42 results about "Theory model" patented technology

The invention discloses a method for analyzing the vertical dynamic response of an end-bearing pile in a double-layer foundation, which adopts a theoretical method, regards a soil body around the pile as a viscoelastic continuous medium, deduces a calculation formula for determining the vertical dynamic stiffness of the end-bearing pile in the double-layer foundation by using the analytical method based on a proposed theoretical model, and calculates the vertical dynamic response of the end-bearing pile in the double-layer foundation by substituting related parameters. The image drawn according to the obtained result can accurately describe the characteristics of the dynamic response of the end bearing pile in the double-layer foundation under the action of the vertical dynamic load, the analysis method for the vertical dynamic response of the end bearing pile in the double-layer foundation is simple, convenient and efficient, the calculation result is specific and clear, and beneficial reference can be provided for engineering design of the end bearing pile in the layered foundation.

The invention relates to the technical field of production process control, in particular to an MES system management and control method and system based on precision mold production and manufacturing, and the method comprises the following steps: obtaining a measurement point cloud and a theoretical model, calculating rigid body transformation matrix registration to generate a registration point cloud, searching a nearest projection point, measuring geometric deviation, and constructing a three-dimensional deviation vector; and calculating the actual residual material thickness, screening and generating margin insufficient risk points, analyzing a numerical control code to extract a coordinate instruction, retrieving a nearest risk point, calculating a compensation distance, and adjusting coordinates to generate a self-adaptive finish machining program. According to the method, the three-dimensional deviation vector is constructed to represent the entity state, the risk area is screened in combination with the machining allowance, the compensation distance is calculated according to the actual residual thickness, and the instruction is dynamically adjusted to generate the self-adaptive program, so that the path is automatically corrected according to the shape of the workpiece, and the overcut risk caused by insufficient allowance is effectively avoided; and accurate matching between the machining process and the workpiece state is ensured.

The invention relates to a source network load storage capacity planning method and system based on a multi-agent game, and the method comprises the steps: constructing a multi-agent game behavior data set, analyzing the dynamic interaction of a strategy through employing a game theory model, and obtaining the strategy preference and interaction mode of each agent; constructing a source network load storage collaborative planning model, and determining an initial capacity configuration scheme of each main body; extracting a benefit distribution proportion of each main body from the initial capacity configuration scheme, and adjusting capacity configuration by adopting a multi-objective optimization algorithm to obtain an optimized capacity planning scheme; analyzing the influence of peak demand fluctuation and transmission capacity limitation on the scheme by adopting a Monte Carlo simulation method to obtain a dynamic adaptability index of the scheme; and adjusting game theory model parameters to obtain updated strategy preferences and interaction modes, adjusting capacity configuration through iterative calculation, and generating a new capacity planning scheme. Compared with the prior art, the method has the advantages of comprehensively considering multi-main-body strategy dynamic interaction, improving the feasibility of the planning scheme and the like.

The invention belongs to the technical field of civil engineering technical construction, and particularly relates to a quantitative prediction method for engineering slurry and muck recycling output, which comprises the following steps: S1, synchronizing a construction scene in real time through BIM / GIS and Internet of Things data, and generating a virtual mirror image of a slurry / muck generation process; s2, correcting a theoretical model error according to real-time monitoring data; s3, predicting the mud / muck yield and the resource rate by adopting a time sequence analysis method and combining with a machine learning algorithm, and quantifying uncertainty; s4, dynamically optimizing model parameters through error feedback, and realizing a prediction-monitoring-correction closed loop; through cooperation of the structures, exclusive correction rules are formulated for different construction types, theoretical model errors can be corrected in time according to stratum changes and construction disturbance, and the adaptability of the model under different working conditions and the reliability of prediction results are improved.

The invention provides a method for evaluating an electricity-hydrogen comprehensive energy system. The method comprises the following steps of: constructing an evaluation standard according to a multi-dimensional comprehensive index; converting the multi-dimensional comprehensive index into a triangular intuitionistic fuzzy number, and performing normalization processing on the triangular intuitionistic fuzzy number; the subjective weight of the triangular intuitionistic fuzzy number is calculated through an optimal and worst method; the objective weight of the triangular intuitionistic fuzzy number is calculated through a CRITIC method; fusing the subjective weight and the objective weight through a game theory model to obtain a final weight; and based on the final weight, sorting the alternative schemes through a multi-attribute boundary approximation comparison method to obtain an evaluation result. According to the method, a comprehensive evaluation system based on fuzzy comprehensive evaluation is constructed, the evaluation index subjective and objective combination weighting method is constructed by introducing the game theory idea, the rationality and reliability of weight quantification are improved, and a reliable basis is provided for planning and decision making of a comprehensive energy system.

The invention provides an anchor rod shear strength prediction method and device for rock mass reinforcement, and relates to the technical field of data processing, and the method comprises the steps: constructing an anchor rod stress theoretical model based on anchor rod design data and anchor rod displacement data, and constructing the anchor rod stress theoretical model and a strength criterion to obtain a shear strength physical model; carrying out finite difference processing according to anchor rod design data and anchor rod historical monitoring data to obtain an information data sample, inputting the information data sample into a neural network for training, and carrying out optimization processing on a training result and parameters in the neural network by an improved sparrow optimization algorithm to obtain a final neural network; and predicting the shear strength of the joint surface of the rock mass reinforced by the anchor rod according to the optimization parameters and historical monitoring data in the final neural network to obtain a shear strength prediction model, and inputting anchor rod design data into the shear strength prediction model for prediction. According to the method, the problems of various parameters and complex mutual coupling among the parameters are solved, and the safety and the stability of an engineering structure are ensured.

The invention discloses a military strength resource scheduling method based on multi-objective optimization, which comprises the following steps: analyzing a strategy selection problem in a confrontation environment through a game theory model according to a resource demand matching degree and an enemy action prediction result, and if an enemy threat mode changes, triggering a self-adaptive adjustment mechanism specified by scheduling, dynamically correcting resource allocation strategy parameters by adopting a reinforcement learning algorithm to obtain an optimal scheduling rule adapted to the current confrontation situation; and calculating a resource consumption rate and supplement demand prediction according to an accurate resource allocation result, predicting a consumption trend of various resources in a future time period through a time sequence analysis algorithm, if the predicted consumption rate exceeds the supplement capability, triggering a resource allocation plan in advance, and determining an optimal resource reserve and supplement strategy by adopting an inventory optimization model. According to the method, the military strength resource scheduling efficiency and the combat effectiveness in a complex confrontation environment are effectively improved.

The invention provides a seismic peak response prediction method for a composite damping structure system. The method comprises the following steps: S1, constructing a theoretical model of the composite damping structure system; s2, deducing and correcting key parameters of the composite damping structure system, wherein the key parameters comprise an equivalent period, an equivalent damping ratio and an equivalent damping ratio correction coefficient; and S3, compound damping structure system seismic peak response derivation and nonlinear dynamic time history analysis verification are carried out, wherein peak response comprises peak relative displacement response and peak absolute acceleration response. The provided seismic peak response prediction method for the composite damping structure system does not need the processes of structural modeling, seismic oscillation screening, nonlinear dynamic time history analysis and the like, has a high-precision and efficient response prediction effect, and makes up for the defect that in a design method of a structure based on performance, the nonlinear damping degree is high and prediction is not accurate; the method is different from a'black box 'problem existing in prediction methods such as machine learning and the like, and has principle interpretability.

The invention discloses a method for measuring the difference degree between a plurality of evidence theory models, the method comprises a plurality of evidence models, a complex value distribution model, a probability distribution model and a calculation KL divergence, the plurality of evidence models comprise a plurality of basic probability distributions, the complex value distribution model comprises a complex value probability distribution, and the probability distribution model comprises a probability distribution model. The probability distribution model comprises probability distribution, and the calculation of the KL divergence mainly comprises the calculation of the KL divergence of RBetM1 and RBet2 and the calculation of the KL divergence of RBetM12 and RBet1. Through the provided mapping method, the complex evidence theory model can be mapped to a single distribution model in a real number field, so that understanding and analysis of the complex evidence theory model in the real number field are facilitated; by calculating the KL divergence in a real number field, the model can measure the difference degree between two complex evidence theory models, and the difference degree can be further practically applied.

This invention provides a method, apparatus, and storage medium for estimating the geometric parameters of a spherical cone target. The method includes: acquiring sparse echo data of the spherical cone target; determining the value range of the parameters to be estimated based on prior information of the spherical cone target, obtaining a parameter combination set including several parameter combinations; the parameters to be estimated include the base radius and the semi-cone angle; substituting the parameter combinations in the parameter combination set into a geometric diffraction theory model to obtain the RCS data of the spherical cone target; performing two-dimensional imaging and transformation processing on the sparse echo data and the RCS data respectively to obtain a first column vector and a second column vector; constructing a parameter dictionary based on the second column vector; and inputting the first column vector and the parameter dictionary into a preset optimization algorithm for iteration to obtain the estimated target parameter values. The geometric parameter estimation method for spherical cone targets provided by this solution reduces the computational load while ensuring the accuracy of parameter estimation.

A method for determining a process hole for a part connection hole in an assembly, wherein the method is based on a known theoretical model of an assembly of at least two connected parts, and a three-dimensional process tolerance simulation analysis model is established by processing the assembly theoretical model. In the simulation analysis model, the part where the connection hole to be analyzed is located is used as a reference, an assembly relationship is established, tolerances are defined, and a measurement relationship is established, and the hole center offset or the maximum interference between holes is obtained. The maximum process aperture of the connection hole on the part is then converted through the hole center offset or the maximum interference between holes. Finally, the process hole of the connection hole is manufactured in the part prefabrication stage according to the maximum process aperture.

The application discloses a kind of horizontal load friction type pipe pile top rigidity determination method, adopt theoretical method, the soil around pile is regarded as viscoelastic continuous medium, and based on the proposed friction type pipe pile theoretical model under horizontal load, the horizontal load friction type pipe pile top rigidity expression is deduced using analytical method, with rigorous logic;The influence of the resistance of soil around pile and the resistance of pile core soil on pipe pile is considered simultaneously, which is more in line with reality;By substituting relevant parameters for calculation, the image drawn according to the obtained results can accurately describe the horizontal load friction type pipe pile horizontal top rigidity under horizontal load, the method is efficient and simple, the calculation result is specific and clear, and can provide a good reference for the practical application of friction type pipe pile in pile foundation field.

The application relates to a grouting and filling mining surface subsidence dynamic prediction method, which comprises the following steps of: dividing a rectangular working face into a plurality of mining units; calculating the subsidence influence of each mining unit on any surface point by using a probability integral method; calculating a Weibull model time function value of each mining unit at a preset time; and multiplying the subsidence amount of each mining unit at any surface point and the Weibull model time function value, so as to obtain the dynamic subsidence value of any surface point affected by mining and grouting of each mining unit at the preset time. n T T The application improves the subsidence coefficient in the probability integral method according to the technical features of the mining and grouting technology of the bed separation grouting and filling mining, and simultaneously considers the influences of the mining and grouting on the surface deformation; the Weibull model with the improved subsidence coefficient is used as a theoretical model of the grouting and filling mining surface subsidence dynamic prediction, the model basis is more reasonable, and the surface subsidence dynamic prediction precision is higher.​​

This invention discloses a method, medium, and device for analyzing the influencing factors of residents' green travel behavior. Based on the theory of planned behavior and interpersonal relations theory, the method constructs a comprehensive theoretical model of the influencing factors of urban residents' green travel behavior from a static perspective. Secondly, based on a survey of 817 residents in the Yangtze River Delta region, structural equation modeling is used to empirically test the driving mechanisms of different categories of green travel behaviors among urban residents. Furthermore, a social interaction perspective is introduced, and a simulation model is constructed based on scale-free networks and opinion propagation dynamics to simulate and analyze the group response characteristics and dynamic trends of residents participating in various green travel behavior decisions under different scenario parameters. Finally, targeted policy recommendations are proposed to more effectively promote urban residents' practice of green travel.

The invention relates to the technical field of helicopter control, and discloses a display model tracking flight control method and system based on an extended state observer, and the control method comprises the steps: building a helicopter six-degree-of-freedom kinetic equation, building a helicopter pitching channel display model, and building a helicopter pitching channel display model. A helicopter pitching channel theoretical model and a helicopter pitching channel inverse model are constructed, a helicopter pitching channel theoretical model differential form is obtained based on the helicopter pitching channel theoretical model, an extended state observer ESO is obtained, a model tracking control system is completed based on a helicopter six-degree-of-freedom kinetic equation, and a compensation model is determined. According to the model tracking control system, the gain of a pitching channel is improved, the ESO is introduced on the basis, the modeling error and / or disturbance of the helicopter are / is estimated, the precision and stability of the control system are effectively improved, and the reliability of the helicopter is improved. The control method provided by the invention has the advantages of outstanding anti-interference capability and comprehensive state estimation and control.

The application relates to the technical field of bridge engineering and provides a method for determining the spatial dynamic response of a four-corner elastic support bridge, which comprises the following steps: introducing a virtual rigid arm, converting a complex four-corner elastic support bridge system into a simplified mechanical model with clear physical meaning, and obtaining a parameter-adjustable analytical simplified theoretical model; based on the parameter-adjustable analytical simplified theoretical model, solving bridge vertical and torsional dynamic response equations by using Duhamel integral, and outputting dynamic response analytical solutions. The application converts the traditional bridge dynamic response problem depending on high-dimensional finite element simulation into an analytical expression which can be obtained by using Duhamel integral, greatly improving the solution efficiency; the application can be used for bridge design, evaluation and health monitoring: the dynamic response analytical solution of the simplified theoretical model can be embedded into a bridge structure response analysis tool chain, realizing bridge performance prediction and diagnosis under the working conditions of extreme load action, support degradation and the like, and having good engineering popularization value.

The present invention provides a task replication and offloading method based on game theory in mobile edge computing, including: constructing a mobile edge system architecture; taking the task replication and offloading strategies of each IoT device as the problems to be solved, taking the maximization of the overall service performance of the mobile edge system in cycle T as the objective function, and combining with the constraint conditions to construct an optimization model for task replication and offloading and transform it into a game theory model; using a Nash equilibrium solving method based on multi-agent reinforcement learning to solve the game theory model and obtain the optimal task replication and offloading strategies of each IoT device. The present invention proposes a task replication and offloading method based on game theory in mobile edge computing, which effectively combines a robust game theory model with a multi-agent reinforcement learning algorithm, and can effectively improve the system service performance and system reliability.

The application discloses a kind of minimum safety distance determination method and system of tunnel excavation face crossing gob area, method includes the following steps: set the failure mode of tunnel excavation face instability under the condition that coal mine gob area is contained in stratum, and establish theoretical model based on failure mode;Minimum safety distance condition is judged based on theoretical model;The shape of the failure region is optimized, and the optimal solution of minimum safety distance is obtained based on minimum safety distance condition.The application proposes a failure mode suitable for the instability of tunnel excavation face crossing coal mine gob area, and the analytical solution of minimum safety distance is derived using the upper bound method of limit analysis.Compared with numerical simulation and analytical solution, the model proposed by the application has high precision and can reflect the mechanism of tunnel excavation face instability and failure.

The invention discloses a gas explosion venting overpressure zoning calculation method combined with a physical information neural network, which comprises the following steps of: constructing a three-zone-one-state balance state control equation through a conservation equation, an explosion mechanics theory and a zoning calculation thought, and dividing required input parameters into static characteristics and dynamic characteristics as input characteristics of a TFT (Thin Film Transistor) algorithm, a theoretical model is introduced into a loss function to construct constraint terms of explosion physical information, a PINN-TFT algorithm coupled with the physical information is constructed, a data set is constructed through gas explosion venting test data, PINN-TFT algorithm training is carried out, and a gas explosion venting overpressure partition calculation method combined with a physical information neural network is formed. The method has excellent interpretability and generalization performance, and can be used for explosion venting overpressure prediction of any gas and any ignition position in a limited space.

This invention relates to the field of user churn prediction technology and discloses a member churn prediction method based on model evaluation, comprising the following steps: extracting member behavior data, time series data, member feature data, and churn tag data from a member management system; performing data cleaning and normalization; and extracting time features; quantitatively evaluating the importance of features in member behavior data based on information entropy and conditional entropy calculations, and screening key features with conditional entropy values ​​below a preset threshold; constructing a synergistic effect function between features, and determining a dynamic weight allocation scheme for features through a game theory model; and based on the screened features and their corresponding weights. By quantifying the explanatory power of each feature for churn tags and screening key features, this method achieves the technical effect of improving model training efficiency and reducing interference from irrelevant features, solving the problem of model performance degradation due to insufficient feature importance evaluation.

This invention relates to the field of text processing technology and discloses a method for structuring unstructured information based on multi-agent systems. The method includes: outputting candidate data definition languages ​​and multi-table distribution samples from a generator, statistically projecting them to obtain discrete statistics; constructing a query plan cost phase transition surface based on the statistics, and calculating the steady-state probability of each plan using a Markov steady-state model combined with a plan caching mechanism; calculating the high-quantile tail delay using a queuing theory model, and solving for the second derivative of the tail delay with respect to the distribution perturbation in the minimum transport direction in Wasserstein space to obtain the optimal transmission bifurcation buffer congestion curvature; finally, updating the generator with minimizing this curvature as a constraint and outputting the table structure. This invention effectively reduces the risk of performance avalanche caused by data perturbations and significantly improves database robustness.

The application discloses a kind of based on parameterization model's precision retention evaluation method of roller linear guide pair, belong to high-end numerical control machine tool and precision equipment manufacturing technical field.It includes: step 1: establish the precision degradation theory model of roller linear guide pair.Step 2: set the parameter system required for evaluation.Step 3: execute parameterized simulation analysis.Step 4: extract precision degradation law and establish mapping relationship.Step 5: generate evaluation conclusion and optimization strategy.Compared with prior art, the present application has the following significant advantages: efficient prediction, low cost;The established degradation theory model couples elastic deformation, wear and creep, more in line with the actual complex failure physical process of guide pair, improve the accuracy of long-term prediction.The present application can not only be used for performance estimation and scheme comparison in new product design stage, but also can be used for state evaluation, residual life prediction and maintenance planning of in-service machine tool guide, and the application scenario covers the whole life cycle.

The invention relates to the technical field of particle flow simulation, in particular to a CAE (Computer Aided Engineering) simulation method in a C-type particle flow state based on a double Euler model, which comprises the following steps of: defining model parameters under a secondary agglomeration theoretical model condition according to an agglomeration mechanism of C-type particles from initial agglomeration to secondary agglomeration; the model parameters comprise particle phase diameter, particle phase density, particle phase volume fraction, particle phase shear viscosity and the like, so that a local dynamic agglomeration particle model, namely an LDAP model, of the C-type particles is established based on an Euler multiphase flow model, and flow state simulation of the C-type particles is carried out; according to the method, the setting of numerical simulation conditions can be realized through simple flow field calibration and parameter setting, namely, the flow behavior simulation of the C-type particles can be realized, and the real-time state of the particle aggregate diameter in any local part of the flow field can be intuitively reflected; the motion state description of particles and gas under the condition of particle aggregate diameter difference has higher accuracy, the number of particle phases is not increased for the changed particle size, and the calculation efficiency can be considered.

The embodiment of the present application provides a kind of prediction method of sheet forming performance.The method comprises: obtaining the mechanical property parameters of candidate sheet and forming limit curve;According to the forming limit curve, select target theoretical model from at least one candidate theoretical model;According to the mechanical property parameters of the candidate sheet and the target theoretical model, the finite element simulation of target part forming process is carried out, the simulation strain when the target part simulation cracks is determined, and the lowest forming limit curve is generated;Obtain the plane strain point in the lowest forming limit curve, and according to the plane strain point and the target theoretical model, the forming performance prediction of the candidate sheet is completed.The technical scheme of the embodiment of the present application can predict the forming performance of the sheet for a specific part forming process.

The invention discloses a joint optimization method for DNN partition and resource allocation, which realizes collaborative reasoning and resource optimization of a deep neural network in an environment of a single edge server and a plurality of mobile devices, and comprises the following steps of: determining DNN hierarchy segmentation points of each device and the number of computing resource blocks and wireless resource blocks purchased from the edge server; decoupling modeling is performed on a DNN structure and an edge environment through a heterogeneous graph attention network, an optimal partition point and a resource deployment strategy are determined through Actor-Critic under the constraint of an M / M / 1 queuing theory model, and an edge-end cooperative reasoning scheme with price-demand-time delay closed-loop optimization is formed.

The invention relates to the technical field of compressed air energy storage underground chamber construction, in particular to a burial depth design method, equipment and medium based on a limit equilibrium theory model. The method is improved based on the model solving process of an existing burial depth control equation, the determination conditions of the initial cycle set burial depth and the initial cycle rupture angle are modified, the model criterion is adjusted, the burial depth serves as the control target, and compared with the model solving process of a traditional limit equilibrium theory model, the design process is more reasonable, and the design efficiency is improved. Burial depth precision control is easier to visually grasp, difference of burial depth calculation results is reduced, burial depth control precision is improved, and the method is more suitable for practical engineering.

Embodiments of the present application provide an evaluation method of an operating mechanism and a related device, applied to the technical field of data processing, input the first score and the second score of each state evaluation index into an equilibrium game theory model, and obtain the optimal score of each state evaluation index output by the equilibrium game theory model. Since the first score represents the score of each to-be-evaluated index based on expert experience, and the second score represents the score of each to-be-evaluated index based on an artificial intelligence model, the optimal score obtained by fusing the first score and the second score through game theory improves the evaluation accuracy of the to-be-evaluated index. Moreover, the equilibrium game theory model is a game theory model constructed based on a dynamic game function, the weight of the first score is a first dynamic weight coefficient, and the weight of the second score is a second dynamic weight coefficient. It can be seen that the accuracy of the optimal score is further improved through the game theory with variable weights.

Disclosed is a prediction system for a price of raw and fresh milk based on large data, including: collecting and preprocessing original market data to obtain market data; implementing an adaptive clustering algorithm on the market data; constructing a game theory model and introducing Nash equilibrium analysis of mixed strategies to calculate an optimal strategy combination of each market stage; predicting a price of raw and fresh milk using the optimal strategy combination; and modifying the game theory model, predicting the price of raw and fresh milk using the modified game theory model, and visually displaying a prediction result. In the present disclosure, the problems of a fixed algorithm structure mostly adopted in the existing clustering algorithms and lack of a dynamic adjustment mechanism are solved.

The application relates to the field of network security, and discloses a system security management method: by monitoring user behavior data in real time and evaluating the security risk, the user access permission is dynamically adjusted; by combining reinforcement learning, optimal control theory and game theory model, the permission adjustment and protection strategy are optimized; by the adaptive feedback mechanism, the key model parameters are adjusted, the flexibility, response speed and security of the system are improved, and the maximization of resource utilization is ensured; the application also provides a system security management system: a behavior monitoring module, a permission adjustment module, a game theory model module and an adaptive feedback module. By combining reinforcement learning, optimal control theory, game theory model and adaptive feedback mechanism, the application realizes dynamic permission adjustment, intelligent risk assessment and optimized resource utilization, improves the system security and response speed, and solves the problems of permission management lag, excessive limitation and resource waste in the prior art.

The invention relates to the field of photo-thermal mirror field control, and discloses a three-tower one-machine photo-thermal mirror field cooperative control method based on a game theory model, and the method comprises the following steps: calculating the power contribution of each heliostat to each heat absorber at a certain moment; according to the obtained power contribution of each heliostat to each heat absorber at a certain moment, a game theory model is constructed by taking a total power value of a maximized heliostat field as a game target and taking a combination scheme that each heliostat is distributed to which heat absorber as a strategy space; the strategy space is updated through iterative optimization until the convergence condition is met, that is, all heat absorbers cannot improve effectiveness through unilateral strategy change, and the final strategy space is obtained; and if falling into local optimum, applying random disturbance to the equilibrium state, and restarting the dynamic process until convergence. According to the method disclosed by the invention, the game theory model is introduced into the cooperative control field of the multi-tower photo-thermal system for the first time, and the overall energy efficiency optimization of the system is realized by calculating the dynamic game behavior between the heat absorption towers.