329 results about "Automaton" patented technology

The invention discloses a low-altitude airway flow field sensitive area dynamic identification optimization method based on set simulation, and the method comprises the steps: building a low-altitude flow field preprocessing data base with consistent time and space based on Beidou subdivision grids and multi-source heterogeneous data fusion; constructing a low-altitude airspace digital twinning environment based on the data; based on the low-altitude airspace digital twin environment and the cellular automaton-fluid coupling model, generating a diversified flow field evolution scene covering extreme weather and equipment faults; based on a set simulation result, extracting a high-conflict probability region through a spatio-temporal clustering algorithm and quantifying region risk features; generating an air route planning scheme meeting security constraints through a multi-objective evolutionary algorithm based on the quantitative regional risk features; on the basis of a low-altitude airspace digital twin environment and an air route planning scheme, verifying the feasibility of the air route planning scheme through historical data playback and virtual-real fusion test; and according to a verification feedback result, carrying out dynamic feedback optimization on the low-altitude air route flow field sensitive area identification and air route planning scheme.

According to the automatic software development method and device and the computer program, intelligent demand analysis is achieved through a natural language processing technology, dynamic task arrangement is conducted through a finite state automaton, collaborative development is completed by means of a multi-specialized role agent, intelligent verification is implemented based on a template matching mechanism, and the development efficiency is improved. And a complete automatic closed loop from demand to delivery is constructed. According to the scheme, full-process automation is realized, manual intervention is greatly reduced, and the development efficiency is remarkably improved; through division and cooperation of multiple agents, the professionality and decision-making quality of each link are ensured, and the capability limitation of a single agent is overcome; flexible and reliable process control is provided based on state machine management, and development state changes are dynamically adapted; and the standard consistency of the delivery result is ensured by combining template verification. According to the method, the problems of long development period, large quality fluctuation and the like caused by chain splitting, low intelligent level and excessive dependence on manpower of an existing development tool are effectively solved, and a feasible path is provided for comprehensive intelligence of software development.

The invention discloses a ship knowledge graph construction method based on a large model and a graph neural network, and the method comprises the steps: carrying out the format conversion and protection type partitioning processing of a professional document, and completing the recursive segmentation through a placeholder protection formula, a table and other structures according to the semantic hierarchy, and obtaining a text block suitable for the extraction of an entity and a relation; extracting domain entities by utilizing a large language model containing thinking chain cues, and positioning candidate entities in combination with an AC automaton so as to improve the coverage rate and accuracy of relation triple extraction; performing new entity backfilling and relation standardization on an extraction result, and constructing an initial knowledge graph with a consistent structure; and inputting the initial knowledge graph into a graph neural network model with directional expansion and a multi-scale decoder, and complementing a missing relationship through link prediction, so that node distribution and a relationship structure of the graph are more complete. According to the method, a continuous processing chain from text preprocessing, knowledge extraction to graph completion is formed.

The invention provides a cable path intelligent optimization method fusing a cellular automaton and an ant colony algorithm, and the method comprises the steps: obtaining a three-dimensional boundary range of a target region, constructing a three-dimensional underground space voxel model, and dividing the target region into voxel units containing five-dimensional attribute tensors; constructing and inputting the five-dimensional attribute tensor into a physical constructable potential field model, and generating a corresponding three-dimensional physical constructable potential field; performing construction scoring according to the three-dimensional physical constructable potential field and the five-dimensional attribute tensor; constructing a composite cost function in combination with the three-dimensional physical constructable potential field and the construction score, generating a composite passing cost of each voxel, and generating an optimal cable path in combination with a path search algorithm which takes an improved ant colony algorithm as a control mechanism and introduces a rule of a cellular automaton on a path state propagation structure; and performing three-dimensional geographic mapping, structure reconstruction and geometric fairing on the optimal cable path, and outputting a standardized path result.

The invention discloses a wind power plant voltage and frequency cooperative tuning control method, and relates to the technical field of tuning control, and the method comprises the steps: obtaining the real-time operation data of a wind power plant, carrying out the preprocessing of the real-time operation data of the wind power plant, carrying out the voltage fluctuation and frequency disturbance prediction through a cellular automaton model in combination with the pre-obtained power grid data, and carrying out the voltage fluctuation and frequency disturbance prediction. Obtaining a prediction state matrix; carrying out multi-objective optimization solution in combination with a pre-constructed multi-objective optimization problem and constraint conditions, and obtaining an optimal droop coefficient vector in combination with a preset rule; and the optimal droop coefficient vector is used as a control reference, and voltage and frequency cooperative tuning is carried out in combination with grid-connected point voltage and frequency obtained in real time and communication network topology data. According to the method, prediction is carried out through the cellular automaton model, the rapid and cooperative regulation capability of the voltage and the frequency of the wind power plant is improved, and therefore the urgent demand of a power system for rapid, accurate and cooperative control under the access of high-proportion new energy is better met.

Techniques for generating a layout for computing equipment in a data center are disclosed. The system represents a physical environment as a layout polygon and obstacles within the physical environment as obstacle polygons. The system represents groupings of racks as pod polygons. The system executes a positioning algorithm to place pod polygons in the layout polygon. The initial layout is optimized according to layout criteria. The system determines if any of the pod polygons in the initial layout collide with an obstacle polygon. The system attempts to resolve the collision by moving the colliding pod polygons or removing racks from a pod polygon. The system generates a basket tray path that minimizes the length of the basket tray path while avoiding obstacles in the path.

The invention discloses a flexible resource adjustment capability assessment method and system based on labels and risk analysis, and relates to the technical field of power system demand side management. The method comprises the following steps: acquiring real-time operation parameters of load side flexibility resources, and generating a multi-dimensional capability envelope of individual resources based on a multi-state finite automaton model; constructing a multi-dimensional value label, clustering and grouping the flexible resources in combination with a multi-dimensional capability envelope, and constructing a virtual polymer; quantizing the aggregation adjustment capability of the virtual aggregate by adopting an opportunity constraint robust aggregation method to generate a multi-dimensional vector; and fusing the multi-dimensional vector with geographic information, realizing visualization through a thermodynamic diagram and an interactive interface, and generating a system-level capability map. According to the method, the full-dimensional capability evaluation of the flexible resources from individuals to aggregation is realized, the value attributes and the operation risk are considered, and a visual and reliable decision support is provided for power grid dispatching.

The invention relates to the technical field of land data planning, and discloses a reasonable land planning system based on machine learning carbon storage, and the system comprises a multi-source data fusion module, a carbon storage prediction module, a three-generation coordination discrimination module, a land use intelligent optimization module, a scene interaction deduction module, and a planning result generation module. By integrating data such as standardized land utilization and carbon density, a machine learning model is utilized to predict the dynamic state of the carbon density in real time, and the functional coordination degree of the three plants is quantitatively evaluated; and then, by taking the improvement of the carbon reserves and the coordination of the three plants as targets, carrying out spatial simulation and iterative optimization in combination with multi-objective optimization and a cellular automaton, comparing different policy carbon sink effects through scene deduction, and finally outputting an optimization scheme, thereby realizing the real-time closed loop of evaluation and optimization, and synergistically improving the carbon sink benefits and the three-plant function.

The invention provides a heterogeneous unmanned aerial vehicle forest fire rescue cooperative scheduling method based on reinforcement learning and quantum particle swarm optimization, and relates to the field of cooperative scheduling, and the method comprises the steps: constructing a cellular automaton fire spread model based on wind speed, vegetation and gradient, and generating a combustion cell priority sequence; establishing a three-state conversion model of the multi-type unmanned aerial vehicle, and combining the combustion loss and the flight time to construct a comprehensive cost; task allocation and track solving are realized through a quantum particle swarm optimization algorithm enhanced by reinforcement learning; and a scheduling scheme is corrected in real time by adopting a rolling updating mechanism, and fault-tolerant re-planning is triggered under an abnormal condition, so that the cooperative fire extinguishing efficiency of the heterogeneous unmanned aerial vehicle group is improved.

An automated model based guided digital twin synchronization system is described. The system comprises visual sensors configured to acquire raw visual data of a physical 3D scene content from a real site, a database to provide a 3D model of the physical 3D scene content, a processor and a memory for storing computer-executable instructions executed by the processor. The instructions comprise an automated machine learning model based logic to: generate and maintain an as-built digital twin of the assets and large-scale infrastructures present in the physical 3D scene by ingesting the raw visual data to a common and binding structured representation, compare the as-built digital twin representation obtained from the real site against corresponding an as-planned digital twin to determine spatio-temporal differences between the as-built and the as-planned digital twins, and update automatically the as-planned digital twin to reflect any changes to the physical 3D scene based on the spatio-temporal differences.

Disclosed are methods, systems, and non-transitory computer readable media that control an autonomous vehicle via at least two sensors. One aspect includes capturing an image of a scene ahead of the vehicle with a first sensor, identifying an object in the scene at a confidence level based on the image, determining the confidence level of the identifying is below a threshold, in response to the confidence level being below the threshold, directing a second sensor having a field of view smaller than the first sensor to generate a second image including a location of the identified object, further identifying the object in the scene based on the second image, controlling the vehicle based on the further identification of the object.

The invention discloses a supervision and control-based punctual scheduling method and system for wafer combination equipment, and mainly solves the problems of high probability of blockage, path conflict and low scheduling efficiency during multi-resource parallel operation of the existing wafer combination equipment. According to the implementation scheme, the method comprises the following steps: respectively constructing corresponding automaton models for process units in equipment, and carrying out synchronous splicing according to a real process flow to form an overall model capable of reflecting dynamic behaviors of a system; a corresponding constraint model is established by combining factors such as process sequence constraint, equipment capacity limitation, carrying time constraint and residence time limitation; and the supervision controller continuously judges whether the event to be executed can cause blockage or not, gradually eliminates the blockage by disabling the controllable event, triggers the optimal event according to the priority of the event, and guides the scheduling path to propel and output the optimal scheduling scheme along the optimal direction. According to the method, the overall model capable of being dynamically adjusted is constructed, the event priority and multi-class constraint collaborative optimization scheduling is utilized, the wafer residence time can be remarkably shortened, the overall scheduling efficiency is improved, and the method can be used for operation inspection, evaluation and optimization of an equipment system.

The invention discloses an unmanned ship autonomous control method and system based on a standard world model with a body, and relates to the technical field of intelligent ships and autonomous control. The method comprises the following steps: receiving and analyzing a natural language task instruction; driving a standard automaton to run based on the task target, the constraint condition and the maritime affair rule, and generating a standard embedding vector; constructing a body specification world model, and combining the physical hidden state of the multi-source observation code with the specification embedding vector to form a unified body specification hidden state; the hidden state is used as input, a control strategy is solved by adopting a safety reinforcement learning algorithm, and the algorithm strictly meets a safety threshold value while maximizing long-term task return by converting a maritime rule into an independent constraint cost function and performing Lagrange optimization; and finally executing a control instruction and updating the model and the automaton in a closed loop manner. According to the method, standard knowledge is deeply embedded into a world model and a decision process, and safe, efficient and explainable autonomous control of the unmanned ship in a complex maritime environment is realized.

The invention discloses a quantum key distribution system and method. According to the system, a phase coherence monitoring mechanism is innovatively introduced, and early attack detection is realized through a dynamic consensus sampling protocol; a zero-trust relay network is constructed by adopting a wavefront fragmentation principle, and trust dependence on relay nodes is eliminated; self-adaptive safety monitoring is realized based on a finite state automaton, and a system safety strategy is dynamically adjusted. According to the method, the problems of resource consumption type attack, relay trust dependence, static protocol limitation and the like faced by an existing QKD system are solved through a strict mathematical framework, and long-distance quantum key distribution with efficient resources, endogenous security and elasticity and physical layer security guarantee is realized. Experiments show that compared with a traditional scheme, the detection delay of the system is reduced by about 38%, the resource waste is reduced by about 40%, and the availability of the system reaches 99.995% or above.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a computer network intrusion detection method and system based on artificial intelligence, and the method comprises the steps: constructing a finite state automaton to carry out the state jump compliance verification of a connection flow, intercepting the illegal flow, only sending the compliance flow into a feature engineering module, and extracting the multi-dimensional behavior features; inputting a deep neural network classification model to determine whether the behavior is an intrusion behavior; according to the technical scheme provided by the invention, the data input to the artificial intelligence model can be ensured to have complete compliance on the protocol level, so that the model is prevented from learning false feature association caused by protocol violation, and the antagonistic attack based on protocol state jump can be effectively resisted on the premise of not depending on adversarial training.

A framework for easy development of a machine learning solution is provided. The framework includes connecting data sources at all scale levels from a user; assessing data schema, data risk, and data quality status; performing scalable feature engineering and transformation; and automating machine learning model optimization. The framework also includes functionalities for generating production code and automatic model documentation.

The utility model relates to the technical field of positioning and clamping, in particular to an automatic machine pneumatic positioning and clamping mechanism which comprises a workbench. The left side of the top of the workbench is connected with a first mounting frame, the right side of the first mounting frame is connected with a first sliding mechanism, the right side of the first sliding mechanism is slidably connected with a first lifting mechanism, the front face of the first lifting mechanism is connected with an L-shaped plate, and the inner side of the L-shaped plate is connected with an air cylinder. By arranging the air cylinder, the limiting block, the sliding block and the clamping plate, when the air cylinder is started, air enters the air cylinder through the first air hole or is exhausted from the air cylinder through the second air hole, and the piston can move up and down under the action of air pressure; the piston can pull or push the sliding blocks on the two sides to move towards the inner side or the outer side through the connecting rod, the lifting plate and the hinge rod, the sliding blocks can drive the clamping plates to clamp or loosen the coils, the air cylinder is rapid in response compared with motor driving, the time for stacking each coil on the bracket body can be shortened, and the coil stacking efficiency is improved. Therefore, the coil production efficiency is improved.

This application relates to the field of data processing technology and discloses a method and system for Chinese word segmentation and semantic unit parsing based on rule enhancement. The method includes: constructing a multi-level domain rule base from forced matching rules, pattern template rules, and context constraint rules to generate a set of rule triples; loading the set of rule triples into an AC automaton to linearly scan the input text to obtain a set of candidate segments and trigger word position indices; constructing a candidate directed acyclic graph, and obtaining a structured word segmentation sequence and a pruned candidate pool through dynamic programming after dynamic modulation and fusion scoring; verifying the integrity of downstream slots, and locating backup candidate edges in the pruned candidate pool using gap signals when failure occurs, and obtaining a corrected word segmentation sequence through renegotiation and scoring. This application improves the completeness of professional terminology recognition in professional vertical scenarios and the self-correction capability of cross-domain word segmentation results.

Provide a system. 【Solution means】 Means for receiving unstructured data including unclear points, Means for analyzing the received unstructured data and extracting relevant information, Means for searching past materials based on the extracted relevant information, Means for generating a plurality of information sets based on the search results, Means for assigning reference information to each generated information set, Means for presenting a plurality of information sets to the user, Means for displaying an information set on a device for controlling an industrial automation machine, A system including the above.

The utility model relates to connecting equipment technical field, concretely to a kind of USB Type-C female seat assembly type double-row injection molding connector, comprising: upper row terminal;Injection molding semi-product, upper row terminal and injection molding semi-product can be assembled buckling to form plug-in piece by automatic machine, injection molding semi-product includes middle clamping piece and lower row terminal, middle clamping piece and lower row terminal can be by injection molding;Injection molding semi-product is provided with terminal slot for upper row terminal pressing buckling on, and upper row terminal can be buckled into the terminal slot of injection molding semi-product;Injection molding semi-product and upper row terminal secondary injection molding can form connector product with shell.The utility model is equipped with the plastic groove position matched with upper row terminal on injection molding semi-product, 12pin upper row terminal is buckled into plastic groove position, molding reduces frequency, makes tongue piece head not to use glue point, reduces injection molding frequency, only twice injection molding MD can be molded, compared with three times injection molding in traditional technology, it is more efficient, and appearance is more neat.

An artificial intelligence system can be implemented to identify relationships through the propagation of ripple patterns through a grid. In such a system, the grid may comprise cells which operate as cellular automata. Relationships may be identified based on collisions of signals detected by the cells in the grid, and, when a relationship is identified, it may be used to create high speed connections between cells.

The invention discloses a PUF (Physical Unclonable Function) circuit based on a memristor cellular automaton and a use method thereof, and belongs to the technical field of integrated circuit design and information security, the circuit comprises a first cellular initialization module, a second cellular initialization module, 2N cellular node modules, 2N-bit excitation signal input terminals, 2N-bit response signal output terminals, and power supply terminals VCC, VDD, VEE and GND, the 2N cellular node modules are connected end to end to form an annular array, N is an integer which is a positive integer multiple of 4, and each cellular node module comprises a Rule30 logic module and a cellular module, so that the problems of high hardware overhead, poor expandability and insufficient attack resistance of a traditional PUF (Physical Unclonable Function) are effectively solved; the circuit structure is simplified; the hardware resource consumption is reduced; and the flexible expansion of response bits is supported.

The invention discloses a rock mass parameter inversion method and system based on automatic machine learning, and the method comprises the steps: obtaining temporal and spatial change features from rock mass monitoring data, constructing a feature importance evaluation system, and obtaining a standardized feature vector; according to the coordinated parameter transmission and model synchronization result, rock mass strength and deformation parameters are obtained, a correlation analysis model is adopted to calculate a safety coefficient and a damage probability, and a harmfulness evaluation index is obtained; the method comprises the following steps: acquiring a parameter distribution rule and a change trend, constructing a parameter database system for classified filing and version control, obtaining centralized management platform data, extracting historical tracing information, triggering a dynamic adjustment inversion strategy if the change trend exceeds a preset threshold, and obtaining a real-time updated parameter statistical analysis result for integrated risk prediction. According to the method, the accuracy of rock mass parameter inversion and the real-time performance of engineering risk prediction are remarkably improved, the slope damage probability is reduced, and engineering safety and efficient management are ensured.

Embodiments include an automatic set top box placement (STB) process and system that balances video playback needs against the performance characteristics of individual devices and the communications system. For video playback, this involves maintaining required sustained data rates needed to support video of various levels of quality and resolution and matching these against the capacity of the Wi-Fi system in terms of channel capacity and gateway / Access Point to STB connection quality. An intelligent network controller calculates the STB total airtime. Each STB is associated with a Service Set Identifier (SSID) that the controller uses to identify the STB clients. The controller calculates the End-to-End PHY rates for each client. The total STB airtime can then be calculated and compared to the default allocation for the STBs. Recommendations regarding moving STBs, gateways, and or satellite / booster devices can then be provided to the user.

The application relates to the technical field of power system dispatching, and discloses an intra-day forward-looking dispatching fast solving method considering large-scale new energy cluster power generation fluctuation, which comprises the following steps: S1: new energy cluster space-time fluctuation scene generation based on neuron cellular automata, S2: power grid dynamic security domain definition and simplification based on physical information neural network, S3: dispatching fast optimization solving based on model prediction path integral, and S4: dispatching scheme dynamic elasticity and stability evaluation based on the theory of Koopman operator. The new energy cluster space-time fluctuation scene generation method based on neuron cellular automata can effectively generate a space-time scene reflecting the large-scale new energy cluster power generation fluctuation, support uncertainty analysis, has the advantages of high calculation efficiency and scene authenticity, and solves the problem that the traditional statistical model ignores space-time coupling, thereby causing inaccurate scene generation.

An unsafe location enumeration unit (131) enumerates, based on a code of a program, locations that do not satisfy a predetermined condition indicating that type conversion is safe among locations where a type casting occurs in the program. A context extraction unit (132) transition an automaton corresponding to the locations enumerated by the unsafe location enumeration unit (131) and extract a context reaching the locations. A vulnerability verification unit (133) verifies whether the location extracted by the context extraction unit (132) satisfies an annotation prepared in advance.

The invention relates to the technical field of operator overflow control, in particular to an AI processor operator overflow optimization method and system.The method comprises the steps that a finite automaton is introduced into numerical values for state combination and sorting, a continuous state sequence covering an operator execution stack is generated, and an intermediate result obtains a state number carrying bit width section information and stack position information at the same time; the method comprises the following steps of: setting a section to which an intermediate value of each operator belongs to a discrete identifier in a fixed-point space, executing weighted truncation reduction transformation by introducing a graph neural network, and deducing a clipping weight under topological connection constraints among the operators, so that the intermediate value of each operator obtains differential correction strength in a longitudinal accumulation direction and a transverse link direction at the same time; an operator correction set is generated by guiding an intermediate numerical value through a clipping weight, so that the effective dynamic range utilization rate after right shift and truncation are matched and reduced is improved, and the stability and repeatability of a reasoning process in a long-chain accumulation scene and the tracking capability of an abnormal calculation behavior are enhanced.

The present invention relates to the device and method of automatic transport and delivery of travel baggage, and this invention contains two devices connected in some form (1) so that the first main device calls the travel baggage from the warehouse after the traveler's request, either through a smart phone application or through the reader on the device, and the device summons the passenger's baggage, transports and sterilizes it through the second device until it reaches the first delivery device, at which point the device sends a notification to the traveler stating that his baggage has arrived and that it is ready to be received.

The utility model relates to the technical field of maintenance tools, in particular to a railway vehicle air automaton maintenance tool which comprises a unified storage mechanism, the unified storage mechanism comprises a tool box, a tool storage box, a classification assembly, a part storage disc and an auxiliary assembly, and when an air automaton is maintained, the tool box is opened, and the part storage disc is taken out; the auxiliary assembly is installed on one side of the tool box, an internal hexagonal wrench is selected and taken from various tools separated by the classification assembly in the tool storage box to disassemble the air automaton, other taken parts are placed in the part storage disc, and then the specific condition of the air automaton is observed in an auxiliary mode through a glare flashlight. And the inside of the air automaton is cleaned by tools such as a brush and the like, so that the problems that the existing railway vehicle air automaton overhauling tools are generally used in a scattered manner, cannot be stored in a unified manner and are inconvenient to use when the air automaton is overhauled are solved.

The utility model discloses an integrated USB B-type male seat iron shell structure, relates to the technical field of USB B-type male seat assembly, and provides the following scheme aiming at the problems that manual assembly connection is needed in the prior art, the assembly mode is long in time consumption and easy to cause assembly errors, the integrated USB B-type male seat iron shell structure comprises a shell and a plug rubber core assembly, the shell is designed in an integrated structure, and the plug rubber core assembly is arranged in the shell. The shell comprises an iron shell and a connecting plate, a local connecting material is connected between the iron shell and the connecting plate, the local connecting material is used for driving the connecting plate to be folded upwards, the plug rubber core assembly is connected to the interior of the shell, and the plug rubber core assembly and the iron shell in the shell are mutually clamped and fixed. An automatic machine only needs to pull up the riveting claw to bend the connecting plate and then push the plug rubber core assembly to complete assembly, so that the assembly efficiency is remarkably improved, and the labor cost is reduced.