140 results about "A* search algorithm" patented technology

The invention discloses a document generation system and method based on multi-agent collaboration, and the method comprises the steps: understanding and extracting the high-level semantic information of a text input by a user, and dynamically generating a problem to guide the user to define a demand, so as to form a detailed document demand; recognizing the theme and key elements of the document from the detailed document requirements; the optimal sequence of task execution is determined based on a shortest path algorithm, potential conflicts in task execution are predicted and solved through parallel processing and a search algorithm, and optimized task planning is formed through feedback circulation; generating a document outline according to user requirements, retrieving associated contents of document chapters so as to write chapter contents, and performing grammar and format verification to form a preliminary document; defining a document quality evaluation index according to user requirements and industry standards, performing document quality evaluation on the preliminary document, and feeding back the document quality evaluation result to the user; and generating a complete final document and presenting the complete final document to the user. According to the invention, the document generation quality is improved.

Disclosed in the present application are an integrated circuit routing method and system, and a device and a medium. The method comprises: acquiring an integrated circuit layout model; performing routing area generation processing on the integrated circuit layout model on the basis of a particle swarm optimization algorithm, so as to obtain a routing area; performing routing processing on the routing area on the basis of an improved A* search algorithm, so as to obtain a routing path; on the basis of the routing path, removing a redundant segment, so as to obtain a post-processed path; and performing dictionary conversion processing on the post-processed path, so as to obtain a routing layout. In the embodiments of the present application, a discrete particle swarm optimization algorithm can be used to reduce a routing search space, and a detailed routing area is determined by means of an improved A* search algorithm, thereby further enhancing routing speed, and improving the routing efficiency of an integrated circuit. The embodiments of the present application can be widely applied to the field of integrated circuits.

The invention provides a quantum circuit optimization method, device and equipment for a ZUC algorithm subcomponent, and the method comprises the steps: encoding a signal transmitted by communication into quantum bits, and inputting the quantum bits into a ZUC algorithm structure for quantum implementation; representing a first linear subcomponent in the ZUC algorithm structure as a matrix in a binary field; after a matrix in the binary field is expressed as a block matrix, a low-dimensional matrix M in the binary field is derived from the block matrix, and quantum implementation of the M is searched by using a search algorithm designed based on a matrix decomposition principle; and according to a quantum gate parallel rule, carrying out optimized multi-layer division on the quantum of the M again, obtaining the quantum of the M, carrying out optimized layering operation, and optimizing the quantum of the first linear subcomponent. According to the method provided by the invention, the quantum circuit of the subcomponent of the ZUC algorithm is optimized, so that the resource overhead of quantum implementation of the ZUC algorithm is saved.

The invention discloses a quick video generation method and system based on structured space-time sparsity, and belongs to the field of computer vision and artificial intelligence. According to the method, an inherent structured and heterogeneous sparse mode of an attention matrix in a video diffusion model is systematically analyzed and revealed, and the core of the method is as follows: 1) a self-adaptive partitioning strategy is adopted, and various spatial interaction modes are approximated through dynamic image block grouping; 2) dynamically adjusting the sparse level of a window with time sequence change according to the inter-frame distance; and 3) automatically configuring a search algorithm, and optimizing a sparse mode while keeping a key attention path. The sparse attention mask optimized through offline pre-calculation is directly applied to attention calculation in a reasoning stage, so that 1.8-2.5 times of attention calculation acceleration is realized on a single GPU while the visual quality equivalent to a full attention baseline is kept, and a brand new solution path is provided for efficient long video generation.

The invention relates to the technical field of digital photoetching equipment, in particular to an LDI machine image segmentation and exposure splicing method, which comprises the following steps: carrying out primary segmentation on an original complex graph, and carrying out segmentation again after refinement processing; in the exposure process, periodically collecting a gray histogram of an exposure pattern, aligning the exposure images of adjacent areas to form a continuous exposure image, and dynamically adjusting exposure parameters by a light beam modulator according to the characteristics of each second segmentation area to realize closed-loop control on the exposure quality; all exposed images are spliced through a search algorithm and a multi-frame fusion technology, smooth transition of image edges is realized, discontinuity of local features is effectively avoided, the overall consistency and integrity of the spliced images are ensured, the imaging quality and precision are further improved, finally, the spliced images are verified, and the image quality is improved. And seamless splicing of each segmented region is ensured, so that high-quality graphic output is generated.

The invention relates to the technical field of laser spectrum gas detection, and particularly discloses a TDLAS (tunable diode laser absorption spectroscopy) double-gas concentration synchronous calibration and decoupling method in the presence of spectrum aliasing interference, and the method comprises the following steps: acquiring a multi-band harmonic signal subjected to adaptive optimization while acquiring environmental parameters; an optimal frequency band signal is determined based on the signal quality index; and calculating a spectral aliasing coefficient according to the characteristics of the optimal frequency band signal, dynamically adjusting operation parameters of a search algorithm based on a numerical value interval in which the spectral aliasing coefficient is located, and determining an initial range of dual-gas concentration in a search space. According to the method, the improved genetic algorithm based on the spectral aliasing coefficient dynamic adjustment search strategy is combined with the incremental support vector regression model, stage processing from coarse calibration to fine decoupling is achieved, and the calculation efficiency and the search precision can be automatically balanced when the spectral aliasing degree changes; and online correction is carried out on the model in combination with aging characteristics.

Systems, methods and interfaces are provided for processing natural language queries. A machine learning-powered search interface may process complex natural language queries across specialized domains. The method may utilize a transformer-based natural language processing model that analyzes user intent by examining both current and historical user inputs. A graph data structure may be used to represent interconnected domains like patient records, insurance claims, and business metrics enables dynamic information retrieval. The system may use an A* search algorithm to navigate domain nodes and identify relevant answers. An abbreviation expansion mechanism resolves technical shorthand by referencing domain-specific mapping databases, ensuring precise interpretation of user queries. The method may identify keywords, traces optimal answer pathways, and adapt by updating graph relationships and abbreviation mappings. By generating contextually rich natural language summaries, the system delivers precise, comprehensive responses through an intuitive search interface.

The invention relates to the technical field of automatic driving, and discloses a tramcar path planning method, device and equipment based on a reference line and a storage medium. According to the method, an improved A * search algorithm is combined with reference line discretization and smoothing processing, the node expansion number is reduced, the path smoothness is optimized, and the tramcar path planning efficiency is improved. Meanwhile, a double-factor heuristic function and dynamic constraint verification are utilized to ensure that the path is safe and feasible, and the method has the advantages of improving path planning efficiency, reducing path fluctuation, meeting special terrain and dynamic constraint requirements of a mining area and ensuring that the mine car stably travels along a predetermined reference line.

The invention relates to the technical field of service scheduling, and discloses a dynamic rule engine and state tracking service request automatic scheduling processing system. According to the system, scheduling is realized through a five-stage processing chain of request intake, state acquisition, rule fusion, decision generation and execution monitoring which are connected in sequence. The request intake stage captures a service request stream and generates a request feature topology; in the state acquisition stage, resource operation data is acquired in real time, and a state multi-dimensional map is constructed; in the rule fusion stage, time-space alignment is carried out on the two, and scheduling fitness is output through rule reasoning; in the decision generation stage, based on the scheduling fitness, a search algorithm is adopted to generate a scheduling command sequence; and tracking an execution result in the execution monitoring stage, calculating a scheduling deviation value and feeding back the scheduling deviation value to the request intake stage, and adjusting a feature topology generation parameter. According to the system, a closed-loop scheduling mechanism is formed, the dynamic adaptation of the service request and the resource state is realized, and the flexibility and pertinence of scheduling processing are improved.

The invention belongs to the technical field of fan arrangement, and discloses a fan point location automatic arrangement method and system based on artificial intelligence, and the method comprises the steps: firstly receiving a plurality of spatial constraint layers and deployment parameters, and unifying the coordinates; a conflict relation graph is constructed based on the processed constraint layers, nodes of the graph are different constraint layers, and edges are conflict strength among constraints; inputting the map into a pre-training map attention network, and reasoning to obtain a conflict slow-release factor which quantifies a constraint relaxation degree; then the factors are fed back to a point location search algorithm, and candidate point locations are evaluated by using a scoring function of the fusion factors; and finally, outputting a final arrangement scheme according to a scoring result. According to the method, through artificial intelligence middleware, such as a graph attention network, an artificial intelligence-based search algorithm and the like, the problem of excessive region deletion of a traditional method is solved, and the area and arrangement reasonability of a deployable region are improved.

The invention relates to the technical field of tunnel construction geological disaster early warning, and discloses a tunnel construction geological disaster early warning method and system. According to the method, multi-source geological monitoring data and environment dynamic parameters of a tunnel construction area are collected; and then through data fusion and feature engineering processing, data contradiction and redundancy are eliminated, and a standardized training data set is formed. And then training and verifying a disaster risk prediction model by using the data set and adopting a machine learning algorithm so as to obtain an optimized model to accurately predict the disaster risk. And performing risk value prediction on different geological structure units by applying the optimization model, generating a risk distribution map, and determining an optimal geological structure unit through a search algorithm. Based on this, numerical simulation of geological disaster triggering and propagation is executed, a disaster evolution rule is analyzed, and a path simulation data set is output. And finally, performing multi-objective optimization on the data set according to a safety early warning objective, generating a geological disaster early warning scheme, and performing iterative calibration.

The invention discloses an aircraft taxiing path automatic generation method and system, and the method comprises the steps: obtaining airport GIS map data, and constructing a taxiway hierarchy graph based on an H3 space grid; after an instruction containing a sliding path name sequence is received, the instruction is automatically integrated with machine position and target point information and mapped into starting and ending nodes in a graph structure; and furthermore, a search algorithm combining path name matching and turning angle punishment is executed in the graph, and a continuous and reasonable optimal geometric sliding path is automatically generated. According to the method, full-automatic mapping from a text instruction to a standardized geometric path is realized, the defects of dependence on manpower, low efficiency and high error rate in the prior art are overcome, and the intelligent level and operation safety of airport ground sliding guidance are remarkably improved.

The invention provides a book recommendation method and system based on multi-agent reinforcement learning, and relates to the technical field of book recommendation, and the method comprises the steps: constructing a multi-agent reinforcement learning model, and achieving the information interaction and cooperation between agents through a centralized training architecture; based on the deterministic characteristics of the multi-agent reinforcement learning model, optimistic search is introduced to optimize book search; performing attention weighting optimization on strategy gradient updating through a dominant function to optimize a recommendation strategy; and the strategy parameters of the multiple agents are synchronized through the distributed execution architecture to realize collaborative decision making. According to the method, the multi-agent reinforcement learning models are constructed for mutual assistance and distributed execution, so that the calculation complexity is remarkably reduced, and real-time recommendation of large-scale users and books is supported. On the basis of the deterministic characteristics of the multi-agent reinforcement learning model, optimistic search is introduced to optimize book search, a search algorithm based on quantile optimistic estimation is proposed, and the search efficiency is remarkably improved. And the advantage value searched by the Monte Carlo tree is combined with the strategy gradient, so that the strategy degradation problem of the sparse reward scene is solved.

The invention discloses an intelligent adaptive personalized learning method and system based on AIGC and a knowledge graph. The technical problems that an existing online learning system is low in individuation degree, a knowledge system is fragmented, the evaluation dimension is single, the adaptive capacity is weak, and different requirements of teachers and students are not distinguished are solved. The method comprises the following steps: constructing and updating a domain knowledge graph library with weights, establishing a self-adaptive course resource library associated with knowledge entities, respectively generating multi-dimensional portraits of teachers and students, generating differentiated personalized learning / teaching paths based on an A * search algorithm, and realizing self-adaptive content recommendation, continuous self-adaptive evaluation and dynamic adjustment through a mixed recommendation algorithm. A closed-loop intelligent ecology is formed; the corresponding system comprises core modules such as a knowledge graph library, a self-adaptive course resource library and a teacher and student portrait module. According to the method, all-dimensional personalized support of teachers and students, dynamic self-adaptive adjustment and resource generation according to needs are realized, the teaching and learning efficiency is remarkably improved, and the method is suitable for practical subjects and has system self-evolution ability.

The invention discloses an evolved memory system and interaction method for a universal virtual agent in a GUI (Graphical User Interface) environment, and the system integrates sub-task nodes after decomposition of various tasks and the dependency relationship thereof by constructing a global memory graph, forms a memory graph, and generates a feasible GUI operation sequence by adopting a search algorithm based on the graph. And abstracting the sequence into a transferable guide rule by means of a large language model. When the task is executed, the matching rule and the subtask nodes are retrieved through semantic and structure mixing, the agent decision is assisted, the memory graph is updated after successful execution, and continuous evolution is achieved. When the system is practically applied, the intelligent agent can be driven to execute a GUI task through a natural language instruction, the intelligent agent generates an operation action by utilizing a rule and a retrieval mechanism in the memory graph, interacts with an interface to complete the task, and feeds back an interaction track which is successfully executed to the system, so that the structure of the memory graph is continuously optimized.

The invention discloses a method and system for cooperatively chasing a moving target by an unmanned surface vehicle cluster in an obstacle environment, and relates to the technical field of unmanned surface vehicles, and the method comprises the steps: obtaining the surrounding environment related information of the unmanned surface vehicles, carrying out the fusion processing of the surrounding environment related information of the unmanned surface vehicles, and obtaining the global environment information of a whole chasing region; based on the global environment information of the whole chasing area, adopting an algorithm to track and predict the position and the motion state of the moving target in real time to obtain the motion trail of the moving target in a future period of time, and based on the global environment information of the whole chasing area and the motion trail of the moving target in the future period of time, adopting a search algorithm to search the moving target in the future period of time; generating a chasing path of the unmanned ship; the tracking task is generated based on the tracking path of the unmanned ship, the related data of the unmanned ship is acquired, the tracking task is allocated based on the related data of the unmanned ship, the unmanned ship tracks the moving target based on the tracking task, and the tracking efficiency and success rate of the unmanned ship cluster in a complex environment can be improved.

The invention discloses a parking path planning method and related equipment, and relates to the technical field of vehicle control, and the method comprises the steps: obtaining environment information of a target parking space and a parking starting point and a parking terminal point of a vehicle; constructing a grid map corresponding to the environment information; executing a mixed A * search algorithm in the grid map, performing node expansion on the parking starting point to form a grid index sequence, and storing node state information in the node expansion process in a data chain table according to a grid index corresponding to the node state information; and generating a target parking path from the parking starting point to the parking ending point based on the grid index sequence. According to the method, a node expansion and index linked list management mechanism based on mixed A * is introduced into the grid map, the feasible node state is completely reserved on the premise of meeting the vehicle motion constraint, the continuous, reliable and high-performability parking path can be generated, and the stability and success rate of parking path planning are improved.

The invention discloses a valve inner leakage signal identification method based on variational mode decomposition and a search algorithm, and belongs to the field of valve inner leakage signal identification, and the method comprises the steps: collecting an original signal of an acoustic emission sensor; optimizing the decomposition number and penalty factor of the variational mode decomposition VMD algorithm by using a particle swarm algorithm to obtain an optimized variational mode decomposition VMD algorithm; performing signal noise reduction processing on the original signal by using the optimized variational mode decomposition (VMD) algorithm to obtain a denoised valve signal; extracting an energy ratio characteristic quantity from the denoised valve signal by using a small packet wave method; and according to the energy ratio characteristic quantity, utilizing a support vector machine SSA-SVM optimized by a sparrow algorithm to obtain a valve inner leakage signal identification result. The method solves the problem that the recognition efficiency of a classifier is low due to the fact that the signal noise reduction effect of an existing method is not ideal.

Described herein is NLS using a bounded linear initial search space and a fixed grid with pre-calculated variables. Specifically, first and second signals with unknown first and second elevation angles, respectively, are received that have been reflected by an object, with the second signal also having been reflected off the ground. A line of second angles is then established as a function of first angles, a sensor height, and a range to the object. The first angles being bound by a function of the sensor height and the range and a function of the sensor height, the range, and the maximum height. A search algorithm is then used to search for an initial elevation angle pair along the line. The initial elevation angle pair may then be fed into a refinement algorithm (e.g., non-linear least squares) to determine the elevation angles associated with the first and second signals.

The invention provides a composite material fan blade cold state blade profile parallel extraction method and device. The method comprises the following steps: S1, inputting a guide node and a cold state finite element model surface unit; s2, according to the number of the guide nodes, determining the number of parallel computing cores, equally dividing the guide nodes, and sending the equally divided guide nodes and surface nodes to each sub-process by the host process; s3, executing a search algorithm by each sub-process, and determining all nodes of a cross section where each guide node is located; and S4, each sub-process sends the node of each section of the sub-process to the host process, and the host process outputs a cold-state leaf profile according to the sections after merging. According to the cold-state leaf profile parallel extraction method and device, cold-state leaf profile extraction can be automatically executed, the calculation efficiency is improved, the error probability is reduced, and the design efficiency is improved.

This invention discloses a method, apparatus, medium, and device for parameter optimization of analog circuits, relating to the field of analog circuit technology. The invention automatically identifies current paths through a search algorithm to deeply analyze the circuit topology, determine the symmetry structure in the analog circuit, and constructs symmetry constraints based on the identical optimization parameters of electrical components within the symmetry structure. Simultaneously, it transforms the product of the transistor's gate width and the number of parallel connections into the total width and sets the optimization boundary. This combination reduces the dimensionality of the optimization variables while ensuring that the parameter optimization process conforms to the layout design of the analog circuit. Furthermore, it combines a population mutation algorithm and a non-dominated sorting genetic algorithm with an elitist strategy to perform iterative optimization within the constructed efficient search space, significantly improving the convergence speed of analog circuit parameter optimization, reducing computational costs, and enhancing the practicality of the analog circuit parameter optimization method.

The application discloses an automatic generation method and system of an aircraft taxiway, which comprises the following steps: acquiring airport GIS map data, and constructing a taxiway hierarchical graph based on an H3 spatial grid; after receiving an instruction containing a taxiway name sequence, automatically integrating the instruction with gate and target point information, and mapping starting and ending nodes in a graph structure; and then, automatically generating a continuous and reasonable optimal geometric taxiway by executing a search algorithm combining path name matching and turning angle punishment in the graph. The application realizes automatic mapping from a text instruction to a standardized geometric path, overcomes the defects of the prior art, such as dependence on manual operation, low efficiency and error-prone, and significantly improves the intelligent level and operation safety of airport ground taxiway guidance.

The invention discloses a deep space probe landing point selection method based on topographic feature quantification, and the method comprises the steps: constructing a multi-target topographic feature optimization model through analyzing the parameters of a landing region, such as the topographic slope, the surface roughness, the obstacle distribution and the regional area, and achieving the automatic selection of a safe landing point. The method comprises the following specific steps: firstly, detecting spatial distribution of potential obstacles such as rocks and meteorite craters, and secondly, quantitatively analyzing topographic feature parameters such as topographic roughness, gradient change rate and topographic relief; and finally, an optimal landing position is determined under multiple terrain constraint conditions by using an optimization search algorithm, so that the landing safety and task success rate of the detector are effectively improved. According to the method, the safe landing point of the detector is accurately obtained by innovatively applying terrain feature quantification and a search algorithm, so that effective detection of a safe position in a landing area is efficiently realized, and safe landing of the detector is practically guaranteed.

The invention discloses an SQL (Structured Query Language) fuzzy test case generation method based on dynamic metadata dependence. The method comprises the following steps: firstly, extracting structural metadata from a database system directory in a dynamic introspection manner during operation to construct a base layer of a hierarchical semantic model, and initializing an enhancement layer of the hierarchical semantic model for storing explicit semantic rules and implicit semantic rules learned during operation; secondly, converting the structural metadata into a semantic dependency graph to describe a semantic relationship; in the test case generation stage, ANTLR is adopted to analyze SQL and mutate SQL intermediate representation, a semantic dependency graph is utilized to analyze semantic requests and detect conflicts, and restored semantic effective queries are automatically generated through a search algorithm. In the execution stage, the next round of SQL generation is guided according to operation feedback. Through the dynamic metadata extraction and runtime learning mechanism, the semantic validity of the SQL test case and the database defect discovery efficiency are effectively improved.

Disclosed are systems and methods for enhancing local node performance in a storage system through offloading cache replacement tasks to remote nodes. A periodic time-series analysis of CPU cycle utilization and network latency is conducted on one or more arrays to identify and / or forecast underutilized nodes in the one or more arrays. A first array detects a shortage of available cache slots in an allocation queue and identifies underutilized remote nodes in either its own array or another array. The array shares the metadata pages with the remote node. A worker thread on the remote node runs a search algorithm on the received meta data pages and creates a list of candidate replacement memory slots.

A method, apparatus and product comprising: obtaining alternative quantum circuits implementing a quantum program, each having a respective design error; identifying, for each quantum circuit, respective quantum resources that are used by the quantum circuit and are associated with respective hardware errors of a quantum computer; determining a total hardware error bound for the quantum circuit; determining a total error bound for the quantum circuit; applying a search algorithm over a plurality of total error bounds of the plurality of alternative quantum circuits, to identify an optimal total error bound that is associated with an optimal quantum circuit; and providing the optimal quantum circuit for execution on the quantum computer.

The invention provides an unmanned aerial vehicle multi-mode topological map navigation method based on language guidance. The unmanned aerial vehicle multi-mode topological map navigation method comprises the steps that a multi-frame image sequence and a natural language task instruction in the flight process of an unmanned aerial vehicle are obtained; based on the natural language task instruction, extracting a semantic key frame from the multi-frame image sequence; based on the semantic key frame, constructing a topological node representing image, language and spatial information; based on the topological node, determining a topological edge of semantic space joint constraint; and on a semantic space topological graph, the optimal path of the unmanned aerial vehicle is determined by adopting a search algorithm, and the semantic space topological graph is constructed by topological nodes and topological edges. According to the invention, the unmanned aerial vehicle can autonomously construct the semantic map in an unknown environment and complete effective navigation according to the language instruction.

Systems, methods and interfaces are provided for processing natural language queries. A machine learning-powered search interface may process complex natural language queries across specialized domains. The method may utilize a transformer-based natural language processing model that analyzes user intent by examining both current and historical user inputs. A graph data structure may be used to represent interconnected domains like patient records, insurance claims, and business metrics enables dynamic information retrieval. The system may use an A* search algorithm to navigate domain nodes and identify relevant answers. An abbreviation expansion mechanism resolves technical shorthand by referencing domain-specific mapping databases, ensuring precise interpretation of user queries. The method may identify keywords, traces optimal answer pathways, and adapt by updating graph relationships and abbreviation mappings. By generating contextually rich natural language summaries, the system delivers precise, comprehensive responses through an intuitive search interface.

The invention provides a data processing method which can be applied to the technical field of big data and the technical field of financial science and technology. The data processing method comprises the steps that in response to a received query statement for a database, an index search tree corresponding to the database is obtained, the index search tree is pre-constructed based on a data table field of the database and a preset action space, and all nodes of the index search tree represent corresponding index configurations; the index configuration at least comprises a single-column index or a multi-column index; a target index combination is obtained based on the index search tree, the target index combination is obtained by searching the index search tree in advance based on a search algorithm and calculating node revenue, the node revenue is determined based on a cost estimation model, and a target execution plan of the query statement is determined based on the query statement and the target index combination. The invention further provides a data processing device, equipment, a medium and a program product.

The invention provides a multi-granularity code clone detection method based on clustering search and a large model, and belongs to the technical field of code clone detection. Comprising the steps that an MGCD analyzes a code library to generate a vector database, and each vector represents a function-level code snippet; the code to be detected is analyzed, and the MGCD identifies function clone candidate items in a database by using a search algorithm; an automatic heuristic method is used as a filter to obtain a highly correlated and accurate function-level result; and the MGCD realizes multi-granularity clone detection. According to the method, the semantic clone recognition capability is remarkably enhanced, and complex code snippets with similar semantics are effectively detected. The clustering algorithm improves the retrieval efficiency in a large-scale code library and reduces the calculation cost. The multi-granularity code clone detection is supported, multiple levels such as a function level, a module level and a project level are covered, a more comprehensive and multi-dimensional code similarity analysis result is provided for a user, the detection efficiency is improved, and the flexibility and expansibility of the system are enhanced.