53results about How to "Guaranteed relevance" patented technology

The invention discloses a data isolation and privacy protection method and system for a data security large model, and relates to the technical field of artificial intelligence, the method comprises the following steps: setting an independent storage area for each enterprise in an external knowledge base in advance, and transmitting encrypted data to the corresponding storage area based on an enterprise identifier, setting corresponding access authority for the encrypted data of each storage area; judging whether the user identity information and the user access permission information are compliant or not, extracting a keyword corresponding to the user demand information under the compliant condition, and performing similarity retrieval in an external knowledge base based on the keyword to obtain corpus data with the highest similarity with the keyword; the corpus data and the user requirements are jointly input into the large data security model to generate the data security document, and the problems that in the prior art, data security isolation and privacy protection cannot be achieved, and security and compliance use of data in the whole process cannot be guaranteed are solved.

The invention belongs to the technical field of digital bid evaluation, and provides an intelligent bid evaluation method and system based on a knowledge enhancement large language model.The method comprises the steps that firstly, a to-be-evaluated file library of project bid inviting and tendering files is established; then, files in the to-be-reviewed file library are analyzed, file slices are generated, and a reviewed file knowledge base is formed; then, text slices in the file knowledge base are retrieved and reviewed through key fields, and input cue words of the knowledge enhancement large language model are generated in combination with the key fields and the file slices; then, interacting the input cue word with a pre-trained knowledge enhancement large language model to obtain all key field information; then, scoring the bidding file according to a preset bid evaluation algorithm for all the obtained key field information; and finally, sorting the scores of all the bidding files in a descending order to generate an intelligent bid evaluation report. According to the method, the application of the knowledge-enhanced large language model in the aspects of bidding and tendering key information extraction and intelligent bid evaluation is realized, the flexibility and adaptability are relatively high, the influence of human factors on bid evaluation work is reduced, and the fairness and justice of the bid evaluation process and result are actively promoted.

The invention provides an oil well oil production prediction method based on CEEMDAN-SA-LSTM, and the method is characterized in that the method comprises the following steps: 1) collecting oil well feature data, complementing missing values, processing abnormal values, and converting a data set into a format suitable for model training; 2) carrying out importance analysis by utilizing a Boruta algorithm, and constructing an oil well oil production characteristic data set; 3) performing data set division on the data converted in the step 2); and 4) carrying out feature decomposition by using CEEMDAN and carrying out data dimension reduction by using PCA to obtain a final component feature data set. 5) inputting the final component feature data set into the SA-LSTM model for training, and constructing a prediction model; 6) adjusting and optimizing the model by adopting a parallel genetic algorithm to obtain an optimal parameter combination; and 7) according to the trained oil well oil production prediction model, using test set data to verify the model performance, and predicting the oil well oil production. The invention discusses the method for predicting the oil production of the oil well by using the CEEMDAN-SA-LSTM model, and the method can obtain a better prediction result.

The invention provides a financial question and answer method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring original financial data; constructing a financial database based on the original financial data, and establishing a data index corresponding to the original financial data in the financial database; receiving a financial question input by a user, and matching a target data index corresponding to the financial question in the financial database; querying reference data of the financial problem in the financial database based on the target data index, and generating prompt information based on the reference data; and inputting the prompt information into a large language model, generating a target answer corresponding to the financial question, and returning the target answer to the user. According to the method, the query analysis and information integration capabilities of the large language model in the financial field are improved, and the accuracy, correlation, integrity and security of financial answers are ensured.

The invention discloses an urban road traffic state prediction method based on a macro-medium-micro hybrid simulation model, a storage medium and equipment, and the method comprises the steps: collecting historical electronic police data and traffic channelization data, inputting the historical electronic police data and traffic channelization data into a constructed macro-medium-micro integrated multi-level hybrid simulation model, and carrying out the simulation, obtaining a road traffic state in each time period and traffic flow data at each moment; constructing a traffic flow parameter prediction model based on an MVF-FA-LSTM algorithm, inputting the traffic flow data into the traffic flow parameter prediction model, and predicting the traffic flow and the passing speed of the road; and constructing a traffic state prediction model based on a fuzzy C-means clustering algorithm, inputting the predicted traffic flow and passing speed of the road into the traffic state prediction model, and predicting the traffic state of the road. According to the method, unification of microscopic, mesoscopic and macroscopic simulation models is realized, and road flow and passing speed prediction is realized, so that road traffic states are divided, and a traffic management department is guided to command and make decisions.

The invention provides a channel section transport volume measuring and calculating method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: carrying out the data preprocessing of maritime ship port reporting data, and obtaining the initial maritime ship port reporting data; performing data preprocessing on the ship AIS data to obtain initial ship AIS data; constructing constraint conditions according to the initial maritime ship port reporting data and the initial ship AIS data, and performing data association according to the constraint conditions to obtain an associated data set; constructing a ship passing channel section algorithm according to the ship AIS track information and the channel section information; and identifying ship behaviors according to the associated data set and a ship passing channel section algorithm to obtain the transport volume of the ship passing the channel section. Real-time, accurate and comprehensive channel operation data can be provided for related management departments, and channel management efficiency and decision-making scientificity can be improved.

The invention provides an instruction fine tuning data generation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining domain background data, inputting the domain background data and a first instruction into a preset large language model, and enabling the preset large language model to output problem data based on the domain background data and the first instruction; and inputting the question data, the domain background data and the second instruction into a preset big language model, so that the preset big language model answers the question data based on the domain background data and the second instruction, and outputting answer data. The field background knowledge to which the instruction fine-tuning data belongs is added as one-dimensional input, so that the large language model can generate the instruction fine-tuning data based on the related field background knowledge, the field correlation of the instruction fine-tuning data is ensured, and the accuracy of the instruction fine-tuning data is improved. And in addition, field background knowledge can be referred to in the question and answer generation stage, the correctness of answer data is improved, and the accuracy of instruction fine adjustment data is further improved.

The embodiment of the invention provides a domain name resolution path determination method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring an internet protocol address IP of a target server; generating a prefix part of the second-level domain name according to the IP address of the target server; splicing the prefix part with the secondary domain name to determine a detection domain name of the target server; controlling the client to send an analysis request for the detection domain name to a target server, so that the target server sends a request data packet to an authoritative server; receiving all request data packets sent by the authoritative server, and screening all request data packets according to the detection domain name to obtain a first target data packet; judging whether a source address in the first target data packet is consistent with a target server IP; and if the source address is consistent with the IP of the target server, determining that the analysis path is composed of the client, the target server and the authoritative server. The method is used for achieving the effect of comprehensively restoring the recursive analysis path.

The invention provides an information processing method and device, equipment, a storage medium and a computer program product.The information processing method comprises the steps that identification information of a target object is determined; according to the identification information, obtaining analysis reference information corresponding to the target object; the analysis reference information comprises industry information, market feedback information, historical trend information and technical index information; and determining an analysis result corresponding to the target object according to the analysis reference information. According to the scheme, analysis can be carried out according to more comprehensive information, comprehensive consideration is carried out on related information, the relevance between the information is ensured, comprehensive judgment is formed, a comprehensive and professional analysis result is provided, the analysis accuracy is improved, and the analysis efficiency is improved. The problem that in the prior art, related schemes for data analysis are low in analysis accuracy is well solved.

The invention discloses an article recommendation method, electronic equipment, a storage medium and a program product, and relates to the field of large model technology and data recommendation. The method comprises the steps that in response to a detected article recommendation instruction, article feature vectors of recommended articles are obtained, and the recommended articles comprise a first article displayed to a user and a plurality of second articles waiting to be displayed to the user; inputting the feature vector combinations corresponding to the plurality of second articles into a sequence recommendation model, and screening out a target article from the plurality of second articles by using the sequence recommendation model; an article recommendation sequence is updated based on the target article to obtain a target recommendation sequence, and the article recommendation sequence is used for displaying the first article to the user; and outputting the target recommendation sequence. The technical problem that the interest of the user in browsing the articles is affected due to the fact that the articles pushed to the user are lack of diversity in the related technology is solved.

The utility model provides a control terminal for large-scale machine operation hydraulic data acquisition, and relates to the technical field of power electronics, the control terminal comprises a power supply module, a lightning protection module, an industrial control computer, a GPS positioning module and an alarm lamp module, the power supply module is used for converting external 220V alternating current into 24V direct current; the lightning protection module is connected with the power supply module, and the lightning protection module is connected with an external data acquisition box; the industrial control computer is connected with the power supply module and the lightning protection module. The GPS positioning module is connected with the industrial personal computer, and the GPS positioning module is used for acquiring geographic position information of the large computer in real time; the alarm lamp module is connected with the industrial personal computer, and the alarm lamp module is used for triggering sound-light alarm when the industrial personal computer detects that the hydraulic system is abnormal. According to the utility model, the stability and the reliability of the monitoring system are improved, data can be transmitted in real time, and the efficiency and the safety of railway maintenance operation are remarkably improved.

The invention provides an expressway business form extraction method and system based on a neural network, and the method comprises the steps: obtaining to-be-processed sub-business forms, carrying out the data cleaning, and generating rule data; performing compliance verification on the rule data based on the agreed rule, and if the verification is qualified, storing the rule data as a standard business form according to the category; traversing each standard service form in sequence, identifying coincident entries, taking the coincident entries as association keys, and extracting a high-speed service form set belonging to the same user based on the association keys; and inputting the high-speed business form set into a pre-trained statement extraction model to generate a passing behavior statement. According to the invention, by integrating the expressway business forms, standardized processing and efficient management of data are realized. According to the method, the data compliance is ensured, the business forms of the same user are identified and associated, the traffic behavior statements are generated by using the statement extraction model, and convenient and accurate information support is provided for expressway business management.

The invention relates to a QEC detection method and system based on AR. The method comprises the steps that a pre-constructed engine standard model is disassembled into part units, a three-dimensional model set in the installation process of all the part units is obtained, and the three-dimensional model obtained after installation of each part unit is finished is a part unit standard model; obtaining an engine real-time model based on AR equipment; when the difference degree between the engine real-time model and the standard model is higher than a first threshold value, a first part unit with the largest difference degree is obtained, whether the corresponding real-time model is matched with the three-dimensional model set or not is judged, if yes, the first part unit is maintained towards the corresponding standard model state, and if not, the first part unit is maintained; and when all the part units in contact with the first part unit are synchronously changed to the corresponding standard model states, the engine real-time model is obtained again to continue execution, and otherwise, a QEC request is sent out. Compared with the prior art, the method has the advantages that the safety and the efficiency of the whole QEC operation inspection and verification process are improved, and the like.

The present invention relates to the technical field of database construction, and in particular to a method and system for constructing a knowledge base for brain disease nursing. The method comprises the following steps: acquiring multi-source brain disease data; performing structured data screening on the multi-source brain disease data to generate structured brain disease data and unstructured brain disease data; performing multi-modal data structured stratification on the unstructured brain disease data to generate multi-modal structured stratified data; performing data preprocessing on the multi-modal structured stratified data and the structured brain disease data to generate a standard structured brain disease data set; performing context analysis on the standard structured brain disease data set to generate a semantic vector set of brain disease information; performing redundant relationship pruning processing on the semantic vector set of brain disease information to generate spatial semantic optimized data. The present invention improves the construction quality and practicality of the brain disease nursing knowledge base by integrating multi-source data, structured and unstructured information, real-time dynamic mapping of nursing needs and system feedback evaluation.

This invention discloses a non-load-bearing front engine compartment structure, a frame, and a chassis. The front engine compartment structure includes two sets of wheel arch assemblies spaced apart along the width of the vehicle body. A first crossbeam and a second crossbeam are arranged parallel to each other and spaced apart between the two sets of wheel arch assemblies. Two hinge mounting members are arranged between the two wheel arch assemblies. The hinge mounting members are provided with mounting surfaces for mounting hood hinges. The structural strength of the wheel arch assembly itself is improved by the first and second structural beams. The parallel first and second crossbeams are fixed to the two sets of wheel arch assemblies respectively, further improving the correlation and stability between structural components and maintaining the structural strength of the wheel arch assemblies as a whole. The hinge mounting members are arranged on the wheel arch assemblies to provide the mounting base for the hood hinges. Under the premise of reliable overall structural strength, the additional hood mounting structure is avoided in the front engine compartment, thus improving overall reliability and space utilization.

The invention relates to the technical field of web crawlers, and discloses a web crawler-based financial information crawling method, which comprises the following steps of: collecting websites needing to be crawled, performing crawling test on the websites, judging whether the current website can be crawled or not according to a crawling test result, and crawling the websites capable of being crawled. The data conforming to the keyword is used as a first set, a crawling data collection strategy is carried out on the first set, and the data collection strategy specifically comprises the steps that the number of data collected each time is set, elements in the first set are selected, a comparison set is input, and the number of repetitions between the data collected each time and the elements in the comparison set is judged; and the repetition rate of each time is calculated, and the number of times of subsequent crawling is predicted according to the repetition rate.

The invention relates to the field of wind power generation, in particular to a wind turbine generator yaw static error correction method and system based on a multi-beam laser radar. The method comprises the following steps: S1, scanning a wind field area in front of an impeller of a generator set through a multi-beam wind measurement laser radar mounted in a cabin of the wind turbine generator set to obtain parameter information of a plurality of spatial points; s2, performing fitting calculation on the parameter information system to obtain a fitting circle representing a horizontal wind vector of the wind field area, and solving the fitting circle to obtain a free flow wind direction; s3, the free flow wind direction is compared with the current cabin orientation, and a real-time static yaw error angle is obtained through calculation; generating a yaw control instruction according to a preset control strategy; s5, solving and calculating the fitting circle to obtain a transverse wind component, and correcting the yaw control instruction; according to the method, the control instruction is generated through the control strategy to drive the yaw system to perform dynamic compensation, so that the wind turbine generator can continuously maintain the optimal windward attitude, and the stability and long-term effectiveness of control are ensured.

The invention relates to the technical field of signal enhancement, in particular to a high-efficiency wireless signal enhancement method and system, and the method comprises the steps: obtaining a current wireless signal and a historical wireless signal, determining a signal transmitting position and a signal receiving position according to the current wireless signal, the method comprises the following steps: screening historical wireless signals based on a receiving and transmitting range between a signal transmitting position and a signal receiving position to obtain reference wireless signals, performing signal transmission fluctuation analysis on the reference wireless signals to obtain a signal transmission curve and a transmission label, training a signal enhancement model to obtain a signal enhancement model, and performing signal transmission analysis on the signal enhancement model to obtain a signal enhancement result. And performing signal transmission fluctuation analysis on the current wireless signal to obtain a current signal curve, inputting the current signal curve into the signal enhancement model for enhancement to obtain an enhanced current signal curve, and generating a wireless signal to be transmitted based on the enhanced current signal curve. According to the invention, the transmission efficiency of the wireless signal is improved.

The invention relates to the technical field of intelligent event processing, and provides an event dialogue collecting and processing method and system.The method comprises the steps that a corresponding cache instance is created according to a received dialogue request, and the cache instance is initialized; modifying a preset information extraction cue word template according to the cache instance, obtaining an information extraction cue word, and updating slot position information of the cache instance according to the information extraction cue word; when a picture is received in the dialogue, the cache instance is updated by analyzing and adding picture information, and when an instruction of deleting the picture is received in the dialogue, the picture is deleted by modifying the picture information in the cache instance; and modifying a preset content reply prompt word template according to the cache instance, obtaining a content reply prompt word, and generating dialogue reply content according to the content reply prompt word. Through accurate cache management, slot state control and picture content maintenance, the information acquisition and processing flow is optimized, the response speed and the data processing precision of the system are improved, and the intelligent level of user interaction is improved.

The invention discloses a multi-view stereo matching quality prediction method, system, device and medium, and relates to the technical field of multi-view stereo matching. The method comprises: obtaining left and right image film altitude angles, film azimuth angles, solar altitude angles, solar azimuth angles and left and right image film altitude angles, azimuth angles, solar altitude angles, azimuth angle difference values, left and right image intersection angles, and the number of left and right image SIFT same-name points; constructing a multi-view stereo matching quality prediction model; inputting imaging parameter data of the image to be predicted into the multi-view stereo matching quality prediction model, encoding the imaging parameters using an encoder, inputting the encoded features into a decoder for decoding, and obtaining an image pair reconstruction quality prediction value; the method solves the problem of low matching accuracy and efficiency due to uneven quality of multi-view images.

This application provides a method for finely characterizing the fractured area of ​​the floor strata in a mining face, relating to the field of coal seam floor characterization technology. The method includes: collecting the original microseismic event signals and environmental correlation parameters corresponding to each microseismic event in the fractured area of ​​the mining face floor strata; performing feature extraction to obtain a microseismic event feature matrix corresponding to each microseismic event; inputting a microseismic event classification model to obtain the rupture correlation confidence score of the microseismic event; if the source type of any microseismic event is rupture type, and the corresponding rupture correlation confidence score is greater than a preset rupture correlation confidence score threshold, then the fractured area of ​​the mining face floor strata is characterized based on this microseismic event. This application achieves fine characterization of the fractured area of ​​the mining face floor strata, providing a reliable basis for engineering safety control.

The present invention relates to a data-driven testing method and system based on intelligent driving, belonging to the field of intelligent driving technology. The method includes: obtaining point cloud data, speed data, position data, and acceleration data through vehicle-mounted sensors; presetting a vehicle trajectory prediction model and extracting model input data categories, performing balanced processing on the data obtained by the vehicle-mounted sensors based on nonlinear multi-category responses according to the model input data categories and constructing a vehicle power data set, optimizing the vehicle trajectory prediction model through vehicle power data set optimization training; constructing a vehicle motion model, constructing test cases based on the vehicle trajectory prediction model, applying the test cases to the vehicle motion model for test evaluation to obtain test results, and optimizing the vehicle motion model and the vehicle trajectory prediction model according to the test results. The problem of data imbalance in test data collection is solved, and the representativeness and effectiveness of the test cases are improved by dynamically setting the test cases.

The invention discloses a weighing experiment device and method for an electric shovel with an externally-hung load, which are characterized in that on the premise that the electric shovel is in a static state, the electric shovel meets a moment balance condition at the moment, a bucket rod and a bucket are rigid bodies, and a hinge point is a saddle rotation center, so that the moment generated by a lower-hung balancing weight on the saddle rotation center is uniform; and the moment is equal to the moment generated to the center when the material is placed in the bucket, so that the moment balance state of the electric shovel can be equivalent, the weight equivalent simulation of the lower hanging counterweight and the internal material is realized, and an accurate, efficient and safe load simulation scheme is provided for the electric shovel weighing experiment.

The present application belongs to the technical field of vehicle inspection and certification, and specifically relates to a method for generating inspection project configuration for multiple registered declared values, including the following steps: constructing an entry framework, dividing it into entries related to and unrelated to the inspection project, and dividing it into single-matching entries and multiple-matching entries according to the uniqueness and diversity of the declared values ​​corresponding to each parameter; for multiple-matching entries, generating entry configurations through numerical closure relationships, position alignment relationships, and cross relationships; obtaining an initial configuration set of the inspection project according to a full-entry permutation and combination method or an entry combination method related to the inspection project, and then screening based on the binding relationship between the parameters, and finally filtering and removing duplicates according to the inspection project parameters to obtain the final configuration of the inspection project. The present application solves the problem of low efficiency and error-proneness in manually combing project configurations due to the diversity and complexity of registered parameters, and improves the practical value of the inspection project configuration through a flexible, accurate, and efficient configuration generation method.

This invention provides a method for optimizing process parameters of aluminum foam based on physical information deep learning, belonging to the field of deep learning-based process parameter optimization. The method includes: data preprocessing, mechanical property prediction, and process parameter optimization. Data preprocessing includes generative data augmentation based on physical information, data standardization, and feature dimensionality reduction. Mechanical property prediction utilizes enhanced data of aluminum foam to predict mechanical properties by constructing a multimodal information fusion prediction framework based on graph neural networks. Process parameter optimization uses a trained graph neural network as the objective function and embeds it into an improved Bayesian optimization framework to iteratively locate the parameter combination that yields the optimal energy absorption performance. This method can not only predict the mechanical properties of aluminum foam but also optimize process parameters during its preparation, significantly reducing R&D costs, shortening the development cycle, and improving the effectiveness of material R&D.

A system for determining a non-linear surge pricing is described. Typically, the system obtains historical data, as well as original non-linear surge pricing models and service parameters, related to service usage by a user and service provision by a provider, respectively. From the data, the system determines a user pricing elastic model and a provider pricing elastic model, and optimize the objective function based on a weighted combination of the predicted number of service uses and the predicted total amount of merchandise transactions (predicted GMV), an original non-linear surge pricing model, service parameters, and one or both of a user pricing elasticity model and a provider pricing elasticity model. The optimized objective function is an updated model for non-linear surge for generating an enhanced surge multiple for a new request for service use based on the optimized objective function and the original surge multiple.

The utility model discloses mechanical processing technical field especially relates to a kind of aluminium alloy rack for cutting machine, including rack base and the rack shell of covering rack base setting, still include the feeding cabin and cutting cabin of setting on rack shell, feeding cabin is provided with feeding plate inside, rack base is provided with the feeding frame of intercommunication feeding cabin and cutting cabin, cutting frame is located on the rack base of cutting cabin one side, cutting slide rail is slidably connected with cutting saw, utilize feeding cabin and cutting cabin respectively corresponding feeding function area and cutting function area, so it can be in actual use, the cabin of two different working contents is distinguished, realize the effect of separate processing, when adjusting the working environment in feeding cabin, cutting cabin does not need to open, keep closed state, and when adjusting cutting cabin, feeding cabin keeps closed state, so two cabins are independent of each other, to be able to protect the security of surrounding working environment.

The invention relates to an enterprise data display method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: obtaining the job data of a target person, and determining the job time range of the target person in a target enterprise based on the job data; obtaining enterprise data of the target enterprise from the plurality of data sources, screening out the target enterprise data in a random time range from the enterprise data, and establishing a first association relationship between the target enterprise data and the target personnel; and in response to an evaluation request for the target personnel, displaying the target enterprise data in a preset page based on the first association relationship. By adopting the method, the efficiency and the accuracy of querying and evaluating the enterprise data required by the enterprise management personnel can be improved.

The invention relates to a power battery SOC estimation method and device, and the method comprises the steps: building an equivalent circuit model of a power battery, and constructing a state equation and an observation equation of the power battery according to the equivalent circuit model; constructing an adaptive unscented information filtering SOC estimation algorithm, and determining a state estimation value and an error covariance at any moment through the adaptive unscented information filtering SOC estimation algorithm; according to the adaptive unscented information filtering SOC estimation algorithm, a prediction error covariance is processed through a Levenberg-Marquardt operator, and a measurement noise variance is processed through an adaptive filter. And solving the SOC value of the power battery at any moment in the state equation and the observation equation according to the state estimation value at any moment and the error covariance. According to the technical scheme provided by the invention, the estimation accuracy and stability of the SOC of the power battery are ensured while the implementation is easy.