23results about How to "Achieve optimal configuration" patented technology

The invention relates to the technical field of copper pipe heat dissipation, in particular to a micro-channel heat dissipation device based on a copper pipe structure, which comprises a heat dissipation substrate, a copper pipe type heat dissipation channel and a liquid cooling circulation system, the copper pipe type heat dissipation channel is composed of a plurality of plastic copper pipes and replaces a traditional micro-channel or vapor chamber structure. The copper pipe is embedded or fixed in the heat dissipation substrate or on the surface of the heat dissipation substrate, cooling liquid circulates in the copper pipe, and efficient heat dissipation is achieved through the combined action of forced convection heat exchange and heat transfer; the copper pipe has good plasticity and can be subjected to three-dimensional bending forming according to heat source distribution and spatial layout, through the synergistic effect of forced convection and phase change heat transfer, the heat transfer efficiency is improved, particularly, extremely high local heat flow density can be coped, the chip is effectively prevented from being overheated, and the heat transfer efficiency is improved. The heat dissipation channel can be bent and formed in a three-dimensional space according to heat source distribution, accurate matching with the heat source form is achieved, limitation of traditional plane heat dissipation is broken through, and optimal configuration of heat dissipation capacity and heat flux density is achieved.

The invention provides a wave position dynamic transfer method, system and device based on inter-satellite linkage and a medium, and the method is executed by an overload satellite and comprises the steps: judging whether a self load is overloaded or not; if the load is judged to be overloaded, selecting a to-be-transferred wave position from self-managed wave positions; acquiring state information of the adjacent satellites through inter-satellite interaction with the adjacent satellites; based on the obtained state information, determining a target satellite capable of bearing a to-be-transferred wave position from adjacent satellites having coverage overlapping with the target satellite; negotiating with the target satellite through an inter-satellite link to confirm beam position transfer, and triggering the target satellite to adjust the beam to cover the to-be-transferred beam position; and after negotiation confirmation, controlling the user equipment in the to-be-transferred wave position to be switched to the target satellite, and releasing the wave position resources. By adopting the method, the communication delay of the user equipment can be reduced, the throughput of the user equipment and the constellation resource utilization rate can be improved, and the service quality and user experience of a satellite communication system can be comprehensively optimized.

The invention provides a transmission optical path routing planning method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an optical path planning request; based on the endpoint information and pre-stored optical network resource data, generating a plurality of candidate optical paths meeting connectivity requirements among service endpoints; constructing a multi-target fitness function according to an optimization target in the routing strategy, and determining a fitness value of each candidate light path based on the multi-target fitness function; and selecting a target light path from the plurality of candidate light paths. According to the method, the multi-target fitness function is constructed based on the optimization targets in the routing strategy, and the fitness value of each candidate light path is determined based on the multi-target fitness function, so that the comprehensive performance of the plurality of candidate light paths under the plurality of mutually restricted optimization targets is objectively evaluated; therefore, the optimal target light path can be selected from the plurality of candidate light paths based on the fitness value, and the automation level and decision-making efficiency of light path planning are improved.

The invention relates to the technical field of beverage preparation, in particular to a processing method of a functional beverage containing embryo elements, which comprises the following steps: separating corn germs from corn kernels, drying the corn germs, and performing microwave treatment at preset microwave power to obtain inactivated corn germs; when it is judged that preparation of the inactivated corn germs does not meet a preset standard according to the oxidation risk characterization value, preset microwave power is increased or the inactivated corn germs are abandoned; the method comprises the following steps: crushing and breaking walls of inactivated corn germs meeting preset standards to obtain germ powder, and performing enzymolysis treatment on the germ powder to obtain a corn embryo base solution; when it is judged that the preparation of the embryo base solution does not conform to a preset standard according to the curve goodness of fit, the reason that the preparation of the embryo base solution does not conform to the preset standard is determined according to the absorbance; and diluting, homogenizing and sterilizing the corn embryo base solution to prepare the functional beverage containing the embryo. The processing efficiency of the functional beverage is improved.

According to the method, the complexity of a remote rural distribution environment is considered, the high dispersion characteristic of order space-time distribution is considered, the differentiation characteristic of multi-vehicle-type transport capacity resources is also considered, and the order combination distribution method based on space-time clustering in a rural common distribution mode is provided. In the first stage, customer geographic positions and order time window constraints are comprehensively considered, reachability-guaranteed clustering is formed to realize order combination, and an initial path feasible solution is constructed based on a space-time clustering result; in the second stage, a simulated annealing framework is designed to be fused into adaptive large neighborhood search, a clustering result is dynamically adjusted according to multi-vehicle-type differential time-space characteristics, and an initial solution is improved; on-demand combination of orders, accurate path planning and multi-vehicle collaborative distribution are realized, and logistics enterprises are helped to cope with distribution challenges of scattered orders, fuzzy time windows and complex road networks in remote rural areas with lower cost on the premise of ensuring distribution timeliness and service quality.

The invention relates to the technical field of bird repelling equipment and image recognition, and particularly discloses an active positioning bird repelling system based on vision and radar fusion. The system comprises a multi-sensor fusion sensing module, a target cooperative processing and positioning module, a dynamic strategy generation module and a multi-mode bird repelling execution module. Through fusion processing of millimeter-wave radar and double-spectrum vision, accurate identification and three-dimensional positioning of a bird target are realized, an optimal bird repelling strategy is dynamically generated based on threat assessment and environmental perception, and directional sound waves and laser are controlled to execute accurate repelling, so that the bird repelling efficiency is improved, and environmental interference is reduced.

The invention discloses a method and a device for guiding and optimizing data traffic across virtual network domains. The method comprises the following steps: edge gateway equipment of a first communication branch receives data traffic sent from the first communication branch to a second communication branch; according to the invention, through the architecture of combining centralized strategy control and distributed data forwarding, the single-point fault risk in the traditional scheme is eliminated. The data transmission path is directly established between the edge gateway devices, the performance bottleneck caused by the fact that data flow passes through a single agent node is avoided, when any transmission path breaks down, the system can be automatically switched to the standby path within millisecond time, and the reliability and continuity of enterprise cross-branch network communication are remarkably improved.

The application discloses an omnidirectional channel prediction and dynamic coding joint decision method, system and medium, belonging to the multimedia field, and the method is applied to an FTTR gateway and comprises the following steps: determining the communication connection type of the FTTR gateway, a screened terminal and a terminal to be screened according to the IP addresses of the terminal to be screened and the terminal to be screened; determining a first available bandwidth of a video stream flowing from the FTTR gateway to the terminal to be screened and a second available bandwidth of the video stream flowing from the terminal to be screened to the FTTR gateway; determining the smaller value in the first available bandwidth and the second available bandwidth as a maximum code rate B_max available for the screen projection, and notifying the terminal to be screened of the B_max to trigger the terminal to be screened to determine target video coding parameters. The method can provide highly stable bandwidth guarantee for the screen projection service.

The invention discloses an intelligent packing decision-making system based on multi-modal data fusion and deep reinforcement learning, which relates to the technical field of intelligent logistics and comprises a cloud decision-making layer deployed in a regional computing center, an edge execution layer arranged in each sorting center and an equipment sensing layer integrated with an IoT (Internet of Things) sensor, the system further comprises an intelligent analysis decision module, a dynamic resource scheduling and elastic capacity expansion module, a digital twinborn verification module and a self-adaptive control closed-loop management module which run on a cloud decision layer. According to the intelligent packing decision-making system provided by the invention, multi-dimensional information such as a time sequence, a spatial topology, an equipment state and package vision is comprehensively considered through a multi-modal data fusion technology, the data limitation of traditional manual decision-making is overcome, and the system can capture dynamic change of data in real time through application of a deep reinforcement learning model; the optimal packing scheme is quickly generated, the business volume fluctuation is effectively dealt with, and the optimal configuration of logistics resources is realized.

The invention belongs to the technical field of industrial wireless networks, and particularly relates to an industrial wireless network resource scheduling method based on a multi-dimensional conflict graph. The method comprises the following steps: modeling each controlled object into a discrete time linear time-invariant system, and deriving an evolution rule of a remote estimation error covariance along with the growth of information age; constructing a minimization system long-term average estimation error trace optimization problem according to an evolution law, and converting the minimization system long-term average estimation error trace optimization problem into a time slot-by-slot optimization problem; a multi-dimensional conflict graph is constructed, and the time slot-by-slot optimization problem is mapped to the multi-dimensional conflict graph; solving a maximum weight independent set of the multi-dimensional conflict graph to obtain a network resource scheduling scheme; according to the invention, the dynamic distribution of network resources is realized, the long-term average estimation error and information age of the system are effectively reduced, and the overall stability of the system under the condition that the resources are limited is enhanced.

This invention proposes an intelligent matching and allocation method and device for experts and projects. The method includes: constructing a multi-dimensional fusion matching model based on acquired expert and project information. This model calculates a comprehensive matching score between experts and corresponding projects by weighted fusion of sub-scores based on expert professional matching degree, experience fit, workload balance, and geographical distribution balance; selecting a matching algorithm based on the number of experts and projects to be allocated; using a first matching algorithm when the problem size is no greater than a preset threshold; and using a second matching algorithm when the problem size is greater than the preset threshold; and generating the optimal matching scheme between experts and projects based on the comprehensive matching score using the selected matching algorithm. Based on this method, this invention also proposes an intelligent matching and allocation device for experts and projects. This invention achieves more accurate quantitative matching by constructing a comprehensive evaluation model integrating four dimensions: professional expertise, experience, workload, and geographical distribution.

The invention relates to a water transmission and distribution dynamic scheduling optimization method, which comprises the following steps that a water transmission and distribution test area is established, the water transmission and distribution test area comprises a test branch pipe, a gas pumping unit and a test user side, and two ends of the test branch pipe are respectively connected with a target water plant and the test user side; performing water hammer disturbance effect analysis on the test branch pipe to obtain a water hammer focus of the test branch pipe; air is pumped into the test branch pipe based on the air pumping unit, and vibration parameters and cutoff parameters of the water hammer focus are obtained through strain vibration monitoring and underwater sound cutoff monitoring; establishing an interference factor modulation unit, and performing interference parameter correction on the vibration parameter and the cutoff parameter based on the interference factor modulation unit to obtain a training parameter; circularly executing the previous step to obtain multiple groups of training data, and constructing and training based on the obtained training data to obtain a filtering matching unit; establishing a water transmission and distribution optimization network in the target pipe network area; and managing and optimizing water supply scheduling in the target pipe network domain based on the water transmission and distribution optimization network.

The application relates to the technical field of hydraulic pumps, in particular to a multistage pressure regulating control device of a hydraulic pump. The regulating control device comprises a plug, a valve seat, a valve body, three valve cores, three jacks, a pressure regulating spring, the left side of the plug is mounted on the valve seat to seal, and the right side is sealed by rotating a regulating screw; the valve body is installed in the valve seat, three valve cores are sequentially installed in the valve body from left to right, the outer side walls of the middle sections of the three valve cores are tightly attached to the inner side walls of the valve body, the outer diameters of the middle sections of the three valve cores sequentially decrease from left to right, three cavities are formed between the plug and the three valve cores, one jack is inserted in each valve core, and the pressure regulating spring is installed at the right end of the rightmost jack; and corresponding ports and holes are formed on the valve seat and the valve body to form an oil flow channel. The device is designed with three oil inlets corresponding to three cavities, so that the hydraulic pump can work in a multistage pressure mode, the system heating and energy loss are reduced, and energy saving, emission reduction and energy optimization are realized.

The invention discloses a high and large supporting system for dismantling and rebuilding an existing cantilever structure and a construction method. The high and large supporting system is applied to an existing building comprising existing columns, a lower layer cantilever structure and an upper layer cantilever structure. One end of the system is supported by stand columns, the other end of the system is supported by existing columns, and the system comprises the stand columns, bases, guide rails, hoops, guide beams, bearing beams, supporting plates and the like. In the dismantling stage, the supporting plate serves as an unloading receiving plate to receive the crushed objects; and in the reconstruction stage, supporting rods and formworks are arranged as a working platform, and loads are borne. The system can drive the stand columns and the top sliding seat to slide synchronously through the power device to achieve positioning, the two purposes of protection removal and support reconstruction are achieved, the construction efficiency is improved, and the cost is reduced.

This invention discloses a data governance and application system and method for construction land approval, supply, and use based on an authorization chain, belonging to the field of construction land data management technology. This invention uses electronic supervision numbers to link approval data, supply data, and ownership change registration data to generate a data chain; it performs time-series and integrity checks on the data chain; analyzes abnormal features in the data chain and analyzes comprehensive problem indicators based on these abnormal features; it corrects the data in the problematic time-series chain; it analyzes the matching of approved and supplied land parcels and generates preliminary matching pairs based on the matching results; it analyzes the confidence index of each preliminary matching pair; it filters the preliminary matching pairs based on the confidence index; it classifies land parcels into idle risk warning levels based on a land idleness sensitivity index; and it divides land parcels into spatial clustering patterns using a local Moran's index, sending the division results to the administrator. This improves data reliability and reduces the risk of misjudgment.

The present application belongs to the technical field of power system energy storage, and discloses a gravity energy storage system inertia support optimization method and device based on VSG control, comprising the following steps: obtaining real-time power grid state parameters, the power grid state parameters including power grid frequency, active power and reactive power, dynamically calculating the virtual inertia support power required by the gravity energy storage system based on the VSG control algorithm; dynamically adjusting the control parameters of the VSG based on the power grid frequency and the virtual inertia support power; using the model predictive control method, taking the virtual inertia support power as the control target, rolling optimization of the power distribution strategy, and recording the state of charge change data of the gravity energy storage system in the optimization process; effectively solving the frequency stability problem caused by insufficient system inertia when a high proportion of new energy is connected to the power system in the prior art.

The embodiment of the invention discloses a robot control method, a robot control system and a computer readable storage medium. The robot control method is applied to the robot control system, and the robot control system comprises a control end, a cloud end and an execution end. The method comprises the following steps: a control end obtains interaction data of a user and unifies the interaction data into a task instruction; task information is obtained according to the task instruction, and the task instruction and the task information are sent to the cloud; the cloud performs task splitting analysis based on the task instruction and the task information to generate a corresponding composite task planning set; issuing the composite task planning set to an execution end; and the execution end generates an execution instruction according to the composite task planning set and drives the robot to complete corresponding actions. Therefore, generalization is improved through interaction between the execution end and the user, the cloud end completes control planning and execution end control of the task execution end, the problem of long-view composite tasks is solved, and optimal resource configuration is achieved.

The invention relates to a remote sensing image semi-automatic labeling method and system, and realizes high-efficiency and high-quality remote sensing image labeling. Preprocessing the to-be-processed remote sensing image, and constructing to obtain a remote sensing image slice sample set; screening the remote sensing image slice sample set by adopting an active learning strategy based on the pre-trained CNN model to obtain remote sensing image slices; a pre-trained CNN model is adopted to extract depth features of the remote sensing image slices, and multi-scale feature fusion is carried out to obtain a fusion feature map; reconstructing the fused feature map to obtain a pixel-feature matrix, predicting the pixel-feature matrix by adopting a pre-trained random forest model to obtain the category probability of pixels in the remote sensing image slices, and marking the remote sensing image slices according to the category probability of the pixels in the remote sensing image slices to obtain a pixel-level probability map; performing boundary refinement processing on the pixel-level probability graph by adopting a conditional random field mechanism to obtain a pre-labeled graph; and manually correcting the pre-annotated graph to obtain an accurate annotated graph.

The application discloses a kind of multi-source data management method and device based on federal mechanism, belong to computer data processing technical field, it includes the local data of each data source node is collected and extracts semantic summary, is formed distributed data source register by consensus verification;Cross-source collaborative analysis request is received, and is parsed as non-cyclic directed task graph;According to task graph, query is executed locally in each node, and collaborative calculation is completed by encrypted shared intermediate result, generates final analysis result and task execution log;Analysis task execution log is generated for each node Dynamic credit score;According to credit score, update node weight to adaptively optimize the node selection of subsequent task.The application adopts the closed-loop management strategy that multi-source heterogeneous data is semantically abstracted, collaborative analysis request is parsed as execution task graph, dynamic credit score is generated in combination with task execution log and is adaptively optimized according to node selection, and cross-domain data collaborative analysis and management of safe, efficient and intelligent can be realized.

The application relates to a network security alarm efficient disposal method based on a dynamic graph neural network and belongs to the technical field of artificial intelligence and network security. The application comprises the following steps: collecting network security alarm, agent and disposal tool information, and performing data preprocessing; creating an initial dynamic graph; monitoring network environment changes in real time and updating the dynamic graph; training a dynamic graph neural network model using historical network security alarm disposal data, inputting the dynamic graph, and outputting recommended results of the agent and the disposal tool; continuously updating and optimizing the model according to disposal result feedback; determining the most suitable agent and disposal tool to dispose of the current network security alarm; converting the determined disposal scheme into specific instructions, sending the specific instructions to the corresponding agent and disposal tool for execution, monitoring the disposal effect in real time during the disposal execution process, feeding back the result to the alarm system, and optimizing the dynamic graph and the model. The application has intelligent analysis and efficient disposal capabilities and is highly expandable.

This invention discloses a deep learning-based invoice image recognition method and system, belonging to the field of computer vision and artificial intelligence technology. The method includes the following steps: Intelligent routing decision step: Receiving the original invoice image and dynamically deciding whether to allocate it to a fast processing channel or a deep processing channel based on scene analysis results; Adaptive preprocessing step: Performing preprocessing operations of corresponding intensity on the original invoice image according to the allocation results of the intelligent routing decision step, obtaining a preprocessed image. This achieves a dynamic balance between efficiency and accuracy. Through intelligent routing decision, the system can dynamically select the processing path based on image complexity. Most simple invoices are processed quickly via the fast channel to meet high-concurrency scenarios; a few complex invoices are processed in the deep channel for detailed analysis to ensure high accuracy. This achieves optimal resource allocation at the system level.

The application discloses a kind of based on quality factor furnace temperature field reconstruction effect comprehensive evaluation and pixel number parameter optimization method, it is related to furnace temperature field reconstruction technical field, including the quality factor of constructing fusion positive temperature cell ratio and root mean square error;Based on the quality factor, determine the pixel number threshold inflection point;According to the pixel number threshold inflection point, determine the optimal pixel number under different grid division.The application solves the one-sidedness problem that traditional single index is difficult to consider global error and local feature, realizes the all-round accurate judgment of furnace temperature field reconstruction effect;The improvement of reconstruction effect will tend to saturation, not only can guide the fast positioning of optimal pixel number under different grid division, greatly improve research efficiency, but also can effectively avoid reconstruction failure caused by insufficient pixel number or waste of computing resources caused by excessive pixel number, realize the optimal configuration of reconstruction precision and computing cost.

The present application relates to the technical field of unmanned aerial vehicle application, and more particularly to a park inspection method and system based on unmanned aerial vehicle cooperative scheduling, comprising the following steps: acquiring a park basic geographic base map, sequentially performing geographic hierarchical labeling, inspection area classification and problem point label library construction, and outputting an inspection topological map; through inspection point positioning and differentiated path planning, controlling the unmanned aerial vehicle cluster to collect multi-source inspection data and transmit it to the ground control center; through a double deep learning model, extracting and fusing park dynamic and static problem point features, and outputting real problem point feature information; based on the feature information, completing multi-dimensional evaluation and grading of the problem points, and generating an optimal scheduling scheme by fusing maintenance resource information; implementing the optimal scheduling scheme and forming a closed loop through secondary inspection verification by the unmanned aerial vehicle to update the park inspection database. The present application constructs a fine park inspection topological map, combines differentiated unmanned aerial vehicle scheduling and a double deep learning model, and is suitable for various inspection requirements and reduces costs and improves efficiency.