5093 results about "Information system" patented technology

The invention provides a procurement supply chain collaborative intelligent management method and a procurement supply chain collaborative intelligent management system. Belongs to the technical field of supply chain management. Constructing a purchase demand prediction model; dynamically adjusting the purchasing strategy according to the prediction result; the record and the evaluation result are stored on the block chain; the system automatically sends order information to a supplier; the supplier confirms the order through the block chain platform and updates the production progress and the logistics information; the system adjusts an inventory strategy in real time; the logistics state is monitored in real time; the system analyzes data of each link of the supply chain in real time and identifies potential risks. Through dynamic path planning and real-time transportation optimization, the logistics path can be adjusted in real time according to traffic conditions, environmental factors and emergencies, the transportation time is shortened, the transportation cost is reduced, and therefore the overall efficiency of a supply chain is remarkably improved.

In an intelligent pollution and carbon reduction method based on combustion control and load distribution, a data processing layer, a multi-unit load distribution and operation optimization layer and a single-unit boiler multi-objective combustion optimization layer are used. The data processing layer, the multi-unit load distribution and operation optimization layer and the single-unit boiler multi-objective combustion optimization layer are embedded in a power plant information system in the form of modules. A load distribution and operation optimization method for a multi-source fuel blending combustion unit with economy as an objective is provided to overcome the operation optimization difficulty of the key production process of a multi-source fuel blending combustion cogeneration unit, such as sludge drying-steam distribution.

The invention discloses a data analysis platform management method and system, and belongs to the technical field of computer data processing, and the method comprises the steps: obtaining multi-source heterogeneous data from a medical information system; establishing a cross-system data association model, performing dynamic feature extraction and weight distribution on multi-source heterogeneous data, and outputting a resource supply-demand relationship graph; analyzing the resource supply-demand relation graph, and identifying business conflicts in medical resource scheduling; generating a conflict solution of the business conflict based on a multi-objective optimization algorithm, and generating an execution instruction; and issuing an execution instruction to the target medical system, verifying an execution result of the execution instruction, and updating system parameters. According to the method, a cross-system dynamic modeling and multi-objective optimization strategy is adopted, and a closed-loop verification mechanism and a multi-source heterogeneous data fusion technology are combined, so that intelligent prediction, accurate scheduling and self-learning optimization of medical resource conflicts can be realized, full-process traceable execution of high-value consumables is ensured, and the resource utilization efficiency and the emergency response capability are comprehensively improved.

Automatically investigating security incidents and generating security incident reports using a Large Language Model (LLM). A computerized system receives an incoming Security Alert Message pertaining to a possible security-related incident. The system automatically feeds into the LLM at least: the content of the Security Alert Message; the metadata of the Security Alert Message; context information describing a security domain; and organization context information pertaining to users and machines of that organization. The system automatically prompts the LLM to automatically investigate the Security Alert Message and to automatically generate a detailed Incident Report pertaining to the Security Alert Message.

A database system generates a prompt for an LLM or other machine learning (ML) model to narrow the search space to highly relevant information about a database. A distinct instance of a classifier, a clustering algorithm, or a topic modeling model can be trained based on information from ML automation within the database system, respectively for each column or table in the database. Model instances can then be used during generative LLM inferencing to identify relevant sources of data to answer the user's question. Thus, the prompt generation combines ML automation and other ML models or an LLM for topic modeling and schema description.

The invention provides a security management and retrieval method based on Internet of Vehicles data, and the method comprises the steps: carrying out the cooperative training of a global key management model through a federated learning technology on the premise of not leaking the original data of all parties, and achieving a security key management scheme under the participation of multiple parties through a model parameter aggregation and updating mechanism; when data retrieval is needed, a user submits a retrieval request and identity authentication information, and after a system verifies the identity of the user, a ciphertext data identifier meeting conditions is matched in an attribute index according to a keyword and an authorization attribute of the request; the system acquires corresponding ciphertext data from a distributed database according to the ciphertext data identifier, and directly performs keyword matching calculation on the ciphertext data through a secure multi-party computing protocol under the condition of not decrypting the data; and according to the mined security threats and abnormal modes, a data encryption strategy and an access control strategy are dynamically adjusted, authority limitation or access blocking is performed on suspicious users, and the security protection capability of the system is improved.

The invention relates to the technical field of computers, and discloses a distributed task scheduling method and system for heterogeneous tasks based on cloud native, and a medium, and the method comprises the steps: a user submits a task through a task management module, and the task carries description information; the system obtains hardware states and task load information of all nodes in a cluster in real time through a resource monitoring module, a scheduling optimization module analyzes task characteristics according to task types and selects an optimal scheduling strategy in combination with a current resource state, and a task distribution module distributes tasks to optimal computing nodes and starts task execution. In the task execution process, the system continuously monitors the task state, and dynamically adjusts resource allocation or executes preemptive scheduling when necessary. According to the method, efficient management and scheduling of heterogeneous computing resources are realized by optimizing a scheduling strategy and a resource allocation mechanism, and the overall performance and the resource utilization rate of the system are improved.

Systems, devices, and methods are provided for determining contextually relevant user-based product recommendations based on scene information. In at least one embodiment, techniques described herein may be used to determine, using a first machine-learning model, first information associated with a first object within a first image of digital content, determine, using a second machine-learning model, similarity scores between the first object and a first plurality of products of an online purchasing system, detect, in association with the first image of the digital content, performance of a first computer-based action by a user, determine, using a third machine-learning model and based on contextual data of the user, one or more affinity scores for the user, select a first product based on the one or more affinity scores, and present a recommendation to the user to perform a second computer-based action in association with the first product.

The invention relates to a sponge city design optimization method and system based on rainfall calculation, and the method comprises the following steps: predicting the occurrence probability of a rainfall event in a target sponge city based on rainfall analysis data and climate data, and obtaining the probability distribution of future rainfall and the future calculated rainfall; performing spatial analysis on the target sponge city through a preset geographic information system to obtain an easy water accumulation point distribution map; adopting a Bayesian network algorithm to evaluate the waterlogging risk level of each region in the target sponge city based on the distribution map of the points prone to water accumulation, the future measured rainfall and the probability distribution of the future rainfall, and obtaining a waterlogging risk map; and performing layout optimization design on the target sponge city based on the waterlogging risk map by using a preset multi-target optimization algorithm to obtain an optimal configuration scheme, thereby solving the problem of how to scientifically and reasonably predict a rainfall mode and influence, and effectively relieving the urban waterlogging problem.

The invention relates to the technical field of marine biological diversity assessment, and particularly discloses a marine biological diversity geographic information system and an ecological diversity risk assessment method.The marine biological diversity geographic information system comprises a water quality diversity risk assessment module, a diversity and water quality assessment comprehensive model module and an RDA analysis method screening module; according to the system and the method, marine organism data and water quality data of a sea area for many years are integrated, an interactive visual system is developed, data interconnection and intercommunication are realized, and the sea area can be evaluated through diversity investigation of multiple organisms in the sea area, water environment physical and chemical factor analysis, correlation mining and evaluation model construction. The model can assess the sea water environment condition, the water body environment quality and the biodiversity risk, provides basic data and methods for related research, powerfully promotes ocean monitoring to be converted from manual work to intelligence, promotes biodiversity data integration and ecological environment monitoring in a bay area, and tracks the biological activity and survival state.

The invention provides a micro-grid cooperative scheduling method and device, and relates to the technical field of smart grids, and the method comprises the steps: obtaining historical operation data and real-time operation data of a micro-grid system, and data of an external information system; generating load demand and energy equipment output prediction information based on the historical operation data and the data of the external information system; constructing a layered multi-time-scale decision architecture, and performing decision optimization on each layer of agents by adopting a reinforcement learning algorithm; constructing a plurality of heterogeneous agents, and carrying out cooperative scheduling on the plurality of heterogeneous agents by adopting a centralized training and distributed execution multi-agent reinforcement learning algorithm; inputting the prediction information and the real-time operation data into a decision framework, and outputting a real-time control instruction; and setting a security constraint condition, and realizing optimization of the security constraint in combination with a Lyapunov function, a Lagrange multiplier method, a security layer mechanism and a reinforcement learning algorithm. According to the method provided by the invention, the safe, efficient and reliable operation of the micro-grid in the grid-connected / off-grid mode can be realized.

The invention discloses an electronic medical record automatic quality control system and method based on a large language model, and the method comprises the steps: extracting medical record data from a medical information system, and carrying out the data preprocessing; and performing deep semantic analysis on the medical text by utilizing a large language model, and extracting key diagnosis and operation information. And performing semantic representation on the medical terms by fine tuning the pre-training language model and combining with a multi-layer attention mechanism. And constructing an ICD coding knowledge graph, and calculating the semantic similarity between the diagnosis terms and the ICD coding terms in the electronic medical record by using an embedded vector technology to realize automatic matching. And according to a predefined quality control rule, automatically checking the electronic medical record through the logic expression, and generating a quality control report and an improvement suggestion. And finally, visually displaying quality control and coding results, and outputting a quality control report. The electronic medical record quality control efficiency and accuracy are improved, and standardization and automation of quality control work are achieved.

The present disclosure, among other benefits, provide a technological solution which leverages electronic templates, information systems, and / or machine learning to generate gaming tickets which automatically generate and provide natural language descriptions of gaming opportunities. Aspects disclosed herein provide a wagering ticket win curation system, integrated with an online and / or retail sportsbook platform, to assist players during bet selection and placement, additionally documenting the winning outcomes of a placed wager in a plain language, in a manner that is easy to comprehend.

The invention relates to the technical field of Otwei interactive maps, and discloses a geological data interaction method and system based on an Otwei interactive map. The method comprises the following steps: carrying out feature recognition and structural analysis on original geological data to obtain a standardized data packet, and establishing a geographic space reference conversion index table; performing feature extraction and classification on geological elements in the standardized data packet to obtain structured geological data; importing the structured geological data into an Ovoucher interactive map, and carrying out local registration through a mesh generation technology to obtain a visual geological element map layer; geological element drawing and attribute input are carried out, and an edited geological data set is obtained; and carrying out structure recombination and reverse coordinate conversion to obtain a standard format data file adaptive to the target geological information system. According to the method, accurate conversion of multi-source geological data between different coordinate systems and measuring scales is realized, and the problem of spatial dislocation during integration of different-source geological data in a traditional method is effectively solved.

The invention relates to the field of intelligent inspection and resource allocation, in particular to an electric power information system inspection and resource allocation method based on a knowledge base and an intelligent agent, and the method comprises the steps: collecting the data of an electric power information system, carrying out the heterogeneous data integration, and constructing the knowledge base of the electric power information system; constructing an intelligent agent oriented to the electric power information system based on a large language model, and performing RAG on the intelligent agent based on a knowledge base and open source knowledge to enhance the performance of the intelligent agent; acquiring a routing inspection demand in a natural language form, automatically generating a routing inspection script by the intelligent agent based on the routing inspection demand, and compiling the routing inspection script to generate a routing inspection task; the intelligent agent automatically executes the inspection task and compares the inspection result with the knowledge base to generate an inspection report; and the intelligent agent performs intelligent analysis on the inspection report, and performs resource allocation on abnormal items in the inspection report in combination with the knowledge base. According to the method, the operation and maintenance efficiency of the electric power information system is effectively improved, and the operation and maintenance cost is reduced.

The invention provides a large language model intelligent interaction method and system with memory management capability in the technical field of artificial intelligence. The method comprises the following steps: S1, creating a work memory module, a long-term memory module, a memory fusion module and an intelligent interaction module; s2, acquiring external knowledge and integrating the external knowledge into a long-term memory module; s3, the intelligent interaction module obtains an intention sequence based on a user query statement and sends the intention sequence to a work memory module; s4, the memory fusion module retrieves context information from the long-term memory module based on the user query statement and sends the context information to the working memory module; s5, the work memory module constructs a work memory sending intelligent interaction module based on the intention sequence, the context information and the system instruction; s6, the intelligent interaction module outputs a query result based on the working memory; s7, a memory fusion module extracts semantic memory and plot memory from user query statements and query results and stores the semantic memory and plot memory in a long-term memory module. The method has the advantage that the man-machine interaction performance is greatly improved.

A web-based interface enables medical personnel to remotely monitor medical devices. A monitoring system records operational data and alarms from the medical devices in a file. However, since network connections between the medical devices and the monitoring system are intermittent, the file does not contain a contiguous stream of data for each medical device. The file pauses recording during gaps in network connectivity. The system displays current data, as well as a list of alarms. If medical personnel wish to view more detail about an earlier time or one of the alarms, the system calculates where in the file the medical device data was recorded. This calculation accounts for the discontiguous nature of the data. The system uses times the network connection is made and broken to calculate an index into the file that corresponds to the time of the user-selected alarm.

The invention discloses a cloud information system index collection method, system and device and a medium, and relates to the technical field of cloud information system operation and maintaining.The method comprises the steps that information collection interfaces of a cloud system are integrated, data flow information entropy is quantized, and an entropy value sequence is constructed; an interface calling serial number is traced based on a historical log, a calling chain is formed, a directed graph topological structure is established, an influence propagation path of an entropy mutation node is identified, and a collection regulation priority of an interface cluster is determined; an acquisition strategy is formulated in combination with entropy time sequence data and a load level, a state-strategy mapping relation matrix is optimized, and a time period driving type strategy adjustment parameter set is generated; and issuing the strategies in sequence, dynamically regulating and controlling the acquisition frequency, and if state transition or fitting degree abnormity occurs, triggering strategy rollback and optimizing the learning weight. According to the method, on the premise of guaranteeing the integrity of the monitoring data of the power equipment, the utilization rate of edge computing resources is remarkably optimized, and high-timeliness and high-fidelity data support is provided for safe and stable operation of a power grid.

The invention discloses a road intelligent induction and dynamic early warning method and system integrated with meteorological perception, and relates to the technical field of intelligent traffic and road safety. The method comprises the following steps: acquiring real-time weather, traffic and road data, performing multi-source data fusion by adopting an improved Kalman filtering and attention mechanism, and generating unified state estimation; dynamic risk assessment is carried out in combination with Bayesian reasoning and a Markov model, and speed-limiting adaptive adjustment is realized based on safety, traffic efficiency and energy consumption multi-objective optimization; and further calculating the length and position of the dynamic early warning area, and controlling devices such as intelligent spikes to issue induction information. The system comprises a data acquisition unit, a fusion estimation unit, a risk prediction unit, a speed adjustment unit, an early warning calculation unit and an induction unit. According to the invention, real-time monitoring, risk prediction and intelligent regulation and control of the road traffic environment in complex weather are realized, and the driving safety and the traffic efficiency are improved.

The invention discloses a medical and educational informatization comprehensive supervision and diagnosis platform system based on multi-modal data fusion. A data acquisition module acquires multi-modal data from a medical and educational information system and preprocesses the multi-modal data; the data storage module constructs a hybrid architecture to classify and store data and establishes an index. The multi-modal data fusion module deeply fuses medical records, images and physiological monitoring data of medical treatment and teaching resources, learning behaviors and teaching evaluation data features of education by means of a feature extraction technology and a fusion algorithm. The supervision and diagnosis module constructs models of medical service quality evaluation, disease diagnosis assistance, teaching quality monitoring and the like based on fusion features to realize accurate analysis. The user interaction module provides interaction interfaces for different roles and supports operations such as data query and uploading. The platform system breaks the data barrier, fully mines the data value, provides powerful support for informatization management, decision making and service optimization in the medical and education fields, and promotes the innovative development of the two fields.

The invention discloses a cargo transportation real-time path planning method based on artificial intelligence, and relates to the technical field of artificial intelligence and intelligent traffic, and the method comprises the following steps: collecting real-time data from a traffic monitoring system, a vehicle-mounted sensor, a road event platform and a weather information system in a transportation process, forming an original data set containing multi-source information; time synchronization and space alignment are carried out on source data in an original data set, and a standardized data frame is constructed to ensure the consistency of different source information in a space-time dimension. According to the method, the accuracy, the real-time performance and the intelligence of path planning are effectively improved through multi-source data consistency identification, weighted fusion and a dynamic re-planning mechanism. The system can timely identify data conflicts, dynamically adjust paths and enhance transportation safety and efficiency, has a self-learning capability, continuously optimizes path strategies and adapts to complex traffic environments.

The invention provides a photovoltaic power station operation state monitoring method based on unmanned aerial vehicle inspection, and the method comprises the steps: carrying out the surveying and mapping of the geographic position, landform and photovoltaic array layout of a photovoltaic power station through employing a surveying and mapping technology and a geographic information system, so as to build a digital photovoltaic power station model; acquiring technical parameters of each component of the photovoltaic power station, and mapping the technical parameters to the digital photovoltaic power station model; based on a preset inspection plan and the digital photovoltaic power station model, automatically generating an unmanned aerial vehicle inspection path; obtaining monitoring data obtained by the unmanned aerial vehicle according to the unmanned aerial vehicle inspection path, wherein the monitoring data comprises an appearance image of a photovoltaic array, temperature distribution of a photovoltaic module and illumination intensity data of different areas of a photovoltaic power station; vectorizing the monitoring data to obtain an input vector; and the operation state monitoring model performs feature extraction on the input vector so as to analyze the operation state of the photovoltaic power station.

A third-party authentication and encryption method, known as spatio-temporal encryption, is used to protect sensitive information by guaranteeing the origin and integrity of its content for recording or transmission purposes. This method is based on hidden characteristics associated with the message's location and creation date, derived from GNSS signal processing. Without requiring additional dedicated security infrastructure, the method allows for the protection and authentication of any data entered into the information system, anytime and anywhere, and enables the assessment of associated security risks at any system level. Leveraging the various levels of access protection for GNSS signal services, the solution offers different levels of robustness, with complexity and security that can be tailored to the threat level, while minimizing the impact on communication network performance.

The invention discloses a battlefield target behavior prediction method capable of being guided by micro-physical representation and a thinking chain, and the method comprises the steps: obtaining satellite images, radar / communication detection and open source text multi-source time sequence data, completing the entity recognition, relation extraction and event detection, and constructing a dynamic space-time knowledge graph; the maneuverability, sensor detection, weapon range and terrain accessibility mechanism are micronized to serve as a physical consistency constraint embedded prediction model; generating an intention-action-result causal priori chain and parameterizing the causal priori chain into a computable structure; performing multi-branch long-time-sequence situation deduction, and outputting a future target behavior track and a scene probability; and evaluating and explaining by integrating the causal confidence coefficient, the physical consistency and the data goodness of fit, and giving a key event probability and situation evolution report. According to the method, unified modeling of semantic causal and physical constraints is realized, and the method has explainable, verifiable and robust prediction capabilities, and is suitable for target behavior prediction and command information system decision support in a complex environment.

Systems and methods for the protection of information systems utilize business impact analysis (BIA) data to assess the risk of security mitigation operations. A detected security incident is enriched using BIA data. A proposed mitigation action and a risk of implementing the proposed mitigation action are determined using the enriched data so that an administrator user can understand the impact or risk to the business for the proposed mitigation action.

The invention belongs to the field of disaster early warning, and provides a disaster early warning method and system based on key target detection and image segmentation, and the method comprises the steps: obtaining the real-time image data of a site, and carrying out the preprocessing of an image; processing the preprocessed image through a YOLOv5 target detection algorithm, detecting a key target in a disaster site, and outputting a category label and a bounding box of the target; performing pixel-by-pixel segmentation processing on a bounding box region output by target detection by using a U-Net image segmentation algorithm to generate an accurate segmentation mask of the target; and inputting the image segmentation mask, historical disaster data, meteorological data and geographic information system data into an LSTM prediction model, carrying out multi-source data fusion and time sequence analysis, and outputting dynamic prediction information and early warning levels of disasters. According to the invention, real-time monitoring and early warning of disasters are realized, the response speed of the early warning system is obviously improved, more comprehensive disaster early warning information is provided, high precision of disaster prediction is ensured, and the phenomena of false alarm and missing alarm are reduced.

The invention provides an automatic pavement settlement monitoring method and system based on a shield undercrossing airport runway. The dynamic database is constructed by collecting operation parameters such as shield tunneling machine propelling pressure, cutterhead torque and synchronous grouting pressure in real time and combining three-dimensional deformation data obtained through laser scanning. Strain sensing units are arranged in the soil layers to form a layered monitoring network, strain changes of the soil layers of different depths are collected, and spatial correlation is established between the strain changes and the tunneling position. And analyzing a spatial attenuation rule through a dynamic association processing unit, and generating a multi-dimensional feature data set. And establishing a settlement prediction model, fusing the shield dynamic load sequence and the layered strain conduction characteristics, and outputting settlement distribution information. And the system automatically compares the settlement difference value of the adjacent areas with a preset safety threshold value, and generates a graded early warning signal after verification of the three-dimensional deformation data space. According to the technical scheme provided by the invention, real-time three-dimensional prediction and spatial verification type graded early warning of settlement of the airport runway are realized.

The invention provides a transfer learning-based power transmission line fault positioning method and system. Real-time monitoring data of a target power transmission line are collected, meteorological information and satellite remote sensing images are combined, ambient environment changes are analyzed, anomaly detection is performed, an abnormal data set is obtained, and a comprehensive fault feature space is constructed; an adversarial domain adaptation algorithm is adopted to optimize a comprehensive fault feature space, and a long-short-term memory network, an attention mechanism and a graph convolutional network are used for data processing to generate an enhanced fault feature representation; constructing an integrated learning framework based on Bayesian optimization, predicting the target power transmission line by using the plurality of preliminary basic models, integrating all prediction results through an adaptive weighting strategy, and generating initial fault probability distribution; determining fault positioning information by using a geographic information system technology and a topological sorting algorithm; the invention provides an efficient and accurate power transmission line fault positioning method, and provides powerful support for safe operation of a power system.

The invention relates to the technical field of agricultural management, in particular to a corn cultivation environment monitoring system based on a sensor, which comprises a data acquisition module, a data processing module, a corn growth model module, an environment dynamic monitoring and early warning module, a decision support module and a visualization module, and a geographic information system and a dynamic monitoring model are combined to capture the dynamic change trend of the cultivation area environment factors. A corn growth model of a deep neural network and a long-short-term memory network is adopted to predict the growth state and resource requirements of corn, a decision support module intelligently generates cultivation management suggestions based on a model prediction result, and a visualization module displays environment data, prediction results and management suggestions through a multi-dimensional graph and an interactive interface. According to the method, the accuracy of corn cultivation management and the resource utilization efficiency are improved, and technical support is provided for intelligent agricultural development.

The present invention provides an unmanned aerial vehicle-based electric power patrol inspection control method and system. The method comprises: creating a flight path on the basis of an electric power patrol inspection area, and collecting images and position information of electric power devices by means of various types of devices carried by an unmanned aerial vehicle, the images and the position information being transmitted to a receiving terminal at a ground station in a wireless transmission mode; the ground station receiving the images and the position information that are collected in real time, processing and analyzing the images to obtain analytic status, such as defects, damage and corrosion, of the electric power devices; and, on the basis of the analytic status from the ground station, using the position information as distinguishing features to generate an electronic patrol inspection report, providing service lives, maintenance costs and maintenance measures of the electric power devices on the basis of the electronic patrol inspection report, and notifying maintenance staff of the position information of the electric power devices. The system comprises an unmanned aerial vehicle control module, an image processing and analysis module and an electronic patrol inspection report generation module. The present invention is of great significance to maintenance and management of electric power devices.