The invention belongs to the technical field of mobile communication, and particularly relates to a mobile communication terminal network switching method and system, and the method comprises the steps: collecting multi-dimensional network parameters and terminal state parameters; judging the working mode of the terminal and dynamically distributing parameter weights; pre-judging a source network state through a machine learning model, and screening a target network; establishing a pre-connection channel, and executing differentiated seamless switching; generating a feedback result, inhibiting ping-pong switching and optimizing the model; and multi-terminal collaborative switching is supported. The system comprises functional modules on a terminal side and an optional cloud auxiliary module. Core logic of multi-dimensional decision making, active pre-judgment and seamless switching language feedback optimization is adopted, switching precision, real-time performance and low power consumption are achieved, switching delay is smaller than or equal to 50 ms, the ping-pong switching occurrence rate is reduced by more than 80%, hardware does not need to be newly added, and the method is suitable for various mobile communication terminals and application scenes.

The invention relates to a scheduling method which schedules deep learning jobs through a primitive-dual framework and a dynamic programming algorithm in a heterogeneous GPU cluster and can meet different deadline requirements of the jobs. According to the method, on-line analysis and historical data are combined in a heterogeneous GPU cluster environment, so that the overhead of obtaining the job throughput is reduced; according to the method, job scheduling and job placement are decoupled, the complexity of job scheduling is reduced, meanwhile, a simple and effective job placement scheme is designed, and the degree of resource fragmentation is effectively reduced; a scheduling target is modeled in a scheduling module, reward value functions are respectively designed for strict deadline operation and soft deadline operation, an optimization problem is constructed by taking maximization of an overall reward value as the scheduling target, and strict deadline requirements and soft deadline requirements of the operation are considered at the same time; and reconstructing the target optimization function into an integer linear programming problem, and solving by using a primitive-dual framework and a dynamic programming algorithm to ensure the theoretical effectiveness of the solution.

The application discloses a kind of based on multi-source fusion and reinforcement learning's composite material additive manufacturing adaptive control method, first in printing process Synchronous acquisition space position, infrared temperature, tension and compression force and multi-source sensor data such as visible light image;Through the lightweight perception module constructed to each road data is parallelly processed and feature extraction, to force data adopts second-order difference to carry out state discrimination, to temperature data adopts multistage threshold segmentation and extracts forming area statistical feature, and reward feature is generated in combination with image recognition and position mutation detection;The multi-dimensional state features after fusion are combined with reward function, and the agent is trained using reinforcement learning algorithm to learn the optimal printing parameter decision strategy;The trained agent is used for real-time control, and the best printing speed and layer thickness instruction are dynamically output to the mechanical arm according to the current state. The application realizes accurate description and real-time adaptive control of complex multi-physical field coupling process, effectively improves printing quality and process stability.

The invention discloses an intelligent report generation system and method based on knowledge graph enhancement, and belongs to the technical field of natural language processing and knowledge graph fusion. In order to solve the problems of insufficient accuracy, low efficiency and opaque reasoning process in the existing structured report generation only depending on large model intrinsic knowledge, the method comprises the following steps of: constructing a knowledge graph containing entities, attributes and relationships, and converting a user natural language problem into a structured query statement by utilizing a first large model; after an entity relationship result is obtained in the knowledge graph, a report with a clear basis is generated by the second large model; and adaptation can also be realized through query languages. By means of structured knowledge and efficient query of the knowledge graph, the accuracy and generation efficiency of the report conclusion are improved, the reasoning process is traceable, meanwhile, the flexibility and universality of the scheme are enhanced, and the method is suitable for structured report generation scenes such as enterprise data analysis and industry research.

This invention discloses a heterogeneous hybrid expert large model architecture and alignment method for high-concurrency online medical dialogue. First, the method proposes a dual-pool heterogeneous routing strategy of "4 general experts + 2 departmental experts." Through physically isolated parallel routing channels, it forces the model to simultaneously activate general language capabilities and specialized medical reasoning when processing input, fundamentally ensuring the focus and professionalism of responses. Second, it adopts a structural evolution strategy based on parameter expansion and selective freezing. By completely freezing the pre-trained basic parameters and training only newly added departmental experts, it completely eliminates catastrophic forgetting. Finally, in the model alignment stage, it employs the Group Relative Policy Optimization (GRPO) algorithm for valueless models to reduce memory overhead and designs a dual-track hybrid reward function combining low-level semantic similarity rewards and high-level structured large model referee scoring, effectively solving the "reward hacking" problem and guiding the model to generate refined responses that combine clinical accuracy and humanized interaction. This invention significantly improves the performance of medical dialogue systems. Its sparse activation and parameter freezing characteristics further ensure low latency and high throughput in online high-concurrency scenarios, providing a complete solution for the deployment of reliable medical dialogue systems.

The invention relates to the technical field of Internet of Vehicles, and discloses a resource allocation method, a resource request method and a storage medium, and the resource allocation method comprises the steps: obtaining a target instance type requested by a target vehicle-mounted terminal; selecting a basic resource instance matched with the target instance type from the resource pool as a target resource instance, and allocating the target resource instance to the target vehicle-mounted terminal, so that the target vehicle-mounted terminal applies the target resource instance; the resource pool comprises basic resource instances of at least two instance types. According to the application, the basic resource instance of the corresponding type matched according to the request of the target vehicle-mounted terminal can be allocated to the target vehicle-mounted terminal, so that allocation according to needs is realized, and the overall utilization rate of resources is improved.