12 results about "Cellular automaton" patented technology

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.

The invention discloses a wetland nitrogen cycle optimization method and system based on machine learning, and belongs to the technical field of ecological engineering.The method comprises the steps that according to a comprehensive environment data set, a transverse lateral infiltration path and a vertical priority flow path are recognized, spatio-temporal evolution simulation is conducted through a cellular automaton model, and a nitrogen migration path is constructed; analyzing the interaction between the water flow driving flux and the underground water level on the path resistance, and determining the broadening degree of the transverse lateral seepage path; if the widening degree exceeds a preset threshold value, integrating the water body turbulence intensity data and the flow velocity shear effect value, and obtaining a bubble escape rate and a surface sediment disturbance frequency; calculating the nitrogen saturation and the spatial distribution of the sediment particle suspension amount, and obtaining the total re-release flux through flux overlay analysis; and constructing a nitrogen loss flux model in combination with the fluctuation rule, simulating the change of the nitrogen loss proportion, and determining the net nitrogen loss flux. According to the invention, fine monitoring of the dynamic change of wetland nitrogen can be realized.

The method may comprise determining a geometry of a stockpile based on the haulage data, engineering drawings and material characteristics; predicting, by the one or more processors using an algorithm implementing a cellular automaton, material movements within the stockpile, based on the geometry of the stockpile, physical parameters of the material movements and emergent rules for the material movements; predicting material movements exiting the stockpile, based on the material movements within the stockpile; predicting, using a concentrator transit model, the material movements across a comminution process in a concentrator, based on material movements exiting the stockpile; and optimizing mining operations based on the knowledge of the material movements through the comminution process. A determination of the material movements may include a determination of the material characteristics of the material.

The invention relates to a method for determining thermal properties of a printed circuit board by means of a thermal cellular automaton model, comprising the following steps: modeling the printed circuit board in the thermal cellular automaton model in such a way that the printed circuit board is divided into individual cells (1, 2, 3), each cell (1, 2, 3) being implemented as a cellular automaton; defining a plurality of thermal states for each cell (1, 2, 3) such that each cell (1, 2, 3) is in one of said states in each time step; defining a rule based on the Fourier thermal conduction law, and according to the rule, determining the state of each cell (1, 2, 3) in each time step; and ascertaining the state of all cells (1, 2, 3) in parallel step by step in order to ascertain the thermal properties of the circuit board in real time. The invention also relates to a control device, a computer program product and a computer readable storage medium.

The invention discloses a coal mine fire extinguishing intelligent command method, a coal mine fire extinguishing intelligent command system, coal mine fire extinguishing intelligent command equipment and a computer readable storage medium. The method comprises the following steps: acquiring underground multi-source heterogeneous data, performing space-time alignment and fusion processing, and constructing a data basis for reflecting a fire scene state in real time; mapping the fusion data to a pre-constructed digital twinborn model, and generating a three-dimensional visual expression of the fire scene; a cellular automaton model is utilized to dynamically predict a fire spreading trend, and an optimal fire extinguishing resource allocation scheme is generated through a scheduling optimization algorithm by taking response time and a resource utilization rate as optimization targets in combination with a current fire and a resource distribution state; and finally, the scheduling scheme is visually presented in the digital twinning scene, and a scheduling instruction is issued to a related execution unit. According to the invention, fire behavior prediction and resource scheduling are realized, and systematic technical support is provided for coal mine underground fire emergency disposal.

The invention provides a scene demand peak-valley prediction method and system based on a space-time large model, and relates to the technical field of intelligent traffic, and the method comprises the steps: obtaining multi-source heterogeneous space-time data of a target region, carrying out the non-uniform space grid division, calculating an instantaneous supply-demand ratio and a settlement price rolling fluctuation ratio, and constructing a settlement risk enhanced space-time feature tensor; inputting the settlement risk enhanced spatio-temporal feature tensor into a peak-valley prediction spatio-temporal large model, extracting features through a spatio-temporal diagram attention network fusing settlement price fluctuation features, and respectively outputting a transportation order demand prediction value and an uncertainty quantitative index by a double-branch decoder; inputting the transportation order demand predicted value and the uncertainty quantitative index into a strategy to generate a cellular automaton, simulating supply and demand propagation by dynamically adjusting state transfer resistance between cells, and generating a non-uniform distributed settlement parameter adjustment instruction; and directly outputting a settlement parameter configuration result of each sub-region in the target region based on the distributed settlement parameter adjustment instruction.

The application discloses a kind of based on the hydrophilic biological protection watershed ecological flow scheduling method and system, by comprehensively considering the final water flow velocity in target watershed and final flow direction as the first influencing factor, water conservancy engineering facilities of tributary where target watershed is as the second influencing factor, the activity range and migration route of target species are set as seed cell and organization cell, seed cell and organization cell are evolved using cellular automaton model control, and the evolution result of the target watershed is obtained;Subsequently, the ecological situation of the target species in the target watershed is determined according to the evolution result, and the corresponding scheduling strategy is selected in the resource library, and the intelligent scheduling of the target watershed is completed;To solve the technical problem that the existing technology cannot realize comprehensive scheduling in the face of whole watershed ecology, the present scheme uses cellular automaton model to comprehensively deduce the multidimensional data of whole watershed ecology, realizes the intelligent scheduling and ecological restoration of whole watershed.

The application relates to an image encryption method, which comprises the following steps: obtaining three groups of encryption keys based on a hash method and superimposing preset real number key parameters; dividing a plaintext image into P 11 , P 12 , P 13 ; making a five-dimensional double-memory-block chaotic system generate sequences to globally scramble P 11 , P 12 , P 13 ; obtaining P 21 , P 22 , P 23 ; performing cat map scrambling on P 21 , P 22 , P 23 to obtain P 31 , P 32 , P 33 ; generating sequences by the second group of encryption keys to perform block DNA operation on P 31 , P 32 , P 33 ; performing block cellular automaton operation on the block DNA operation result to obtain P 41 , P 42 , P 43 ; performing block affine transformation scrambling on P 41 , P 42 , P 43 to obtain P 51 , P 52 , P 53 ; generating sequences by the third group of encryption keys to perform finite field diffusion on P 51 , P 52 , P 53 , and then merging the layers to obtain a ciphertext image. The application can improve the system differential attack resistance, the system key space and the image data security.

The application discloses a kind of 3D printing microstructure and performance accurate regulation and control method by thermal field behavior monitoring feedback, belong to the technical field of additive manufacturing, including: step one, obtain the process parameters in the process of additive manufacturing and real-time monitoring thermal field behavior;Step two, optimize 3D thermal field model and generate a group of selected process parameters under temperature field;Step three, utilize cellular automaton coupling through the temperature field under selected process parameters generated by 3D thermal field model optimized in step two and its corresponding multi-physical field, to simulate the microstructure topography under corresponding process parameters;Step four, train microstructure accurate regulation and control model;Step five, target part printing and its microstructure distribution real-time accurate regulation and control.It can be seen from this that the application can accurately regulate the generation of microstructure, improve the overall mechanical properties of target printed parts.

The present application relates to the technical field of power internet of things security, especially to a kind of power internet of things penetration testing method based on dynamic attack surface analysis, steps are as follows: the close degree between analysis equipment and attack accessibility are determined, the state transition relationship of information domain equipment under attack is determined;The probability of each device in the information domain being affected is calculated using the cellular automaton model;The influence degree of information domain under specific attack scenario is calculated;The physical domain state of power internet of things system is monitored, and the state transition relationship of physical domain node under attack is determined;The probability of each physical domain node being affected is calculated using the cellular automaton model, and the influence degree of physical domain under specific attack scenario is calculated;Traditional attack surface calculation method only considers attack cost and vulnerability availability, the present application considers attack cost, vulnerability availability, attack on system overall influence degree three parameters to calculate attack surface, more in line with the goal of power internet of things information physical system penetration testing to find security risks.

The application discloses a lightning-caused fire spreading simulation method and system, and the method comprises the steps: acquiring multi-source spatio-temporal characteristic data corresponding to lightning-caused fire; performing feature extraction and fusion on the corresponding multi-source spatio-temporal characteristic data through a pre-constructed spatio-temporal feature fusion network, and outputting prediction parameters for representing fire state conversion; constructing a multi-state cellular automaton including a smoldering state and an open fire state, locating a lightning ignition point, initializing the state of the cell corresponding to the lightning ignition point to the smoldering state, and giving the cell corresponding to the lightning ignition point its initial thermal energy; performing phase change discrimination on the cell in the smoldering state based on the prediction parameters and dynamic time sequence characteristics; performing a neighborhood propagation rule based on vector correction based on the phase change discrimination result to simulate lightning-caused fire spreading, and outputting a simulation result. Through deep coupling of deep learning feature extraction and physical mechanism modeling, the accuracy and scientificity of lightning-caused fire simulation are significantly improved by the scheme.

The application relates to the technical field of optimization analysis systems, in particular to an agricultural land utilization efficiency optimization analysis system based on multi-source data fusion, which comprises a land block parameter integration module, a land block suitability evaluation module, an adjacent relationship correction module and a utilization efficiency optimization module.In the application, multi-source data such as slope, soil organic matter and water accessibility are standardized and integrated as land block basic parameters, a multi-factor comprehensive evaluation is realized by combining an analytic hierarchy process, land block suitability changes are reflected in detail, water and fertilizer migration and crop competition are dynamically simulated by using a cellular automaton based on land block adjacent relationships and crop compatibility parameters, the problems of uneven resource distribution and unreasonable combination are avoided, and genetic algorithm optimization is introduced after water and fertilization parameters are weighted and adjusted, so that efficient configuration of agricultural land and maximization of output benefits are realized, the scientificity of resource allocation and the spatial coordination effect are strengthened, and actual demands and resource rationality are considered.