247results about How to "Improve build efficiency" patented technology

The invention discloses a text robot application system based on a large model, and the system comprises the following modules: a knowledge base and analysis module which receives and processes a business document, decomposes the content into semantic units, and marks context features; the question-answer generation module automatically generates question-answer pairs through deep semantic analysis and stores the question-answer pairs in a vector database; the question extension module is used for dynamically extending similar questions by using a natural language generation technology; the semantic intention analysis module is used for accurately extracting a problem core intention through context semantic analysis and mapping the problem core intention to a service path; the text workflow management module is used for realizing dynamic routing of multiple service scenes by adopting a logic tree model; the context semantic association module is used for analyzing and optimizing problem expression through multiple rounds of dialogues; the bottom response module is used for providing multi-level answers in combination with a question and answer database, document recall and dynamic generation; and the intelligent learning module records unsolved problems and optimizes the question and answer library and semantic rules through a learning algorithm.

The invention discloses a knowledge graph-based nursing corpus automatic creation method, and relates to the field of artificial intelligence technology and medical information processing, and the method comprises a multi-dimensional data acquisition stage, a knowledge graph construction stage, a corpus automatic generation and updating stage, and a corpus quality control and evaluation stage. According to the automatic corpus generation method driven by the knowledge graph, dynamic generation and real-time updating of corpora are achieved by constructing an ontology structure, a corpus generation template and an updating algorithm in the nursing field; through a deep learning model and a transfer learning technology, new nursing knowledge and a diversified information structure are continuously introduced into the corpus, and the diversity of corpus content is increased.

The invention provides a fluororubber field knowledge graph construction method based on a large language model, and the method comprises the steps: obtaining process related knowledge data of the fluororubber field, and carrying out the classification, and obtaining the classification knowledge data of the fluororubber field; based on a preset ChatGLM model, performing knowledge extraction according to the fluororubber field classification knowledge data to extract key entities and relationships; carrying out deep analysis on the key entity and the relationship by utilizing semantic correlation and context association analysis, and enhancing the connectivity of the key entity and knowledge in the relationship through semantic similarity and association strength to obtain fused knowledge data; explaining and expanding the fused knowledge data by using a ChatGLM model to obtain expanded triple data; and performing knowledge fusion on the triple data, and performing graph storage by using a Neo4j database to obtain a knowledge graph. According to the method, the knowledge graph construction efficiency is remarkably improved through automatic knowledge extraction and processing of the large language model, and the time cost of manual labeling and data processing is reduced.

The invention discloses an active learning-based electric power knowledge graph construction method and system, and relates to the technical field of electric power market transaction data analysis, and the method comprises the steps: collecting data, cleaning the collected data, generating word prediction task data of an electric power transaction scene, and training an electric power field word embedding model; generating an entity relationship training sample, inputting a word embedding model, performing entity relationship label prediction through an entity relationship joint extraction model, extracting a high-quality sample based on active learning to perform part-of-speech tagging, and training the model based on a tagged sample; and applying the trained entity relationship joint extraction model to power transaction data to construct a knowledge graph, performing manual correction and entity unification, and storing the knowledge graph into a Neo4j database. According to the method, active learning and deep learning are combined, so that the sample labeling cost is effectively reduced, and meanwhile, the model performance is ensured.

The invention provides an active load shedding optimization control method, system and device of a wind power plant and a storage medium, and belongs to the technical field of active power control of the wind power plant, and the method comprises the steps: constructing and training an SAC intelligent agent through an SAC algorithm; acquiring a wind power plant state quantity; inputting the state quantity of the wind power plant into the SAC intelligent agent to obtain a vector # imgabs0 # composed of active power initial reference values of all wind turbine generators; inputting the # imgabs 1 # into a constraint controller for secondary calculation to obtain a vector # imgabs 2 # composed of active power optimization reference values of the wind turbine generators; the wind power plant executes # imgabs3 #; and repeating the steps, and adjusting the active power of each wind turbine generator in real time. The model is high in generalization, stability, reliability and learning efficiency, real-time online calculation of the equivalent fatigue load can be achieved, reasonable distribution of the active power of the wind power plant can be achieved under the condition that the active power constraint of the wind power plant is met, the equivalent fatigue load of the whole wind power plant can be reduced, and the maintenance cost can be reduced.

The invention discloses a monitoring network construction information processing method and device, a terminal and a medium, and the method comprises the steps: obtaining the video image information and equipment basic information of camera equipment based on the camera equipment which is accessed to a video platform; the method comprises the following steps: acquiring information of a camera device, determining GIS information and an actual coverage range of the camera device according to the acquired information, determining monitoring network planning auxiliary information based on a target monitoring area in which a monitoring network needs to be planned, combining the GIS information and the actual coverage range and according to a maximum coverage site selection problem logic, and determining the monitoring network planning auxiliary information based on the acquired monitoring network planning auxiliary information. The monitoring network construction of the target monitoring area is completed, the intelligent construction of the area monitoring network is realized, the monitoring video information is used, the dependence on extra non-monitoring structured information is reduced, the dependence on manual data processing is reduced, and the construction efficiency of the monitoring network is improved.

The invention relates to the technical field of water affair management, and discloses a modularization-based intelligent water affair light application rapid building system, which comprises a template library management module, which is used for storing and managing a plurality of preset function templates, and each function template is used for executing a specific function in water affair management; the parameter configuration module communicates with the template library management module and is used for performing parameterization configuration on the selected function template according to user requirements, and the parameterization configuration comprises data source configuration, operation parameter setting and output option selection; and the system combination and deployment module is used for combining the function templates subjected to parameterization configuration into a complete application system, and deploying the application system into a running environment through a containerization technology and a Kubernetes arrangement tool. Through modular design and template library management, the system can be rapidly configured and deployed according to different water affair management requirements, the construction time of the system is greatly shortened, and the system adapts to rapidly changing business requirements.

The embodiment of the invention relates to the technical field of communication, in particular to a channel establishment method and device and a first terminal. The method comprises the following steps: under the condition that a channel establishment request initiated by a first application is obtained, executing a channel establishment method in an SDK (Software Development Kit) to obtain establishment parameter information required for establishing a data channel; sending the creation parameter information to a background service to indicate the background service to interact with an IMS protocol stack in the first terminal according to the creation parameter information, and constructing a data channel between the first terminal and a second application of the second terminal; the first application and the second application are the same application.

The invention discloses a construction method and device of a query page, a storage medium and electronic equipment, and relates to the technical field of man-machine interaction interface design. The method comprises the steps that a user request is received, and the user request is used for changing a plurality of query conditions currently displayed in a display page or newly adding query conditions in the display page; a query condition configuration list is displayed in the runtime page, the query condition configuration list comprises N preset query conditions, and N is an integer larger than 1; according to the user request, multiple target query conditions meeting the user request are determined from a query condition configuration list, and the multiple target query conditions represent query conditions needing to be displayed to the user after responding to the user request; and rendering the runtime page according to the plurality of target query conditions to obtain a target query page. The technical problems of high repeatability and low efficiency of the creation process of the query page in the prior art are solved.

The invention discloses a deep mutation scanning method based on protein-protein interaction in bacterial cells and a binding affinity prediction method. In the invention, split dCas9 proteins (SEQ ID NO.1 and SEQ ID NO.2) are respectively subjected to fusion expression with a receptor and a ligand with binding affinity to be detected, and are combined with a toxic sgRNA guide sequence (SEQ ID NO.3), and when PPI occurs, a toxic dCas9: sgRNA complex is formed to inhibit bacterial growth, so that a PPI affinity size signal is converted into a bacterial cell generation speed signal, and the signal can be quantified into a copy number value through next-generation sequencing. The invention further designs a deep learning binding affinity prediction model, high-affinity sequences can be screened from theoretical mutation space, the workload and cost of experimental verification are remarkably reduced, and a reliable basis is provided for subsequent protein function optimization and design.

The invention discloses a visual data construction and display method and system, electronic equipment and a medium, and relates to the technical field of data processing. The method comprises the steps of obtaining asset data of a target enterprise, and generating an asset hierarchical structure based on the asset data; combining the asset distribution layer, the asset association layer and the asset attribute layer to construct an annular visual interface of the target enterprise; in response to a display request of a user, a plurality of asset evaluation paths with different path widths are generated in the annular visual interface, and the path widths represent asset value proportions corresponding to the asset evaluation paths; obtaining the data distribution density of each asset evaluation path in the annular visual interface, and determining a display scale corresponding to each asset evaluation path according to each data distribution density; and displaying each asset evaluation path on an annular visual interface according to the corresponding display scale and path width. By implementing the technical scheme provided by the invention, the effect of improving the efficiency of constructing and displaying the visual data is achieved.

The invention provides a construction method and device for a local knowledge graph, and the construction method comprises the steps: extracting a first concept from the multi-text data of a local database, and carrying out the classification and layering of the first concept; and confirming and supplementing the classified and layered first concepts, and optimizing the first concepts into a plurality of second concepts. And segmenting multi-text data into a plurality of text paragraphs in advance, and matching and associating the text paragraphs with the second concept. And respectively extracting a plurality of local concepts and relationships thereof from the associated text paragraphs, and constructing an entity relationship multi-tuple. And integrating similar local concepts in the entity relationship multi-tuple into the same local concept. And analyzing the similarity of all the relationships in the plurality of entity relationship multi-tuples, and evaluating the relevance among all the entity relationship multi-tuples. And based on this, obtaining the constructed knowledge graph. According to the semi-automatic construction method and device, on the basis that expert knowledge is well utilized, the method does not excessively depend on manual construction rules, and the reasoning and understanding ability of a large model is utilized to the maximum extent.

The invention provides an identification analysis knowledge graph construction method based on an adversarial neural network, and belongs to the technical field of the Internet, and the method comprises the steps: 1, obtaining various types of data related to identification analysis, and carrying out the cleaning and conversion; 2, performing entity recognition on the cleaned and converted data and text, and recognizing semantic relation extraction between entities from the text; 3, constructing an entity-relation-entity triple, and forming a preliminary knowledge graph; 4, taking the preliminary knowledge graph as a data set to train an adversarial neural network, and obtaining the discrimination capability of a discriminator and the data generation capability of a generator; and step 5, obtaining entities and relationships obtained through adversarial neural network training according to the discrimination capability and the data generation capability, and converting the entities and relationships into nodes and edges in the knowledge graph to construct a complete knowledge graph. The defects that the accuracy of entity and relation extraction is reduced, and the construction efficiency and quality of the knowledge graph are reduced are overcome.

The embodiment of the invention discloses a model training method and device, electronic equipment, a medium and a program product, which can be applied to various scenes such as cloud technology, artificial intelligence, intelligent traffic, auxiliary driving and the like. According to the embodiment of the invention, a training sample set is obtained, wherein the training sample set comprises an initial sample text corresponding to an initial scene and a newly-added sample text corresponding to a newly-added scene; translating the initial sample text through a teacher model to obtain a teacher translation result; translating the initial sample text and the newly added sample text through an initial student model to obtain a student translation result; calculating a loss value by combining the teacher translation result and the student translation result; and on the basis of the loss value, updating model parameters of the initial student model to obtain a trained student model, so that the trained student model is used for translating the to-be-translated text corresponding to the initial scene and the newly-added scene. Therefore, according to the scheme, the multi-scene adaptive capacity of the model can be enhanced while the model training efficiency is improved.

The embodiment of the invention provides a software package construction method and device and electronic equipment, and is applied to first equipment, the method comprises the following steps: determining a first software package with dependency loss as a to-be-analyzed software package, and determining a dependency object of the loss of the to-be-analyzed software package; acquiring a compiling file corresponding to the dependent object from second equipment; recording a compiled file of the dependent object and a dependency relationship between the dependent object and the to-be-analyzed software package in a database; determining the compiled file of the dependent object as a new to-be-analyzed software package, continuing to perform iterative analysis on the new to-be-analyzed software package, and stopping analysis until the obtained compiled file does not have a missing dependent object; and according to the dependency relationship and the compiling file recorded in the database, reversely constructing the software package corresponding to each dependency object in sequence until the software packages corresponding to all the dependency objects are constructed, and obtaining a target software package. According to the embodiment of the invention, the construction efficiency and accuracy of the software package are improved.

The invention provides a gene Aokap10 for improving the kojic acid yield of aspergillus oryzae, a method and application. The invention finds that in the Aspergillus oryzae Aokap10 gene, nucleotide sequences from the 198 site to the 217 site are taken as target sequences, the site-specific knockout of the Aokap10 gene can be efficiently realized, and when insertion or deletion occurs at the 198 site to the 217 site of the sequence as shown in SEQ ID NO.2, the encoding protein of the Aokap10 gene can be damaged, so that the kojic acid yield of the Aspergillus oryzae is increased, and the application prospect is broad. The construction efficiency of the engineering strain for high yield of kojic acid based on Aokap10 gene mutation is effectively improved.

The invention relates to a neural network model construction method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a selection operation on a neural network parameter value to be selected in a neural network parameter option component on a configuration interface, and storing the selected neural network parameter value; obtaining structure configuration parameters on the configuration interface, and performing network layer structure configuration according to the structure configuration parameters; configuring the network layer according to the network layer configuration data and the stored neural network parameter value to obtain a creation logic of the network layer; and creating a network construction class, and constructing a neural network model through the network construction class according to the stored neural network parameter value, the configured network layer structure and the creation logic of the network layer. By adopting the method, the construction process of the neural network model can be simplified, and the model construction efficiency is improved.

The present invention relates to the field of digital twin technology, and in particular to a model building method for digital twins, comprising: storing information of each model file in a file to be parsed; determining a file processing method according to whether there is an associated historical parsing file; determining a parsing optimization strategy according to the parsing file status of the file to be parsed; under the condition that the parsing is completed, generating a data interaction relationship between models, extracting key information in a target element and storing it in a preset data structure; analyzing a target file that has been merged and packaged by a compiler to build a syntax tree of the target file; obtaining a target code file of each level model by converting the syntax tree of the target file, and merging each target code file into an executable file by a linker, wherein data exchange is performed between models in the executable file based on the data interaction relationship between models obtained after parsing. The present invention improves the model building efficiency of the digital twin.

The invention discloses a deep learning-based question and answer knowledge graph construction method and system, and the method comprises the steps: collecting multi-dimensional question and answer data of a target domain from a plurality of data sources, carrying out the cleaning and standardization processing of the question and answer data, so as to eliminate noise information, and generating a preliminary data set; performing semantic analysis on the question and answer data by using a deep learning model, and generating a context embedding representation of each question and answer text in the question and answer data; knowledge entities and relationships among the entities are identified from the context embedding representation, and a preliminary knowledge triple is constructed; and based on the knowledge triad, constructing a preliminary question and answer knowledge graph for the identified entities and relationships, and allocating a unique identifier to each node in the preliminary question and answer knowledge graph to generate a structured question and answer knowledge graph. By utilizing the embodiment of the invention, the question and answer knowledge graph construction efficiency and the semantic understanding capability can be remarkably improved, and the application of an intelligent question and answer system in a complex scene is promoted.

The invention belongs to the technical field of medical imaging and diagnosis, and discloses a cerebral apoplexy screening intima-media membrane intelligent detection system which comprises a data acquisition module used for acquiring two-dimensional B ultrasonic image data, color Doppler image data and blood flow velocity waveform data; the data processing module is used for processing the two-dimensional B-mode ultrasound image data and the color Doppler image data to obtain carotid artery imaging data and extracting a carotid artery boundary and a carotid artery intima-media membrane area from the carotid artery imaging data; processing the carotid intima-media area to obtain carotid intima-media thickness data; the blood flow analysis module is used for extracting blood flow velocity and direction information from the color Doppler image data and identifying the blood flow velocity and direction information to obtain abnormal blood flow data; processing the blood flow velocity waveform data to obtain hemodynamic parameter data; through fusion analysis of multi-dimensional data, the cerebral apoplexy risk of the patient can be evaluated more comprehensively, and the treatment effect is improved.

The invention is suitable for the technical field of data mining, and provides a data set construction method and device, terminal equipment and a storage medium, and the method comprises the steps: obtaining a sample example picture which comprises a to-be-detected target in a target detection task; extracting target instance features of the to-be-detected target from the sample instance pictures; according to the target instance feature and a pre-established neighbor relation graph, a first sample graph set is determined, the neighbor relation graph is established according to original instance features of a plurality of original pictures, and pictures in the first sample graph set comprise instance features identical and / or similar to the target instance feature; and updating and mining the first sample image set based on an active learning task process to obtain a target sample data set for the target detection task. The data set can be efficiently constructed, noise data is reduced, the quality of the data set is guaranteed, and meanwhile labor consumption can be effectively reduced.

The invention discloses a meteorological corpus construction method and system and a related device, and belongs to the technical field of meteorological data processing. The method comprises the following steps: collecting an original corpus file in the meteorological field, and converting the original corpus file into uniform Markdown format data; cleaning the data in the Markdown format, and organizing the data in the Markdown format into a uniformly structured meteorological corpus; and combining the uniformly structured meteorological corpus with an external knowledge base to construct various data sets required by the meteorological service large model, wherein the various data sets comprise a data set for pre-training, a data set for fine tuning, and a data set and an evaluation benchmark data set required for retrieval enhancement generation. According to the method, the construction efficiency is remarkably improved, the labor cost is reduced, and meanwhile, the quality and consistency of the meteorological corpus are ensured.

The invention discloses a user load characteristic portrait construction method and system based on branch load monitoring, and relates to the technical field of power load data analysis, and the method comprises the steps: obtaining branch load monitoring data, obtaining power network information, and obtaining user power load data according to the branch load monitoring data and the power network information. According to the method, the reliability and consistency of data are ensured through a data index smoothing coefficient and a linear interpolation method, user power load standard data are analyzed through a data principal component analysis method, user power load characteristic information is obtained through a user power load potential evaluation index, and a user power load electric appliance evaluation index is used for evaluating a user power load electric appliance. The user electric appliance load characteristic information is obtained, the user load characteristic clustering information is obtained, the user load characteristic portrait information is obtained based on user portrait construction, and the user load characteristic portrait construction efficiency and the portrait accuracy are improved.

The invention belongs to the technical field of track monitoring, and provides a digital twinning state monitoring method for a maglev line track fusing air-track-ground multi-dimensional information, and the method comprises the steps: building a three-dimensional model of a segmented line track based on the aerial photography information of an unmanned plane and a BIM technology; acquiring surface feature data of the selected segmented line track by using a section scanner, and reconstructing a three-dimensional model of the selected segmented line track by combining attitude and position information of an inertial navigation system; and finally splicing the reconstructed three-dimensional model and the non-reconstructed segmented line track model to obtain a line track geometric model, improving the modeling precision, constructing a database based on the qualified holographic state data, and constructing a behavior and rule model of the magnetic levitation line track digital base in combination with the constructed geometric model. Information fusion is carried out on isomorphic and heterogeneous holographic state data by using a Kalman filtering fusion algorithm, and diversified intelligent monitoring of the magnetic levitation line track is realized.

The invention provides a Bluetooth connection establishment method and device, electronic equipment and a storage medium, and the method comprises the steps that first Bluetooth equipment sends a Bluetooth pairing request to second Bluetooth equipment to be connected, and receives EIR (Extended Inquiry Response) data returned by the second Bluetooth equipment, the EIR data comprises a first service discovery protocol (SDP) version number supported by the second Bluetooth device, acquiring a first application specification profile associated with the first SDP version number and an identifier of the second Bluetooth device from a preset file under the condition that the second Bluetooth device is determined to be a preset device, and establishing a Bluetooth connection with the second Bluetooth device based on the first profile, therefore, the information for establishing the Bluetooth connection with the second Bluetooth device can be more conveniently obtained based on the preset file, the operation of establishing the Bluetooth connection can be simplified, and the establishment efficiency of the Bluetooth connection is effectively improved.

The invention discloses a photoetching model establishment method and device, a storage medium and a program product, and relates to the technical field of semiconductors. The method comprises the following steps: acquiring actual morphology measurement data of photoresist in a photoetching simulation process and N physical and chemical effect functions of the photoresist corresponding to the photoetching simulation process; based on the N physical and chemical effect functions, establishing an initial photoetching model; based on the initial photoetching model and the actual morphology measurement data, a target parameter combination with fitness meeting a first preset condition is obtained through iterative solution by running a genetic algorithm, and the fitness is determined and obtained based on a loss function and / or a root-mean-square error of the initial photoetching model; and based on the target parameter combination, determining to obtain a target photoetching model of the photoresist under the photoetching simulation process. According to the embodiment of the invention, the method can achieve the building of the photoetching model more efficiently and accurately, thereby effectively improving the building efficiency of the whole photoetching model, and improving the prediction precision of the photoresist morphology.