21results about How to "Improve execution" patented technology

One or more embodiments of the invention provide a question and answer method and device based on a large language model, and the method comprises the steps: obtaining a query text which is input by a user and corresponds to to-be-processed table data, and generating a prompt text corresponding to the large language model based on the query text; wherein the prompt text comprises a query text and an indication text used for indicating that the answer text can contain a data processing instruction corresponding to the table data; inputting the prompt text into a large language model, and generating an initial answer text corresponding to the query text by the large language model under the guidance of the prompt text; wherein the initial answer text comprises a data processing instruction corresponding to the table data; executing the data processing instruction to obtain a data processing result corresponding to the data processing instruction; and updating the initial answer text based on the data processing result to obtain a final answer text corresponding to the query text, and outputting the final answer text to the user.

The invention relates to the technical field of building engineering, in particular to a BIM (Building Information Modeling)-based ship lock engineering virtual construction system, which comprises a project information management module, a process management module, an engineering decomposition structure management module, a mobile terminal module, a plan management module, a progress tracking module, an order management module and a progress 4D simulation module, the project information management module provides project information for the process procedure management module and the project decomposition structure management module; the process and process management module defines a construction process and a process according to project information, and is bound with components of the project decomposition structure management module; the engineering decomposition structure management module is responsible for generating decomposition structures and codes of the components; the plan management module formulates a project progress plan based on the generation information of the project decomposition structure management module; the progress tracking module monitors the progress of a construction site in real time, if the progress accords with a plan, a material order is generated through the order management module, and if the progress is abnormal, the material order is fed back to the plan management module for adjustment; the mobile terminal module provides progress update to the plan management module, and submits a production order to the order management module at the same time; and the order management module ensures synchronization of material supply and construction according to the order, and shares progress data with the progress 4D simulation module to generate dynamic visual display of the construction progress.

The invention provides a dexterous manipulator fused with an ontology visual perception function, and belongs to the technical field of electromechanical control. The depth camera is arranged in the palm, the size of the device is remarkably reduced, the size of the device is closer to the size of a human hand, and therefore flexibility and naturalness are improved, the depth camera and a control system are highly integrated, the structure is simplified, synchronism of visual data and hand actions is improved, operation precision is improved, the dexterous manipulator has 16 degrees of freedom, and the flexibility and the reliability of the device are improved. The system is completely driven by a steering engine, the operation flexibility and the fine action execution capability are greatly improved, the requirements of complex tasks are met, the production and maintenance cost is effectively reduced through optimization design and reduction of external accessories, multiple objects are positioned at the same time through a developed instance-level multi-target positioning method and by using a neural network, pre-training is not needed, and the operation efficiency is improved. The space perception capability of the dexterous hand is further improved, and the autonomous operation capability of the dexterous hand in a complex environment is enhanced.

The invention discloses an intelligent project evaluation method supporting a custom standard and multi-dimensional semantic analysis. The method comprises the following steps: constructing an overall standard system according to a project evaluation standard; data arrangement, corpus cleaning, automatic sample generation, sample generation, index evaluation model design and model training are carried out on the basis of collected enterprise historical project materials, finally, an index evaluation model library is generated, and the index evaluation model library is managed in a mode of combining product life cycle management (PLM) and language model (LLM) so as to construct an index evaluation model; performing qualitative evaluation and quantitative evaluation on the enterprise project review material; and comprehensively considering the constructed evaluation standard system, the index evaluation model and the report content quality evaluation result, and intelligently generating a quality evaluation report. The method has the remarkable beneficial effects of improving the evaluation efficiency, reducing the cost, enhancing the evaluation accuracy and objectivity and the like.

This invention relates to the field of multi-UAV cooperative control and target detection technology, specifically to a multi-UAV cooperative search method for underwater targets, comprising: acquiring a probability distribution heatmap; determining UAV parameters and sensor parameters, and establishing the fitness of a genetic algorithm based on the time taken for multiple UAVs to complete all search tasks, total flight time, weights of high-risk hotspots, and arrival times at each target hotspot; optimizing the genetic algorithm based on the probability distribution heatmap and the fitness to obtain an optimal task allocation sequence; performing Dubins transition and spiral search based on the optimal task allocation sequence, the minimum turning radius of the UAVs, and the maximum allowable distance between adjacent routes to obtain a flight path; and for each UAV, tracking the flight path based on the real-time position of the UAV and the eccentricity of the flight path. This invention can improve the anti-interference capability and efficiency of multi-UAV cooperative target detection.

The invention relates to the technical field of control equipment, and discloses a three-redundancy-based electromagnetic valve control system which comprises a time delay relay circuit, a DC / DC and anti-reverse circuit and a three-redundancy control circuit, the time delay relay circuit comprises a first time delay relay, a first rectifier diode, a first control module, a second control module and a third control module, and the first control module, the second control module and the third control module are connected in parallel. The first control module, the second control module and the third control module are respectively connected with three groups of different electromagnetic valve control signals, and any group of electromagnetic valve control signals effectively control the first delay relay to work; the DC / DC and anti-reverse circuit comprises a first DC / DC conversion circuit and a first ideal diode; the triple-redundancy control circuit comprises a fourth control module, a fifth control module and a sixth control module which are connected in parallel, one end of the first control module is connected with the negative electrode of the electromagnetic valve working power supply, the other end of the first control module is connected with the other end of the electromagnetic valve, and any group of electromagnetic valve control signals effectively control the electromagnetic valve to work. By adopting the method, three-redundancy control can be realized, and the reliability of an electromagnetic valve control system is improved.

The application discloses a farmland planning analysis method and system based on satellite data, relates to the technical field of farmland planning analysis, and comprises the following steps: obtaining multi-satellite image data of a target farmland area, pre-processing and performing semantic segmentation, constructing a binary image, fitting line segment endpoints, forming a farmland closed polygon, obtaining agricultural machinery parameters, forming constraint conditions, performing regional decomposition on the farmland closed polygon based on the constraint conditions, forming a plurality of sub-regions with continuous operation attributes, constructing a bidirectional optional coverage path and a state set, judging the direction consistency of the path connection relationship between the sub-regions according to the coverage path, generating a complete path for division and evaluation based on the judgment result, and performing local path reconstruction according to the evaluation result to obtain a complete continuous path as the farmland planning analysis result. The application significantly improves the intelligent level of farmland planning analysis.

The application discloses an immersive neural rehabilitation training method based on virtual reality, and particularly relates to the technical field of neural rehabilitation training, and comprises the following steps: acquiring action data, tactile data, proprioceptive data and gaze data when a trainee performs a target action, performing uniform time sequence alignment on the data in a virtual reality environment, reorganizing according to a starting section, a pushing section and a reaching section of the target action, and outputting a target action response sequence; performing segmented comparison on the differences of multi-source responses of the target action under the conditions of visual weakening, tactile weakening and proprioceptive weakening to determine a perception dependency relationship, rearranging the prompt items and feedback items in the virtual reality scene according to the perception dependency relationship, and then performing recovery checking on the rearranged results.

The invention relates to the technical field of filtering algorithms, and discloses a filtering algorithm implementation method based on an RISC-V architecture, a coprocessor, computer equipment and a computer readable storage medium in order to solve the problem that an implementation mode of an existing filtering algorithm is low in execution efficiency. The method comprises the following steps: obtaining a filtering algorithm, wherein the filtering algorithm comprises a 128-order FIR module, an EQ module and a mute module; defining a first instruction, a second instruction and a third instruction for a filtering algorithm; a first instruction, a second instruction and a third instruction are called, corresponding operation in a filtering algorithm is executed, the first instruction is used for achieving multiplication and addition operation in the FIR module, the EQ module and the mute module, the second instruction is used for achieving multiplication and subtraction operation in the EQ module, and the third instruction is used for achieving multiplication and subtraction operation in the EQ module. The third instruction is used for carrying out zero clearing on a register used for caching the multiply-add operation and multiply-subtract operation results before each calculation. By adopting the method, the execution capability of the processor on the filtering algorithm can be improved on the basis of increasing the richness of the instruction set of the processor.

The invention discloses an optimal path planning method of a pulse coupling neural network based on double constraints. The method comprises the following steps: mapping a path planning environment to a DC-PCNN network; a DC-PCNN neural network model is constructed, and all neurons are initialized; activating a target neuron, and recording the current neuron as a father node; calculating an exponential decay function of the torque deviation, and multiplying the calculated value as a penalty factor by an update item of the internal activity item; calculating a gravitational function value of the flow field constraint, and using the calculated value to update a current neuron dynamic threshold value; comparing the internal activity item with a dynamic threshold; when gt; if yes, activating the neuron, and recording the current neuron as a father node; repeating the steps S4-S6 until the initial neuron is activated; and backtracking all activated nodes, and planning an optimal path. According to the method, the search efficiency is remarkably improved while the path optimality is ensured.

The application relates to a compiled graph fusion optimization method, device, equipment, storage medium and computer program product. The method comprises the following steps: acquiring breakpoint information corresponding to a plurality of operation logic segments generated in a front-end tracking process of a computation graph compilation, the breakpoint information comprising operation information triggering a breakpoint, context tensor attributes and a dependency relationship, the dependency relationship being an association relationship between the operation triggering the breakpoint and the context tensor; based on the operation information triggering the breakpoint, the context tensor attributes and the dependency relationship, performing fusion reconstruction on the plurality of operation logic segments to obtain at least one fused logic segment; and performing back-end compilation based on the at least one fused logic segment to obtain compilation information of the computation graph. The method can reduce graph breakpoints.

The application discloses a supply chain link risk analysis method based on a block chain and big data, and comprises the following steps: S1, collecting multi-source heterogeneous data in a physical supply chain network, constructing a distributed ledger and a unified knowledge structure, and chaining and solidifying the cryptographic hash digest of core data, the application has the beneficial effects that: by collecting multi-source heterogeneous data in the physical supply chain and constructing a graph structure knowledge representation, the temperature, humidity, vibration, position and other physical states are mapped to the environment on the alliance chain in real time; the system can not only perceive the risk in advance, but also automatically execute multi-objective optimization and parallel simulation verification through the smart contract, so that the emergency scheme with better comprehensive performance considering the cost, time efficiency and reputation is screened out before the physical loss occurs; the mechanism helps to alleviate the problems of perception lag, decision dependence on artificial and slow response in the traditional supply chain, realizes the full-process automation closed loop from risk early warning to scheme execution, and is favorable for reducing the actual loss caused by supply interruption or quality accidents.

The embodiment of the invention provides a micro-architecture performance analysis method and device, a readable storage medium and a program product, and relates to the technical field of computers, the method comprises the following steps: respectively collecting micro-architecture events generated when a micro-architecture executes each function of a predetermined application program; determining each predetermined performance index corresponding to each function based on a preset index evaluation model of the micro-architecture and the micro-architecture event corresponding to each function; and performing performance analysis according to each predetermined performance index to obtain a performance analysis result of each function running on the micro-architecture. According to the performance analysis method provided by the embodiment of the invention, the accuracy of a performance analysis result can be improved.

Embodiments of the present specification provide a method and device for training a multi-task model, wherein the multi-task model comprises a backbone network for determining a user representation, and k head networks for performing k user prediction tasks based on the user representation. The method comprises: determining, based on m user samples, k sets of original gradient vectors of the k user prediction tasks with respect to the backbone network, wherein each user sample comprises a user feature and k user labels; mapping the k sets of original gradient vectors to a subspace of an original space in which the k sets of original gradient vectors are located, to obtain k sets of mapped gradient vectors; determining r weights corresponding to the r spatial dimensions of the subspace based on the component distribution of the k sets of mapped gradient vectors on the r spatial dimensions of the subspace, and performing weighted processing on the r dimensional components of each mapped gradient vector respectively by using the r weights to obtain k sets of weighted gradient vectors; and mapping the k sets of weighted gradient vectors back to the original space to obtain k sets of processed gradient vectors, which are used to update the network parameters of the backbone network.

The present application provides a method, device, equipment and machine-readable storage medium for processing multi-table connections, including: generating a first detection execution plan according to a multi-table connection query request; inputting a first detection feature corresponding to the first detection execution plan into a trained target network model, and obtaining a second detection feature by the target network model according to the first detection feature; generating a second detection execution plan based on the second detection feature; wherein the connection sequence in the second detection execution plan is different from or the same as the connection sequence in the first detection execution plan; and performing multi-table connection query processing based on the second detection execution plan. Through the technical solution of the present application, a better execution plan can be found, and the execution plan of the database can be optimized to improve the efficiency of multi-table connection queries in the database.

This application discloses a reminder method, device, electronic device, and computer-readable storage medium, relating to the field of health management technology. The method includes: determining the proximity of a user's medication anchor point based on the location of the target medication and the user's location; predicting the risk of medication unavailability based on the target medication's dosing plan, the user's historical outing patterns, calendar busyness, historical medication carrying success rate, and proximity to the medication anchor point; predicting a target medication preparation time window based on the distance between the user and the medication anchor point, the user's busyness level, and current activity status; continuously monitoring the real-time distance between the user and the medication anchor point, and the user's real-time busyness within the target medication preparation time window; and pushing a medication preparation reminder to the user when the real-time distance is less than a distance threshold and the real-time busyness is less than a busyness threshold for a specified duration. Thus, this solution ensures that the medication is readily available to the user when the scheduled dosing time arrives.

The present disclosure provides a blockchain-based Web3.0 system registration method and a spatial information network system, and is applied to a spatial information network system. When a first consensus ground node receives a user registration request, the first consensus ground node generates a blockchain identity and determines assistance nodes, each of which generates a key fragment. The client and the first consensus ground node generate a user public-private key pair based on system parameters and each key fragment. The first consensus ground node generates user storage information of a mobile user based on the public key in the user public-private key pair and the blockchain identity, and stores the user storage information in the blockchain. Through performance adaptation, scientific screening of assistance nodes is achieved, which not only avoids the efficiency bottleneck of a single node bearing too much load, but also replaces the traditional centralized mechanism with a distributed key fragment generation mode, greatly reducing the risk of single-point failure and the probability of key attack as a whole, while dispersing the computing pressure and improving the efficiency and security of key generation.

The present invention discloses a multi-type robot collaborative operation method based on dynamic environment perception modeling. Through multimodal data acquisition and fusion technology, combined with three-dimensional environment modeling and multi-robot collaborative communication mechanism, optimization and dynamic adjustment of task allocation are realized, and a complete solution is formed; multimodal data fusion improves the comprehensiveness and real-time nature of environmental perception, dynamic environment modeling ensures the accuracy and updating efficiency of the model, and multi-robot communication and task collaboration optimize resource allocation and execution effect; the present invention improves the problems of information isolation, single task allocation and insufficient flexibility of collaborative operation in traditional robot systems, and the proposed technical solution realizes efficient collaboration and resource optimization among multiple robots in complex environments, significantly improves the system's perception ability, task response speed and overall operation efficiency, and is widely applicable to complex scenarios such as inspection, rescue and industrial production.

The application provides an industry knowledge graph-based large model enhancement training method, which comprises the following steps: constructing an industry task structure graph, structurally encoding task nodes to obtain a task structure vector set and a task structure hop number matrix; dividing a training task into stages based on the graph to form a stage task set and a corresponding stage sample set; training a large model stage by stage, and introducing a structural consistency constraint in each stage to align the model internal task representation with the task structure vector and make the relationship between tasks comply with the hop number matrix; and finally, fusing the model parameters and task intermediate representations of each stage, optimizing in a unified structure space, making the task representation of the final model close to the original graph structure, retaining the stage training memory and maintaining the hop number distance relationship between tasks. The method effectively improves the structural understanding and generalization ability of the large model in the industry task.

The invention discloses a multi-mechanical-arm cooperative task allocation method and system based on a high-order network, and relates to the technical field of automatic control. The method comprises the following steps: firstly, constructing a high-order network by taking each mechanical arm as a node, integrating a state of each mechanical arm and a target position vector, constructing an energy function reflecting a distance relationship between an end effector and a target, and deducing a gradient descent function by analyzing the energy function, the state of each mechanical arm and the target position vector; based on the gradient descent function and the adjustment parameters of the angular velocity of the mechanical arms, angular velocity expressions of all the mechanical arms are obtained through processing, meanwhile, communication, scalar states, activation states and neighbor sets of the mechanical arms are comprehensively monitored, and task allocation is dynamically adjusted according to the monitoring result so as to optimize the overall task execution effect. The cooperative operation efficiency of the mechanical arm system is improved, reasonable allocation of tasks and flexible scheduling of the mechanical arms are achieved, therefore, optimal allocation of resources is ensured, and excessive or insufficient resource allocation is avoided.

This application discloses a physical downlink control channel repetition method and apparatus, and user equipment. The PDCCH repetition method according to embodiments of this application includes: in a case that UE has received information for PDCCH repetition, determining, by the UE, X PDCCH candidates of repetition, X being an integer greater than 1; and executing, by the UE, an overbooking rule based on an assumed first blind decoding count on the X PDCCH candidates, or executing, by the UE, a target operation based on a time domain resource of a target PDCCH candidate; where search spaces corresponding to the X PDCCH candidates are associated with each other, and the target PDCCH candidate is a PDCCH candidate satisfying a predetermined condition in the X PDCCH candidates.