16results about How to "Achieving system performance" patented technology

The invention discloses a method for optimizing key structure parameters of a deep well electric submersible pump based on performance simulation, and relates to the technical field of design optimization of electric submersible pumps, a three-dimensional geometric model of a deep well submersible centrifugal pump is built in advance, the three-dimensional geometric model comprises an impeller, a guide shell, a pump shaft, a pump shell, an upper connector, a lower connector and a full-flow-channel structure, and initial structure parameters are calibrated; and establishing a centrifugal pump simulation model based on a computational fluid dynamics technology, performing fluid domain extraction, grid division and grid independence verification on the three-dimensional geometric model, and setting fluid attributes, boundary conditions and a turbulence model. According to the method, a closed-loop iteration framework for simulation, optimization, evaluation and feedback is constructed by adopting a mode of coupling a computational fluid dynamics simulation technology and a genetic algorithm, the limitation of local parameter optimization in the prior art is broken through, systematic and collaborative optimization of key structure parameters of the submersible centrifugal pump is realized, and the method is suitable for large-scale popularization and application. And the efficiency of the optimization process and the final optimization effect are obviously improved.

The application discloses an industrial robot flexible operation control method and system, and the method comprises the following steps: acquiring physical interaction representation of a robot and a workpiece to be processed, combining historical workpiece representation, determining a new task operation type through a task graph neural network, including reuse, combination or new establishment; generating or selecting corresponding strategy head parameters according to the operation type, combining environment observation to generate and execute mechanical arm action instructions; when the number of strategy heads exceeds a preset capacity, triggering compression maintenance, screening and retaining representative strategy heads to form an optimized active strategy library. The application realizes rapid strategy determination and generation based on physical interaction and graph structure relationship, significantly reduces manual demonstration and training time, and improves production line change response speed; through a structured compression mechanism, the strategy diversity and global knowledge are maintained under limited storage resources, and the adaptive ability and decision efficiency in long-term operation are guaranteed.

The present invention discloses a systematic method for radon shielding construction of underground projects, including survey, diagnosis, test, construction, acceptance, and maintenance stages; through on-site survey and measurement of the internal dimensions of the underground project, the original radon exhalation rate, and the background radon concentration of the external environment; setting the target radon concentration of the underground project, estimating the target radon exhalation rate; calculating the radon shielding efficiency target value of the anti-radon layer, and determining the construction plan; carrying out experimental construction on the wall of a local area of ​​the underground project according to the construction plan; carrying out comprehensive construction according to the construction plan; conducting an overall verification of the radon shielding effect of the underground project, and if the overall verification is unqualified, it is necessary to conduct a local verification of the radon shielding effect of the underground project; formulating the engineering use instructions and maintenance plan. The embodiment of the present invention carries out full-process planning of the entire radon shielding project, and optimizes the construction plan through on-site survey and testing, thereby realizing the scientificity, systematicness, and effectiveness of radon shielding of underground projects.

The invention provides an automatic driving multi-agent performance evaluation system and method based on a virtual-real fusion scene, and belongs to the technical field of automatic driving evaluation, and the system comprises a scene simulation subsystem which is used for obtaining environment parameters, constructing and obtaining a virtual-real fusion test scene according to a structured scene configuration template, and employing a generation point three-level verification algorithm to obtain a virtual-real fusion test model; obtaining an initialized automatic driving agent; the scene performance evaluation subsystem is used for collecting and complementing multi-dimensional data, evaluating to obtain a comprehensive score according to a preset evaluation dimension, and performing unsupervised clustering, anomaly detection and performance prediction by utilizing machine learning to obtain a machine learning analysis result; the comprehensive evaluation report and decision support subsystem is used for receiving the comprehensive score and the machine learning analysis result, obtaining a comprehensive evaluation report through problem diagnosis and generating decision optimization; according to the invention, the problem that systematic, multi-dimensional and benchmark performance evaluation cannot be carried out on a plurality of automatic driving agents in the prior art is solved.

This invention belongs to the field of corrosion information technology and relates to a corrosion data and control platform. The corrosion data and control platform designed in this invention includes a corrosion big data management module, a risk assessment module, a corrosion prediction module, an overall corrosion control module, and a system management module. The corrosion big data management module is used to connect the data interface of the corrosion business system; the risk assessment module is used to calculate risk assessment values ​​based on the operating data of the site and pipeline; the corrosion prediction module is used to calculate the corrosion rate of the experimental object based on the corrosion rate prediction model and the wall thickness prediction model; the overall corrosion control module is used to realize the input or update management of corrosion control information; and the system management module is used to manage the corrosion data and control platform. This platform automates data acquisition, structuring various types of corrosion data, such as site basic data, corrosion failure data, and indoor laboratory data, into a database for centralized and unified management.

The application discloses a grain boundary solute segregation and co-segregation behavior prediction and key element screening method based on first principles, and the method comprises the following steps: 1, constructing a grain boundary model to obtain a stable grain boundary structure; 2, identifying typical segregation sites in the grain boundary region and classifying; 3, calculating the segregation energy, and analyzing the site selectivity segregation behavior of the candidate solute element; 4, determining the main segregation site; 5, constructing a double solute atom co-segregation model of the main segregation element and other segregation elements; 6, calculating the co-segregation energy and the co-segregation energy difference, and determining the synergistic segregation or competitive segregation behavior; 7, establishing the correlation between the co-segregation energy and the physical property parameters, and establishing a grain boundary co-segregation behavior prediction model. The application establishes a grain boundary segregation and co-segregation behavior prediction method based on the coupling of segregation energy and physical property parameters, realizes high-throughput screening and rapid determination of the segregation behavior of solute elements in a multi-component system, and provides a theoretical basis for grain boundary composition regulation.

The invention relates to a northeast black soil area water and soil resource bearing capacity evaluation system and method.The northeast black soil area water and soil resource bearing capacity evaluation system is characterized in that a multi-scale data acquisition module is connected with a comprehensive database in a wired or wireless connection mode, the comprehensive database is connected with a dynamic monitoring module through a data transmission module, and the dynamic monitoring module is connected with a data evaluation system; the data evaluation system is connected with the early warning analysis module; data acquired by the multi-scale data acquisition module comes from mobile acquisition equipment, fixed acquisition equipment and networked acquisition equipment, and the mobile acquisition equipment, the fixed acquisition equipment and the networked acquisition equipment perform multi-scale data acquisition on a water resource basin and a land resource area; on-site data acquisition and verification work are carried out through mobile acquisition equipment, the accuracy of multi-source data acquisition is ensured, then dynamic monitoring is carried out on calculated data, dynamic real-time evaluation is carried out according to evaluation indexes, and then an optimization scheme or early warning work is carried out.

The invention relates to a cloud computing resource preemption management method and device, equipment and a storage medium. When the cloud computing resources of the cloud host are adjusted, each pre-occupation record corresponding to the cloud host can be stored in the pre-occupation record linked list corresponding to the cloud host, and each pre-occupation record comprises the pre-occupation record identifier corresponding to the previous pre-occupation record, so that the pre-occupation records can be associated according to the sequence, and the pre-occupation records can be associated according to the pre-occupation record identifier corresponding to the previous pre-occupation record. According to the method, the pre-occupation records corresponding to the cloud hosts are counted through the pre-occupation record chain tables corresponding to the cloud hosts, repeated reading and writing of resources of the cloud hosts and the pre-occupation records of the cloud hosts are not needed, data reading and writing burdens are reduced, traceability of the pre-occupation records is achieved, the difficulty of data management and troubleshooting of the cloud hosts is reduced, and the efficiency of data management and troubleshooting of the cloud hosts is improved. And systematicness and orderliness of camping management of cloud computing resources are realized.

The invention provides an offshore small target detection method and system based on low-altitude remote sensing image enhancement, and relates to the technical field of target detection. Obtaining spectrum features of the to-be-detected low-altitude remote sensing image, and quantifying a rain potential feature value and a haze feature value based on a shielding mask; comparing the rain vigor characteristic value with a rain vigor threshold value, and if the rain vigor characteristic value is greater than the rain vigor threshold value, triggering rain removal processing: through a multi-scale Transform network, in combination with implicit neural representation, learning rain degradation characteristics and carrying out cross-scale characteristic interaction, and removing rain stripe interference to obtain a rain removal image; comparing the haze feature value with a haze threshold value, and if the haze feature value is greater than the haze threshold value, triggering defogging processing: filtering low-frequency haze information through a histogram self-attention mechanism and retaining high-frequency image details to obtain a defogged image; and inputting the processed image into a small target detection model, and identifying and obtaining an offshore tiny target detection result, thereby effectively solving the problem of insufficient detection robustness caused by low-altitude remote sensing image degradation.

This invention discloses a method and system for industrial carbon reduction path planning based on an evaluation matrix, belonging to the field of intelligent industrial process technology. The method first fuses multi-source industrial data in real time through an edge gateway, dynamically generating virtual carbon flow triples based on a material and energy balance model to construct a dynamic carbon flow topology network. Then, graph wavelet transform is applied to extract multi-scale spatiotemporal carbon potential features from the network and organizes and compresses them into a two-dimensional carbon potential evaluation matrix. Next, a structured set of carbon reduction operators is generated through matching with an expert rule base. Then, an improved multi-objective evolutionary algorithm incorporating carbon potential feature similarity constraints is used to optimize the operators, balancing emission reduction, economic benefits, and execution costs, outputting a Pareto optimal path scheme. Finally, the scheme is converted into control commands and executed via the OPC UA protocol, achieving intelligent triggering based on real-time matrix monitoring. This invention achieves intelligent and precise control and continuous optimization of industrial carbon emissions throughout the entire process.

This application discloses a method, apparatus, equipment, medium, and product for evaluating the effectiveness of transportation and tourism services, relating to the field of intelligent transportation technology. The method includes: acquiring data on first transportation stations, first tourist attractions, and first road network in a target area under a first scenario, and data on second transportation stations, second tourist attractions, and second road network in a second scenario; determining the number of first transportation stations, the proportion of first transfer stations, and a first accessibility index based on the data under the first scenario, and determining the number of second transportation stations, the proportion of second transfer stations, and a second accessibility index based on the data under the second scenario; and determining the effectiveness evaluation result based on the number of first transportation stations, the proportion of first transfer stations, the number of second transportation stations, the proportion of second transfer stations, the first accessibility index, and the second accessibility index. This method can achieve accurate evaluation of the effectiveness of transportation and tourism services.

The present application relates to permafrost roadbed engineering technical field, specifically relates to a kind of permafrost zone overhead roadbed ventilation efficiency multi-parameter comprehensive evaluation method, steps include obtaining overhead layer pipe diameter, arrangement length, paving height, roadbed form and other key parameters design two-level evaluation index;Based on four evaluation dimensions, construct evaluation system, design evaluation index quantization grading standard;Ventilation efficiency index is calculated using entropy value empowerment method modeling;According to ventilation efficiency index grading threshold interval, ventilation efficiency grade evaluation is carried out.The present application proposes overhead roadbed ventilation efficiency evaluation method, realizes the multi-parameter, quantitative comprehensive evaluation of overhead roadbed ventilation efficiency, provides key technical support for full-face overhead roadbed ventilation structure design optimization, for improving permafrost zone overhead ventilation roadbed cooling heat dissipation efficiency, safeguarding high-cold area road engineering toughening and prolonging life, has important engineering application value.

This application belongs to the field of sedimentary basin analysis technology, and relates to a method and system for characterizing magma underplating uplift based on seismic data. The method includes: acquiring drilling and logging data and seismic data volumes of the study area; extracting seismic profiles from the seismic data volumes; interpreting anomalous and non-anomalous seismic data volumes on the seismic profiles; constructing a first trend surface based on the anomalous seismic data volumes and a second trend surface based on the non-anomalous seismic data volumes; calculating the uplift caused by magma underplating based on the first and second trend surfaces; and quantitatively characterizing the degree of magma underplating uplift based on the uplift caused by magma underplating. The technical solution of this application, by constructing two mathematical surfaces representing the actual morphology and the regional background trend respectively and performing spatial difference calculations, achieves a fundamental shift from qualitative description to objective quantitative characterization of magma underplating uplift, providing accurate and reliable technical support for deep basin process research and oil and gas exploration.

The invention provides an intelligent forest tree breeding method based on multi-modal data and a large model, and relates to the technical field of forest tree genetic breeding. The method comprises the steps of obtaining and integrating genotype data, phenotype data, multi-omics data and environment time sequence data of a target tree species, and performing preprocessing and feature fusion to form a multi-modal data set for analysis; on the basis of the multi-modal data set, key genes or gene modules for regulating and controlling target characters are mined by adopting a genotype-environment interaction algorithm and multi-omics coupling analysis; constructing a dynamic model fusing genotypes, environmental factors and time dimensions, and predicting breeding values of individuals or combinations on a whole genome level based on mined key genes or gene module information; and based on a prediction result, performing multi-objective optimization and intelligent screening at three levels of parents, combinations and offspring, and outputting a breeding decision scheme. According to the method, a complete, efficient and accurate forest tree intelligent breeding solution is formed.

The invention belongs to the technical field of corrosion informatization, and relates to a corrosion data and control platform which comprises a corrosion big data management module, a risk assessment module, a corrosion prediction module, an overall corrosion control module and a system management module. The corrosion big data management module is used for getting through a data interface of a corrosion business system; the risk assessment module is used for calculating a risk assessment value according to the station and pipeline working data; the corrosion prediction module is used for calculating the corrosion rate of the experimental object based on the corrosion rate prediction model and the wall thickness prediction model; the overall corrosion control module is used for recording or updating management of corrosion control information; and the system management module is used for managing the corrosion data and the control platform. According to the platform, data acquisition automation is realized, various corrosion data such as station basic data, corrosion failure data, indoor laboratory data and the like are structured to a database, and centralized and unified management is realized.

The invention relates to the field of remote sensing satellite management and control, in particular to a hot spot area prediction method based on historical observation task data, and the method comprises the steps: obtaining the combustion position and combustion time of a historical combustion point observed by a remote sensing satellite in a target area; dividing the target area into a plurality of grids to be detected, and determining the number of combustion points in each grid to be detected according to the combustion position; determining the grid type of the to-be-detected grid according to the number of the combustion points; determining a combustion condition; and selecting a prediction strategy for the hot spot area of the remote sensing satellite based on a determination result. According to the method, the observed hot spot area is predicted by performing fine grid division and multi-dimensional analysis on the target area, the accuracy and pertinence of remote sensing satellite hot spot area prediction are remarkably improved, satellite resource configuration is optimized, and the observation efficiency is improved.