41495 results about "Computer equipment" patented technology

The invention discloses a computer equipment fault monitoring system and method based on artificial intelligence, and relates to the technical field of computer equipment fault monitoring. The system comprises a data access module, a semantic analysis module, a knowledge graph construction module, a dynamic semantic association module, a data fusion processing module, a decision output module and an adaptive optimization module. The data access module collects and standardizes hardware, software and network data; the semantic analysis module extracts and enhances semantic tags; the knowledge graph construction module forms a data semantic relation network; the dynamic semantic association module screens potential semantic relationships; the data fusion processing module generates a multi-dimensional feature vector; the decision output module triggers fault early warning; and constructing a feedback knowledge graph of the self-adaptive optimization module. According to the method, through event-driven interpolation, dynamic weight fusion, closed-loop feedback optimization and the like, the problems of multi-source data alignment, semantic fusion and dynamic adaptation are solved, the fault monitoring accuracy and the system adaptability are improved, and the method is suitable for fault monitoring and early warning of computer equipment.

The invention relates to the technical field of servo motor control, and discloses an intelligent servo motor control method and device and computer equipment. The method comprises the following steps: carrying out multi-dimensional data acquisition and preprocessing on a position loop, a speed loop and a current loop of the intelligent servo motor to obtain standard structured parameter data; identifying a working condition characteristic parameter set of the intelligent servo motor; establishing a two-stage optimization architecture comprising a motor parameter layer and a control algorithm layer, and generating a dynamic parameter adjustment mapping table; a depth deterministic strategy gradient network is trained based on the characteristic parameter set and the dynamic parameter adjustment mapping table, and an optimal control strategy model for different working conditions is generated; and the optimal control strategy model is utilized, control parameters are automatically switched according to the working condition types recognized in real time, and smooth transition control of the intelligent servo motor among different working conditions is achieved. Smooth switching among different working conditions is achieved, system oscillation caused by sudden change of control parameters is avoided, and the disturbance influence in the working condition switching process is greatly reduced.

The present disclosure generally relates to a computer device, method and system utilizing machine learning for capturing and analyzing profile data communicated across a computing environment including but not limited to: each user's profile, online behaviors and career progression path and provides dynamic recommendations of online actions to be performed to reach a desired target state.

The invention relates to the technical field of data processing, and discloses a bridge displacement remote intelligent monitoring method and system and computer equipment. The method comprises the following steps: setting a multi-stage trigger threshold to perform grouped polling sampling to obtain displacement data; adopting dynamic weight fusion to denoise and identify abnormities, and utilizing a Kriging method to generate a digital twinborn model; extracting features to classify and distinguish environment and structure response displacement; calculating a deviation index to estimate fatigue damage to form a health report; calculating a risk entropy value and setting an early warning generation disposal scheme; and evaluating improvement rate update configuration to complete closed-loop optimization. According to the method, the environment data and the historical monitoring data are fused, a self-adaptive sampling strategy and an intelligent analysis processing mechanism are established, displacement changes caused by environment factors and structural factors are accurately distinguished, and accurate risk quantification and automatic decision support are carried out.

The invention relates to the technical field of power system optimization scheduling, and discloses a multi-load equipment energy consumption management method and device and computer equipment, and the method comprises the steps: obtaining electricity price data, and the energy consumption data, the operation state and the load demand of electric equipment, based on the electricity price data, the energy consumption data, the operation state and the load demand, the priorities of the electric equipment are classified; adopting a preset multi-task learning model to predict the load demand of the electric equipment in a future preset time period; generating a multi-target optimization model based on the priority, the load demand and the electricity price data of the electric equipment, and generating a dynamic power distribution scheme of the electric equipment based on the multi-target optimization model; and obtaining the load demand and the external environment of the electric equipment in real time, and adjusting the dynamic power distribution scheme of the electric equipment based on the load demand and the external environment. According to the method, the energy consumption optimization and the operation efficiency are always kept balanced, and the problem that the energy consumption optimization and the operation efficiency are not balanced is solved.

The invention relates to the technical field of wind power generation, and discloses a wind turbine generator gearbox fault diagnosis method and device and computer equipment, and the method comprises the steps: collecting multi-source data of a wind turbine generator gearbox; respectively extracting a time domain feature, a frequency domain feature, a temperature feature and a working condition feature of the multi-source data; performing weighted feature fusion on the time domain feature, the frequency domain feature, the temperature feature and the working condition feature to obtain a real-time fusion feature; obtaining historical health data of the wind turbine generator gearbox, establishing a health degree reference of the wind turbine generator gearbox based on the historical health data, and constructing a health degree model based on the real-time fusion features and the health degree reference; and performing fault diagnosis on the wind turbine generator gearbox by adopting the health degree model. According to the method, multi-source data of the gearbox of the wind turbine generator is combined, and gearbox health state evaluation and fault type identification are realized through dynamic feature fusion and deep learning modeling.

The present application relates to a retrieval model training method and apparatus and a computer device. The method comprises: acquiring a knowledge document, and performing text segmentation processing on the knowledge document to obtain a text block set (501); on the basis of the text block set and summary information comprised in each text block, writing a question for each text block to obtain one or more question texts corresponding to each text block, separately combining the one or more question texts corresponding to each text block with the corresponding text block to obtain one or more data pairs corresponding to each text block and, on the basis of the one or more data pairs corresponding to each text block, generating a data pair set (502); and using the data pair set to train a first retrieval model so as to obtain a second retrieval model (503).

The invention discloses a code generation method and device based on LLM multi-agent cooperation and computer equipment. The method comprises the following steps: acquiring a user programming demand; analyzing the user programming demand based on LLM and decomposing a programming task to generate a task tree; selecting a to-be-allocated sub-task from the task tree, and evaluating the matching degree of an intelligent agent in an intelligent agent pool and the to-be-allocated sub-task based on LLM to generate a task allocation instruction; sending the task allocation instruction to a corresponding target agent, so that the target agent executes the to-be-allocated sub-task, and feeding back an execution result; and outputting the execution result. By implementing the method provided by the invention, the programming efficiency and quality can be improved, the resource allocation can be optimized, and the efficient development of complex requirements and large projects can be supported.

The invention relates to a gas sensing compensation method and device and computer equipment, and the method comprises the steps: obtaining original output signals of a gas sensor under various environmental conditions within a preset time, and recording corresponding environmental parameters at the same time; based on the collected original output signals and the corresponding environment data, a gas compensation model used for describing the internal relation of sensor output, environment parameters and actual gas concentration is constructed; the method comprises the following steps: acquiring current environmental parameters in real time through a gas sensor, inputting the current environmental parameters into a gas compensation model, and carrying out correction calculation on output signals of the gas sensor through the gas compensation model to obtain compensated gas concentration signals so as to realize omnibearing correction of measurement errors caused by various factors. The gas sensor can stably and accurately output measurement results under complex and changeable environmental conditions, reliable data support is provided for application in various fields, and the overall performance and practicability of the gas sensor are improved.

The invention belongs to the field of artificial intelligence and financial science and technology, and relates to a document segmentation method, which comprises the following steps: carrying out style feature recognition and title text recognition on a to-be-segmented document to obtain a title style result and a title text result, and then carrying out recognition verification on the title style result and the title text result through a multi-modal title recognition large model to obtain a segmented document. And obtaining a final title recognition result, constructing tree hierarchical representation based on the title recognition result to obtain a document chapter structure, and segmenting the to-be-segmented document according to the document chapter structure. The invention further provides a document segmentation device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the to-be-segmented document can be stored in a block chain. According to the method and the device, the document is segmented in a chapter form, the semantic integrity of segmentation is ensured, and key information is effectively extracted and structured.

The present invention provides an inverter control method, device, computer equipment and storage medium, belonging to the field of power electronics. The method comprises: determining a frequency control equation of the inverter under a grid-connected condition when the inverter is in a VSG control mode; determining a relationship between a virtual electromotive force of a virtual synchronous generator in a reactive state and an output voltage of the inverter; constructing a voltage-current double closed-loop control structure of the inverter under the VSG control mode, and determining a current reference value and a voltage reference value of the virtual synchronous generator under dq axes through the frequency control equation and the relationship; constructing a fuzzy control rule of a virtual damping coefficient and a virtual inertia according to the current reference value and the voltage reference value; and controlling the virtual damping coefficient and the virtual inertia through the fuzzy control rule, thereby improving the stability and performance of the inverter during the grid-connected process, reducing the harmonic disturbance of the power system, and helping to improve the adaptability and reliability of the entire photovoltaic power generation system.

The invention relates to a power station screen cabinet equipment temperature early warning method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a dual-light image of power station screen cabinet equipment to be analyzed according to acquisition parameters corresponding to current acquisition; the dual-light image comprises an infrared thermal imaging image and a visible light image; performing preprocessing, feature extraction processing, spatial registration processing and information fusion processing on the dual-light image to generate a fused image; performing temperature field reconstruction processing and hot spot detection processing on the fused image to obtain temperature field distribution information and hot spot area information; and according to the temperature field distribution information and the hot spot area information, performing temperature analysis on the power station screen cabinet equipment to obtain temperature early warning information of the power station screen cabinet equipment. By adopting the method, the temperature early warning accuracy of the power station screen cabinet equipment can be improved.

The invention belongs to the technical field of stirring control, and particularly relates to an intelligent speed regulation stirring control method and system and computer equipment, and the method comprises the steps: determining a target control value of stirring control according to the requirements of a stirring technology; various sensors are installed on the stirring equipment, it is ensured that key parameters in the stirring process are accurately collected in real time, the data collection frequency is set, and it is ensured that dynamic changes in the stirring process are captured; filtering processing is carried out on the collected sensor data, noise interference is removed, the sensor data is corrected, and the accuracy of the data is ensured; key features in the stirring process of the combustion furnace are extracted through a data analysis method, and a mathematical model of the stirring process is established for prediction and control; a closed-loop control system is established, the stirring speed of the combustion furnace is adjusted according to data monitored in real time, the stability and accuracy of the stirring process are ensured through an intelligent algorithm and real-time parameter monitoring, insufficient stirring or excessive stirring is avoided, and therefore the product quality and the production efficiency are improved.

The invention belongs to the field of artificial intelligence and finance, and relates to a text classification method, which comprises the following steps: preprocessing an original text data set, labeling classification labels to obtain a labeled text data set, inputting a training set into a large language model for keyword extraction to obtain a candidate keyword set, cleaning the candidate keyword set to obtain a classification keyword set, constructing an instruction template based on the classification keyword set, and inputting the training set and the instruction template into a large language model to obtain a prediction classification result; and based on a prediction classification result and a loss function between the classification labels, performing fine tuning on the large language model to obtain a fine tuning model, evaluating that the fine tuning model is qualified to obtain a text classification model, and inputting the to-be-classified text into the text classification model for classification. The invention further provides a text classification device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the tagged text data set can be stored in a block chain. According to the method, the text classification accuracy and stability can be improved.

The invention relates to a method and a system for constructing a dynamic gene regulation network, computer equipment, a computer readable storage medium, a computer program product and a computer program. The method comprises the following steps: constructing a plurality of single cell quasi-time sequence differentiation trajectories based on single cell transcriptome data of a plurality of single cells; determining a dynamic change gene in a target quasi-timing sequence differentiation trajectory based on the plurality of single cell quasi-timing sequence differentiation trajectories; constructing an initial static gene interaction network based on the dynamic change gene; and performing inspection based on the initial static gene interaction network to obtain the dynamic gene regulation network. According to the method, key gene regulation mechanisms corresponding to different differentiation stages of the cells can be rapidly determined, and the real dynamic change condition of the gene regulation relationship in the biological process is reflected.

The invention relates to a user question information response method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring question information input by a user; based on semantic retrieval and vector retrieval, retrieving corresponding private domain knowledge information from a preset private domain knowledge base; obtaining a first cue word according to the question information, the private domain knowledge information and a pre-configured agent database; inputting the first prompt word into the large model, obtaining an agent calling link through the large model, and calling a corresponding agent according to the agent calling link; obtaining a second prompt word, inputting the second prompt word and an execution result obtained by calling the corresponding agent according to the agent calling link into the large model, and determining whether the execution result meets a condition or not through the large model; if yes, response information for the problem information is output based on the execution result. By adopting the method, resource loss caused by fixed code development can be reduced.

The invention relates to the technical field of kiln temperature control. The kiln temperature consistency control method comprises the steps that kiln internal environment information is input into a temperature change prediction model, temperature fluctuation trend information is obtained, kiln temperature control optimization parameters are generated according to the temperature fluctuation trend information, and the kiln temperature consistency is controlled according to the kiln temperature control optimization parameters. The current operation parameter is kept if the adjusted environment information conforms to a kiln temperature control target value, and the adjusted environment information is input into the temperature change prediction model again if the adjusted environment information does not conform to the kiln temperature control target value to generate a new kiln temperature control optimization parameter. And on the basis of the new kiln temperature control optimization parameter, the operation parameter in the kiln is adjusted again until the adjusted environment information accords with the kiln temperature control target value. The method has the effect of ensuring the consistency of the internal temperature of the kiln.

The invention discloses an extension equipment function configuration method and device, computer equipment and a storage medium, and relates to the technical field of data processing. According to the method, a hardware and firmware collaborative dynamic configuration framework is constructed, and a receiving queue is adopted at an extension equipment end to trigger a central processing unit firmware processing mechanism; in combination with virtualization design of a shadow configuration space and a shadow register, dynamic reconstruction of configuration parameters and an address mapping strategy during operation is realized; a host end supports configuration space access, base address register remapping and memory data transmission interaction through a transaction generation and routing mechanism driven by an event type. Hardware solidification limitation of traditional extension equipment is broken through through software and hardware decoupling design, the problems that function extension capacity is insufficient, resource dynamic allocation is difficult and protocol updating and virtualization scenes cannot be adapted are solved, and the technical effects of improving configuration reconstruction efficiency and address space utilization rate and supporting virtual function creation are achieved. And the adaptability of the equipment in cloud computing and edge computing environments is enhanced.

The invention relates to the technical field of intelligent vehicle control, in particular to a loader vehicle control method and system, computer equipment and a storage medium. The method comprises the following steps: collecting multi-modal data of the loader, wherein the multi-modal data comprises working environment data, dynamic load state data and vehicle attitude data of the loader; constructing a three-dimensional operation scene digital twinborn model based on the multi-modal data, and predicting vehicle stability influence data of the influence of the load change on the vehicle stability based on the dynamic load state data; based on the digital twinborn model of the three-dimensional operation scene and the vehicle stability influence data, a dynamic control strategy is generated by utilizing a reinforcement learning algorithm, and cooperative actions of steering, lifting and walking mechanisms are synchronously optimized; according to operation environment data and a dynamic control strategy, hydraulic system pressure and motor torque distribution are adjusted in a self-adaptive mode, and operation efficiency and safety are ensured.

The invention provides an emergency rescue assisting method based on a large language model and computer equipment, and relates to the technical field of computers, and the method comprises the following steps: obtaining a current question text of a target user; performing intention recognition on the current question text to obtain a target intention type corresponding to the current question text and target intention recognition information under the target intention type; determining a target big language model matched with the target intention type from a plurality of pre-trained big language models according to the target intention type; the plurality of pre-trained large language models are pre-trained large language models of a plurality of different model frameworks in the field of emergency rescue; and by adopting the target large language model, according to the target intention identification information and a preset emergency knowledge base, generating target emergency rescue auxiliary information corresponding to the current problem text. The method does not need manual analysis, and improves the efficiency and accuracy of generating the target emergency rescue auxiliary information.

An icing detection method based on tension and tilt angle sensors. Two kinds of sensor data are comprehensively utilized, cross validation and mutual compensation are realized, and the precision of an icing monitoring result is improved; compared with a single sensor, data fusion of a multi-source heterogeneous sensor improves the robustness and the anti-interference ability of ice volume assessment, and improves the reliability of icing detection; an uncertainty analysis model for icing thickness is established, a confidence interval of a monitoring result is given, and more sufficient reference information is provided for related decisions; by setting a scientific and reasonable monitoring and early-warning mechanism, intelligent monitoring and early-warning of an icing condition are realized, and the intelligent level of the technology is improved; and by establishing an icing monitoring model, the icing condition of wires can be accurately predicted, and the early-warning and monitoring capabilities are improved to ensure the safe operation of a power grid. Also disclosed are an icing detection system based on tension and tilt angle sensors, a computer device and a computer-readable storage medium.

The road crack detection method based on the improved RT-DETR comprises the following steps: shooting a road at a preset flight height by using an unmanned aerial vehicle to obtain an original road image containing a crack; a pre-trained crack detection model is utilized to carry out crack detection based on an original road image to obtain crack parameters, and the crack detection model is obtained through improvement and training based on an RT-DETR (Real-Time Detecting Transformer) model; the method for improving the RT-DETR model to obtain the crack detection model comprises the following steps: replacing a basic residual block at the tail end of a ResNet18 backbone network in the RT-DETR model with a dynamic snakelike convolution residual block (DSCRBlock); a cross-scale feature fusion module (CCFM) in a hybrid encoder in an RT-DETR model is replaced by a bidirectional diffusion focusing pyramid network (BDFPN), and the bidirectional diffusion focusing pyramid network comprises a primary focusing sub-network and a secondary focusing sub-network. The method can efficiently and accurately identify the road crack, can be applied to the unmanned aerial vehicle, and is easier to implement.

The invention provides a long document semantic coherence processing method and device, a storage medium and computer device.The method comprises the steps that block coding is conducted on a long document through a sliding window converter, and the sliding window converter comprises a window dividing unit, a position coding unit and a converter coding unit; the window division unit adjusts block positions according to sentences and paragraph boundaries and sets overlapping areas between adjacent blocks; the encoded document content is stored and managed through a memory management module, the memory management module comprises a chapter-level memory pool and a gating memory unit, the chapter-level memory pool stores the document encoding content, and the gating memory unit maintains entities and event timelines; performing deep semantic understanding on the document content through a semantic processing module, and calculating a multi-dimensional attention weight capture dependency relationship between paragraphs; providing a retrieval result through a retrieval module; and generating semantically coherent output content through a content generation module. According to the scheme, the semantic coherence of long document processing is improved.

The invention relates to an optimal configuration method, device and equipment based on virtual power plant resources. The method comprises the following steps: acquiring resource parameters of each virtual power plant resource, historical load data associated with each virtual power plant resource, external load data and user behavior data, and constructing a resource characteristic model for each virtual power plant resource according to the resource parameters, the historical load data, the external load data and the user behavior data, according to historical load data, external load data and user behavior data, load prediction is carried out according to the historical load data, the external load data and the user behavior data to obtain a load prediction result, adjustable capability indexes are determined according to the load prediction result and the resource characteristic model, and weighted fusion is carried out according to the adjustable capability indexes and the index weights of the adjustable capability indexes to obtain a resource evaluation result. And performing optimal configuration on each virtual power plant resource according to a preset configuration demand and the resource evaluation result corresponding to each virtual power plant resource. The method can improve the resource utilization rate and reduce the energy consumption.

The invention discloses an index transaction attribution analysis method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining problem information, and decomposing the problem information into an intention, a business index and an index dimension; determining whether the user question needs to be subjected to index attribution or not; if the index attribution needs to be carried out, determining whether the business index is abnormal or not; if the business index is abnormal, determining an attribution diagnosis model according to the intention and the index type, and predicting an attribution result of the business index through the attribution diagnosis model; and determining a target external factor and a target internal factor which influence the attribution result, and obtaining countermeasures of the target internal factor or the target external factor. Through dialogue questioning and introduction of a large language model and an attribution analysis model, the reason of abnormal fluctuation of the index can be quickly positioned, minute-level attribution analysis is realized through a dialogue mode, and the method has wide application scenarios and potential.

According to the knowledge text retrieval method and device, the storage medium and the computer equipment, when knowledge text retrieval is carried out, the retrieval statement and the target knowledge document corresponding to the retrieval statement are obtained firstly, the document structure tree of the target knowledge document is determined, the document structure tree is of a tree structure constructed by utilizing the directory structure of the target knowledge document, and the retrieval statement is stored in the document structure tree; according to the method, a target knowledge document is taken as a component of the target knowledge document, an index structure between each index node in the component of the target knowledge document and the target knowledge document is recorded, and leaf nodes in the index nodes are connected through pointers to form a linked list structure. The corresponding index node can be dynamically retrieved based on the association relationship between the index structure and the linked list structure of the tree structure, and the context content corresponding to the retrieval statement in the target knowledge document is intercepted by adopting different modes based on the type of the index node. And omission of unrelated contents of other chapters and key contents of the same chapter is avoided, so that the retrieval precision and quality are improved.

The invention belongs to the field of artificial intelligence and finance, and relates to a personalized copywriting generation method, which comprises the following steps: classifying all customers according to historical customer feature data to obtain different customer groups, obtaining copywriting keyword combinations of the customer groups according to historical copywriting of each customer group, and generating personalized copywriting keywords of the customer groups according to the copywriting keyword combinations; and constructing a customer group portrait according to the customer group characteristics and the customer group document keyword combination, matching a target customer group portrait according to the customer characteristics of the target customer, and generating a product recommendation scheme according to the customer characteristics and the target customer group portrait through a product recommendation model. And generating a personalized copywriting according to the customer features, the customer group portrait features and the product recommendation scheme through the copywriting generation large model. The invention further provides a personalized copywriting generation device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and historical customer feature data can be stored in a block chain. According to the invention, the client can be accurately positioned, and the generated copywriting can be accurately put.

Provided is a defect detection method and device, computer equipment and a storage medium. The method includes: acquiring an RGB image, a depth image and a sample label of a detection object sample; performing feature map extraction and feature map fusion on the RGB image and the depth image by a feature extraction network of the defect detection model, to obtain a fused feature map; performing defect detection based on the fused feature map by a feature reconstruction network of the defect detection model, to obtain a defect score map, wherein the defect score map being obtained by fusing a global defect score map which is generated based on a global defect detection network with a local defect score map which is generated by a local defect detection network; and updating parameters of the defect detection model based on the defect score map and the sample label.

The invention discloses a thinking chain-based text2sql model implementation method and device, computer equipment and a readable storage medium, and the method comprises the steps: firstly obtaining a sample SQL query instruction text, carrying out RAG retrieval, constructing cue words, calling at least two open source large language models for output, carrying out the evaluation of a target large model to obtain a step-by-step and reward training data set, and carrying out the calculation of the step-by-step and reward training data set; and performing fine tuning training on the initial step-by-step and reward model. And after the target instruction input by the user is obtained, reasoning is performed in combination with the trained step-by-step and reward model to obtain the corresponding SQL statement, so that efficient and accurate text-to-SQL conversion is realized.

The invention relates to a battery fault diagnosis method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring operation data of a target battery in an operation process; determining a target operation characteristic of the target battery in at least one dimension according to the operation data; and based on a pre-trained fault classification model, according to the target operation characteristics of the target battery in at least one dimension, determining a target fault type of the target battery. By adopting the method, the accuracy, robustness and interpretability of battery fault early warning can be improved.