7786 results about "Information technology" patented technology

The invention provides a notarization intelligent question and answer customer service method and system based on a knowledge graph, and relates to the technical field of information, and the method comprises the steps: collecting multi-source heterogeneous data in the notarization field, forming an entity set and a relationship set, combining to form an initial knowledge graph, carrying out a dynamic update mechanism based on time decay, and supplementing to form a dynamic knowledge graph. Carrying out vectorization expression to obtain an atlas vector; receiving a multi-modal problem, determining fusion features, performing deep semantic understanding, obtaining semantic features, determining a user intention, and forming a structured query expression; based on the user intention and the structured query expression, carrying out multi-hop reasoning in the dynamic knowledge graph, carrying out similarity calculation by utilizing graph vectors, determining a reasoning path in combination with the user intention, carrying out knowledge association reasoning along the reasoning path, obtaining a preliminary reasoning result, carrying out interpretability analysis on the preliminary reasoning result, and obtaining a final reasoning result; and generating a reasoning chain and a confidence score, forming a detailed reasoning result, and finally generating a personalized answer.

The invention relates to the technical field of information, in particular to a multi-task data analysis method and device and a storage medium, and the method comprises the steps: constructing a multi-dimensional task state feature vector as the input of a task loss prediction model by collecting a task execution progress, a resource use condition and an abnormal log index in a task operation process; constructing a task dependency graph and a resource conflict graph according to the dependency relationship between the tasks and the resource occupation condition, learning the relevance between the tasks and a resource competition mode through a graph neural network algorithm, and obtaining an influence factor and a propagation path of task loss; the performance of a task loss prediction model is continuously tracked, model parameters are dynamically updated through an incremental learning mechanism, the method adapts to changes of a multi-task environment, prediction accuracy and real-time performance are improved, and a reliable decision basis is provided for task scheduling and resource optimization.

The invention provides a cold machine and water pump linkage energy-saving control method under a low-load working condition, which relates to the technical field of information and comprises the following steps of: dynamically predicting load requirements under the low-load working condition by analyzing historical operation data of a refrigeration system and combining weather forecast information, equipment operation parameters and data of building personnel activity rules; obtaining a cooling capacity demand curve and a load demand prediction result in future preset time; establishing a system low-load operation mode optimization model, taking the screened control combination meeting the preset energy-saving operation target as model input, and obtaining an optimized system low-load operation mode through the training model; the optimal energy efficiency interval is determined by analyzing the relation between equipment energy consumption and cold storage capacity, and during load demand prediction and control optimization, the interval serves as a target constraint to guide a refrigerator and water pump equipment to operate in a high-energy-efficiency area. And the operation efficiency and the energy-saving effect of the refrigerating system under the low-load working condition are improved.

The invention discloses a multi-sensor information fusion method for monitoring the insulation state of a high-voltage cable, and relates to the technical field of information. The method comprises the following steps: acquiring magnetic flux distribution data at different spatial positions in a grounding box according to a three-axis orthogonal magnetic flux sensor, and analyzing magnetic flux distribution characteristics to obtain a spatial sensitivity distribution map; the method comprises the following steps: acquiring a magnetic field signal generated by a cable fault discharge source, decomposing and calculating a magnetic field gradient tensor by adopting an inversion method based on the magnetic field gradient tensor, positioning a defect position of cable insulation, and acquiring three-dimensional space coordinate information of the defect position; according to a cable insulation state space distribution evaluation result, the arrangement density of the fluxgate sensors is increased in an insulation fault high-incidence area, the arrangement of the tetrahedral configuration sensor array is optimized, and a comprehensive evaluation index system is constructed. Data support is provided for state monitoring and life prediction, and the operation reliability of the cable is improved.

The invention provides a hydropower station auxiliary machine equipment real-time monitoring method and system based on the Internet of Things, and relates to the technical field of information, and the method comprises the steps: constructing a pressure oil pump fault diagnosis model for a temperature and vibration related feature subset, and training a temperature and vibration feature sample of a preset fault type, establishing a mapping relation between the temperature and vibration characteristics of the pressure oil pump and the fault type; on the basis of the pressure oil pump fault diagnosis model, typical faults of bearing abrasion and poor gear meshing of the pressure oil pump are classified and recognized, and the temperature and vibration fault diagnosis result of the pressure oil pump is determined through the mapping relation between the temperature and vibration characteristics of the pressure oil pump and the fault type; and according to the fault diagnosis results of the temperature and vibration of the pressure oil pump, carrying out comprehensive decision making on a plurality of diagnosis results, according to the preset confidence of different diagnosis results, giving corresponding weight coefficients, and generating a final health state evaluation result of the pressure oil pump. The operation reliability and the maintenance efficiency of the pressure oil pump are improved.

The invention provides an intelligent operation and maintenance method and system for a photo-thermal power generation system based on the Internet of Things, and relates to the technical field of information technologies, and the method comprises the steps: obtaining temperature, humidity and vibration environment parameter data collected by a sensor disposed on power generation equipment; and receiving the environmental parameter data, comparing the environmental parameter data with a preset threshold value, and judging whether the environmental parameters exceed a normal range or not. According to the method, environmental parameters such as temperature, humidity and vibration of the equipment are collected in real time by arranging the sensors, when the parameters exceed the preset threshold value, performance parameter collection is triggered, weighted average calculation is carried out in combination with the environmental parameters, and the equipment health index is obtained; according to the method, intelligent assessment and predictive maintenance of the health state of the power generation equipment are realized, the operation reliability and the maintenance efficiency of the equipment are improved, the equipment fault risk is reduced, and the service life of the equipment is prolonged.

The invention discloses an accurate advertisement putting method and system based on artificial intelligence, and relates to the technical field of information, and the method comprises the steps: collecting user behavior data and real-time situation data, and carrying out the preprocessing of the user behavior data; analyzing the preprocessed user behavior data to generate a user interest label; combining the real-time situation data with the user interest label, constructing a situation interest model by adopting a deep learning technology, and predicting a user interest change mode; using an interest-driven recommendation method to obtain an initialized advertisement putting strategy; generating feedback information based on the analysis of the initialized advertisement putting strategy; and optimizing the feedback information through a reinforcement learning algorithm to generate an optimized advertisement display strategy. By vectorizing the user interest and combining the advertisement strategy characteristics, the generator model can meet the user preference and follow the advertisement materials of the optimal display strategy, so that the visual experience and the emotion resonance of the user are improved, and finally the click rate and the conversion rate of the advertisement are improved.

The invention discloses a switching loss evaluation method and system based on a semi-soft switching modulation technology, and relates to the technical field of information. According to the method, parasitic inductance parameters and buffer capacitance parameters of a device are obtained, a resonant circuit working model is established, an initial voltage waveform and an initial current waveform are obtained by solving the model, and corresponding voltage stress and current stress are calculated; a parasitic inductance parameter and a buffer capacitance parameter of the device are optimized by using a genetic algorithm; adjusting the design of the buffer circuit according to the optimized device parameters, carrying out the simulation of the resonance process again, carrying out the frequency domain analysis of the optimized resonance voltage waveform and resonance current waveform, and optimizing the device parameters and the design of the buffer circuit. And finally, semi-soft switching modulation simulation is carried out, a temperature coefficient mapping relation between simulation switching loss and actually measured switching loss is constructed, an optimal design scheme of the device is determined, the switching loss of the device is effectively reduced, and it is ensured that the device works in a safe working area.

The invention belongs to the technical field of information, and relates to a multi-level dynamic intelligent automatic data processing and information evaluation method and system. The method comprises the steps that a database environment operation data set is constructed, targeted training and fine adjustment are conducted on a large language model in combination with reinforcement learning, and full-automatic data analysis, query and information extraction of multiple tables in a database are achieved; a multi-level agent interaction and cooperation framework is established, a scheduling agent is responsible for global decision making and strategy planning, an operation agent is responsible for execution of specific tasks, and the scheduling agent and the operation agent share information and coordinate the tasks to form a highly cooperative whole; and establishing a cyclic supervision and error correction mechanism, scheduling the intelligent agent to learn a normative workflow example of the target working environment and track the state of the operation intelligent agent in real time, identifying the behavior of the operation intelligent agent deviating from a predetermined path, and taking corrective measures. According to the method, high efficiency, intelligence and automation of data processing are realized, and the method has remarkable practical value and innovative significance.

A system for automating information technology software actions using advanced AI techniques including a processing system, storage medium, a communications interface, a user interface, a natural language processing model or neural network, operable to interface with at least one of an embedded prompt or chatbot prompt and hosted on a control node which communicates with one or more nodes comprised by a node network via the communications interface, and program instructions on storage medium that direct the processing system to receive an instruction from the user interface, process the instruction using the one or more natural language processing model or neural network, along with one or more AI agents, and execute the instruction one of locally or on a node of the node network via the communications interface.

The invention provides an electronic certificate management and supply chain quality tracing method and system based on a block chain, and belongs to the technical field of information. According to the method, encryption storage and tamper-proof protection are carried out on the electronic certificate information through the distributed account book of the block chain and the Hash algorithm, and verification, approval and data updating operations are automatically executed based on the intelligent contract. Fine-grained authority management and abnormal access detection of all parties of the supply chain are realized through a user access control module; and through a tracing query module, performing multi-condition combination query on the electronic certificate information stored in the block chain, and generating a quality tracing report meeting supervision requirements. According to the method, through tamper-proofing, distributed storage and intelligent contracts of the block chain, trusted storage, automatic verification and full-chain quality tracing of the electronic certification are realized, data security and supply chain transparency are improved, trust cost is reduced, and supervision and tracing efficiency is improved.

The invention provides a first-aid platform work order management method based on digital twinning and artificial intelligence, and belongs to the technical field of information technology application innovation, and the method comprises the steps: collecting historical first-aid data and real-time data of a first-aid scene, and constructing a task scheduling system based on a knowledge graph; decomposing the task into a plurality of sub-tasks according to the work order data, and allocating an optimal first-aid resource combination for the sub-tasks; an optimization strategy is set to carry out collaborative allocation control on each resource, and task allocation is optimized; the optimized task allocation is monitored in real time, and meanwhile, in combination with real-time data flow monitored in real time, it is ensured that the change of the dynamic environment is responded at any time in the task execution process; and re-inputting the optimized task allocation and resource scheduling strategy into the knowledge graph, and carrying out closed-loop optimization. According to the invention, the problems of inaccurate task scheduling, weak real-time response capability, low resource utilization rate and the like in the existing work order management system of the emergency platform are effectively overcome, and the overall efficiency and the automation level of the emergency platform are greatly improved.

The invention relates to the technical field of information, and discloses a ciphertext execution exception handling method and system for a privacy computing algorithm, which quantifies the data query sensitivity of each tenant by collecting differential privacy query parameters of a plurality of tenants, and performs time sequence analysis on the sensitivity quantification result by using an ARIMA model to predict the future trend of the tenant, so as to improve the accuracy of the ciphertext execution exception handling of the privacy computing algorithm. The residual error between the actual sensitivity and the predicted sensitivity is calculated to identify abnormal tenants; a sliding window method is adopted to extract statistical features of the abnormal tenants to construct a feature set, and clustering analysis is carried out on the feature set to identify abnormal modes and abnormal fingerprint feature clusters corresponding to the abnormal tenants; and training a model based on the positive and abnormal fingerprint feature clusters of the abnormal tenants, and quantifying the influence degree of each abnormal mode on the privacy protection level of the abnormal tenants by using the model, so as to adjust and execute the privacy budget allocation proportion of each abnormal tenant according to the obtained quantitative analysis result. And therefore, the exception in the ciphertext execution of the privacy calculation algorithm can be effectively processed.

The invention relates to the technical field of information, in particular to an error compensation method for multi-axis linkage machining of a mold blank hole system, which comprises the following steps: judging the time range of a tool changing window based on an error accumulation trend, if error accumulation reaches a preset threshold value, triggering a compensation action, otherwise, continuously monitoring error change; aiming at the complexity of a motion track, a nonlinear optimization algorithm is adopted, an execution path of a compensation action is optimized, and conflicts with a processing action are reduced; according to the optimized compensation path, the control parameters of the servo motor are adjusted in real time, and it is ensured that the compensation action is stably executed in the machining process; dynamically updating an error model through data of a main shaft temperature sensor and a tool wear monitoring device, and continuously optimizing a time point and an execution path of a compensation action; in the machining process, the error accumulation condition is monitored in real time, if the error exceeds the preset range, the compensation action is triggered again, and the machining precision is ensured.

The invention discloses a multi-level storage control method based on access popularity, and relates to the technical field of information, the method comprises the following steps: building a storage resource monitoring module, and collecting data volume change, read-write frequency and capacity occupation proportion information of each node from a storage system in real time; the method comprises the following steps: collecting original data, carrying out preliminary cleaning and formatting processing on the collected original data to obtain a standardized resource state data set, comparing predicted data with operation parameters of a current storage system, and if a predicted demand exceeds a current capacity limit, automatically generating a capacity expansion scheduling task to obtain a final resource optimization configuration scheme; according to the multi-level storage control method and device based on the access popularity, intelligent monitoring, load balancing and capacity planning of storage resources are achieved, the resource utilization efficiency and expandability of a storage system are improved, and an effective solution is provided for stable operation and performance optimization of a large-scale storage system.

The invention relates to the technical field of information, in particular to a high-precision thread machining method and system for an electronic cigarette connecting column in the technical field of precision hardware machining.The method comprises the steps that temperature distribution data of a material in the machining process is obtained, the thermal deformation amount is calculated through a heat conduction model, and a pre-compensation offset value is generated in combination with thread geometrical characteristics; an initial machining path adjusting scheme is obtained; extracting a multi-axis linkage moving trajectory from the initial processing path adjustment scheme, analyzing the change trend of the speed and acceleration of each axis in the trajectory, and judging dynamic error distribution characteristics to obtain an error distribution prediction map; obtaining geometric accuracy data of each key point in the machining path adjusted in real time, and analyzing a mapping relation between machining parameters and accuracy through a quality prediction model to obtain a parameter optimization suggestion table; and extracting a deviation value of the current processing parameter from the parameter optimization suggestion table, updating a control instruction of the processing equipment in combination with a closed-loop coordination mechanism, and generating a dynamically adjusted processing parameter set.

The invention relates to the technical field of cold-chain logistics information, and discloses a multi-mode AIGC cold-chain logistics information processing method and system, and the method comprises the steps: carrying out the feature extraction and feature enhancement of video data, temperature data and position data in a cold-chain logistics system based on a logistics information AIGC model, and obtaining an enhanced feature matrix; carrying out digital twinborn modeling to obtain a digital twinborn model of the logistics system, and constructing a state parameter space; performing deep reinforcement learning and information delay index calculation to generate a real-time data synchronization scheme; constructing a distribution network graph structure, and performing depth map network coding on the distribution network graph structure to obtain a distribution network representation vector; and performing multi-agent collaborative decision-making on the distribution network representation vector to obtain a cold chain distribution scheduling scheme, and updating the cold chain distribution scheduling scheme to the logistics system digital twinborn model. Therefore, intelligent scheduling and accurate control of the cold-chain logistics system in a complex scene are realized.

The invention, which relates to the technical field of supply chain information, discloses a comprehensive supply chain control system comprising a transaction and collaborative service module, an order management and decision support module and a data interaction and integration module. The transaction and cooperation service module is used for processing transaction information of supply chain participants, ensuring information safety and accuracy, managing the full life cycle of a contract and performing real-time monitoring, establishing a real-time communication and cooperation project management channel, and improving cooperation efficiency; according to the invention, the transaction and collaborative service module has a significant effect, encryption processing ensures the security of transaction information, leakage and tampering are prevented, contract management is efficient and flexible, a multi-parameter evaluation optimization template reduces the default risk, a collaborative mechanism improves the collaborative efficiency of all parties, and the response speed of a supply chain is enhanced.

The invention provides an online monitoring analysis method and system for hydropower station pump equipment, and relates to the technical field of information, and the method comprises the steps: judging that a bolt group has a fatigue failure risk when a fatigue damage degree D value reaches a preset critical threshold value, and comprehensively evaluating the health state of the bolt group in combination with bolt pre-tightening force monitoring data and a loosening failure critical threshold value of the bolt group, obtaining a residual service life prediction result of the bolt group; and by analyzing the stress nephogram and the strain nephogram of the stress concentration area around the bolt hole and the residual service life prediction result, a topological optimization and parameter optimization method is adopted to carry out optimization design on the structural arrangement and the pre-tightening force application scheme of the bolt group, and optimal bolt group design parameters for prolonging the fatigue life are obtained. Accurate prediction and optimal design of the fatigue life of the bolt group are realized, and the operation reliability and safety of the pump are improved.

The invention discloses a road bridge design method and system based on a BIM real scene model, and relates to the technical field of constructional engineering information, and the method comprises the steps: a BIM model carries out multi-objective optimization through a quantum annealing algorithm in combination with a bridge-crossing topology library, synchronously optimizes topological connectivity, structural stress and energy consumption indexes, generates a parameterized component, and feeds back the parameterized component to the BIM model; the model of the BIM model is loaded and optimized based on augmented reality equipment, the model is superposed to a reality scene through space anchoring, and the BIM model is corrected in combination with a conflict monitoring engine and a knowledge graph; the corrected BIM model is deployed to edge computer equipment, a dynamic deviation thermodynamic diagram is generated by scanning a construction surface, a lofting robot is driven to execute coordinate dotting, and meanwhile construction error data is transmitted back; according to the method, the problem that a global optimal solution is difficult to find when a traditional optimization algorithm is used for processing a complex multi-target problem is solved by utilizing an advanced quantum computing technology, and the economical efficiency and the structural safety of bridge design are greatly improved.

The invention provides a defect detection method for a metal code disc without coating, and relates to the technical field of information, and the method comprises the following steps: fusing an external geometric model of the metal code disc obtained by three-dimensional scanning with internal defect information of the metal code disc obtained by X-ray flaw detection, and constructing a three-dimensional model of the metal code disc containing internal defects; if a stress concentration phenomenon exists around the defect, carrying out stability analysis on the defect in the metal coded disc by utilizing a fracture mechanics theory, calculating a stress intensity factor at the tip of the defect, evaluating the risk of crack propagation of the defect under the action of external force, and determining the critical dimension and the safety margin of the defect; and obtaining a metal code disc defect distribution rule according to the internal defect information of the metal code disc, and carrying out optimization design on the structural layout and key dimension parameters of the metal code disc in combination with the metal code disc defect distribution rule and a safety evaluation criterion. The failure risk caused by internal defects of the code disc is reduced, and the use reliability and safety of the code disc are improved.

The invention relates to the technical field of social information, in particular to a social network influence prediction method and system. According to the method, brand-related users, content and interaction data are obtained from multiple platforms, a multi-dimensional influence scoring model is constructed, and initial influence scores of the users are calculated. And in combination with a social network cascade propagation theory, constructing a propagation probability calculation model, and predicting an information propagation range and user influence changes. And finally, generating an influence prediction report containing KOL ranking, hot topic analysis and optimal intervention opportunity suggestions. According to the method and system, through organic combination of a plurality of innovation points, the accuracy, comprehensiveness and practicability of prediction are remarkably improved, the existing technical problems are effectively solved, and a powerful support tool is provided for a brand to formulate a precision marketing strategy in a complex social media environment.

The invention belongs to the technical field of information, and relates to a semantic guidance pedestrian re-identification method and system based on text prompt. The method comprises the following steps: inputting a training image into a visual encoder to obtain visual embedding; mapping the visual embedding into a text space by using a reverse network to obtain a pseudo token, and integrating the pseudo token into a natural language sentence to obtain a language prompt for an input image; inputting the language prompt into a text encoder to obtain text embedding; training a multi-modal interaction module by utilizing visual embedding and text embedding; and inputting a query picture into the trained multi-modal interaction module to obtain a feature vector fusing vision and text information, and executing similarity retrieval in a pedestrian image database by using the feature vector fusing vision and text information to obtain a pedestrian re-identification result. According to the method, the retrieval performance on an existing pedestrian re-identification data set is remarkably improved.

The invention discloses an engineering project progress multi-dimensional monitoring system and method based on an information technology, and belongs to the field of monitoring. The engineering project progress multi-dimensional monitoring system comprises an initial construction plan construction module, a data acquisition and environment monitoring module, a data analysis and plan optimization module, a construction progress prediction module and a risk management module. By collecting multi-dimensional data of a construction site in real time and applying the intuitionistic fuzzy reasoning algorithm, a construction plan can be dynamically adjusted to cope with constantly changing site conditions and external environment factors, the intuitionistic fuzzy reasoning algorithm is utilized to analyze requirements and bottlenecks of a construction project, and the construction efficiency is improved by combining construction logic and physical constraints. Resource configuration can be carried out more accurately; fuzzy and uncertain conditions are processed through the fuzzy logic controller, it is ensured that a project meets all related building and safety standards, and project quality and safety are ensured through continuous monitoring and timely adjustment.

Distributed automated response control (ARC) networks and related systems and methods are disclosed. A distributed automated response controller network includes a plurality of a plurality of information technology devices and a plurality of operational technology devices. The plurality of information technology devices and the plurality of operational technology devices include a plurality of communication endpoints organized to operate in a distributed hierarchy. The distributed hierarchy includes a bottom tier and one or more higher tiers. The bottom tier includes a first portion of the plurality of communication endpoints configured to perform device controls for the plurality of operational technology devices responsive to a detected threat. The one or more higher tiers include one or more other portions of the plurality of communication endpoints. The one or more other portions of the plurality of communication endpoints are configured to perform network controls responsive to the detected threat.

The invention discloses a power Internet of Things terminal attack tracing method based on lightweight dynamic causal reasoning, relates to the technical field of network security, and solves the problems of sample unevenness, graph scale expansion and calculation delay in power Internet of Things terminal attack tracing in the prior art. The method comprises the following steps: processing a log text to obtain vector data; a residual error generation network is adopted, and the time sequence and logic relevance between attack events is introduced in the GAN training process; then, constructing a preliminary attack traceability graph, designing a graph neural network and attention mechanism combination method to calculate weights among nodes, and introducing a mutual information technology to dynamically adjust causal confidence among the nodes; and finally, generating high-quality embedding by utilizing the GAT teacher model, and migrating traceability knowledge of the teacher model to the lightweight GIN student model through knowledge distillation. In conclusion, the method can systematically construct an efficient attack traceability technical framework oriented to the power Internet of Things terminal from three key stages.

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform configured to manage process and production workflows for a set of distributed manufacturing network entities through design, modeling, printing, and supply chain stages. The information technology system includes an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the set of distributed manufacturing network entities of the distributed manufacturing network to optimize digital production processes and workflows. The information technology system includes a distributed ledger system integrated with a digital thread configured to provide unified views of workflow and transaction information to entities in the distributed manufacturing network.

The invention discloses a line loss treatment method based on low-voltage power grid multi-source data fusion, and belongs to the technical field of information, and the method comprises the steps: reconstructing a power supply path based on a power grid topological structure and a changed power access point; extracting reverse power flow characteristics of the frequency points for correcting a node impedance matrix of the current power supply path to obtain a power supply access point impedance parameter set; updating a power transmission path through the reverse power flow characteristic to obtain a power distribution characteristic; and a power grid topological structure, a current power supply path, a power supply access point impedance parameter set and power distribution characteristics are fused to construct a line loss distribution prediction model and identify a line loss abnormal region, and the line loss abnormal region is treated. Through implementation of the method and the device, the problem that the line loss treatment effect is poor due to the fact that the influence of factors such as transformer area topological structure change, power access point change and load fluctuation on the line loss is not considered in the prior art, and the predicted line loss distribution has a large error compared with the actual situation can be solved.

Embodiments relate to providing self-learning automated information technology change risk prediction. A processor inputs a change request to a first machine learning model, the first machine learning model determining at least one word pair in the change request, the change request being a modification in an IT environment. The processor classifies the at least one word pair into a change category for the IT environment using a second machine learning model, the change category identifying a type of the modification to be executed in the IT environment. The processor determines a likelihood of causing a problem in the IT environment as a result of executing the modification. The processor automatically performs an action to prevent the modification of the change request in the IT environment.

The invention relates to the technical field of application of information technology in constructional engineering, and discloses a method for intelligently extracting engineering quantity application in highway engineering. The method comprises the following steps: standardizing an engineering scale in highway engineering design to form a standardized engineering scale; establishing a preliminary budget project reference template; establishing a connection relationship between the preliminary budget project reference template and the standardized engineering scale, wherein the connection relationship at least comprises a semantic correspondence relationship between project sections and engineering scale fields, a logic matching rule between quota subitems and engineering parameters, and a self-adaptive adjustment mechanism for table format differences; when a new engineering quantity table is imported, automatically identifying and analyzing a data field and a structure of the new engineering quantity table based on a connection relationship, mapping data in the new engineering quantity corresponding table to a corresponding project section and a quota sub-target of a preliminary budget project reference template through semantic analysis and a logic matching rule; and generating a budget file meeting the cost compilation requirement.