18results about How to "Adapt to dynamic changes" patented technology

The invention discloses an electric meter intelligent communication detection method and system based on a power line carrier, and relates to the technical field of electric meter communication detection, and the method comprises the steps: collecting the communication data of an electric meter at different time periods, inputting an electric meter communication state dynamic sensing model, analyzing features, and obtaining an initial evaluation result; channel characteristic parameters are calculated by using a carrier channel characteristic dynamic estimation algorithm based on the result, and the channel characteristic parameters are input into a power carrier signal demodulation optimization algorithm to generate an optimized demodulation scheme; signals are demodulated and data are verified according to the scheme, related results are uploaded to an electricity meter communication performance optimization management platform, and the platform evaluates performance and generates optimization suggestions and fault early warning. The system comprises a data acquisition unit, a state analysis unit, a channel calculation unit, a demodulation optimization unit, a data processing unit and a performance management unit which operate cooperatively. The communication state can be dynamically sensed, the channel characteristics can be accurately estimated, the demodulation process can be optimized, the integrated management of the communication performance can be realized, and the accuracy and reliability of the electric meter communication can be improved.

This invention discloses a comprehensive optimization method and system for green travel routes in multi-agent decision-making. The method includes: constructing a travel-specific spatiotemporal environment, comprising a static environment describing the topological relationships of traffic infrastructure and individual travel plans; a dynamic environment describing the time-varying characteristics of traffic states and supporting dynamic interaction and feedback with agent decision results; and a user-perceived environment describing the probability distribution of individuals' perceptions of travel parameters such as carbon emissions, costs, and time consumption under different travel mode categories; performing comprehensive route optimization based on the environment, calculating the perception weight of a certain type of traveler to a certain topological edge at the current time according to the current moment, the current traveler's category, the attributes of the road segment to be evaluated, and the accumulated amount of travel states generated, and searching for the optimal path in the time-varying topological network with the objective of minimizing the sum of perception weights from the start point to the destination; and the agent moving according to the optimal path and updating the traffic state parameters in the dynamic environment. This invention makes the green travel route recommendation results more closely match the actual choice preferences and heterogeneous decision-making needs of different users.

The application discloses a double-embedding model hybrid training method, system, device and storage medium, which is applied to the technical field of recommendation systems and comprises the following steps: determining the routing parameters of each classification feature based on the historical access information of the classification features in a training data set; selecting a corresponding embedding table for the classification features input currently according to the routing parameters; wherein the embedding table comprises a first embedding table and a second embedding table; extracting the embedding vector corresponding to the classification features from the selected embedding table, and performing forward calculation and loss calculation of the model based on the embedding vector; and updating the parameters of the first embedding table, the second embedding table and a downstream model according to the result of the loss calculation. The application simulates the embedding hybrid use mode in reasoning in the training stage, enhances the collaborative ability of the two embedding tables, and improves the performance and robustness of the model in a real reasoning scene.

The invention discloses a power distribution network operation method and device based on reconstruction and cluster collaborative optimization, electronic equipment and a storage medium, and belongs to the field of power grid operation optimization, and the method comprises the steps: obtaining the initial network topology, photovoltaic output, branch parameters and load data of a power distribution network, and constructing a network reconstruction model based on the branch parameters and loads. And constructing a collaborative optimization model according to the initial data. And carrying out iterative optimization operation until the relative deviation is smaller than a convergence threshold value, and obtaining the optimal network topology and photovoltaic output. In each round of optimization, the network reconstruction model is solved according to the current photovoltaic output, and the current optimal network topology is generated; and carrying out cluster division on the photovoltaic power stations, and solving the collaborative optimization model to obtain the optimal power output of each photovoltaic power station. Calculating a difference value of the whole network operation indexes, generating a relative deviation, and judging whether the relative deviation is converged or not; by implementing the method, the problem that the optimization result is caught in local optimum in the prior art can be solved.

The invention discloses an intelligent question and answer result comparison and traceability method and system for power marketing, and relates to the technical field of intelligent question and answer, and the method comprises the steps: S1, generating a plurality of intelligent responses according to the consultation content; s2, identifying key information associated with the power marketing business according to the intelligent response and performing information comparison; s3, querying a power marketing background business system in real time and performing conflict judgment according to the key information after comparison is completed, and obtaining target business data directly associated with the key information; s4, in the generated response, embedding a traceability link pointing to the target business data based on a traceability mechanism, and performing data traceability according to the traceability link; according to the method, specific business data and calculation logic can be traced, the credibility and transparency of the question and answer result are enhanced, and the reliability of the answer result is improved.

The invention relates to the technical field of cloud computing and data center operation and maintenance, and provides a data center resource scheduling optimization method based on artificial intelligence, and the method comprises the following steps: collecting multi-dimensional data; preprocessing the data; constructing and training a hybrid intelligent scheduling model; and real-time scheduling decision generation, scheduling execution and closed-loop optimization are carried out. According to the artificial intelligence-based hybrid intelligent model-driven data center resource scheduling optimization method provided by the invention, through multi-dimensional data acquisition, feature engineering optimization, hybrid intelligent model construction and closed-loop iterative optimization, multi-target collaborative optimization of a resource utilization rate, an SLA standard-reaching rate and energy consumption is realized; and the intelligent level and the dynamic adaptability of resource scheduling of the data center are improved.

The invention discloses a system performance simulation verification method based on information data analysis, and relates to the technical field of system performance testing and simulation. The system performance simulation verification method based on information data analysis comprises the six steps of information data collection, preprocessing, simulation model construction, model calibration, performance simulation verification and result analysis, the real-time collection and historical data are combined, a high-precision simulation model is constructed, performance verification is carried out in various load scenes, and the system performance simulation verification efficiency is improved. And finally generating a verification report containing performance bottleneck diagnosis and optimization suggestions. According to the system performance simulation verification method based on information data analysis, the accuracy and comprehensiveness of system performance simulation can be effectively improved, the actual test cost is reduced, and a scientific basis is provided for system optimization.

This application provides a data processing method for the printing process of a dynamic thoracolumbar spine brace. The method obtains a first human model of the target object's thoracolumbar spine region in a retracted state and a second human model in a expanded state. Then, it determines characteristic shaping surfaces based on the first and second human models, and generates a solid model of the corresponding thoracolumbar spine brace based on these surfaces. Finally, it uses a 3D printer to generate the thoracolumbar spine brace from the solid model, better adapting to the morphological and dynamic changes of the thoracolumbar spine region. This ensures support for the lumbar spine region while further improving user comfort.

This application discloses an online identification method and system for pipe resistance coefficient based on an improved recursive least squares method, belonging to the technical field of heating systems. The method includes: collecting operating data of the heating pipe network; constructing a resistance coefficient identification model based on the operating data; using an improved recursive least squares method to identify the resistance coefficient online based on the identification model; evaluating the reliability of the identification results; and updating the verified resistance coefficients to the intelligent valve control system in real time. The method boasts strong real-time performance, enabling online real-time updates of the resistance coefficient to adapt to dynamic changes in the pipe network. The improved RLS algorithm enhances identification accuracy, with a measured error of <5%. No special testing conditions are required, and it does not affect the normal operation of the system. A variable forgetting factor design allows the algorithm to adapt to different operating states. It is suitable for real-time operation in embedded systems and has been verified in actual projects.

The invention provides an inter-harmonic traceability method and system based on an electric energy meter and micro-synchronous phasor measurement units, and relates to the technical field of electric energy quality monitoring, and the method comprises the steps: at the beginning, all micro-synchronous phasor measurement units (mu PMUs) collect basic electric parameter data and upload the basic electric parameter data to a master station system; the master station system reconstructs a complete layered topological structure based on the basic electric parameter data; after topology identification is completed, the master station system only issues an inter-harmonic detection analysis instruction to the muPMU of the grid-connected point PCC, and other muPMUs enter a basic monitoring mode; when the mu PMU of the PCC of the grid-connected point detects that the inter-harmonic content exceeds a first preset threshold value, inter-harmonic over-limit alarm is given to a master station system; and after receiving the inter-harmonic overrun alarm, the master station system issues an inter-harmonic detection analysis instruction to the [mu] PMU related to the inter-harmonic overrun alarm, and performs inter-harmonic overrun traceability to the tail end of the node in sequence according to the hierarchical relationship of the complete hierarchical topological structure. According to the scheme, the engineering practicability is high, and accurate positioning of the new energy harmonic source point can be realized.

The application provides a hierarchical collaborative optimization and settlement method for large-scale industrial demand response, relates to the technical field of power systems, and comprises the following steps: dividing large-scale industrial demand response resources into multiple levels and constructing an optimization model; decomposing a global optimization problem into local sub-problems, defining consistent variable constraints for global consistency, and generating scheduling instructions through iterative calculation; obtaining actual response data in response to the scheduling instructions, performing hash operation and digital signature processing on the actual response data to generate a signed digest; verifying the signed digest by using a smart contract, executing real-time settlement after verification to obtain real-time settlement data, and summarizing to obtain periodic settlement data; calculating performance indicators according to the scheduling instructions and the actual response data, and performing numerical correction on the real-time settlement data and the periodic settlement data by using the performance indicators to obtain adjusted settlement data. The application realizes fast scheduling and convergence of large-scale resources, and effectively improves the enthusiasm and fairness of users participating in scheduling.

The application discloses an agent collaborative optimization data center management system based on a knowledge graph driver and relates to the technical field of data center management, and specifically comprises the following modules: a modeling and entity management module, a cross-region global scheduling optimization module, an agent game negotiation optimization module, an agent trust management module, a game negotiation conflict identification module, an inference evidence management module and a cross-region consistency verification module; the application establishes a complete knowledge graph model, realizes systematic modeling of resource attributes, constraints, historical decisions and strategy preferences, provides a unified data basis for negotiation among multiple agents, effectively solves suboptimal solution problems caused by information asymmetry, adopts a hierarchical inference mechanism, combines global-region-node three-level inference and multi-round game negotiation, realizes recursive optimization from the global to the local, effectively reduces inference complexity and improves negotiation efficiency.

A core network resource dynamic scheduling method, apparatus and device, and a storage medium are applied to the field of communication network optimization, and the method comprises the steps of generating a dynamic scheduling causal graph of core network resources according to a core network resource scheduling field knowledge base and obtained core network reference data; performing incremental causal distillation training according to the dynamic scheduling causal graph to generate a lightweight causal model; and performing real-time reasoning according to the lightweight causal model to generate a scheduling decision and an interpretable resource scheduling report. According to the method, the structured business causal relationship can be efficiently extracted, and the operation and maintenance efficiency and the system reliability are improved. Meanwhile, the generation time of a scheduling strategy can be effectively shortened, real-time reasoning is achieved, flexible and accurate resource scheduling is achieved, and resources can be dynamically allocated according to actual requirements. And clearer decision basis and explanation can be provided for operation and maintenance personnel, and the operation and maintenance personnel are supported to better understand system behaviors and quickly position problems.

The present application relates to the technical field of criminal case data analysis and early warning, in particular to a multi-technology coordinated criminal case intelligent early warning system and method fusing pre-training large model customization adaptation, dynamic weighted clustering and semantic vector retrieval, belonging to the cross technical field of judicial big data and artificial intelligence, through the coordinated technical path of "large model label extraction-weighted clustering-vector deduplication", a full-process intelligent system of "data input-intelligent analysis-accurate early warning-feedback iteration" applicable to judicial case analysis and processing scenes is constructed, not only effectively solving the core problems of low efficiency and early warning redundancy under the traditional manual analysis mode, but also completely solving the many common problems existing in the current technical system of criminal case analysis and early warning.

The invention discloses a canal system optimization water distribution method, a medium, equipment and a product, and relates to the technical field of agricultural irrigation. The method comprises the following steps: taking the water distribution starting time, the water distribution duration and the water transmission and distribution flow of all levels of canal systems as decision variables; taking minimization of the total water shortage amount of crops in an irrigation area, the excessive irrigation water amount of the crops in the irrigation area and the water transportation and distribution loss water amount as objective functions, and taking a water diversion flow constraint, a channel water transportation capacity constraint, an irrigation time constraint and a water balance constraint as constraint conditions to construct a channel system optimization water distribution model; and solving the canal system optimization water distribution model by adopting DCNSGAIII. The model provided by the invention can adapt to dynamically changing incoming water flow and effectively process complex constraints.

The application relates to a kind of automobile injection molding piece zero-defect closed-loop control method and system based on digital twinning, relate to the high-precision intelligent manufacturing technical field of automobile injection molding piece, comprising: initialization and modeling stage, based on injection production data calibration mechanism model and train LSTM compensation model, construct digital twin; Real-time synchronization and control stage, using model predictive control MPC algorithm, based on real-time driven digital twin, the process parameters of future mode are rolled optimization and issued;Online learning and evolution stage, according to the actual and predicted size deviation of each mode, dynamically trigger the incremental training of LSTM model and the periodic fine-tuning of mechanism model;Abnormal self-healing stage, when size is out of tolerance, predicted defect or equipment anomaly, execute hierarchical parameter optimization, process switching or shutdown verification strategy.The advantage lies in that the production of automobile injection molding piece is changed from "after detection" to "before prediction and during regulation", and the key dimension qualified rate is stably improved to more than 99.5%.

The application relates to a UAV inspection path planning and optimization system and method, and relates to the technical field of visual detection. The system comprises a data acquisition module for acquiring trajectory data of a plurality of construction safety helmets and trajectory data of a plurality of inspection safety helmets; a site modeling module for collecting real-time modeling data of a construction site based on the trajectory data of the plurality of construction safety helmets, and constructing a real-time three-dimensional model of the construction site; a path constraint module for inputting a constraint condition set of a UAV inspection path; and a path optimization module for generating an optimal UAV inspection path based on the real-time three-dimensional model of the construction site, the constraint condition set of the UAV inspection path, the trajectory data of the plurality of construction safety helmets and the trajectory data of the plurality of inspection safety helmets. The application has the advantages of improving the comprehensiveness and safety of UAV inspection path planning.

The invention discloses a noise source positioning method and system based on multi-integral-surface acoustic monitoring. The method comprises the following steps: arranging a microphone array on an outermost integral surface, converting a sound pressure signal into a time-frequency domain through short-time Fourier transform, and reconstructing a whole sound field at one time by using a regularization equivalent source method; and then the active sound intensity on the multi-layer nested integral surface is calculated in sequence, and the net sound power is solved, so that the normalized sound power divergence of the adjacent shell layers is obtained. And performing time-frequency accumulation and peak value detection on the divergence spectrum to quickly lock a shell layer where a sound source is located, and determining a three-dimensional coordinate in the shell layer according to an equivalent source energy density extreme value. The device comprises an array module, an acquisition module, a time-frequency conversion module, a reconstruction module, a divergence calculation module and a peak value detection and positioning module, and can complete noise source visualization in real time. The method has the advantages of high spatial resolution, strong noise immunity and millisecond processing speed, and is suitable for online noise source identification and fault diagnosis of vehicles, aerospace and industrial equipment.