263 results about "Data interpretation" patented technology

The invention relates to the technical field of remote monitoring, in particular to a remote monitoring method and system for intelligent water purification equipment. The system comprises a sensing execution unit, a data routing unit, an intelligent central unit and an interactive service unit. The intelligent central unit is used for comparing underground water quality data collected in real time with corresponding month threshold values over the years, water quality fluctuation caused by natural changes such as seasonal replacement can be accurately distinguished, the water quality data interpretation accuracy is improved, when the water quality data deviates from a normal range and influences of natural laws are eliminated, the system introduces real-time weather data, and the water quality data interpretation accuracy is improved. And the analysis module considers the effect of weather on water quality by means of a dynamic structure equation model and resets a threshold value. The intelligent self-adaptive mechanism can effectively distinguish water quality abnormity caused by non-natural laws, for example, normal fluctuation of water quality after rainstorm is recognized, accuracy and intelligence of water quality monitoring are enhanced through multiple times of accurate judgment, and abnormity can be quickly recognized and early warned.

The present invention discloses an artificial intelligence-based (AI-based) system and method for generating optimised operation planning and scheduling output. The AI-based system obtains at least one of: one or more data explanation videos, one or more process understanding videos, and unconstrained operational planning data, along with one or more prompts as an input. The AI-based system extracts one or more informative image frames and audio data, to train the one or more AI models and generate a planning standard operating procedure (SOP). The AI-based system processes the planning SOP, the constrained operational planning data, and the one or more prompts to generate the optimised operation planning and scheduling output based on an optimised function with a continuous feedback loop in response to at least one of: the one or more prompts, updated planning SOP, and real-time changes in the constrained operational planning data.

A conversation agent is described. An example method includes receiving a user request from a user interface of a conversation agent; determining a predicted intent of the user request; selecting a prompt template from a plurality of prompt templates corresponding to respective intents based on the predicted intent of the user request; generating a prompt using the prompt template and the user request; processing the prompt using a generative language model to generate an output; and displaying, on the user interface, a response to the user request generated based on the output.

The invention discloses a soil pollution accurate positioning method based on a geophysical exploration technology. The method comprises the following steps: S1, analyzing geologic features of a research area: analyzing the geologic features of the research area; s2, constructing a geological model; s3, measuring line arrangement and data acquisition; s4, data processing: obtaining a two-dimensional resistivity and polarizability image and an internal structure image of ground penetrating radar data by adopting least square inversion, training an anomalous body recognition model by utilizing a convolutional neural network, automatically recognizing anomalous body features in ERT and GPR data, and automatically screening out potential pollution areas; s5, data explanation: performing comprehensive analysis on inversion results of ERT and GPR, constructing an intelligent explanation model, automatically adjusting explanation parameters by the intelligent explanation model according to data features, and providing a plurality of explanation schemes; and S6, establishing a three-dimensional electrical structure model: establishing the three-dimensional electrical structure model of the research area by adopting a Kriging interpolation method according to the ERT inversion result and the earth surface coordinate data.

The invention relates to the technical field of unmanned aerial vehicle video data interpretation, in particular to an unmanned aerial vehicle video abstract semantic description method and system based on a multi-modal large model, and the method comprises the steps: obtaining a plurality of segmented video frame images of unmanned aerial vehicle video data; extracting image features by using a multi-modal large model, wherein the multi-modal large model adopts an image encoder in a visual language basic model to encode the input segmented video frame images and extract the corresponding image features; performing adaptive clustering on the image features to obtain a clustering center of each segmented video, and generating an unmanned aerial vehicle video abstract by taking a frame position where the clustering center is located as a frame position where the video abstract is located; and acquiring scene semantic description of the unmanned aerial vehicle video abstract by utilizing a semantic description model, wherein the semantic description model is obtained by finely adjusting a large model by utilizing an unmanned aerial vehicle image semantic description data set. The core intelligence information can be accurately and efficiently extracted from the unmanned aerial vehicle video data, and the utilization efficiency of the unmanned aerial vehicle video data is improved.

The invention provides a hydraulic fracturing fracture net distribution form near-field monitoring method, which comprises the following steps of: arranging a plurality of roof monitoring holes in roadways on two sides of an underground coal mine working surface, installing electromagnetic signal sensors in each roof monitoring hole and on anchor rods of roadway stoping sides, and constructing a full-space monitoring network covering a hydraulic fracturing layer; a data interpretation processing module of the electromagnetic signal time-shifting imaging analysis system comprises a multi-field coupling mathematical model for analyzing and deducing real-time imaging of electromagnetic signals; in the hydraulic fracturing process, an electromagnetic signal sensor is used for monitoring a current field, an electromagnetic field and an ion diffusion field in the rock mass fracture development and expansion process, a monitoring result is substituted into an electromagnetic signal time-shifting imaging analysis system for calculation and feature value extraction, and the fracture net distribution form is deduced through the feature value. According to the invention, the expansion path of the fracturing fluid in the rock stratum can be monitored in real time, the three-dimensional distribution form of the hydraulic fracturing fracture network can be inverted, and a new technical support is provided for the inspection of the hydraulic fracturing pressure relief effect of the underground coal mine.

The invention provides a low-code enterprise-level intelligent assistant development platform, and relates to the field of intelligent assistant development. The low-code enterprise-level intelligent assistant development platform comprises an application layer, a platform layer, a capability layer and an underlying service. According to the low-code enterprise-level intelligent assistant development platform, a low-code enterprise-level intelligent assistant development platform is realized, and by means of the platform, a user can develop enterprise-level intelligent assistants suitable for various industries, thereby helping enterprises to realize cost reduction and benefit increase; a user can complete the creation of a knowledge base, a workflow and an intelligent agent only through simple configuration or arrangement, a low use threshold is achieved, enterprise internal services or third-party MCP services can be accessed by means of a plug-in tool and a platform, uploading and publishing of user-defined tools are supported at the same time, high expandability is achieved, and the method can be widely applied to the field of enterprise management. The platform supports high-order functions such as multi-person collaborative development, multi-modal knowledge base construction, multi-modal data interpretation and processing and construction of multiple types of agents, and can meet complex enterprise-level application scenes.

The invention relates to the technical field of pipeline anomaly detection, in particular to a petroleum pipeline network anomaly recognition and early warning system which comprises a pressure fluctuation monitoring module, a flow anomaly analysis module, a state association optimization module, an early warning strategy adjustment module and an anomaly early warning generation module. According to the method, deep correlation analysis is carried out on the relation between pressure fluctuation and flow abnormity, the change trend of pipeline pressure and flow can be accurately captured, the abnormal state in pipe network operation can be recognized in time, the abnormity early warning structure is dynamically adjusted, the early warning strategy can be flexibly optimized along with the change of the working condition, and therefore the detection precision and the response speed are improved; the state can be mastered in real time in a complex pipe network environment, missing detection and false alarm phenomena caused by insufficient data interpretation or early warning strategy solidification are effectively reduced, the adaptability of the system to emergency situations is enhanced, and the problems of response lag and insufficient sensitivity caused by single data source under variable working conditions are avoided.

In embodiments, an apparatus includes a user data interpretation circuit structured to interpret user data corresponding to a first user; a bootstrap circuit structured to: match the first user to a second user via querying one or more databases based at least in part on the user data; retrieve historical time sequence data associated with the second user via querying the one or more databases; extract a time sequence trend from the historical time sequence data; identify a portion of the historical time sequence data corresponding to the extracted time sequence trend; and generate, based at least in part on the identified portion, time sequence data corresponding to the first user; and a time sequence data provisioning circuit structured to transmit the time sequence data.

The invention provides an information personalized interpretation method and a related device, and relates to the field of data interpretation. Responding to the information recommendation instruction, obtaining target information to be recommended to a target user, determining an initial user portrait of the target user, adjusting the weight of a user tag in the initial user portrait according to a content portrait of the target information to obtain a target user portrait, constructing a prompt word based on the target user portrait, and recommending the prompt word to the target user. And performing personalized interpretation on the target information by using the cue word to obtain a personalized interpretation result of the target information, the personalized interpretation result comprising influence information of the target information on the target user, and outputting the personalized interpretation result of the target information. According to the method, after the target information which the user is interested in is screened out, the target information is interpreted based on the target user portrait to obtain the influence of the target information on the user, namely, the value of the content of the target information on the user is obtained, the user does not need to perform information extraction by himself, the reading efficiency of the user is improved, and the user experience is improved.

The invention discloses a seismic fault identification method based on a Dual-Attention mechanism and a multi-scale fusion network, and belongs to the technical field of seismic data interpretation, and the method comprises the following steps: S1, obtaining three-dimensional post-stack seismic data, and carrying out the slicing of a seismic data body, and obtaining multi-channel seismic data; s2, a DAMFault Net fault recognition model is constructed; s3, completing fault feature extraction in a coding stage; s4, obtaining an intermediate aggregation feature and an original same-scale feature from an encoder in a decoding stage; s5, adding a depth supervision mechanism to a tail end decoder; and S6, splicing and recovering prediction results to the size of the original seismic section. According to the seismic fault identification method based on the Dual-Attention mechanism and the multi-scale fusion network, excellent accuracy and fault continuity identification capability are shown in a fault identification task, and automatic, efficient and accurate identification of the fault in the seismic image is realized; and powerful technical support is provided for seismic analysis and research.

The invention discloses an intelligent report generation method based on a big language model, which comprises the following steps of: obtaining report data interpretation by utilizing the big language model and combining industry knowledge according to original data for generating a report; according to report data interpretation, a report is intelligently generated in combination with mode requirements; and adjusting the content and / or mode of the report according to the user input. According to the method, highly automatic and intelligent data processing is realized by utilizing the large language model, manual intervention is not needed in the whole process from data collection to report generation, time and cost are remarkably reduced, and data analysis depth and accuracy are improved. And performing context analysis in combination with industry knowledge, identifying key business driving factors and potential risk points, and generating a high-quality report. Through a user input function, report content and format can be adjusted in real time, and user experience and decision effectiveness are greatly enhanced.

The invention discloses a BiLSTM-based while-drilling electromagnetic wave logging data rapid inversion method and system, and the method achieves the efficient processing of logging data through constructing a deep network structure composed of four BiLSTM layers and a full-connection layer. According to the method, ideal magnetic dipole response is adopted as training data, and the problem that local minimum is likely to occur in traditional data interpretation is solved. And the recurrent dropout technology is utilized to reduce overfitting, so that the generalization ability of the model is improved. The technology not only can accurately classify the stratum model, but also can predict various stratum parameters, so that the accuracy and processing speed of data interpretation are remarkably improved, and powerful technical support is provided for geological exploration and stratum evaluation.

The invention provides an AI-based ChatBI platform design and implementation method, which comprises the following core steps of: constructing a first semantic layer database, receiving a natural language problem of a user, and generating an executable SQL (Structured Query Language) statement through an NL2DSL engine; extracting keywords and performing vector similarity calculation on the keywords and the first semantic layer database to generate a second semantic layer knowledge base; judging query complexity according to the quantity of the knowledge bases, and scheduling corresponding processing engines; checking the user access authority, and automatically generating a chart configuration template and recommending an adaptive chart type when the user access authority exists; based on user selection, data interpretation and a core conclusion are generated through a large model in combination with SQL statements and a knowledge base, and an output result is integrated. According to the invention, by optimizing the platform architecture, accurate data insight can be obtained by non-technical personnel in a dialogue manner, the use threshold is reduced, terms are unified, and the result accuracy is improved; meanwhile, operation efficiency is improved, and waiting time is shortened; and the data security is enhanced through permission setting.

The invention mainly relates to the technical field of spectral analysis, and provides a white spirit brewing spectral analysis method and system based on a multi-modal large language model in order to efficiently and accurately obtain white spirit brewing information according to multi-modal spectral data of all links of white spirit brewing. The method is characterized by comprising the following steps of: collecting multi-mode spectrum data including gas chromatography data, infrared spectrum data and Raman spectrum data in each link of white spirit brewing; converting the multi-modal spectral data and the natural language instruction into a feature embedding vector which can be recognized by a large language model to train the large language model which is finely adjusted based on professional knowledge in the field of white spirit, and receiving a question of a user in a natural language instruction form by the trained large language model; wine making analysis tasks such as flavor compound identification, key microorganism detection, fermentation state evaluation and base wine quality grading are carried out, and finally analysis results and wine making process optimization suggestions are output in a natural language form, so that the accuracy and efficiency of spectrum data interpretation in the white wine making process are improved.

The invention relates to the technical field of flexible riser motion analysis, in particular to a marine dynamic flexible riser motion response reconstruction method based on monitoring data, which comprises the following steps of: arranging sensors in a flexible riser system by adopting a structure embedded type arrangement method or an external attachment type arrangement method, and optimizing a sensor arrangement mode; a data acquisition and transmission system is arranged on an ocean platform to obtain flexible riser motion response data, the flexible riser motion response data is converted into flexible riser displacement data based on a Timoshenko beam model and Tikhonov regularization, the flexible riser displacement data is subjected to noise reduction processing based on a wavelet threshold noise reduction method to obtain flexible riser displacement noise reduction data, and the flexible riser displacement noise reduction data is subjected to flexible riser displacement noise reduction. And motion response reconstruction is performed on the flexible riser displacement noise reduction data based on variational mode decomposition (VMD). According to the method, the data interpretability, the data reconstruction precision and the real-time performance of motion reconstruction of the flexible riser can be effectively improved.

The invention provides a strike-slip fracture derived fracture parameter prediction method and system, and belongs to the field of oil and gas field exploration and development. The method comprises the following steps: based on three-dimensional seismic data interpretation data, establishing a three-dimensional geologic model; carrying out mechanical parameter assignment and gridding processing on the three-dimensional geologic model in sequence based on predetermined rock mechanical parameters to obtain a three-dimensional grid model; based on the three-dimensional grid model and predetermined geological model boundary conditions, solving stress data corresponding to each grid in the three-dimensional grid model to obtain stress distribution data corresponding to a strike-slip fracture formation period; and based on the exploration data and the stress distribution data corresponding to the strike-slip fracture formation period, predicting the occurrence and development degree of the strike-slip fracture derived tectonic fracture to obtain a strike-slip fracture derived fracture parameter prediction result. The purpose of quantitatively predicting the occurrence and development degree of the derived fracture in the strike-slip fracture forming process is achieved, and the problem of parameter prediction of the derived fracture in the strike-slip fracture forming process is solved.

The invention provides a report interpretation method and a related device, and relates to the field of data interpretation. In the application, a plurality of target reports with an association relationship are acquired, report types of the target reports are identified, key information is extracted from the target reports by using the report type of each target report, a key information set is obtained, and a target retrieval result of at least one piece of target key information in the key information set is retrieved in a knowledge graph. Determining professional interpretation results corresponding to the plurality of target reports by utilizing the key information set, the target reasoning path and node paraphrases of all nodes in the target reasoning path, and performing content adjustment operation on the professional interpretation results according to common paraphrases of all the nodes in the target reasoning path to obtain the target reports. And obtaining a common interpretation result corresponding to the professional interpretation result. In the application, the general interpretation result of the target report is obtained through the report interpretation operation, so that the user can understand the report content.

The invention discloses a land subsidence area permeable channel identification and cause analysis method based on a high-density electrical method, which overcomes the limitation of traditional single profile data interpretation by arranging a three-dimensional observation grid and fusing and collecting multi-source data. Through combination of finite element three-dimensional inversion and the improved convolutional neural network model, accurate description of the three-dimensional spatial morphology, the extension direction and the connectivity of the permeable channel is realized, and the accuracy and the spatial resolution of low-resistance abnormal region identification are improved. Compared with the prior art, the method has remarkable advantages in the aspects of permeable channel recognition accuracy, cause analysis comprehensiveness, result application practicability and the like, and effective support can be provided for long-acting prevention and control work of geological disasters in land subsidence areas.

Computing systems, computer-readable media, and methods for providing multiple computer-generated seismic data interpretation options, of which the method includes receiving a training input, sorting the training input into a first group and a second group, subgrouping the second group into a plurality of subgroups, generating a plurality of trained models based on the plurality of subgroups and the first group, receiving a prediction input having a set of data to be interpreted, generating a plurality of interpretation options for the prediction input by applying the plurality of training models to the prediction input, and outputting the plurality of interpretation options.

A method and system are disclosed for improving the accuracy, efficiency, and scalability of data interpretation and extraction of structured data from unstructured documents utilizing Large Language Models (LLMs). Applicable in finance, healthcare, legal, and government contexts, the disclosed invention addresses limitations of conventional Optical Character Recognition (OCR), machine learning, and LLM-based methods. In particular, the system and method incorporate feedback loops for continuous learning and leverage pre-processing, contextual tagging, customized prompt engineering, and post-processing to achieve robust data extraction. By integrating data enrichment techniques, the invention manages the inherent complexities of multilingual documents and evolving content standards.

The invention discloses an electrical source transient electromagnetic ground-air detection method and system, and relates to the technical field of geophysical exploration. The method comprises the following specific steps: arranging a transient electromagnetic transmitting device and a receiving device in a detection area; carrying out ground-air transient electromagnetic measurement at different flight height positions to obtain a transient electromagnetic data total set; preprocessing electromagnetic data in the transient electromagnetic data set to obtain preprocessed data; data interpretation is carried out on the preprocessed data, an underground electrical structure is reconstructed by using an inversion algorithm, and a resistivity distribution image of the underground geologic body is obtained to identify a low-resistance abnormal region; and based on an inversion result, expressing spatial distribution and physical property parameters of the deep geologic body by adopting a three-dimensional modeling technology. According to the invention, the deep geological target body can be accurately explored, so that the accurate and detailed geological information of the deep geological target body can be obtained.

The invention discloses a phased array, TOFD and magnetic powder integrated detection system and method for medium and large diameter pipeline welded joints, the detection system comprises a control system, a liquid storage and supply system and a scanning system, the control system is connected with the liquid storage and supply system, the control system is connected with the scanning system, and the scanning system is connected with the control system. The liquid storage and supply system is connected with the scanning system through a flexible water pipeline and a flexible magnetic suspension pipeline; the liquid storage and supply system comprises a magnetic suspension tank and a water tank which are respectively used for storing magnetic suspension and water; the scanning system is a data acquisition center, is provided with a phased array probe, a TOFD probe, an electromagnetic yoke and a video sensor in a centralized mode, operates in a sub-control mode, is driven by a magnetic attraction wheel driving mechanism to achieve automatic scanning of a welding joint, and transmits detection data information to the control system. The device is compact in structure, convenient for later maintenance and low in manufacturing cost; according to the invention, the parameter control is accurate, the detection data can be analyzed in real time, the data interpretation is convenient, the detection precision is high, the detection speed is fast, and safety and reliability are realized.

The invention discloses a method and a device for predicting an anode copper refining reaction endpoint, and relates to the technical field of anode copper refining process management. The prediction method comprises the following steps: S1, sensor deployment and data acquisition; s2, data preprocessing; s3, constructing a feature project; s4, model training and optimization strategy implementation; s5, carrying out online prediction and decision support; and S6, continuously improving closed-loop feedback. According to the method, the gradient boosting decision tree, the LSTM + Attention hybrid architecture and the Stacking integration are adopted, and the data interpretability and the nonlinear fitting capability are considered; bayesian hyper-parameter optimization and an early stop method are combined to prevent overfitting, and the generalization performance of the model is ensured.

The invention provides a wounded consciousness state evaluation system based on face recognition, and relates to the technical field of health evaluation. Comprising a facial information extraction module, a facial feature analysis module, a consciousness state calculation module, an anomaly detection module and a consciousness state evaluation module. According to the invention, the infrared camera carefully captures the fine movement of the muscles around the eyes, the mouth corner and the frontal part, the accuracy and comprehensiveness of data acquisition are improved, the accuracy and dimension of evaluation are improved by evaluating the blinking frequency, the mouth corner displacement and the frontal muscle stretching amplitude, and by utilizing the extraction of the deformation characteristics and the calculation of the movement amplitude gradient, the accuracy and the comprehensiveness of the evaluation are improved. The time sequence analysis is combined, the evaluation of the consciousness state becomes more sensitive and accurate, potential changes of consciousness can be found in time, and therefore, rich data interpretation is provided for diagnosis and monitoring through quick response, and the density and distribution characteristic analysis of sudden change points, so that the consciousness state can be quickly and accurately evaluated under the condition that a wounded person is not contacted.

The present invention relates to a well seismic calibration method during the drilling process of a horizontal well, and belongs to the technical field of seismic data interpretation. The specific steps are as follows: main data preparation work; performing time-depth conversion to clarify the structural absolute error value of each marker layer; obtaining the error grid of the layer-by-layer velocity field of each marker layer segment; correcting the layer-by-layer velocity field of each marker layer, and then performing three-dimensional spatial interpolation to obtain a new velocity field as the stacking velocity, performing projection comparative analysis, and clarifying the structural absolute error value of each upper stable marker layer; continuously correcting the interlayer velocity by comparing and obtaining the velocity error of each marker layer, and using the corrected velocity field to extract the velocity curve for well seismic calibration, so that the correlation coefficient after well seismic calibration gradually increases and reaches the target value and meets the structural relative error standard value, and the spatial position in the target layer can be finally obtained. This well seismic calibration method significantly improves the prediction accuracy and work efficiency of target entry.

The application discloses a well logging data interpretation method and device based on large model fine tuning, equipment and a storage medium in the field of computer technology. The method comprises the following steps: connecting a gating selection unit of a fine tuning module to a geophysical logging large model to obtain a scene large model; obtaining a label data set for well logging interpretation in a target environment; dynamically determining a subnetwork matched with the label data set from a classification subnetwork and a regression subnetwork of the fine tuning module by using the gating selection unit, and fine tuning the scene large model to adapt to various well logging interpretation tasks; obtaining well logging data to be interpreted corresponding to the target environment, and interpreting and processing the well logging data to be interpreted by using the fine tuned scene large model to obtain at least one well logging interpretation content corresponding to various well logging interpretation tasks. The application can efficiently process various well logging interpretation tasks, does not need to construct independent models for different well logging interpretation tasks, has a high data feature reuse rate, and has a higher complex scene generalization capability.

A simulation system for hands-on training for medical diagnostic and treatment techniques is provided. The simulation system is provided with a manikin of a human body having a first side and a second side. The second side has a transparent simulated skin, an internal organ simulated model, and a sensor module configured to collect and transmit data based on an input by a user. In addition, the system has a processor with an implemented computer program configured to receive and interpret the data from the sensor module and provide a feedback to the user based on the interpretation of the data.

The application discloses a data intelligent service method and device under a mixed model, equipment and a storage medium, relates to the technical field of artificial intelligence technology, and comprises the following steps: acquiring user question and answer information and user search information; identifying at least one of a corresponding query intention category, an inquiry intention category, an exploration behavior category and a search behavior category based on the user question and answer information or the user search information, and determining at least one of query intention category information, inquiry intention category information, exploration behavior category information and search behavior category information; predicting a corresponding service demand based on at least one of the query intention category information, the inquiry intention category information, the exploration behavior category information and the search behavior category information, and determining service demand prediction information; and analyzing a corresponding data resource based on the service demand prediction information, and determining a data resource analysis result. The application identifies query, inquiry, exploration and search intentions, performs data interpretation, and adapts intelligent service.

The application discloses a two-dimensional distributed optical fiber sensing full waveform simulation method based on a discrete elastic lattice, and belongs to the technical field of seismic wave field simulation and distributed optical fiber sensing. The application comprises the following steps: receiving seismic wave data of a target geological medium layer; setting a two-dimensional calculation region according to the spatial distribution of the longitudinal wave velocity, the transverse wave velocity and the density parameters of the seismic wave, and taking the two-dimensional calculation region as a numerical simulation carrier of seismic wave propagation; discretizing the two-dimensional calculation region into a plurality of particle nodes, and connecting adjacent particle nodes through elasticity to form a discrete elastic lattice, so as to represent the mechanical properties of the stratum medium; and according to the density parameters, the longitudinal wave velocity, the transverse wave velocity or the equivalent elastic parameters of the stratum medium, the elastic connection between the particle nodes is endowed with corresponding elastic coefficients. The application provides a reliable numerical tool for DAS deployment design, data interpretation and seismological inversion, and can be widely applied to the fields of earthquake monitoring, oil and gas exploration, geological disaster warning and the like.