14results about How to "Accurate grouping" patented technology

The invention relates to the technical field of fault detection for a wireless communication network, and discloses a fault detection method for the wireless communication network. By collecting data of base station signal strength, network delay, data packet loss rate and user equipment signal quality, the problem of insufficient fault detection caused by a single index is solved. Through multi-dimensional data acquisition, the system can comprehensively evaluate network performance, the fault detection accuracy is improved, and different fault types can be effectively identified especially in a complex fault mode. By storing the data according to the time sequence, the problem of time sequence chaos is avoided, and accurate detection of time-varying faults is ensured. The comprehensive data vector generated by each time of sampling comprises a plurality of network performance indexes, so that the fault detection and positioning capability is improved. Abnormal values are eliminated through data preprocessing, the data quality is ensured, an accurate basis is provided for subsequent analysis, and the reliability of a detection result is ensured.

The invention discloses a method for generating a three-dimensional building GLTF file based on index compression. The method comprises the following steps: S1, collecting three-dimensional coordinate data of a building; s2, grouping and classifying the data according to floors to form a classification index structure based on a hash table; s3, selecting a reference model and recording Mesh data and vertex coordinates of the reference model; s4, calculating a translation matrix T of the polyhedral structure, and performing coordinate transformation; s5, generating Mesh data of other polyhedrons based on index compression, and reducing redundant surface data by adopting a topology preserving surface optimization algorithm; s6, independently processing the geometric data of each floor, and generating corresponding Mesh data and Node nodes; and S7, combining all floor data to generate a complete GLTF file, and performing compression by using a dynamic Huffman coding algorithm. Through the improved index compression and dynamic Huffman coding technology, the file size is remarkably reduced, the transmission efficiency is improved, and the geometric and topological integrity of the model is ensured.

The invention discloses a Neper-DEM-based apparent crystal rock modeling and calculation method with a bedding structure, relates to the field of numerical calculation of a tunnel engineering technology, and solves the problem that a simulation and calculation method for apparent crystal rocks with transverse isotropy such as gneiss and granite gneiss is lacked in the prior art. The method comprises the following steps: constructing a polycrystal structure with crystal characteristics in Neper, and generating a geometric parameter text of crystal grains from the polycrystal structure; constructing a discrete element rock sample model in the DEM; performing a numerical simulation test on the discrete element rock sample model to obtain a stress-strain curve and a sample failure mode, wherein the numerical simulation is realized by adopting a Brazilian splitting test and a triaxial test; according to a numerical simulation result, discrete element sample calculation parameters are calibrated, and the effectiveness of the modeling and calculation method of the discrete element rock sample model is verified; according to the modeling method, construction and assignment of the crystal structure and the bedding structure are achieved at the same time, so that the rock structure is closer to a real rock structure.

The invention discloses a capacity grading method and a capacity grading device for battery cell capacity, and a computer readable storage medium. The method comprises the following steps: determining a target capacity grading environment temperature interval; under the condition that the environment temperature is in the target capacity grading environment temperature interval, the conversion rate between the capacity grading capacity and the calibrated capacity grading capacity is determined; and correcting the actual capacity grading capacity based on the conversion rate to obtain a corrected capacity grading capacity, and carrying out capacity grading on the battery cell according to the corrected capacity grading capacity. According to the capacity grading method, the influence of temperature fluctuation can be eliminated, the problem that the current capacity grading capacity test of the battery cells is inaccurate is solved, and the battery cells can be accurately grouped, so that the service life of the battery module is prolonged.

The invention belongs to the technical field of call service processing, and discloses a real-time call question and answer matching processing method, which comprises the following steps of: converting voice into characters in real time, and sending preprocessed voice data into an ASR service for real-time conversion; real-time text processing and grouping are carried out, and texts are extracted, sorted and grouped through role detection and grouping and timestamp correction; and processing the text after the call, and matching the text with the identified groups in the call process. According to the method, calling of the TEXTCNN model is dispersed to the call process, so that the processing method remarkably reduces the time required for centralized text processing after the call is ended, which means that even if the call duration is relatively long, the response duration of filing information can be effectively controlled due to the fact that the processing is dispersed to the whole call period, and the user experience is improved. Therefore, the performance requirement of outputting filing information within 5 seconds after on-hook can be met even in peak hours.

The present application relates to the technical field of artificial intelligence and federated machine learning, and particularly relates to an asynchronous federated learning aggregation method and system based on clustering cache. The present application clusters clients by intermediate features of the clients. In global aggregation, intra-cluster aggregation is firstly performed, and then global aggregation is performed based on client clusters. The client clusters are dynamically updated. In intra-cluster aggregation, an active set and a slow set are introduced to realize an asynchronous participation mechanism of intra-cluster aggregation. Weighted aggregation of the active set and the slow set solves the problem of system heterogeneity. The present application solves the defect of insufficient timeliness of existing federated learning methods in a data heterogeneous scene, and guarantees the timeliness and model training accuracy of federated learning in the data heterogeneous scene.

The embodiments of this specification provide a tag processing method, device, electronic device and storage medium, wherein the method includes: in response to a user's edit request operation for a tag rule of a first tag, displaying an editing page of the tag rule; wherein the first tag is used to represent a grouping of user sessions, the tag rule is used to filter the user's sessions, and different tags correspond to different session groups based on different tag rules; obtaining at least one tag rule of the first tag edited by the user in the editing page; wherein a tag rule includes a rule action and at least one rule condition, and when a session meets some or all of the rule conditions, the rule action is executed to filter the user's session to obtain a session corresponding to the first tag; according to each tag rule, determining and displaying the session group corresponding to the first tag. Through this embodiment, a large number of sessions can be managed, and the efficiency of users finding required sessions can be improved.

The invention provides a grouping method and system for mountain terrain triangular facets, and the method comprises the steps: carrying out the dividing of the geometric information of Delaunay triangular facets based on the terrain, obtaining the included angle between each triangular facet of the mountain terrain and the horizontal plane, and forming a first included angle set; screening the included angles in the first included angle set according to a preset included angle threshold to obtain a second included angle set; and grouping the included angles in the second included angle set to obtain groups to which the included angles in the second included angle set belong. According to the technical scheme provided by the invention, the mountain terrain triangular surfaces can be accurately grouped, and support is provided for subsequent construction of a photovoltaic power station.

The invention provides a lung adenocarcinoma EGFR-TKIs curative effect intelligent prediction system and method, and the method comprises the steps: excluding and screening non-small cell lung cancer pathological images through early-stage automatic RECIST evaluation, and obtaining a pathological image set after RECIST exclusion; scanning a pathology image set after RECIST sorting by using a same-mode fixed amplification galvanometer scanning module; performing model training parameter learning, model optimization parameter fine tuning and model test identification generalization on the basic convolutional neural network ResNet model to obtain a training generalization convolutional neural network ResNet model; and performing lung adenocarcinoma EGFR-TKIs curative effect intelligent prediction on the non-small cell lung cancer pathological image according to a training generalization convolutional neural network ResNet model by using the image block level ORR objective remission rate thermodynamic diagram and the image block level ORR objective remission rate average value calculation result.

Acupuncture instrument assembling auxiliary equipment comprises a conveying belt and an intercepting device fixed to the conveying belt, the intercepting device comprises a base, the right side of the base is rotationally connected with a lead screw, the lead screw is connected with a driving assembly, the middle of the base is connected with a set of driving rods, the driving assembly sequentially drives the set of driving rods, and each driving rod is rotationally connected with a gear. The two sides of each gear are meshed with the racks on the base and the racks on the middle rods at the same time, each middle rod is slidably connected with the base, the left side of the base is slidably connected with a driving plate, the driving plate is slidably connected with a set of right-angle plates, the middle rod on the rearmost side is slidably connected with the driving plate, and the middle rod on the front side is slidably connected with the right-angle plates. According to the device, the grouping pitch changing rhythm can be adjusted according to the rhythm of a production line, and grouping pitch changing is accurate.

The invention belongs to the technical field of practical teaching management, and discloses a smart home practical teaching management system and method. Comprising the steps that a student data set is collected, and the student data set comprises student basic information ID and student learning ability information; preprocessing the student data set to obtain a preprocessed student data set; performing clustering processing on the preprocessed student data set to obtain a clustering processing result, and grouping the students based on the clustering processing result to obtain a grouped student data set; classified teaching management is carried out based on the grouped student data set; students are more accurately grouped by using the clustering algorithm, and classified teaching is performed according to the clustering result, so that teaching resources can be more effectively allocated, and the teaching effect is enhanced.

The invention discloses a customer group determination method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining multi-modal data of a plurality of customers, the multi-modal data comprising voice data, image data and structured data; processing the multi-modal data of the plurality of clients through a target model to obtain a target feature vector set; the target feature vector set is classified through a target classifier, a plurality of customer groups are obtained, the target classifier is a classifier trained in advance based on a plurality of category labels, each customer group corresponds to one category label, and the customer groups are used for determining potential customer groups of the target recommendation activity. According to the method and the device, the technical problem of low customer grouping accuracy caused by incomplete customer attribute selection due to the fact that only structured data of customers are analyzed during customer grouping in the prior art is solved.

The invention discloses a risk level assessment method and device for an equipment security event, a medium and a terminal, relates to the technical field of equipment operation and maintenance, and mainly aims to solve the problem that the overall risk identification capability is insufficient due to the fact that an existing method only focuses on risk identification in a single link in an optical transmission process. Comprising the following steps: acquiring alarm information carried by a target equipment security event, and generating an alarm feature vector; deducing a knowledge graph based on pre-constructed equipment security event features, and performing enhancement processing on the alarm feature vector to obtain an enhanced alarm feature vector; and based on the equipment security event risk level assessment model after model training is completed, risk level assessment operation is performed on the target equipment security event according to the enhanced alarm feature vector, a risk level assessment result is obtained, and equipment operation is controlled according to the risk level assessment result.

The invention discloses a projection method and device for a multi-person conference and electronic equipment, and relates to the field of intelligent projection. The method comprises the following steps: acquiring a plurality of illumination intensity values at different positions of a projection space; performing weighted average on the plurality of illumination intensity values to obtain an average illumination intensity value of the projection space; according to the average illumination intensity value, a projection brightness range corresponding to the average illumination intensity value is determined in a preset projection brightness library, and the preset projection brightness library comprises a corresponding relation between the illumination intensity value and the projection brightness range; obtaining vision parameters of each watching user; determining target projection brightness in a projection brightness range according to the vision parameters; and generating a target projection image according to the target projection brightness. By implementing the technical scheme provided by the invention, the average illumination intensity of the conference room and the vision parameters of each user are comprehensively considered, the projection brightness is intelligently adjusted, and the visual experience of a multi-person conference is improved.