42results about How to "Reduce build time" patented technology

The invention relates to the technical field of information retrieval, in particular to a large-scale semantic retrieval optimization method based on deep learning, which comprises the following steps: acquiring to-be-retrieved text data, and converting the to-be-retrieved text data into semantic vector representation through a deep learning model; carrying out topological structure analysis on the semantic vector representation to obtain topological characteristic information of a semantic space; on the basis of the topological characteristic information, a topological perception hierarchical navigable small-world graph index with a multi-layer structure is constructed, and each layer comprises a node set and a connection relation thereof; dynamically optimizing and adjusting the topology-aware hierarchical navigable small-world graph index according to an actual query mode and system performance feedback; and receiving a query request, converting the query request into a query vector, executing multi-layer navigation search in the topology-aware hierarchical navigable small-world graph index, and returning a retrieval result related to the semantics of the query vector.

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.

Embodiments of the present application provide a check matrix generation method, device and electronic equipment. The check matrix generation method comprises: generating a plurality of reference check matrices based on target configuration parameters and error correction performance requirements; generating a plurality of mapping tables corresponding to different parameter combinations based on the target configuration parameters, constraint conditions of an LDPC encoder and constraint conditions of an LDPC decoder; adjusting the plurality of reference check matrices based on the plurality of mapping tables to obtain adjusted check matrices; and checking the adjusted check matrices, and taking an adjusted check matrix that passes the check as the target check matrix, which can shorten the check matrix generation time and reduce the computing power consumption.

The invention discloses a decision-making system and method based on a Dores database, and the system comprises a data access layer which is used for accessing multi-source heterogeneous financial data in real time, a Dores storage calculation layer, and achieves the data storage, column-type bucket separation and materialized view pre-calculation based on the Dores database; the visual application layer is used for providing bidirectional interactive financial data visualization and decision support; wherein the data access layer acquires data in real time through a streaming computing engine and transmits the data to the Dores storage computing layer, and the visual application layer performs real-time data interaction with the Dores storage computing layer through a two-way communication protocol. According to the method, the synchronous delay of financial data is shortened from 6 hours to 1 second, second-level real-time integration is realized, the aggregation query response time of billion-level data is reduced to be within 1 second based on a Dores column type storage and materialized view technology, the user interaction response delay is lower than 500 milliseconds through WebSocket two-way communication, and real-time adjustment of parameters and dynamic refreshing of a billboard are supported.

This application discloses a low-altitude defense platform deployment system and method. The system includes: a data acquisition module for acquiring relevant data of the defense area and information on available platforms; a capability quantification module for uniformly quantifying the capability parameters of each platform to obtain standardized capability descriptions; an AI agent search module, comprising multiple parallel-working AI agents and a shared memory area; each AI agent iteratively executes the generation of candidate deployment schemes, calculation of constraint violations, and evaluation of comprehensive performance scores, and updates the locally optimal deployment scheme based on the evaluation results, exchanging scheme information through the shared memory area to guide subsequent searches; and a scheme determination module for determining the globally optimal deployment scheme when termination conditions are met. This application improves the comprehensive protection effectiveness and planning efficiency of heterogeneous defense platform deployment schemes through capability quantification and multi-agent parallel collaborative search, achieving automated global optimization deployment under complex constraints.

The invention discloses a GPU-based graph vector index construction method and device and a storage medium, and relates to the technical field of graph index construction. The method comprises the following steps: fragmenting an original data set based on a clustering algorithm to obtain a first preset number of fragmented data subsets; sending the ith fragmented data subset to the GPU, wherein i is a positive integer; constructing a local graph vector index of the ith fragmented data subset in the GPU; sending the (i + 1) th fragmented data subset to the GPU until all local graph vector indexes are obtained; and constructing a hierarchical global graph vector index according to all the local graph vector indexes. According to the method, the production line of the producer-consumer model is constructed, so that the data transmission time of the PCIe bus is completely covered by the calculation time of the GPU, the I / O bottleneck is eliminated, and the construction speed of the graph index is improved.

The utility model discloses an assembly type telescopic tower crane man access platform device, including nested keel, cross bracing keel and antiskid steel sheet, the nested keel includes first square tube and second square tube, and the second square tube is inserted to the first square tube, is used for telescopic adjustment nested keel's overall length and is fixed through high -strength bolt connection, and a plurality of cross bracing keels are connected between two nested keels, and the cross bracing keel is flush with the top surface of the nested keel, and the antiskid steel sheet is laid on the nested keel and the cross bracing keel. The utility model solves the problem that traditional tower crane man access builds low efficiency, poor adaptability, insufficient safety, has the advantages of convenient assembly, telescopic adjustable, high reusability, safe and reliable, can be adapted to different models tower crane and construction working condition, effectively promotes construction safety and operation efficiency.

This application relates to the field of multimodal technology, and discloses a method, apparatus, device, and storage medium for point cloud generation based on multimodal information. The method includes: generating a first loss of a point cloud generator based on a first predicted point cloud set, a first real point cloud set, and a first loss model; generating a second loss of the point cloud generator based on a second predicted point cloud set, a second real point cloud set, and a second loss model; generating a third loss of the point cloud generator based on a third predicted point cloud set, a third real point cloud set, and a third loss model; generating a total loss based on the first loss, second loss, third loss, and a total loss function; and generating a complete point cloud of the object to be completed based on a cross-fusion module, a seed generator, and an updated point cloud generator when the total loss meets preset conditions. This application can take into account the overall outline, main structure, and local details of the object to be completed, which is beneficial to improving the generation effect of the complete point cloud of the object to be completed.

This invention relates to the field of container loading optimization technology, and particularly to a container loading optimization method and system considering palletizing. The method includes setting container information, palletizing constraints, and cargo information; generating available pallet sizes and corresponding stack shapes; eliminating stack shapes with bottom coverage below a threshold; using the selected stack shapes to form transverse pallets that meet preset requirements; establishing a mathematical model and solving it using integer programming to obtain an initial loading scheme; performing mixed pallet loading on the remaining container space and remaining cargo, ensuring that the mixed pallet loading meets the requirements of full pallet coverage and full support; generating the mixed pallet loading result and a three-dimensional visualization model. This invention incorporates the entire palletizing-related calculation process into the optimization algorithm to solve the technical problems of cumbersome, inefficient, inaccurate, poor space utilization, and high labor costs in existing container loading calculation processes.

The invention discloses a turbine cold air hole structured grid rapid generation method, which comprises the following steps: acquiring mainstream computational grid data of a target turbine blade, and determining corresponding geometric feature parameters according to the cold air hole type of a target cold air hole; inputting the geometric characteristic parameters into a parameterized geometric model corresponding to the target cold air hole type to generate parameterized cold air hole geometry; based on the mainstream computational grid data, geometrically positioning the parameterized cold air holes to the surface of a target turbine blade; performing adjacent geometric interference check and processing on the parameterized cold air hole geometry; and calling a corresponding preset grid topology division strategy according to the type of the target cold air hole passing the adjacent geometric interference check, and generating a structured hexahedral grid attached to the boundary of the mainstream computational grid. According to the method, a high-quality structured grid is quickly and automatically generated according to a cooling geometric structure.

The invention provides a power grid dispatching method, a control device and a storage medium, and belongs to the technical field of power grids. The method comprises the following steps: inputting acquired operation data into a multi-objective optimization model to output an optimization scheduling variable; performing constraint condition verification on the optimal scheduling variable, when the optimal scheduling variable meets a preset constraint condition, generating a scheduling scheme of the target power grid, and issuing a scheduling scheme instruction; in the process that the target power grid executes the scheduling scheme instruction, monitoring an operation index of the target power grid; and calculating the deviation between the monitored operation index and the optimization target, and when the deviation exceeds a preset threshold value, adjusting the scheduling scheme of the target power grid. Through a technical path of offline training and online reasoning of the neural network, the generation time of the scheduling scheme is greatly shortened, and real-time response to dynamic change of the power grid is realized.

The application discloses a numerical simulation method for spray combustion of an aero-engine combustion chamber, and belongs to the technical field of simulation of spray combustion of an aero-engine combustion chamber. The numerical simulation method is based on an adaptive matching iterative solution control mechanism of liquid droplet and flow field motion scale to perform outer circulation; starting from mixed fraction definition and component transport, a coupling relationship between fuel evaporation and combustion is established by deducing mixed fraction source terms and component transport equation source terms under different definitions, so that the numerical simulation method has high-fidelity coupling simulation capability of flow-spray-combustion; the RCCE method is introduced to establish a flame surface database, a large number of components in a chemical reaction mechanism are mapped to a limited number of constraint variables for dimension reduction solution, and a constraint equilibrium state is obtained according to the maximum entropy principle, and finally, the concentration of each component is reconstructed by using a constraint potential energy; while ensuring the accuracy of key chemical thermodynamic coupling, the generation efficiency of a complex fuel chemical reaction database is improved.

The invention discloses an output method based on 32-bit single-chip microcomputer firmware upgrade memory anti-overflow protection, and relates to the field of single-chip microcomputer memory anti-overflow protection, and the method specifically comprises the following operation steps: S1, environment variable configuration and management; s2, performing core execution of the Python automatic script; s3, performing anti-overflow protection on the memory; and S4, cleaning redundant files and environment variables. According to the output method based on the 32-bit single-chip microcomputer firmware upgrade memory anti-overflow protection, the file path is defined as the environment variable and stored in the independent configuration file in a centralized mode, complete separation of the path and script logic is achieved, the non-transplantable problem caused by a hard coding path is avoided, meanwhile, the adaptation cost in different environments is reduced, and the adaptation efficiency is improved. Operators do not need to modify script codes and only need to adjust configuration files to complete deployment.

The application discloses a method for enhancing position monitoring of a closed space PNT network and a high-precision map, and relates to the field of wireless positioning. The method comprises the following steps: establishing a semantic unit grid of a target closed space; establishing a mapping relationship database of semantic information of any one entity object element and position information of the semantic unit where the entity object element is located; acquiring a grid code of a semantic unit where a target entity object is located; and obtaining position semantic information of the target entity object based on the grid code of the semantic unit and the mapping relationship database. According to the technical scheme, the grid code of the semantic unit where the user is located is calculated only once, the semantic information is obtained by reading the mapping relationship database index based on the grid code of the semantic unit, and the calculation amount and response waiting time of the user position monitoring information are greatly reduced. Furthermore, the rationality of the user position monitoring information is improved, and the calculation amount of the generated user position density monitoring information is reduced.

This application relates to the fields of power distribution network technology and deep learning technology. It discloses a method, apparatus, and device for generating power distribution network topology diagrams based on temporally explicit networks. The method includes: a power distribution network automation system generating an adjacency list for the current time; dividing multiple nodes in the adjacency list into multiple regions, selecting the bus node of each region as the traversal start node for each region, creating a corresponding worker thread for each region, and performing a breadth-first search traversal operation on each region starting from the traversal start node to obtain a connection tree for each region; merging the connection trees of each region to generate the connection tree of the power distribution network; converting the connection tree of the power distribution network into a topology matrix of the power distribution network; inputting the topology matrix of the power distribution network into a drawing tool; and having the drawing tool generate the topology diagram of the power distribution network at the current time. This application is beneficial for improving the efficiency of topology diagram generation.

The invention relates to the technical field of virtual power plants, in particular to a virtual power plant energy scheduling method and system based on distributed optimization, and the method comprises the steps: constructing a distributed energy node state sensing network, collecting the operation state data and load prediction data of each distributed energy unit in real time, and transmitting the data to a distributed optimization scheduling center; based on an improved distributed model predictive control algorithm, establishing a multi-target energy scheduling optimization model, and decomposing a global optimization problem into local sub-problems of each node; parallel iterative solution of each sub-problem is realized through a distributed collaborative solution mechanism, and a scheduling scheme is dynamically corrected; and based on the real-time operation deviation and the external environment change, adaptively adjusting a scheduling strategy and issuing the scheduling strategy to each energy unit for execution. According to the invention, distributed energy resources are integrated through a distributed optimization architecture, efficient collaborative scheduling of virtual power plant energy is realized, the energy utilization rate is improved, the operation cost is reduced, and the system operation stability and flexibility are enhanced.

The present application relates to the technical field of water turbine production equipment, and particularly relates to a stator shell machining method capable of quickly installing an iron core, comprising the following steps: one, a prefabrication machining step; two, a pre-positioning step; three, a tool installation and precision adjustment step; four, a measurement and adjustment step; and five, a deformation-resistant welding step, the present application is provided with a pre-positioning structure of a clamping groove-clamping block, and the initial placement of the dove tail rib can achieve high coarse positioning accuracy, the tedious repeated alignment and auxiliary tool building time in the traditional method are saved, the three-dimensional adjustable tool makes the radial and circumferential precision adjustment one-step, different tools do not need to be repeatedly loosened and tightened, preliminary estimation shows that the installation time of a single dove tail rib can be shortened by more than 50%, and the overall stator shell machining cycle is shortened by 30%.

The invention relates to the technical field of enterprise data management, and discloses a data analysis and management method. The method comprises the following steps: acquiring data from an enterprise multi-source database, and preprocessing through a rule engine to generate a standardized business data set; constructing a business characteristic spectrum with a weight, and fusing multi-source data to form a global data model; training a prediction model based on the time series data to carry out anomaly detection; generating a multi-target resource scheduling scheme in combination with the service rule and the optimization strategy; outputting a multi-dimensional decision report through a visualization engine and monitoring a service state; and finally, dynamically optimizing the data model according to an evaluation result. According to the method, intelligent integration and dynamic optimization of enterprise multi-source data are realized, the accuracy of business decision and the resource utilization efficiency are remarkably improved through feature map construction and a multi-target scheduling strategy, and meanwhile, the method has real-time abnormity early warning and model self-optimization capabilities and provides comprehensive data support for enterprise operation.

This application provides an adjustable disc-lock scaffold horizontal bar and a method for erecting the scaffold, relating to the field of construction scaffolding. It includes poles, comprising a first pole, a second pole, and a third pole. Two first extension plates are fixed to one end of the second pole, which slides into the first pole through the first extension plates. A second extension plate is fixed to one end of the third pole, which slides into the second pole through the second extension plate and extends into the first pole. Connecting fasteners are located at both ends of the poles. A synchronous mechanism includes two pulleys rotatably mounted on the first extension plates, a belt, and connecting members fixed to the upper and lower sides of the belt. The connecting member on one side of the belt is fixedly connected to the first pole, and the connecting member on the other side of the belt is fixedly connected to the second extension plate. A locking mechanism is used to lock the third pole onto the second pole. This application reduces reliance on customized poles and improves construction efficiency.

The invention discloses a generative AI-assisted material data template design method and system, and relates to the technical field of material data management and generative artificial intelligence. The method comprises the following steps: receiving uploaded multi-source heterogeneous original material data, and carrying out decoding and decompression verification to generate a structured file storage path; analyzing the original material data, preliminarily deducing the data type, and generating a formatted intermediate file; generating an initial type mapping table by using a dynamic type discrimination mechanism based on a data scale; inputting the initial type mapping table and a target database template example into a generative AI engine, generating an initial JSON template, and performing man-machine collaborative optimization; and performing multi-dimensional verification on the optimized JSON template, storing the template which passes the verification, and outputting a standardized semantic data entity which can be correctly analyzed by the target database. According to the method, automatic analysis, semantic mapping and interactive optimization of the multi-source heterogeneous material data can be realized.

The utility model relates to power equipment technical field, the utility model aims at providing a kind of turnover type reactor device, solve the problem of time-consuming of multi-section reactor building, including first drive mechanism, second drive mechanism, safety mechanism, bearing plate and reactance mechanism, first drive mechanism and second drive mechanism are located bearing plate both sides respectively, reactance mechanism is set on bearing plate, the first drive mechanism includes first hydraulic cylinder and first hinge shaft, the first hinge shaft both ends are connected the drive end of first hydraulic cylinder and the first end of reactance respectively;Since base rotation is set on bearing plate, and reactor is set on base, when first hydraulic cylinder drives first hinge shaft, second hydraulic cylinder drives second hinge shaft, first hinge shaft and second hinge shaft jointly drive reactor overturn, so that reactor is easily laid flat or vertically overturned, solve the problem of time-consuming of multi-section reactor building.

The invention discloses an anti-seepage wall defect evaluation method based on near-field dynamics, and relates to the technical field of anti-seepage engineering safety evaluation. The method comprises the following steps: firstly, establishing a defect-containing diaphragm wall structure model, and defining a mechanical equation, defect boundary conditions and load constraints; dispersing the structure into material points, constructing a key connection relation and deducing a micro-modulus coefficient; then deducing a near-field dynamic power control equation, and setting a key fracture criterion and a damage evolution model; introducing a proportional boundary shape function, converting the power control equation into a matrix form balance equation, and solving a dynamic response; and calculating a damage value, and evaluating the safety performance and the remaining service life of the diaphragm wall in combination with the safety index. The advantages of the near-field dynamics and the proportional boundary finite element method are fused, the evaluation precision and efficiency are considered, and reliable technical support is provided for safety guarantee of the diaphragm wall.

A core network resource dynamic scheduling method, apparatus and device, and a storage medium are applied to the field of communication network optimization, and the method comprises the steps of generating a dynamic scheduling causal graph of core network resources according to a core network resource scheduling field knowledge base and obtained core network reference data; performing incremental causal distillation training according to the dynamic scheduling causal graph to generate a lightweight causal model; and performing real-time reasoning according to the lightweight causal model to generate a scheduling decision and an interpretable resource scheduling report. According to the method, the structured business causal relationship can be efficiently extracted, and the operation and maintenance efficiency and the system reliability are improved. Meanwhile, the generation time of a scheduling strategy can be effectively shortened, real-time reasoning is achieved, flexible and accurate resource scheduling is achieved, and resources can be dynamically allocated according to actual requirements. And clearer decision basis and explanation can be provided for operation and maintenance personnel, and the operation and maintenance personnel are supported to better understand system behaviors and quickly position problems.

This application discloses a connection node used in the construction of a reinforced concrete structure for a heating network well chamber, belonging to the technical field of connection nodes in building engineering. To address the problem of connecting the large-sized precast steel cage to the well chamber base in existing large-scale heating network well chamber construction, this application embeds a pre-embedded part in the well chamber base and uses this pre-embedded part to replace the traditional connecting steel bars of the well chamber base as the connection part with the precast steel cage. Simultaneously, the steel bar connection part is used to fix the precast steel cage to the well chamber base. This design optimizes the connection between the steel bars in the traditional precast steel cage and connecting steel bars into a connection between the pre-embedded part and the steel bar connection part, and optimizes the traditional regional steel bar connection into a point connection of multiple load-bearing points. This design greatly reduces the workload of fixing the precast steel cage to the well chamber base and also reduces the connection difficulty. This application is mainly used as a connection node in the construction of a reinforced concrete structure for a heating network well chamber.

This invention relates to a dynamic optimization decision-making model for the mining sequence of polymetallic symbiotic ore bodies, comprising an edge layer, a cloud platform, and a control terminal. The edge layer, cloud platform, and control terminal interact through dedicated interfaces, achieving a closed-loop process from data acquisition, processing, decision-making, to execution. The edge layer acquires ore body data in real time via a multi-source sensor network, preprocesses it through an edge computing terminal, and then uploads it to the cloud platform. The cloud platform uses a dynamic geological model engine to construct a real-time 3D ore body model and generates a Pareto optimal mining scheme that comprehensively considers economic, environmental, and safety factors through a multi-objective optimization engine. The control terminal uses a digital twin console to visualize the scheme and allow for manual intervention, while the equipment control system automatically executes mining commands. The model supports hourly dynamic updates, significantly improving resource recovery rate and decision-making efficiency, reducing environmental costs and mining risks, and achieving efficient, intelligent, and green mining of polymetallic symbiotic ore bodies.

This utility model discloses a quick assembly and disassembly device for a green sculpture display stand. It comprises two main support frames arranged symmetrically. Multiple support beams are inserted and installed on each main support frame, and each support beam is equipped with a decorative rod, on which a green sculpture pot is inserted and installed. This utility model achieves quick assembly and disassembly through the insertion structure between the main support frame, support beams, decorative rods, and green sculpture pots, and the cooperation of the first and second insertion blocks with their corresponding insertion slots. Compared to traditional display stands fixed with bolts and nuts, this significantly shortens the assembly and disassembly time, reduces labor costs, and effectively solves the problems of inconvenient assembly, adjustment, and disassembly of existing green sculpture display stands. It has high practical value and significant potential for widespread application.

The present application relates to the technical field of intelligent control of water plants, and discloses a sewage treatment carbon source intelligent dosing method, which comprises the following steps: constructing a sewage treatment biochemical simulation model, and performing static initialization and dynamic optimization based on historical data; in the first control stage, the model is used to perform dosing control, measured data and calculated data are accumulated and screened as a training data set, and an AI model is constructed; in the second control stage, i.e. mechanism and AI fusion, after model self-checking, intermediate state parameters representing microstate are generated; the intermediate state parameters are input into the AI model to obtain instructions, drive the carbon source dosing unit to perform dosing, and perform stepwise feedback regulation according to the effluent water quality. The present application uses an AI model to replace the cyclic iteration trial calculation of a mechanism model, shortens the calculation time, ensures that AI prediction conforms to the biochemical reaction rule through the microstate parameters provided by the mechanism model, and combines a feedback regulation mechanism to realize precise, rapid and stable dosing of the carbon source.

The application discloses an intelligent marketing document generation device and method based on multi-source data fusion, and the method comprises four processes: user instruction analysis, regular cleaning, model extraction parameter, Neo4j knowledge graph verification, and output of structured parameters; external data acquisition, parameter calling of a Baidu large model to collect data, de-duplication, semantic enhancement, and weighted screening of high-quality data; internal case processing, regular slicing of case storage, filtering, propagation calculation, multi-dimensional scoring, and generation of a CoT reasoning chain report; multi-modal output, format adaptation, data integration by a BART model, and output of a metadata document. The device and the method are coordinated, multi-source fusion, knowledge graph association and multi-modal conversion are realized, high-quality marketing documents suitable for multiple industries are efficiently generated, decision-making is supported, and the market response and output efficiency of enterprises are improved.

This utility model relates to the field of agricultural greenhouse technology and discloses a modular blueberry seedling greenhouse frame structure, including a fixed rod, a connecting rod, and an arched support. A vertical cone is fixedly connected to the bottom of the fixed rod, and a connecting component is installed at the top of the fixed rod. A fixed component is installed at the top of the connecting rod. The connecting component includes an mounting block, which is fixedly connected to the top of the fixed rod. A sliding groove is formed in the middle of the mounting block. A housing is fixedly connected to the bottom of the connecting rod, and a locking post is fixedly connected inside the housing. The locking post engages with the sliding groove. In this utility model, the fixed rod and connecting rod are installed through the engagement of the locking post and the sliding groove, making the connection more stable and less prone to loosening. It enables quick and flexible connection and disassembly, improves assembly efficiency, shortens greenhouse construction time, and allows for rapid deployment.

The application relates to the technical field of battery early warning and discloses a battery alarm scene data enhancement and algorithm robustness verification method, which acquires a real alarm sample set; a pre-trained cascade generation model is used to generate a synthetic alarm sample; the synthetic alarm sample and the real alarm sample are mixed in proportion to construct an enhanced training set; a battery alarm related target recognition algorithm is trained using the enhanced training set, and the robustness improvement degree of the battery alarm related target recognition algorithm is quantitatively verified under a plurality of preset disturbance conditions; wherein the cascade generation model comprises the following steps: a denoising diffusion probability model is used to generate a basic sample, a generative adversarial network is used to perform detail enhancement and distribution correction on the generated result, a preset strategy is used to control a random latent variable to complete sample screening, and a high-quality and diversified alarm data set is constructed. Through the method, the robustness and stability of the alarm recognition algorithm can be significantly improved, and reliable prediction and accurate early warning of a battery system under actual complex working conditions can be realized.