84 results about "Selection rule" patented technology

The invention provides a shield intelligent auxiliary type selection system and method based on a large language model. The model selection system comprises a data input module, a rule knowledge base module, a large model reasoning module and a result generation module. The integrated decision-making system integrating a rule knowledge base, a deep learning model and expert system logic is constructed for the practical problems of complicated geological conditions, multiple rule constraints, high expert dependency and the like in shield construction, and the system combines a structured model selection rule and historical case data, and has the advantages of intelligence, standardization, self-learning, high efficiency and the like. The problems of low efficiency, high subjectivity, insufficient intelligent degree and the like of the existing shield tunneling machine model selection depending on artificial experience and partial standardized guide are solved, and the transformation of shield construction management from artificial experience to intelligent decision can be promoted.

The invention provides an unmanned aerial vehicle sharing intelligent management method and system based on artificial intelligence, and relates to the technical field of intelligent control, and the method comprises the steps: constructing a space virtual geometric shape through a coordinate mapping algorithm; extracting a geometric center coordinate of the space virtual geometric shape, and calculating an offset between the geometric center coordinate and a communication coverage centroid as a first correction factor; analyzing signal coverage included angle distribution among the three position points, and generating a second correction factor in combination with a path loss model; calculating a multipath effect compensation coefficient as a third correction factor according to the signal attenuation gradient on the virtual shape boundary; fusing the first correction factor, the second correction factor and the third correction factor into a comprehensive correction value; and according to the comprehensive correction value, evaluating a communication interruption risk through a path planning neural network, and generating a multi-path transmission scheme containing a redundant relay node selection rule and a dynamic fragmentation recombination strategy. According to the invention, the communication reliability is improved.

The invention provides a cross-platform burying-point-free data collection and intelligent circle selection rule generation method and system, and relates to the technical field of intelligent algorithms, and the method comprises the steps: obtaining view hierarchy tree information and interaction event information of page elements through injecting a data collection script, and training a page element recognition model based on a graph neural network. The model is combined with an adaptive feature fusion network to realize cross-platform element alignment and recognition. And classifying the newly added elements by utilizing the element similarity information, and generating and correcting the circle selection rule based on a preset rule template and the context feature vector. And finally, the rule execution engine realizes continuous monitoring and dynamic acquisition of the target element in the cross-platform application program according to the target circle selection rule.

The invention relates to the technical field of brain-computer interfaces, in particular to an online adaptive classification method, device and equipment for electroencephalogram signals in AI glasses. The method comprises the steps that real-time electroencephalogram signals of AI glasses are obtained and serve as original data for quality detection, data streams are generated for category analysis, a classification standard is obtained, a classification sequence is generated for sample processing, key points are marked for feature extraction, a storage sequence is established, and a replay data sequence is generated to generate a self-adaptive sequence; performing category statistics according to the classification sequence, obtaining distribution characteristics, marking equilibrium points based on the distribution characteristics, constructing a selection rule according to the equilibrium points, generating an equilibrium sequence according to the selection rule, generating classification indexes according to the adaptive sequence and the equilibrium sequence, executing resource analysis, obtaining a resource state, performing task division, and generating a scheduling scheme; and carrying out confidence analysis on the scheduling scheme to construct an output sequence to generate classification information. And a complete processing flow from original signal quality control to feature domain construction is realized.

Embodiments described herein relate to methods and apparatuses for enabling selection of a selected machine learning, ML, model for use in providing a service. A method in a model selection function comprises obtaining an indication of a plurality of ML models and a set of parameters with associated values representative of a context for the service; determining, based on the set of parameters with associated values, at least one applicable selection rule, wherein each applicable selection rule is associated with a logical expression which, when evaluated over one or more of the set of parameters, is true, and wherein each applicable selection rule comprises selection weighting values, wi, indicating weightings to be applied to respective features, featurei, in determining respective ranks of the plurality of ML Models, wherein each respective feature comprises a input feature for at least one of the plurality of ML models; for each first ML model in the plurality of ML models: obtaining global weighting values, ui, indicating relative impacts of the respective features when the first ML model outputs predictions; and determining a model rank of the first ML model from the global weighting values and the selection weighting values; and initiating use of the selected ML model from one or more candidate ML models based on the respective model ranks of the one or more candidate ML models.

The invention is suitable for the field of data screening, and provides a member data selection method and system based on artificial intelligence, and the method comprises the steps: obtaining and storing intra-domain user data from a plurality of target data sources, and the target data sources comprise but are not limited to an online sales platform, an offline store system, an intra-domain user management system and a social media platform of a target enterprise; establishing an intra-domain user information set database based on the intra-domain user data obtained by the plurality of target data sources; extracting target feature data in the intra-domain user information set database; presetting a circle selection rule and a training model, and respectively generating users in an intention purchase domain, users in a high-value domain and users in a potential loss domain; based on the users in the intention purchase domain, the users in the high-value domain and the users in the potential loss domain, generating associated reaction actions; and obtaining and verifying a circling result, and generating feedback information, so that a comprehensive intra-domain user portrait can be formed, deep understanding of intra-domain user demands and behaviors is facilitated, multi-dimensional targeted feature data is extracted, different types of intra-domain users are accurately circled, and personalized strategies are formulated for different intra-domain user groups.

The invention belongs to the technical field of filter optimization, and discloses an EMI filter optimization method and system based on noise source impedance, and the method comprises the steps: measuring the noise source impedance and original noise corresponding to a common mode and a differential mode of a converter, judging an insertion loss demand based on the original noise, and determining a concerned frequency point through the insertion loss demand; the capacitance value of the safety capacitor is determined based on a capacitance value judgment rule, after the impedance characteristic value of the safety capacitor is determined according to the capacitance value, the impedance characteristic value is used for analyzing the inductance value needed by the concerned frequency point under the topological cluster, and a common-mode topological structure is determined; selecting a magnetic core based on a magnetic core selection rule, determining the number of turns required by the inductor corresponding to the concerned frequency point and the total differential mode capacity according to the magnetic core information, and selecting a differential mode optimal topology by using the total differential mode capacity; and determining a filter optimization scheme according to the common-mode and differential-mode optimal topology and the impedance characteristic value. According to the method, quantitative accurate optimization topology and parameter optimization design functions of the filter are realized.

The embodiment of the invention relates to the technical field of information security, and discloses a task proving method and device, a task execution method and equipment and a storage medium, and the task proving method comprises the steps: segmenting a to-be-executed calculation task into a plurality of sub-tasks; selecting at least one sub-target task from the plurality of sub-tasks based on a task selection rule; based on the at least one sub-target task, generating at least one arithmetic circuit, at least one proof key and at least one verification key corresponding to the at least one sub-target task; sending the to-be-executed calculation task, the at least one proof key and the at least one arithmetic circuit to a second server, and receiving a calculation result and a proof result of the second server; and proving the validity of the calculation task to be executed based on the at least one verification key, the at least one arithmetic circuit, the proving result and the calculation result. According to the task certification method disclosed by the invention, the problem that a lot of time needs to be consumed in the certification generation and verification process is solved, so that the efficiency of verifying the calculation task is relatively high.

A method of discovering services provided by a network function, NF, in a Service Based Architecture, SBA, based telecommunication network, wherein said network function is registered, in a Network Repository Function, NRF, comprised by said telecommunication network, using a service name, a service address and a selection rule, wherein said selection rule defines a further service address and a precondition for applying said selection rule, said method comprising the steps of receiving, by said NRF, a discovery request, from a Network Function, NF, consumer, wherein said discovery request comprises said service name, determining, by said NRF, that said selection rule applies by determining that said precondition is met based on said received discovery request and transmitting, by said NRF, to said NF consumer, a discovery response, wherein said discovery response comprises said further service address.

The invention relates to the technical field of industrial scheduling, and discloses a flexible job shop self-organizing scheduling-oriented multi-target dual hyper-heuristic method, which comprises the following steps of: generating a process selection rule and an interval selection rule by utilizing a genetic programming rule, and generating a rule set; based on a deep reinforcement learning method, a dynamic decision strategy is constructed in combination with a rule set, and multi-step action sequence optimization is carried out when self-organizing scheduling is triggered; and generating an instance through random combination of parameter indexes of a predetermined dynamic event, and calculating a performance index according to the generated instance to realize feasibility verification. Through a dynamic collaborative optimization mechanism of self-organizing scheduling, an autonomous decision closed loop can be realized under multiple disturbances such as equipment failure, processing fluctuation, new order insertion and the like, and the self-healing capability, response speed and anti-interference toughness of a production system in a dynamic environment are remarkably improved; and an intelligent decision-making scheme with an autonomous evolution capability is provided for a complex scheduling problem in an intelligent manufacturing scene.

The application relates to the technical field of power station dispatching, in particular to a distributed power station response strategy generation method and system, which comprises the following steps: constructing a plurality of state groups, and configuring corresponding classification rules of the state groups and corresponding rotation rules between the state groups; the state groups comprise a dispatching group, a preparation group and an idle group; obtaining site information of each access site in each platform, and matching the site information with the classification rules to put each site into a corresponding state group; obtaining real-time site information changes of each site, and adjusting the state group of each site based on the rotation rules; obtaining demand information corresponding to dispatching demand and / or replacement demand, judging the priority of the site in the preparation group, and electing the site meeting the demand information and the priority requirement as a response site based on a site selection rule and transferring the response site into the dispatching group. The application has the effect of improving the response capability of the distributed energy storage aggregation platform to the dispatching demand.

Embodiments of the present disclosure provide a solution for a cross frequency resource scheduling. In a solution, a terminal device receives, from a network device, configuration information; receives, from the network device, control information on a first frequency resource, the control information comprising an indicator indicating the second frequency resource; and performs one of the following: communicating with the network device on the second frequency resource by using at least one TCI state, wherein the at least one TCI state is selected from a set of activated TCI states associated with the second frequency resource based at least in part on one of the following: a TCI state selection field comprised in the control information, or a default TCI state selection rule, or ignoring the TCI state selection field comprised in the control information.

In a method for trajectory adjustment of a biaxial Lissajin microscanner, a drive device for the microscanner is controlled in the sense of adjustment in such a way that, in each of a plurality of consecutive time periods, the drive frequencies of the two axes form a frequency pair for the respective duration thereof, and the respective corresponding pairs of frequencies of the directly contiguous time periods differ at least with respect to at least one frequency. For a corresponding time period, according to a value of at least one physical parameter which is detected by a sensing technology and has a dependency relationship with the corresponding resonant frequency relative to the at least one vibration axis, a frequency pair corresponding to the time period is selected from a predetermined discrete set of a plurality of different frequency pairs according to a selection rule, so that the frequency pair corresponding to the time period is selected relative to the same vibration axis. The selected frequency pair has a corresponding frequency deviation on at least one of the two frequencies thereof from the resonant frequency corresponding to the value of the detected at least one variable according to the dependency.

An embodiment of a method implemented by a wireless transmit-receive unit (WTRU) includes: receiving information related to a secondary mobile network (SMN) and including an indication of SMN selection rules from a primary mobile network (PMN) registered by the WTRU; selecting an SMN in response to the trigger and an SMN selection rule; registering to the selected SMN; and requesting establishment of a multi-access protocol data unit (MA-PDU) session having a DualSteer functionality and having one access branch on the registered SMN and another access branch on the registered PMN.

The invention provides a software process automatic arrangement method and device and a medium, and relates to the field of software development, the method comprises the following steps: obtaining a plurality of components, corresponding input parameters and output parameters of each component, and an initial parameter and a result parameter of a target process, and setting an initial value of a known parameter as the initial parameter; and circularly selecting a component meeting a preset component selection rule from the plurality of components as a target component, serially adding the target component to a component serial sequence, adding an output parameter of the target component to a known parameter, and terminating circulation until a preset circulation ending condition is met, obtaining a component serial sequence after circular updating; and according to the parameter dependency relationship, carrying out parallel adjustment on the undertaking relationship between the components in the component serial sequence to obtain a component serial parallel sequence, and taking the obtained component serial parallel sequence as an arrangement result corresponding to the target flow.

The application discloses a kind of methods, devices and equipment and storage medium for the synchronization of anti-replay counter of controller area network.The method comprises: constructing data block set based on the high part of anti-replay counter, including multiple data blocks with the same length in the data block set;Based on the CAN communication identifier of the controller area network CAN message to be sent and the low part of the anti-replay counter, use the preset data block selection rule to select one or more data blocks from the data block set as the coded data block;Encoding the coded data block to obtain the encoding fragment;The length of the encoding fragment is the same as the length of each data block;Fill the encoding fragment into the idle bit in the CAN message to be sent, and send the filled CAN message to the receiving end.The method sends data using idle bit, which can reduce bus burden and improve resource utilization.

The application provides a very low frequency atomic magnetometer environment interference suppression method based on polarization selection reception, wherein a precession main magnetic field B e and -B e are respectively applied by a main magnetic field coil in z direction and -z direction in front and back two regions of a gas chamber e and -B e regions are detected by using detection laser in x direction; external very low frequency signals are detected by interaction with atoms polarized in z direction to make the atoms produce precession signals in xOy plane, so that the signals are detected by light detection; when the external signals are linear polarization, according to the selection rule of angular momentum conservation, the precession signals of atoms in B e and -B e regions are offset, so that the system does not respond to linear polarization signals; for circular polarization signals, only atoms in B e or -B e region have precession signals, so that the detection of circular polarization signals is realized. The technical scheme of the application is applied to solve the technical problem of environmental magnetic noise interference of a very low frequency atomic magnetometer in an actual application scene in the prior art.

The present invention provides a parametric data modeling design method and system for a bus duct production process, the method comprising establishing a bus duct product library according to the product categories of the bus duct; constructing a parametric model for each product unit in the product library; establishing a selection rule library based on the parametric models of each product unit under different product categories; using the selection rule library to screen, filter, and perform matching calculations on the bus duct product list to find a unique matching parametric model; substituting various parameters in the bus duct product list into the parametric model in the form of variable values for calculation to obtain the bill of materials and process parameters of the bus duct product unit; and generating a two-dimensional engineering drawing of a self-made part based on the bill of materials and process parameters in combination with the corresponding drawing model. The present invention unlocks the automated design capabilities of bus duct products of different categories, specifications, and quantities through parametric assignment, significantly reducing design time and errors, promoting a smooth production process, and improving overall operational efficiency.

The invention discloses a track fault detection method and system, and the method comprises the steps: dividing a continuous track into at least one to-be-detected track, and obtaining a to-be-detected track image of the at least one to-be-detected track; performing clustering processing on the to-be-detected track images according to a preset clustering rule to obtain at least one to-be-detected track image set; selecting a target to-be-detected track image from a certain to-be-detected track image set by adopting a preset selection rule, and preprocessing the target to-be-detected track image to obtain a target image; performing edge extraction on the target image to obtain a track edge image; and performing fault detection on the track edge image through a preset model to obtain a fault detection result corresponding to the to-be-detected track image. The detection frequency of to-be-detected tracks with the same characteristics can be reduced, so that the track fault detection efficiency can be effectively improved.

The application discloses a kind of ship design multi-criteria decision-making method selection method and system. By generalizing the characteristics of general MCDM problem and defining the characteristics of common MCDM method, and establishing the matching mapping relationship between the characteristics of general MCDM problem in problem domain and the characteristics of common MCDM method in method domain, a generalized MCDM method preliminary selection rule is generated, and a preliminary applicable MCDM method / set under a specific decision situation is obtained. On this basis, a generalized MCDM method applicability criterion and the corresponding evaluation model are established. Following the principle of combining qualitative and quantitative analysis, the actual application effect of the selected MCDM method is compared comprehensively, and the optimal MCDM method under the specific decision situation is selected accordingly. The two-step ship design MCDM method selection strategy and system of preliminary selection and optimization can effectively ensure the applicability of the preliminary selected MCDM method and the superiority of the optimized MCDM method.

This invention proposes a method and system for diagnosing DAS wellbore flow stability based on the square coherence coefficient distribution, belonging to the field of fluid acoustics technology. The method includes: acquiring raw time-series acoustic signals related to wellbore flow using DAS to obtain multi-channel raw time-series DAS data; preprocessing the data and segmenting it according to sliding time windows to obtain multiple time window samples; determining at least one reference channel according to a preset reference channel selection rule; calculating the square coherence coefficient between the reference channel and channels at various spatial locations within the target well section, and constructing a time-space-frequency distribution; extracting high-coherence regions and one or more stability features within the target frequency band; constructing a flow stability index based on the features and performing graded flow stability diagnosis; this invention also discloses a system and storage medium for executing the method, applicable to wellbore or pipeline flow stability diagnosis and abnormal section identification scenarios.

A composite control strategy of a Vienna power factor correction circuit comprises an active-disturbance-rejection voltage control outer loop and an optimized switch sequence model prediction current control inner loop, the active-disturbance-rejection voltage control outer loop designs LTD to arrange a transition process for an output voltage reference value square value to realize rapid tracking, and designs LESO to observe output and total disturbance in real time. An LESF is designed to realize zero static error adjustment through a linear error feedback rate, a switching sequence model is optimized to predict a current control inner ring, redundant vector preprocessing is adopted, a candidate redundant switching sequence is reduced by half according to a redundant vector selection rule, the calculated amount is reduced, a modulation signal is sent to an SVPWM modulation unit, a PWM signal is generated, a switching tube of a main power circuit is driven, and the switching tube of the main power circuit is controlled. And closed-loop control is realized.

The invention discloses a continuous data identifier allocation method, which relates to the technical field of data identifier allocation, and comprises the following steps: S1, determining a preset data identifier bit number, a reserved data identifier, a preset data identifier coding rule, a preset data identifier allocation rule and a preset data identifier bit selection rule; s2, constructing a data identifier management module according to a preset data identifier bit number, a coding rule of the preset data identifier bit number, a preset data identifier distribution rule and a preset data identifier bit selection rule; s3, acquiring a data identifier distribution request of the user; according to the method and the device, the data identification bits with the relevance are given to the data with the relevance, when certain data needs to be called, the data associated with the called data can be called only according to the data identification bits, the range of the called data is expanded, the range of subsequent data analysis is further expanded, and the data analysis efficiency is improved. According to the method, the data analysis precision is indirectly improved, in addition, the data calling speed is increased, and the data calling time is shortened.

A system and method for a multi-stage approach for creating topic models is presented. The method includes applying a first stage topic model to textual data, wherein the first stage topic model is trained to discover a first plurality of topics and distributions of words in each topic of the first plurality of topics from the textual data; generating at least one seeded word for a subset of topics of the first plurality of topics, wherein the at least one seeded word is determined based on a plurality of selection rules and the distributions of words in the subset of topics discovered in the first stage topic model; and creating a second stage topic model by feeding the generated at least one seeded word to direct identification of the subset of topics of the first plurality of topics.

The invention discloses a non-blind area island detection method and system for a new energy networking system, and the method comprises the following steps: building a coherence dual-frequency point optimization mechanism, and formulating a dual-frequency point selection rule based on an impedance angle change rate consistency criterion; enhanced injection of double-frequency composite disturbance is realized; through symmetrical component decoupling and spectral analysis, constructing a system equivalent impedance model in grid-connected and island states, and completing impedance state feature extraction; designing an island characteristic quantity calculation model for double-frequency impedance ratio calculation, calculating a double-frequency harmonic impedance module value, constructing a double-frequency impedance ratio criterion factor with a common-mode rejection characteristic, and eliminating an inherent error of a measurement system through a ratio relation; a judgment criterion of double-frequency impedance ratio change in grid-connected and island states is formulated, an action threshold is determined through grid-connected state double-frequency impedance ratio statistical characteristics based on an operation condition self-adaptive dynamic threshold setting method, a multi-cycle confirmed island detection judgment process is established, and island detection of the new energy networking system is realized.

The present invention discloses a Byzantine fault-tolerant consensus method and system for supply chain traceability, including master node selection rules, dynamic node entry and exit network processes, and optimized protocol mechanisms. The master node selection rules are based on the consistent hashing algorithm and the hash value of the previous block and combined with the average load concept to achieve random and fair selection of master nodes; the dynamic node entry and exit network process adds the concepts of network configuration table and configuration change transaction to achieve the dynamic nature of the network; the optimized protocol mechanism is used to improve the existing protocol mechanism of the PBFT algorithm, mainly including refining the view replacement protocol, proposing a new state synchronization protocol, and optimizing the consistency protocol under no abnormal conditions. Compared with the original PBFT algorithm, the Byzantine fault-tolerant consensus method provided by the present invention has the advantages of random selection of master nodes, support for dynamic networks, low communication complexity, etc., and is particularly suitable for supply chain traceability scenarios with complex members, strong openness, and large node scale.

The application discloses a method, a terminal and a network side device for transmitting UCI on a PUSCH, and is used for solving the problem of how to select one PUSCH from multiple PUSCHs with different priorities to carry UCI on a PUCCH when the multiple PUSCHs with different priorities and the PUCCH exist time domain overlap. It is determined that a PUCCH carrying UCI and multiple PUSCHs with different physical layer priorities exist time domain resource overlap; one PUSCH is selected from the multiple PUSCHs according to a predetermined selection rule, or a PUSCH with the same physical layer priority as the PUCCH is selected from the multiple PUSCHs; and the UCI is transmitted through the selected PUSCH.

Embodiments of the present specification provide a link generation method and device, wherein the link generation method comprises calling a third-party platform, recording calling data generated by calling the third-party platform to a calling log, and preprocessing calling data of the calling log; performing feature labeling on the preprocessed calling data to obtain initial features of the calling data, and selecting target features from the initial features of the calling data based on a preset selection rule; and determining a calling link of the third-party platform based on the initial features and the target features.

To provide an apparatus and a method for encoding and decoding a video coding block of a video signal.SOLUTION: A method for deriving a motion vector (MV) is for deriving the MV for a coding block. In particular, when the coding block is enabled for a geometric partition merge mode, a merge candidate list is partitioned into two geometric partitions. The merge candidate list generation comprises deriving spatial merge candidates from neighboring coding units; after the derivation of the candidates, deriving temporal motion vector predictions (MVPs); and then deriving a uni-prediction MV as a motion vector of each geometric partition on the basis of the merge candidate list including uni-prediction MVs and / or bi-prediction MVs. The derivation of the uni-directional MVs is based on the merge candidate list or a uni-directional MV selection rule. Then, the geometric partition of the coding block is predicted on the basis of, at least the uni-prediction MVs to obtain a predicted value of the geometric partition.SELECTED DRAWING: Figure 11

To provide a successor setting system which can set a successor, without setting the successor in advance, even when a manager of IT infrastructure management information is absent without takeover.SOLUTION: A successor setting system 20 comprises: a successor selection rule management table 35 in which a successor selection rule used for selecting a successor of a manager is managed, when the manager of IT infrastructure management information who manages a resource and a user who operates the resource cannot continue the management of the IT infrastructure management information; and an activity history monitoring unit 21 which monitors an activity history of the user with respect to the resource, applies an evaluation result obtained by evaluating the activity history for each user to a successor selection rule to select the user who becomes the successor, and sets the selected user as the successor.SELECTED DRAWING: Figure 2