346results about How to "Reduce management costs" patented technology

The invention belongs to the technical field of electric power data security management and intelligent question answering, and particularly relates to an electric power data security policy large model question answering system and method based on relation pooling. The system comprises a power data security policy knowledge base, a language model, a question processing module, an answer generation module and a user output module. Data of the electric power data security policy knowledge base comes from an electric power data security policy file; the language model converts a natural language problem into a structured query for knowledge base retrieval; the question processing module retrieves policy terms related to the natural language question to serve as retrieval results; the answer generation module generates a final answer according to the natural language question and a retrieval result of the knowledge base; by introducing the intelligent question-answering system combining the large language model and the knowledge base, the problems of low efficiency, inaccurate interpretation, incapability of dynamically updating and the like in the existing power data security policy query and management are solved.

The invention relates to the field of data asset management, and discloses a DCMM-based data asset active management method and system, and the method comprises the following steps: collecting data assets from all business systems, extracting multi-dimensional features, and generating a data attribute matrix; constructing a data value quantification model, and calculating the value of each data asset; based on a multi-objective optimization model, data assets are subjected to classification management, and optimization balance of data value, security, access efficiency and storage cost is realized; dynamically adjusting the weight of an optimization target according to different levels of the DCMM to enable a data management strategy to adapt to the data management maturity requirement of an enterprise; and performing resource allocation and priority control on the data assets according to an optimization result to realize active management. According to the method and the system, the accuracy, the flexibility and the resource utilization rate of data asset management are improved, and optimal configuration and efficient management of data assets in different development stages of enterprises are facilitated.

The invention discloses an edge-end-side heterogeneous computing power resource scheduling system and method.The system comprises a computing power virtualization resource pool module, a cross-domain distributed computing power soft bus and a computing power resource scheduling management module, the computing power virtualization resource pool module is based on the heterogeneous computing power virtual computing resource pool technology, and the cross-domain distributed computing power soft bus is used for scheduling the computing power resource scheduling management module; performing unified management and virtualized mapping on various equipment systems on the edge side and the end side according to computing power resources, network resources and storage resources to form a unified virtual computing resource pool; according to the cross-domain distributed computing power soft bus, intermediate routing forwarding nodes of computing power resources are established among different communication domains, the routing forwarding nodes support a power system physical layer protocol, and computing power resource lists among different communication protocol networks are synchronously updated in real time; and the computing power resource scheduling management module is used for realizing dynamic allocation management of computing power resources based on a dynamic computing power scheduling system established by the computing power resource pool, evaluating the computing power demand required by each computing task in real time, and requesting the virtual computing resource pool to allocate an optimal computing power resource combination for algorithm application.

The invention discloses a BIM-based whole house intelligent control system. The system is mainly formed by mutual cooperation of a BIM model data integration unit, an Internet of Things access unit, a control and management unit, an energy consumption analysis and optimization unit and a user interaction and platform integration unit. The invention provides a BIM-based whole house intelligent control system, and the system achieves the deep fusion of a BIM model (a building information model) and intelligent household equipment (i.e., Internet of Things equipment), thereby achieving the bidirectional data interaction between the BIM model and the household Internet of Things equipment, achieving the equipment management, energy consumption optimization, automatic control and remote operation and maintenance, and achieving the intelligent control of the whole house. And the living experience of the user and the equipment management efficiency are improved.

The invention discloses an automatic DCMM evaluation system based on a multi-source heterogeneous data integration mechanism, and relates to the technical field of data quality management.The automatic DCMM evaluation system comprises a data source management module, a data integration module, a data quality evaluation module, a data quality diagnosis module and a data quality monitoring module which are connected through electric signals; and the data source management module is used for accessing various types of data sources and collecting original multi-source heterogeneous data from a plurality of data sources. By comprehensively monitoring and evaluating the data quality, the accuracy and integrity of the data are improved, the abnormal early warning coefficient is calculated, the potential data quality risk is recognized in time, and when it is detected that the data quality is abnormal, an early warning mechanism is automatically triggered, and an alarm is sent to inform related personnel, so that the data quality is ensured to be abnormal. Therefore, the data quality problem can be found and solved at the first time, so that the reliability and credibility of the data are improved.

The invention discloses a city appearance environment early warning method and system based on AI intelligent garbage identification, and relates to the technical field of artificial intelligence and garbage classification technologies. The method comprises the steps that firstly, garbage classification throwing stations are set; step 2, acquiring and processing image data; step 3, carrying out image frame selection and tracking; 4, setting a threshold value and generating prompt information; 5, scheduling the garbage trucks, connecting the garbage trucks in series according to the uploaded alarm stations, and designing a route; by monitoring the state of the garbage throwing station in real time, the system can timely find the situation that the number of the garbage cans reaches the standard, and automatically generate early warning information, so that an environmental sanitation management department can timely dispatch garbage trucks to carry out clearing and transportation, and environmental pollution and resource waste caused by long-time garbage accumulation are avoided; the dynamic adjustment function of the system ensures that the driving route of the garbage truck can be rapidly updated when the actual situation changes, for example, early warning is newly added, and the garbage treatment efficiency and the response speed are further improved.

The invention relates to the technical field of material storage management, in particular to a BIM-based construction site material monitoring management method and system. The method comprises the following steps: obtaining a construction project drawing; performing drawing information extraction on the construction project drawing to obtain construction project material information data and construction project structure data; performing construction project three-dimensional modeling on the construction project material information data and the construction project structure data to generate construction project three-dimensional modeling data; obtaining total construction material data; and carrying out material information modeling on the total construction material data by using a BIM technology to generate total construction material modeling data. According to the invention, accurate three-dimensional modeling, intelligent marking, regionalized storage and real-time allocation of the construction site materials are realized through the BIM technology, and the accuracy of construction site material monitoring management and the emergency response real-time performance are improved.

The invention provides an intelligent guard system for large-scale micro-nano processing laboratory equipment, and the system comprises a data collection module, a risk early warning module, a fault positioning module and an operation and maintenance management module, the fault is traced by using the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the details of the fault can be known in time, and fault maintenance, responsibility investigation and the like can be carried out; the operation and maintenance management module can carry out multi-dimensional operation and maintenance management on the laboratory according to the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the efficiency, the performance and the service life of equipment are improved, the maintenance cost of the equipment is reduced, and effective utilization of social resources is facilitated.

The invention provides a staple food grain crop disease grading method and system based on a prompt-driven large model, and the method comprises the following steps: collecting and preprocessing a main food crop image, and obtaining a main food crop data set; training a ResNet-18 network based on the main grain crop data set to perform initial disease grading, and obtaining disease characterization prompt information; utilizing disease characterization prompt information to drive a prompt drive large model, and segmenting a focus area and a leaf area of the to-be-graded main grain crop image; and calculating the proportion of the lesion area in the leaf area, obtaining a final fine-grained disease grading result of the to-be-graded main grain crop image, and completing staple food crop disease grading based on the prompt-driven large model. According to the method, automatic detection and grading of crop diseases are realized by integrating deep learning and an interactive segmentation technology, so that the accuracy of disease detection and classification is improved, possibility is provided for optimizing the use of pesticides, and environmental pollution and the risk of crop drug resistance are reduced.

The invention provides a safety management and control system for an intelligent lock of a transformer substation, and the system comprises an intelligent wearable device which is used for monitoring the physiological data of a wearer in real time; the environment monitoring module is used for monitoring the environment risk of the working area in real time; the video monitoring module is used for monitoring the in-out dynamic state and the behavior standard of the personnel; the intelligent lock linkage management module is used for automatically locking an intelligent lock and giving an alarm according to monitoring results of the intelligent wearable device, the environment monitoring module and the video monitoring module when abnormity is monitored; the risk assessment module is used for establishing a risk assessment model and dynamically adjusting the operation authority of the intelligent lock; and the situation awareness control module is used for changing the operation authority of the intelligent lock according to the situation evaluation result. The invention further discloses a corresponding method. According to the invention, the safety and management efficiency of electric power facilities such as a transformer substation are improved.

The invention discloses a data annotation method based on a large model. The data annotation method comprises the following specific steps: acquiring data and preprocessing the data to obtain input data; performing model training based on the arbitrary-degree large model and the input data to obtain a pre-trained arbitrary-degree large model; performing interface packaging on the pre-trained random degree large model; performing fine tuning on the packaged pre-training arbitrary-degree large model to obtain a target arbitrary-degree large model; acquiring to-be-labeled data, inputting the to-be-labeled data into the target arbitrary-degree large model for labeling, and outputting to obtain labeled data; and monitoring, feeding back and recording the fine tuning process of the pre-trained arbitrary-degree large model and the labeling process of the target arbitrary-degree large model to obtain historical fine tuning data, historical data to be labeled and historical labeling data. According to the method, the problems of label imbalance, label inaccuracy and image label error are solved, the labeling quality and efficiency are improved, and the labeling cost is reduced.

The invention relates to the technical field of air conditioner control optimization, in particular to a control method and device for a multi-connected air conditioning unit, and the control method comprises the steps that an air conditioning area is divided to obtain a plurality of air conditioning sub-areas, and an air conditioning area map is constructed based on the air conditioning sub-areas; and performing video monitoring on the plurality of air conditioning sub-regions based on an infrared camera to obtain infrared videos of the plurality of air conditioning sub-regions, and performing image interception on the infrared videos according to a preset sampling period to obtain an infrared video frame sequence. The air conditioning area is reasonably divided, the whole space is divided into the multiple air conditioning sub-areas, the air conditioning system can be controlled more flexibly, the division can be adjusted according to the actual use condition, and the requirements of different numbers of users can be better met.

The invention relates to a method for improving soil fertility and enzyme activity of a rice field by using a nitrogen-fixing cyanobacteria biological membrane, which comprises the following steps: step 1, expanding propagation of nitrogen-fixing cyanobacteria: selecting anabaena globifera as a rice field application algae species, and performing expanding culture on the algae species to obtain a nitrogen-fixing cyanobacteria secondary algae species; step 2, applying nitrogen-fixing cyanobacteria: applying the nitrogen-fixing cyanobacteria in a rice base fertilizer period and a tillering period, and replacing part of chemical fertilizer with the nitrogen-fixing cyanobacteria to reduce the application amount of the chemical fertilizer; secondly, the nitrogen-fixing cyanobacteria returns to the rice field through biological nitrogen fixation and rotting decomposition of dead algae, the content of nitrogen and carbon in the soil is increased, the soil fertility is improved, and the nitrogen-fixing cyanobacteria can provide nutrient substances for microorganisms in the soil, improve the enzyme activity of the soil and improve the quality of the soil when applied to the rice field.

The invention relates to a forest and grass Internet of Things access control method and system based on a smart contract and KP-ABE. The method comprises the following steps: S1, initializing a block chain network and defining the smart contract; s2, encrypting data transmission attributes of the gateway of the forest and grass Internet of Things and generating an access request; s3, the forest and grass cloud platform verifies the data transmission attribute access request of the forest and grass Internet of Things gateway; s4, the forest and grass cloud platform decrypts the transmission data and stores the data into a data acquisition database; s5, generating a download attribute access request for operation configuration of the forest and grass Internet of Things gateway; s6, the forest grass cloud platform verifies the operation configuration downloading attribute access request of the forest grass Internet of Things gateway; s7, the forest and grass Internet of Things gateway downloads forest and grass Internet of Things gateway operation configuration; s8, carrying out security situation awareness and emergency disposal on the forest and grass cloud platform; s9, ending the process; the system is used for executing the control method. According to the invention, decentralization, transparency, non-tampering and traceability of forest and grass Internet of Things system access control are realized.

The invention provides an intelligent financial management system based on data feature analysis, and relates to the technical field of financial management. The intelligent financial management system based on data feature analysis comprises a data acquisition module used for collecting various financial data inside and outside an enterprise; the data preprocessing module is used for carrying out standardization processing on the financial data; the feature extraction and analysis module is used for carrying out feature extraction and analysis on the preprocessed financial data; the model building and training module is used for building a prediction model based on the extracted features and training the model by using historical data; the financial management module is used for realizing comprehensive management of enterprise finance based on a feature analysis result; and the decision support module is used for presenting results of feature analysis and financial management to an enterprise manager in a visual form. The intelligent financial management system not only can improve the financial management efficiency of an enterprise and reduce the operation cost, but also can enhance the market competitiveness and adaptability of the enterprise.

The invention relates to the technical field of digital human systems, and discloses an enterprise propaganda virtual digital human system based on a block chain and deep learning, and the system ensures the safety and non-tampering of enterprise propaganda data and user interaction data through a block chain storage unit; the intelligent level of the virtual digital human is improved by utilizing a deep learning model construction unit, and the functions of language understanding, dialogue generation, image rendering and the like are realized; the enterprise information extraction unit and the user request processing unit are respectively responsible for data updating and request analysis; the dialogue management unit and the image rendering unit generate proper replies and dynamic images according to user requirements and scenes; the block chain verification unit guarantees the authenticity of the data; the feedback optimization unit realizes continuous optimization of the model; and the multi-channel publishing and managing unit ensures multi-platform synchronization and consistency of contents. According to the system, the personalized, interactive and efficient levels of enterprise propaganda are greatly improved.

A spiral pruning method for crisp and honey kumquats is characterized in that when fruit-bearing branches are hung, branch hanging is carried out step by step from top to bottom in a layered mode, two vertically-adjacent layers of fruit-bearing branches are staggered to form a multi-layer three-dimensional tree crown structure, and after branch hanging work is completed, the whole shape of the hung branches is in a spiral rising shape. Comprising the following steps: (1) erecting a supporting rod; (2) trunk selection and culture; (3) main branch selection and arrangement; (4) selecting, remaining and pruning side branches; (5) branch hanging and the like. According to the spiral pruning method for the crisp and honey kumquats, the layout mode remarkably improves the ventilation and light transmission conditions of tree crowns, the photosynthesis efficiency is improved, and uniform distribution and maturity of fruits are promoted.

The utility model relates to the technical field of key storage, and discloses an intelligent key box for managing borrowed keys of a transformer substation, which comprises a storage box body, an operation panel is arranged on the front side of the storage box body, a storage cavity is arranged in the storage box body, and a box door is hinged to the front side of the storage box body. The storage cavity of the storage box body is closed through the box door; a rotating plate is rotatably mounted in a storage cavity of the storage box body, a plurality of mounting grooves are formed in the front side and the rear side of the rotating plate, and an overturning box is rotatably mounted in each mounting groove. According to the intelligent key box, the rotating plate is arranged in the storage box body, the overturning boxes are arranged on the front side and the rear side of the rotating plate correspondingly, the front side and the rear side of the rotating plate can be switched to face the outer side, keys can be stored and taken in the different overturning boxes, the space in the box is reasonably utilized through the design, people can conveniently find and take the keys, the number of the overturning boxes is doubled, and the intelligent key box is convenient to use. The problem that the number of keys stored in a key box is small is solved.

The invention provides a vehicle back door assembly and a vehicle, and relates to the technical field of vehicles, the vehicle back door assembly comprises a back door and a back door electric supporting rod used for supporting the back door, the types used for selecting the back door comprise an active empennage back door and a large empennage back door, the weight of the active empennage back door and the weight of the large empennage back door are sequentially increased, and when the selected back door is one of the two types, the large empennage back door is connected with the active empennage back door. One end of the back door electric supporting rod is supported on the same supporting point of the back door; when the back door is the active empennage back door, the reference electric supporting rod is arranged on the back door, so that the supporting force of the reference electric supporting rod meets the use requirement of the active empennage back door under the first set working condition; and when the back door is the large-empennage back door and the weight of the back door meets a first preset condition, the supporting force of the reference electric supporting rod is adjusted so that the supporting force of the reference electric supporting rod can meet the use requirement of a second set working condition of the large-empennage back door. In this way, the back doors of the active empennage back door and the large empennage back door can be opened and closed through one set of electric supporting rods.

The invention provides a credible authorization method and system for service software of a credible controller and a related device, and belongs to the technical field of credible controllers, and the method comprises the following steps: respectively collecting hardware feature information and service software operation behavior data of equipment; performing abnormal behavior detection through a pre-trained machine learning model in combination with historical behavior data of business software of the equipment and the collected hardware feature information and business software operation behavior data; and according to the hardware feature information of the equipment, the operation behavior data of the service software and the output result of the machine learning model, generating a unique authorization token through a preset encryption algorithm and a key, and taking the unique authorization token as a certificate for accessing the service software. According to the method, the hardware feature information of the equipment is combined with the operation behavior of the business software for authorization judgment, and an abnormal behavior detection mode of combining the real-time operation behavior of the business software with machine learning is adopted, so that illegal access and operation to the business software can be effectively prevented, and the security of the business software is improved.

The invention relates to the technical field of attendance management, in particular to an attendance management method. According to the technical scheme, the method comprises the following steps: selecting and initializing an attendance system; daily attendance management, wherein the daily attendance management comprises a clock-in mode and clock-in exception processing; evaluating and examining and approving the automatic reissuing card; and attendance data analysis and report generation. According to the attendance management system, a multi-source data collection and comprehensive analysis mechanism is added, and based on a comprehensive judgment function and an equipment fault possibility evaluation function, an evaluation result is used for optimizing the judgment accuracy of automatic card supplement, so that misjudgment is avoided, and the work efficiency is improved. The automatic examination and approval decision function is used for automatically judging according to conditions such as comprehensive evaluation and late times of employees and manually examining and approving related information decisions, so that the workload and the management cost of the employees are reduced, the accuracy and the reliability of attendance data are improved, and the system can adapt to the requirements and changes of enterprise attendance management.

The invention discloses an anti-floating buffering flexible pool for a high underground water level. According to the invention, the anti-floating problem of the flexible pool body when the underground water level is relatively high is effectively solved through the interlayer structure. The interlayer material can automatically expand when the underground water level rises to form supporting force to resist the jacking effect of water buoyancy on the pond bottom, so that the pond body is prevented from floating upwards. Therefore, the application limitation of a traditional flexible pool body in areas with the high underground water level is broken through, the application range of the flexible pool body is widened, and the flexible pool body can be applied to more areas, especially occasions with poor foundations, the high underground water level and the high requirement for the water storage capacity. The anti-floating buffering flexible pool can effectively solve the problems in coastal areas, areas with rich underground water resources, urban underground spaces and the like, and a safe and reliable water storage solution is provided for the areas.

The invention discloses an equipment management method and system, computer equipment, a storage medium and a product, and relates to the technical field of the Internet of Things, and the disclosed equipment management method comprises the steps: obtaining environment data collected by each piece of to-be-managed equipment, and monitoring each piece of environment data; when it is monitored that changed environment data exists in the environment data, the environment data at the current moment is input into a preset intelligent agent, a management decision output by the intelligent agent is obtained, and the intelligent agent is built based on a large language model in advance; and determining a target device according to the management decision, and controlling the target device based on the management decision. The technical scheme of the invention aims to solve the technical problem of how to reduce the management cost of the equipment.

The invention belongs to the field of temperature regulation and control, and particularly discloses a chemical medicine storage cabinet temperature regulation and control method and system, and the method comprises the steps: firstly, carrying out the temperature conformity analysis, dividing regions through internal partition plates, collecting the temperature, and judging whether the temperature in a storage cabinet meets the requirements or not; if not, external environment regulation is carried out, the external environment temperature is collected, the deviation coefficient of the external environment temperature is determined, and the target regulation temperature is set. And then temperature uniformity analysis is carried out, the temperature of the set acquisition points of each region after regulation and control is acquired, a temperature distribution uniformity index is obtained, and regions with non-uniform temperature distribution are screened out. And finally, carrying out temperature uniformity adjustment, collecting the temperature of each collection point in the non-uniform areas, analyzing the temperature influence coefficient, further analyzing the target regulation distance between the internal partition plate and the cabinet wall, and carrying out adjustment, thereby realizing effective control on the temperature of the chemical medicine storage cabinet, and ensuring a proper medicine storage environment.

The invention discloses a multi-modal file data co-processing management system, which relates to the technical field of file management and comprises a data input layer, a data storage layer, a data processing layer, a business logic layer, an application layer, an integration layer, a security monitoring layer and an infrastructure layer. The method not only supports management and processing of various data types, improves data inclusivity and processing capability, but also has real-time cooperation and version control functions, improves team cooperation efficiency, reduces data conflicts, ensures data integrity and consistency, simplifies data entry, classification, filing and retrieval processes through automatic tools and algorithms, and improves the efficiency of team cooperation. And meanwhile, an intelligent search function is provided, required data can be quickly positioned, a user can remotely access archive data from any place with network connection, the accessibility of the data is improved, the system also supports cross-department data sharing, and the circulation and collaboration of information are promoted.

The invention relates to the technical field of separation and purification, and discloses a method and a system for separating and purifying norbornene. According to the method provided by the invention, the light components and the heavy components of the norbornene synthetic liquid are sequentially removed, and the high-purity norbornene product can be obtained by controlling the treatment mode and conditions in the removal process, so that the method has the advantages that the norbornene product is high in yield and purity, the treatment process is easy to control and manage, and the like; the method is suitable for industrial popularization.

The invention discloses a live pig breeding equipment full life cycle monitoring management system, a medium and a terminal. The system comprises a user login module used for user authority management and data query; the data acquisition module is used for acquiring full-life-cycle data of intelligent equipment used for pig breeding; the data preprocessing module is used for preprocessing operation data of various intelligent devices monitored in real time by using the Internet of Things technology; the data storage module is used for storing various data information; the data analysis module is used for predicting and evaluating the state of the intelligent equipment by adopting a deep neural network model; the equipment state early warning module is used for setting an early warning rule and establishing an early warning mechanism according to the characteristics and business requirements of the equipment, and sending out early warning and corresponding measure notifications; the intelligent decision-making module is used for generating an equipment state evaluation report and generating a multi-dimensional data analysis report; and the display module is used for displaying the generated multi-dimensional data analysis report. The intelligent equipment is supervised, and the breeding efficiency and the management level are improved.

The invention provides a vehicle back door assembly and a vehicle, and relates to the technical field of vehicles, the vehicle back door assembly comprises a back door and a back door electric supporting rod used for supporting the back door, the types used for selecting the back door comprise an empennage-free back door and an active empennage back door, the weight of the empennage-free back door and the weight of the active empennage back door are sequentially increased, and when the selected back door is one of the two types, the back door electric supporting rod is used for supporting the back door. One end of the back door electric supporting rod is supported on the same supporting point of the back door; when the back door is an empennage-free back door, the gravitational torque of the back door is adjusted to reach the supporting rod torque of the reference electric supporting rod; and when the back door is the active empennage back door, the reference electric supporting rod is arranged on the back door, so that the supporting force of the reference electric supporting rod meets the use requirement of the active empennage back door under the first set working condition. In this way, the back door with the no-empennage back door and the back door with the active empennage can be opened and closed through one set of electric supporting rods.

The invention relates to the technical field of building construction supervision, in particular to a safety early warning method and system for a concrete construction process, and the method comprises the steps: firstly obtaining data of a monitoring point of a support frame and an adjacent monitoring point, and constructing a deformation feature vector of the support frame; the support frame deformation feature vector comprises a distance feature, an angle feature, a deformation feature and a vibration frequency feature; then determining the number of clustering clusters according to a BIM model of a building, carrying out clustering analysis on the deformation feature vector of the support frame, and judging whether an abnormal cluster exists or not; support frame monitoring points in the abnormal cluster are obtained, and an abnormal support frame monitoring point set is obtained; and obtaining the distance feature, the angle feature, the pouring feature component and the vibration feature component of the abnormal support frame monitoring point to construct an abnormal evaluation index, and if the abnormal evaluation index is greater than a preset abnormal threshold value, triggering safety early warning. By means of the method, real-time monitoring of the formwork supporting frame in the concrete construction process is achieved, and construction safety is improved.

The invention discloses a steel plate drilling automatic online detection system based on machine vision, and relates to the technical field of steel plate drilling machining systems. The system comprises a control system module, the input end of the control system module is electrically connected with an image processing module, the input end of the image processing module is electrically connected with an image acquisition module, and the output end and the input end of the control system module are electrically connected with a deep learning module. The output end and the input end of the control system module are electrically connected with a data processing module. According to the invention, the deep learning module uses a deep learning algorithm to train a large number of drilling images, automatically learns the characteristics and modes of drilling, improves the accuracy and robustness of detection, can continuously optimize the performance of itself, adapts to different types of steel plates and drilling requirements, and improves the accuracy and robustness of detection. And the intelligent diagnosis module is combined with an expert system and data analysis to perform intelligent diagnosis on a detection result.