502 results about "Cellular automation" patented technology

Method and apparatus for synthesizing high-performance linear finite state machines (LFSMs) such as linear feedback shift registers (LFSRs) or cellular automata (CA). Given a characteristic polynomial for the circuit, the method obtains an original LFSM circuit such as a type I or type II LFSR. Feedback connections within the original circuit are then determined. Subsequently, a number of transformations that shift the feedback connections can be applied in such a way that properties of the original circuit are preserved in a modified LFSM circuit. In particular, if the original circuit is represented by a primitive characteristic polynomial, the method preserves the maximum-length property of the original circuit in the modified circuit and enables the modified circuit to produce the same m-sequence as the original circuit. Through the various transformations, a modified LFSM circuit can be created that provides higher performance through shorter feedback connection lines, fewer levels of logic, and lower internal fan-out.

The invention discloses a traffic region dynamic map monitoring and predicating system and belongs to the field of traffic flow monitoring. The traffic region dynamic map monitoring and predicating system comprises a sensing module, a data management module, a map generation module, a map display module, a vehicle analog module, an authentication configuration module and a traffic flow parameter predicating module. By means of combination of a cellular automation model and an RBF (radial basis function) neural network short-term traffic flow predicating model, current jamming conditions and future jamming conditions of road sections can be computed to enable drivers to rapidly know road network situations so as to select proper roads, and accordingly running time is saved while carbon conservation and environment protection are realized. Further, traffic management personnel can know road network conditions in real time and be aware of specific traffic parameters and road condition videos through windows to take necessary measures.

The invention discloses a dynamic firefighting emergency evacuation indication system for a large-scale public building. The dynamic firefighting emergency evacuation indication system comprises an evacuation indication setting subsystem, a firefighting monitoring and predicating subsystem, a dynamic evacuation indication adjusting subsystem and a crowd evacuation predicating subsystem. Firstly, evacuation indication distribution in the large-scale public building is set according to the evacuation indication setting subsystem; secondly, firefighting accidents happening in the large-scale public building are considered, multiple fire detectors are used for obtaining information such as the position and the intensity of a fire, and a computer model is used for predicating the development of the fire; thirdly, the development of the fire is used for dynamically adjusting evacuation indication to ensure that the evacuation indication points to a safe area; finally, a built cellular automaton evacuation model considering the evacuation indication function is adopted to predict crowd evacuation and feeds back a predication result to the dynamic evacuation indication adjusting subsystem. The evacuation indication is corrected again according to the crowd density, the evacuation time and the like, and the evacuation efficiency is improved.

The invention provides a cellular automaton model based urban road network traffic flow simulation design method. The cellular automaton model based urban road network traffic flow simulation design method comprises the following steps of 1 establishing an urban road network consisting of a plurality of bidirectional two-lane roads; 2 establishing an on-lane vehicle update rule; 3 establishing a vehicle update rule at intersection positions and establishing a deadlock avoiding rube, wherein vehicles on the cells in the intersections and cells on the peripheries of the intersections follow different update rules; 4 distributing N vehicles in the urban road network to perform a simulation experiment, wherein the vehicles rung by following the rule in the step 2 and the rule in the step 3; 5 acquiring outgoing data of the vehicles in the step 4 and performing calculation and analysis so as to evaluate the characteristic of traffic flows of the urban road network. By means of the cellular automaton model based urban road network traffic flow simulation design method, the running states of complicated traffic flows of the bidirectional two-lane roads and the intersections can be really reflected, and the truthfulness of traffic simulation can be improved.

The invention discloses an RGBD image salience detection method based on a hypergraph model. The method includes conducting hyperpixel segmentation for a color image to be detected and a depth image, calculating neighborhood depth contrast graphs for each hyperpixel area of the depth image, constructing a depth background hyperedge according to neighborhood depth contrast ratio, extracting hyper pixel areas on the boundary of the image to construct a boundary background hyperedge, calculating the weight of the two hyperedges, expanding hyperedges according to a hypergraph learning algorithm, building an induce graph, prior calculating boundary background salient map by using the boundary connectivity based on the spatial adjacent relation of the induce graph and the edge weight, and obtaining a final salient detection map based on salience degree updating algorithm of cellular automaton and a fusion algorithm in combination with depth prior. Deficiency of conventional 2D boundary background prior is overcome. The improvement is made based on depth information and a hypergraph model, and better effects are achieved than a conventional image salience detection method that combines color and depth information.

The invention relates to an indoor emergency evacuation simulation method for a complex building. According to the method disclosed by the invention, a three-dimensional extended hierarchical node relation model (EHI-NRM) of an internal space unit of the complex building is automatically generated, and the update of a dynamic path of a large-scale complex building is supported; an improved cellular automaton model (ICA) can better simulate jam, avoidance, mass-following and other phenomena of a large-scale crowd during the evacuation process; and an optimal evacuation path is searched in real time in the macro-level through an EHI-NRM dynamic path-finding method, and the ICA is applied in the local level for simulating the behavior characteristics of the crowd. According to the method disclosed by the invention, the evacuation simulation of the large-scale crowd in the large-scale complex building is supported, and the method has important application values for ensuring the safety of staff in the building and improving the decision-making capacity of an emergency rescue department.

The Cellular Automata Music Generator (CAMG) is a software platform, application and engine that generates and modifies musical compositions in real-time using a system of networked modules that utilize the 1-dimensional cellular automata (CA) mathematical model. The music compositions are non-looping (i.e. the same few bars of music do not repeat over and over), can be any length, can have low memory and processing requirements compared to looping WAV or MP3 files, and follow psychoacoustic principles. The music generated is ever evolving and can be globally altered based on one-parameter change. The music engine can be utilized in computer games or to generate unique ringtones or any musical composition for cell phones or other mobile devices based on ten-digit inputs, such as telephone numbers. The ringtones or musical pieces can be generated automatically based on the telephone number of the in-coming telephone call, or manually by the user, who inputs a selected numerical sequence. It can also be used as an audio caller identification system.

The invention belongs to the technical field of harbor road design and relates to a cellular automata based design method of circular curve elements of bends of harbor roads. The method comprises the following steps: preliminarily determining the radius ranges and the arc length ranges of the circular curves to be designed; determining the maximum speeds and acceleration and deceleration probability of the vehicles by analyzing the safety and the comfort and treating the safety boundary conditions; establishing a simulation model of the cellular automata, determining the maximum speeds and acceleration and deceleration probability of the vehicles and designing car-following and lane-changing rules of the vehicles; and simplifying the types of the vehicles, converting the types of various vehicles into a single type, simulating the traffics in the harbor districts by changing the radii and the arc length of the circular curves of the bends of the harbor roads according to the established simulation model of the cellular automata, evaluating the simulation result and investigating whether the design scheme can meet the requirement of the traffic capacity. Compared with the traditional method, the design method of the invention has the advantage that the design scheme of the line shapes of the bends in the harbor districts is further consistent with the traffic characteristics in the harbor districts.

The invention relates to a self-organization method of urban traffic control signal based on fluid dynamics, belonging to the technical field of traffic engineering. The invention takes an urban traffic control signal system as transportation network processing, and every crossing is taken as an intelligent body having the functions of autonomous collection and information processing and simultaneously has two sets of cellular automaton for evolution to realize dynamic decision of the traffic signal control at every crossing; on the other hand, by utilizing the natural similarity between traffic flow and fluid flow, the fluid dynamics is introduced based on the cellular automaton to set up equilibrium model of the traffic flow; meanwhile, urban traffic signal self-organization control regulation based on quaternary-phase sequence switch is set out, and traffic crossing phase position decision rule is correspondingly set out, thereby realizing real time decision of a traffic system signal mode. The invention solves the problems of nondeterminacy and unbalanced traffic flow existing in the urban traffic control, so as to improve the performance and real-time property of the urban traffic control system.

The Cellular Automata Music Generator (CAMG) is a software platform, application and engine that generates and modifies musical compositions in real-time using a system of networked modules that utilize the 1-dimensional cellular automata (CA) mathematical model. The music compositions are non-looping (i.e. the same few bars of music do not repeat over and over), can be any length, can have low memory and processing requirements compared to looping WAV or MP3 files, and follow psychoacoustic principles. The music generated is ever evolving and can be globally altered based on one-parameter change. The music engine can be utilized in computer games or to generate unique ringtones or any musical composition for cell phones or other mobile devices based on ten-digit inputs, such as telephone numbers. The ringtones or musical pieces can be generated automatically based on the telephone number of the in-coming telephone call, or manually by the user, who inputs a selected numerical sequence. It can also be used as an audio caller identification system.

The invention relates to a method for predicting structure evolution of austenite dynamic recrystallization in thermal deformation of plate-strip steel, which belongs to the technical field of steel rolling. The method achieves the predictions of the transformed fraction, the grain size, the grain morphology and the flow stress of dynamic recrystallization by establishing a dynamic recrystallization physical metallurgical model and a dynamic recrystallization cellular automation model. The method achieves the reproduction of the structure evolution of a metal forming process by a computer, not only can save the experimental cost, but also can accelerate the development cycle of a new type of steel. The developed method for predicting the structure evolution of the austenite dynamic recrystallization in the thermal deformation of the plate-strip steel achieves the quantitative, precise and visual descriptions of the grain morphology, the volume fraction and the grain size of the recrystallization process, and can obtain important parameters of the flow stress and the like, thus the method is significant in further analyzing the evolution law of microstructures.

A method for simulating urban land use change merges an idea of dynamic neighborhood into a cellular automation and a Monte-Carlo model and regulates a range of local neighborhood according to different cell state distribution and by a Monte-Carlo method, so that the problems of spatial-dimension uncertainty and time-dimension randomness of urban land use change are solved, and simulation of the urban land use change is implemented. The method includes: acquiring and preprocessing data; determining cell size, cell state and iteration time according to a classification chart, and using the Monte-Carlo model to determine the range of dynamic neighborhood; establishing a land use change simulation system based on the Monte-Carlo model and the cellular automation model; using the land use change simulation system to simulate and predict by the Monte-Carlo method and the cellular automaton method; and analyzing a land use structure based on simulation results. By the method, the problem of uncertainty occurring in simulation of urban land use change is solved, and simulation effect and precision are improved.

The invention provides a method for predicting coupling responses of isothermal forming and dynamic recrystallization evolution of titanium alloys. Grain stress responses, intercrystalline non-uniform deformation and non-uniform dislocation density caused by intercrystalline non-uniform deformation are obtained in an isothermal forming process of the titanium alloys and are adopted as variables and transmitted to a cellular automaton, dynamic recrystallization evolution of the grain size under the condition of non-uniform size deformation is obtained, and dynamic recrystallization nucleation and grown structure morphology as well as grain boundary evolution and updated dislocation density which are caused by the dynamic recrystallization nucleation and grown structure morphology are obtained. The obtained grain and grain boundary information including dynamic recrystallization nucleation and growth as well as the dislocation density is returned to a crystal plasticity finite element method, dislocation gliding resistance of each grain unit is updated, so that subsequent deformation of the titanium alloys is influenced, and the stress responses of the grain size are calculated according to the constitutive relation. The method realizes synchronous prediction of non-uniform deformation of the grain size in isothermal forming of the titanium alloys, dynamic recrystallization structure morphology evolution, recrystallized grain size evaluation, recrystallization kinetics, deformable bodies and grain flow stress.

An embodiment generally relates to systems and methods for enhanced cellular automata (CA) models. A processing module can generate a traffic model that comprises a set of vehicles. The traffic model can be processed according to the enhanced CA model. In particular, a perceived gap between vehicles in the set of vehicles can be identified. Further, a subsequent velocity of a following vehicle can be calculated based on metrics such as a maximum velocity, the perceived gap, and various time components.

The invention belongs to the field of virtual geographical environment research of a geographic information system, particularly relates to an outburst flood routing simulation and analysis technique, and relates to a cellular automata based rapid outburst flood routing simulation and analysis method. By the method, the problem that an error between a final numerical analysis result and actual water regimen is large due to randomness of cellular scale partitioning at present can be solved; meanwhile, accurate and rapid comprehensive simulation and analysis can be performed on dam-break flood routing and influences by means of reasonable setting of a cellular neighborhood range and combination of spatial analysis capacity of a GIS (geographic information system) and spatial-temporal modeling capacity of cellular automata simulation. The method includes construction of a two-dimensional cellular automata simulation model, optimization of a cellular spatial data structure and virtual geographical environment based visual simulation and analysis.

The method treats city traffic signal control system as traffic network as each crossing is an agent which has function of information self-collecting and self-processing. The system can realize dynamic decision for traffic signal control at each crossing by relying on network self-organization. The attribute matrix is used to express state information for local and adjacent crossing with using relative bearing for connected crossing. The system is established to be virtual network model with cellular automara features so the self-organized control for traffic signal can be realized by carrying on dynamic migration of crossing signal state under control rule driving.

The invention discloses a cellular automaton urban growth simulating method based on the random forest. According to the method, based on the random forest algorithm, in the generation process of a decision-making tree, random factors are introduced into candidate space variables produced when sample sets and split nodes are trained; a transformational rule of an urban growth cellular automaton model is extracted and can be used for simulation and prediction of urban growth. The method has the advantages that prediction accuracy is improved on the premise that the operation amount is not obviously increased; the method is not sensitive to multicollinearity, the over-fitting phenomenon does not easily occur, and the method is well tolerant of the random factors in urban growth; error estimation outside a bag can be conducted, and model parameters can be rapidly obtained; space variable importance can be measured, and the effect of each space variable in urban growth is explained.

The invention provides a traffic flow cellular automaton modeling method under a car networking environment. The traffic flow cellular automaton modeling method is applicable to vehicle operation rules under the car networking environment, and automaton modeling simulation is combined for realizing simulation on traffic flow, so that traffic flow characteristics are analyzed. On the basis of a Nasch model, characteristics of the car networking environment are combined, single lane operation rules are established, road operation conditions are simulated; and then a double lane model is built, and road traffic condition is more really reflected. The novel method provided by the invention has the advantages that prediction on speed and lane changing condition of a preceding vehicle is added, the traffic flow in a traffic scene can be effectively simulated, and traffic simulation reality is improved; and results show that a vehicle under the car networking environment has higher operation speed, road capacity is greatly improved, and traffic condition is improved.

The invention discloses a system and a method for predicting a forest pest disaster. The system mainly comprises a forest pest disaster prediction model module, wherein the forest pest disaster prediction model module comprises a geographical cellular automata model, an artificial neural network model and a multi-agent model; each cell in the geographical cellular automata model represents a geographical area and has a cell state which is used for representing disaster degree and one or more cell attributes which are used for representing disaster influence factors; a state conversion rule is acquired by training the artificial neural network model; the input of the artificial neural network model is the disaster influence factors, and the output of the artificial neural network model is the disaster degree; the multi-agent model comprises a human activity influence agent which is used for representing influence of human activity on the cell state, and a pest population change agent which is used for representing the dynamic evolution process of a pest population; and analysis results of the agents are integrated with the current cell state to obtain the updated current cell state.

The present invention discloses a rule mining based flight arrival and departure cooperative scheduling method and belongs to the technical field of flight scheduling. The method comprises the steps of: firstly, analyzing historical operating data of a target airport, performing mapping modeling by applying an artificial neural network, and extracting out operation modes and rules of the airport under weather conditions in different seasons; and then establishing a flight arrival and departure cooperative scheduling model, designing a dynamic optimization algorithm by combination with a cellular automaton, performing optimized sequencing on arrival and departure flights, and inputting an updated scheduling scheme according to real-time data. The method takes the characteristics and interacting factors of the arrival and departure processes of the flights into comprehensive consideration; and meanwhile, with reference to different operation modes, obtained by performing rule mining on the historical operating data of the target airport, of the target airport under different conditions, a flight arrival and departure scheduling model that is more comprehensive and closer to actual scheduling is established, so that the arrival and departure of the flights can be ensured to more efficient.

The invention discloses a mine fire escape route cellular automaton optimizing and guiding method, and belongs to mine fire safe escape methods. An underground monitoring subsystem, a smoke plume migration simulation subsystem, an escape route selection subsystem and a rescue and escape command guiding subsystem are included, and the monitoring system is composed of a ground central station and various underground sensors and monitors temperature, gas and flue gas parameters in real time; the smoke plume migration simulation system simulates dynamic evolution rules of underground fire smoke through FDS software; the escape route selection subsystem applies a cellular automaton for building a mathematical physical model under the mine ventilation network structure actual condition, dynamically quantizes the complex roadway environment and the smoke pollution range, calculates the escape efficiency and determines the best escape route; the rescue and escape command guiding subsystem provides guidance for underground escape persons on the basis of the escape route calculation result, and the best escape route is fed back to underground workers by means of an upper computer and an underground voice alarm system, the escape efficiency is comprehensively improved, and casualties are reduced to the maximum extent.

The invention relates to an image encryption algorithm based on memoristor hyper-chaotic system, cellular automaton and DNA calculation. First of all, a four-dimensional memoristor hyper-chaotic system based on a Chua circuit is employed, at the same time, a secret key is generated by enabling a plaintext image on an SHA256 function; a pseudo random sequence generated by the chaos system is taken as a basis of DNA dynamic encoding, rules of cellular dynamic evolution are determined according to a DNA matrix after diffusion, and in an encryption process, partitioning processing is performed on the image; and finally, the image is encrypted through a pseudo DNA calculation method, and diffusion operation is carried out while the image is scrambled. According to the invention, on one hand, secret key space is increased and the capability of the algorithm in fending off violent attacks is enhanced; and on the other hand, the secret key is enabled to be generated through close reliance on a plaintext, the capability of the algorithm in fending off plaintext attacks is improved, the capability of fending off exhausive attacks is higher, parallel calculation is facilitated, the operation efficiency is further improved, and the security of the algorithm is improved.

The invention discloses a scheduling method for an export container wharf pile-up space. Two-stage modeling is performed from plan allocation to dynamic allocation. At a pre-allocation stage, a block plan is researched, and the follow-up dynamic allocation is guided by the block plan. In the block plan, a block allocation model based on the ecological neutral theory is proposed. According to the block allocation model, container blocks are abstracted as islands, and container groups are abstracted as species, and thus, a process of allocating the container groups to the container blocks is escaped into a process that ecological selection is performed on the islands by a plurality of species. Based on the block allocation model, by aiming at the characteristic of the block plan problem, the block allocation model is optimized by the scheduling method for the export container wharf pile-up space, and an improved ecological neutral theory model is proposed. At a dynamic allocation stage, yard bay allocation and container space allocation are combined, solving is optimized by bi-objective combination, and a combination cellular automaton model is proposed. According to the combination cellular automaton model, the yard bay allocation is abstracted as an external cellular model, and the container space allocation is abstracted as an internal cellular model.

Disclosed is an apparatus and method for estimating a state of charge (SOC) in a battery, in which the battery SOC is estimated using a fusion type soft computing algorithm, thereby accurately estimating the battery SOC in a high C-rate environment. The apparatus includes a detector unit for detecting current, voltage and temperature of a battery cell; and soft computing unit for outputting a battery SOC estimation value of processing the current, the voltage and the temperature detected by the detector unit using a radial function based on a neural network algorithm. Especially, the soft computing unit combines the neural network algorithm with any one of a fuzzy algorithm, a genetic algorithm (GA), a cellular automata (CA) algorithm, an immune system algorithm, and a rough-set algorithm, and thereby adaptively updates the parameters of the neural network algorithm.

The invention relates to a deep learning cellular automaton model-based soil moisture content prediction method. According to the method, a machine learning and geographical phenomenon simulation are used in combination; different time-space prediction aspects of soil moisture content are improved; a soil moisture content prediction function local optimal solution can be obtained by means of deep learning; and a quantitative test is performed on the generalization ability of the model through using a model inspection mechanism, and a self-improvement mechanism of a cellular automaton is put forward, and therefore, the robustness of the model can be ensured better. The hybrid technology provided by the invention is expected to provide technical support for soil moisture content real-time monitoring in complex regions. With the prediction method adopted, prediction cost of the soil moisture content can be reduced, and prediction accuracy of the soil moisture content can be significantly improved. The prediction method has a wide industrial application prospect.

The invention relates to a frequency domain analysis method of bridge fatigue life on the basis of a dynamic weighing system. The frequency domain analysis method comprises the following steps: collecting data including the vehicle weight, the vehicle speed and the axle distance of each vehicle which passes through a bridge; calculating the collected data, and carrying out curve fitting; according to a fitting probability density curve, establishing a cellular automata simulation model of the vehicle, and generating a random traffic flow; simulating load time history under different vehicle flow density conditions, and loading the load time history to a bridge influence line to obtain stress time history data; carrying out FFT (Fast Fourier Transform) on the stress time history, obtaining PSD (Power Spectral Density), and calculating relevant parameters; using a Dirlik method to establish an experience form of a PDF (Probability Distribution Function); and calculating residual service life. Calculation time is greatly shortened.

The invention belongs to the field of transportation station planning, design and management, and aims to create a behavioral simulation model of mutual linkage of wharf stockpiling volume and berthing capability and research positive and negative influences of stockpiling volume planning of a wharf storage yard on actual wharf loading and unloading efficiency and actual wharf cargo handling capacity so as to acquire a realistic internal nonlinear causal relationship to search a reasonable matching method for the wharf stockpiling volume and the berthing capability. The technical scheme includes that a microscopic simulation method for matching the wharf stockpiling volume and the berthing capability includes the following steps of cellular selection, operation of a cellular automation, establishment of a basic frame of a microscopic simulation frame for matching of the wharf stockpiling volume and the berthing capability, cargo congregation, cargo evacuation and establishment of evaluation indexes, a port road traffic volume forecast module, a port road network module, a container terminal storage yard module, a shipside shipment module and a shipside unloading module. The microscopic simulation method is mainly applied to the transportation station planning, design and management.

The present invention proposes and discloses a method for dynamically simulating a land future use scenario. The method integrates a capability that a cellular automaton (CA) simulates a complex systematic space-time evolution process and an advantage that a CLUE-S model simulates multiple types of land use type competitions; and the method overcomes certain inherent defects of a traditional CA or a pure CLUE-S model through advantage integration; in addition, intelligent computation of a distributional probability is realized by adopting an artificial neural network (ANN) algorithm; synchronous simulation of multiple land use changes is realized by introducing a competition mechanism of a roulette, so that the new method is more suitable for multiple types of land use data; and moreover, compared with a traditional model, the method has the practical advantages of higher precision, suitability for multiple scales, low data demand, few parameters, simple and convenient operation, high speed and the like. According to the method for dynamically simulating the land future use scenario, the intelligent algorithm (ANN) and the uncertainty model (the roulette) are effectively combined; and the method is applied to the prediction of the land future use scenario.

The invention discloses a traffic flow modeling method of an unmanned vehicle and belongs to the field of unmanned driving. The method comprises steps that on the basis of analyzing factors that affect the traffic of the expressway, a traditional traffic model based on the differential equation is established; the relation map of the number of lanes affecting the average daily traffic flow in the average period and the peak period is made; the unmanned vehicle hypothesis and the classical Gipps safety distance rule are introduced; the NaSch model is improved; the automatic driving cellular automaton traffic flow model is proposed based on the safe distance; the new control method based on the spring damper is used to analyze the cooperation between the multiple vehicles; and finally the sensitivity detection is performed by increasing the reaction time of the unmanned vehicle from 0.1s to 1s. The traffic flow modeling method of the unmanned vehicle is introduced to improve the traffic safety and solve the traffic jam.