80 results about "Design objective" patented technology

The invention discloses an industrial MBSE model generation and evaluation method based on a large language model, and the method comprises the steps: collecting and sorting an aerodynamic model, assembly design rules and related basic design parameters, and carrying out the formatted expression of the rules applied in MBSE, so as to form a special enhanced knowledge base in the industrial field; the method comprises the following steps: converting a demand described by a natural language of a user into a standard MBSE model code based on a large language model through a cue word engineering technology, selecting an optimization algorithm and a simulation algorithm through a function call technology, performing real-time optimization on the model according to a design target, and applying the generated MBSE model to propulsion device design and verification test. And determining availability and model consistency. Reconstruction and acceleration of digital design are realized through automatic configuration based on requirements and components. The method has remarkable advantages in the aspects of reliability, effectiveness and adaptability.

The invention discloses an ultra-wideband antenna design method and system based on deep learning and a medium, and the method comprises the steps: obtaining a design target of a target ultra-wideband antenna, and extracting structure parameters related to the antenna performance according to antenna design instance data; preparing sample data according to the structure parameters and preprocessing the sample data, building an agent model based on an NAR dynamic network in combination with a multi-layer sensor, training the agent model by using the sample data, and configuring agent model parameters; and obtaining an optimal structure parameter of the target ultra-wideband antenna by using the trained proxy model, performing simulation verification on the output optimal structure parameter, and configuring a design scheme of the target ultra-wideband antenna. According to the method, the NAR dynamic network is combined with the multi-layer perceptron to establish the proxy model, so that optimization tasks of different structural parameters can be adapted, the efficiency is improved on the premise of ensuring the performance, and the design speed and precision of the ultra-wideband antenna are improved.

The invention discloses a large-scale equipment shock resistance optimization design method and device based on multi-objective integration, belongs to the technical field of large-scale equipment shock resistance design and optimization, and particularly relates to a method which comprehensively considers multiple design objectives and carries out optimization design on response of large-scale equipment in a shock environment based on a multi-objective integration method. The problem that an existing impact resistance design method only optimizes a single target and cannot deal with a complex multi-target optimization problem is solved. The method comprises the following steps: scoring the importance of each objective function to form a judgment matrix; calculating the weight of each objective function by using an analytic hierarchy process based on the judgment matrix; and S5, carrying out multi-criterion decision analysis on the optimal solution set by utilizing the weight of the objective function, and selecting an optimal design scheme. The large-scale equipment impact resistance optimization design method and device based on multi-objective integration are suitable for large-scale equipment impact resistance optimization design.

The invention belongs to the technical field of filter modeling, and relates to a reverse modeling method of a microwave coupling filter, which comprises the following steps: acquiring a design target of the microwave coupling filter, defining an ideal coupling matrix, and obtaining a plurality of coupling matrix samples to construct a sample set; calculating an S parameter of each coupling matrix sample at a set frequency point to construct a condition set; the sample set and the condition set serve as input of a diffusion model, the diffusion model is trained, and multiple sets of initial coupling parameters are obtained; obtaining an S parameter corresponding to each group of initial coupling parameters according to the forward model; calculating and screening mean square errors of the target S parameter and the corresponding S parameter to obtain a plurality of groups of optimal coupling parameters; and clustering the multiple groups of optimal coupling parameters to obtain coupling parameter distribution so as to realize reverse modeling of the microwave coupling filter. According to the invention, reverse modeling of the microwave coupling filter can be realized.

The invention discloses a stepped three-band grating coupler and a reverse optimization method thereof, and belongs to the technical field of photonic devices and integration, and the reverse optimization method comprises the steps: determining a design target of the grating coupler, and defining an initial structure; defining optimization parameters including grating height and grating width according to the grating number; defining an optimization quality factor according to a design target of the grating coupler, and dynamically updating a weight coefficient of the quality factor; optimizing the width and height distribution of all gratings by using an improved direct binary search algorithm; and iterative optimization is continuously carried out until a design target is achieved, and width distribution corresponding to gratings with different heights in the optimized stepped grating structure is obtained. The problem that traditional grating diffraction has inherent wavelength dependence is effectively solved, and efficient coupling of three optical communication wavebands is achieved.

The invention discloses a digital circuit design method and device, equipment and a medium, and relates to the technical field of digital circuits, and the method comprises the steps: determining a target type of a to-be-designed digital circuit, and collecting a first training set corresponding to the target type; each training sample in the first training set comprises an input feature item used for designing a target type of historical digital circuit and the actual result quality of the historical digital circuit, and the input feature item comprises a high-level language source code and an HLS constraint parameter; constructing an initial prediction model based on the multi-layer perceptron mixed structure, training the initial prediction model by using the first training set, and searching and optimizing the model architecture based on the network structure to obtain a target prediction model; and predicting the actual result quality corresponding to each parameter combination in a target design space of a to-be-designed digital circuit by using the model, and designing the digital circuit by using the parameter combination of which the quality meets the Pareto frontier. And predicting an accurate actual quality result by utilizing a prediction model without intermediate representation so as to carry out digital circuit design.

A blockchain smart contract execution system supporting artificial intelligence model reasoning comprises a client used for deploying a contract or a smart contract supporting AI model reasoning, a blockchain node used for maintaining the security and consistency of blockchain data, and a trusted execution environment provider. According to the method, the function of realizing complex deep learning model reasoning in the existing block chain can be supported, and four design objectives of supporting non-deterministic AI reasoning, avoiding complex intelligent contract verification, being compatible with the existing block chain and protecting model privacy are realized.

The invention discloses a micro-architecture design space exploration method based on deep learning. The method comprises the following steps: acquiring micro-architecture parameters of a target processor, forming a design space, acquiring performance indexes of different design points in the design space, and dividing key modules based on the design points; creating a directed acyclic sub-graph according to the key module, and constructing a prediction model by using a graph attention network to obtain a parameter optimal solution meeting a design target in the directed acyclic sub-graph; splicing the directed acyclic sub-graphs into a global graph to obtain interconnection parameters of key modules, introducing federal learning to train a global prediction model, and predicting performance data of an optimal solution of the evaluation parameters based on the global graph; and when a performance evaluation result meets a preset performance standard, outputting a target configuration parameter of the target processor under each configuration dimension. According to the method, the micro-architecture design space is explored in the graph embedding space, decision support is provided for chip design, and the design efficiency and flexibility are improved by adopting the thought that different design stages and design modes are coordinated.

The invention provides a design optimization method and device of an MIMO antenna, equipment and a medium, and belongs to the field of antenna design, and the method comprises the steps: obtaining historical design parameters and corresponding performance indexes of the MIMO antenna; preprocessing the historical design parameters and the performance indexes, constructing a mapping relation between the input data and the output data, and training based on the mapping relation to obtain a forward prediction model and a generation model; and receiving target performance index input, generating a candidate design parameter set by utilizing the trained generation model, performing iterative optimization by taking the candidate design parameter set as an initial population and combining a forward prediction model as an agent model and adopting a multi-objective evolutionary algorithm, and outputting a Pareto optimal solution set as a target design parameter set. Therefore, the performance evaluation link is greatly accelerated by means of the agent model, diversified non-inferior solution selection is provided through Pareto frontier analysis, and different design targets can be flexibly balanced according to actual requirements.

The invention discloses a protection device optimization design method and a computer readable storage medium, and belongs to the technical field of bridge engineering structure optimizing.The method comprises the steps that constraints and targets of a protection device are designed according to project basic information; obtaining primary selection parameters and a similarity ratio coefficient set of the protection device according to the constraint and the target; establishing a prediction model of the crushing performance of the protection device, obtaining basic design parameters of the protection device according to the primarily selected parameters and the similarity ratio coefficient set, calculating crushing curves of the protection device under different basic design parameters, and further calculating the protection performance and the construction cost of the protection device under the ship collision condition. And if the fortification requirement and the engineering cost requirement are met, entering an optimization design result set, and returning a similarity ratio coefficient set to carry out the next round of iterative calculation. According to the protection device optimization design method and the computer readable storage medium, constraint conditions and design targets in various actual engineering projects are met based on the extreme learning machine prediction model, and the design efficiency of the protection device is improved.

Embodiments of the present disclosure provide enhanced systems and methods for predicting optimal design flow parameters for optimized output targets for physical design synthesis of a given IC design. A Variational Autoencoder (VAE) along with a regression network are trained using a dataset comprising synthesis design construction flows from historical IC designs to provide a training data representation of the dataset constrained to a latent space of the VAE. The system generates feature vectors based on the training data representation of the dataset and updates the feature vectors with initial design characteristics of the given IC design. The system iteratively performs an input gradient search of the updated feature vectors to optimize an objective function of the design targets to identify locally optimal design parameters. The system identifies globally optimal design flow parameters for optimized design targets based on locally optimal design parameters.

The invention relates to the technical field of electronic design automation, and discloses an EDA layout and wiring optimization method, which comprises the following steps of: firstly, finishing layout and wiring according to initial layout and wiring data of an electronic design layout, and then dividing a whole layout and wiring area into a plurality of relatively independent sub-areas; according to the method, the layout and wiring characteristic parameters of each sub-region are extracted respectively, the processed parameters are analyzed after the parameters are normalized, and each sub-region is optimized according to an analysis result, so that the calculation amount is reduced, the optimization efficiency is improved, and finally, the performance of the whole layout and wiring is evaluated. Global performance degradation caused by local optimization is avoided through real-time performance feedback, and it is ensured that the final scheme meets the design target.

Embodiments of the present disclosure provide enhanced systems and methods for optimal design process parameters for predicting optimal output objectives for physical design synthesis of a given IC design. A variational automatic encoder (VAE) is trained along with a regression network using a dataset that includes an integrated design build stream from a historical IC design to provide a training data representation of the dataset constrained to a potential space of the VAE. The system generates a feature vector based on the training data representation of the dataset and updates the feature vector with initial design characteristics of the given IC design. The system iteratively performs an input gradient search of the updated feature vectors to optimize an objective function of the design objective to identify locally optimized design parameters. The system identifies global optimization design process parameters for optimization design objectives based on the local optimization design parameters.

A model representing a physical object in a shape optimization according to a design objective, and a control point for altering a shape of the physical object are received. The shape is defined by a set of nodes in the model. Sibling models are generated from the model according to a perturbation scheme. The control point is perturbed with respective perturbed values for the sibling models. Each sibling model contains nodal location changes for the nodes. The nodal location changes are determined based on a respective shape function formulated according to a respective perturbed value at the control point and one or more simulated physical behaviors of the model. The model is updated to have an optimal value for the control point. The optimal value is identified from a relationship according to the design objective. The relationship correlates a physical characteristic of the sibling models to the respective perturbed values.

The present invention discloses a method and system for optimizing the layout of communication relay nodes in a cooperative action system. Based on the quantitative description of the attribute information of the cooperative action system, from the perspective of communication connection in the physical layer and information interaction in the logical layer, decision variables are defined, constraint conditions are analyzed, and an objective function is designed to construct a two-layer communication relay node optimization layout model including the physical layer and the logical layer. According to the hierarchical characteristics of the model, based on the artificial bee colony algorithm with high fitness and fast convergence speed, combined with the non-feasible solution forced conversion mechanism, a hierarchical artificial bee colony system for upper and lower layer iterative games is constructed. Through the iterative solution of the hierarchical artificial bee colony system, an optimized layout scheme of communication relay nodes that meets the quality requirements of communication information services is generated, solving the problems of insufficient quantity, lack of optimality, and low adaptability in the existing field of optimizing the layout modeling of communication relay nodes, and being unable to generate an optimized layout of communication relay nodes with relatively high quality and efficiency well.

The present invention relates to an intelligent design optimization method for a lead-bismuth reactor, which includes: establishing a mathematical model of the lead-bismuth reactor to be optimized with a design space, a design objective function, and constraint conditions, conducting Latin hypercube sampling to generate sample points, calculating core characteristic parameters to construct a training data set, and using the BP neural network algorithm to establish a surrogate model S-LFR that can predict the core characteristic parameters of the lead-bismuth reactor; using the niche genetic algorithm Micro-GA to optimize the combination of design parameters predicted by the surrogate model S-LFR, updating the training data set and the surrogate model S-LFR, and repeatedly iterating to approach the target optimization interval until the global optimal solution is obtained. The present invention realizes the collaborative optimization of multi-objective, multi-physics, and multi-variable coupling of the lead-bismuth reactor core, greatly improves the design efficiency while ensuring the calculation accuracy, can automatically search for the optimization interval according to the design objective, and obtain the optimal design scheme.

The invention discloses a fabricated wall BIM model multi-objective optimization method based on acoustic parameter analysis, and relates to the technical field of building information models. The method comprises the following steps: constructing an acoustic parameter analysis-prediction coupling model based on an auto-encoder and a deep network, and generating a lightweight performance prediction proxy model through a knowledge distillation technology; the performance prediction agent model, a cost calculation module and a weight calculation module are jointly packaged into an acoustic parameter analysis-model optimization plug-in conforming to BIM platform interface specifications; and realizing automatic multi-target optimization of the target fabricated wall in the BIM platform through the plug-in. According to the method, real-time prediction of high-precision acoustic performance and collaborative optimization of a multi-dimensional design target are achieved, interactive target and constraint setting of a user in a BIM environment is supported, the technical problems that in a traditional method, performance analysis efficiency is low, the optimization process is split, and multiple targets are difficult to balance are solved, and the method is suitable for popularization and application. And the scientificity, efficiency and engineering practicability of the assembly type wall body design are improved.

The invention discloses a bridge protection device optimization design method and system and a computer program product, and belongs to the technical field of bridge protection device performance optimization, and the method comprises the following steps: determining design parameters and design targets; designing an initial structure of the protection device; a ship, a protection device and a bridge are respectively simplified into a corresponding ship macroscopic module, a protection device macroscopic module and a bridge macroscopic module, and a ship-protection device-bridge simplified dynamic model is established; calculating the impact force borne by the bridge by using the ship-protection device-bridge simplified dynamic model; judging whether the impact force borne by the bridge meets a design target or not, if not, modifying the structure of the protection device, and if yes, outputting a final parameter combination to complete optimization design. The dynamics calculation process is simplified, parameterization analysis is optimized, calculation time consumption and hardware requirements are reduced, and design efficiency is improved.

The invention relates to a microstrip network layout optimization method based on Fourier series, and belongs to the technical field of radio frequency circuit design. The method aims at solving the problems of topology dependence, boundary discontinuity and low efficiency caused by sharp increase of optimization parameters along with the area in a traditional rectangular spliced microstrip network. The core of the technical scheme is that a microstrip network boundary is modeled into a plane closed curve, the curve is represented through Fourier series decomposition, and a Fourier coefficient is optimized by taking circuit performance as a target drive, so that a microstrip layout with any shape and a continuous and smooth boundary is generated. According to the method, automatic design rule checking and port adding processes are integrated, and finally electromagnetic simulation iteration is carried out until a design target is met. The method can break through the limitation of the traditional topology, effectively improves the electromagnetic performance and design efficiency, and is widely applied to the microstrip network design of broadband matching, multi-band matching, harmonic control and the like.

The invention discloses a design method and device of a charging station, electronic equipment and a storage medium, and the method comprises the steps: determining at least one parameter value of each design parameter item according to the allowable design range of the charging station and each design parameter item, and combining the parameter values of each design parameter item to obtain a combined parameter value; obtaining at least one group of initial design data of the charging station; performing search optimization on the at least one group of initial design data by utilizing a design target of the charging station to obtain at least one group of target design data; inputting each group of target design data into a pre-trained performance analysis model for performance analysis to obtain an actual performance analysis result corresponding to each group of target design data; and generating and displaying a performance analysis report according to each group of target design data and the actual performance analysis result corresponding to each group of target design data. According to the method, the problem that the design period of the charging station is long due to more design data combinations is solved, and the overall design period efficiency is improved.

To provide a system and method for generative design of an energy storage device.SOLUTION: A method automatically builds at least one model of an energy storage device. The building is based on a design parameter space and employs a machine learning process. The method automatically performs a simulation of the energy storage device using the design parameter space, a design evaluation space, and the at least one model built. The performing produces at least one prediction. The method automatically evolves at least one of the design parameter space and the design evaluation space. In an event the at least one prediction indicates that a product design objective or model design objective has been achieved, the method automatically converges on the design parameter space evolved, thereby completing a generative design of the energy storage device and, otherwise, repeats the building, performing, and evolving.SELECTED DRAWING: Figure 1A

The present invention realizes an update support system capable of optimizing a QoS during an update of a system. An update support system according to the present invention comprises: a design unit that designs an updated concrete configuration of a target system providing a service by repeatedly executing, with respect to a service requirement, a concretization procedure in which a plurality of concretization rules defining a method for concretizing an abstract configuration of the target system are referred to, and one or more of the concretization rules corresponding to the abstract configuration are specified and applied to generate one or more abstract configurations or concrete configurations, and generates an operation model of the target system corresponding to the updated concrete configuration; a generation unit that generates a QoS evaluation function for evaluating, when updating the abstract configuration of the target system to the concrete configuration designed by the design unit, a quality of service (QoS) of the configuration of the target system in the middle of the update; and a planning unit that plans, by using the operation model and the QoS evaluation function, an update procedure satisfying a QoS-based criterion.

The invention discloses a training data acquisition method and device applied to electromagnetic device design, a medium and equipment, and relates to the technical field of electromagnetic device design. According to the method, the inverse mapping relation between the electromagnetic response curve and the topological distribution of the frequency selective surface structure is utilized, topological modeling and full-wave simulation are firstly carried out, a topological structure is expressed by utilizing a binary matrix, in iteration of a target function, the topological binary matrix and the electromagnetic response reserved in each iteration are used as a training data set, and the frequency selective surface structure is obtained. According to the method, more useful design information can be reserved, the electromagnetic response and the design target have more similar characteristics, misleading information is less, and the quality of training data in electromagnetic device design is improved.

The present invention discloses a method for randomly generating a rotating rigid body structure based on an interpolation boundary, which relates to the technical field of rotating rigid body processing, and includes the following steps: S1. Generate a random domain according to the size of the rotating rigid body and determine a number of limit points; S2. Generate an interpolation function according to the number of limit points; S3. Use a number of fine points to draw an interpolation curve corresponding to the interpolation function, and transform the interpolation curve to generate a flexible hinge and its surrounding local structure as well as a rotating rigid body unit; S4. Generate a three-dimensional model of the rotating rigid body according to the flexible hinge and its surrounding local structure as well as the rotating rigid body unit. The present invention can quickly generate a large number of structures, reduce intermediate labor and does not require prior knowledge and design experience; compared with the local topology generation method, the present invention has stronger randomness and globality, and does not need to consider complex constraint conditions and design objectives.

The present application provides a cross-platform collaborative parametric modeling design method, device and equipment for hyperbolic curtain walls. The method includes determining file parameter information corresponding to the hyperbolic curtain wall according to the parametric modeling software and structural modeling software corresponding to the hyperbolic curtain wall modeling; obtaining the design objective corresponding to the hyperbolic curtain wall to be modeled, and dividing the hyperbolic curtain wall model to be modeled into multiple modules in the parametric modeling software according to the design objective; setting the design parameters corresponding to each module in the parametric modeling software, and the design parameters at least include curvature and size; generating a cross-platform design file in the parametric modeling software according to the file parameter information and the design parameters corresponding to each module; in the structural modeling software, performing detailed design and structural analysis on the hyperbolic curtain wall model corresponding to the cross-platform design file; setting the material corresponding to each module in the structural modeling software according to the analysis result corresponding to the structural analysis and updating the design parameters.

The invention relates to an isolation type three-active-bridge converter numerical parameter optimization design method based on hierarchical constraint, and belongs to the field of power electronics. According to the method, the working principle of the isolated three-active bridge converter is analyzed, and a frequency domain steady-state analysis model is established; according to design requirements, working characteristics and a safe working domain of the ITAB converter, voltage gain constraint, inductance range constraint and maximum transmission power constraint are introduced in sequence; all main circuit parameters are constrained step by step, so that the parameter optimization range is greatly reduced; a power loss model of ITAB is established, and a mapping relation between a design space and a performance space is defined; and with the minimum weighted average loss of the whole working domain of the converter as a design target, parameter optimization design of the ITAB is completed, and an optimal circuit parameter combination is determined. According to the optimization design method, the parameter design space can be greatly reduced, the optimization difficulty is remarkably reduced, and the average efficiency of the converter in the whole working domain is improved.

The embodiment of the invention discloses a structural reliability optimization design method and device based on uncertainty measure, and the method comprises the steps: determining a performance parameter of a structure, and constructing a limit state function of the structure under cognitive uncertainty according to an uncertain variable affecting the performance parameter, the uncertain variables obey continuous or regular uncertain distribution; according to the limit state function in combination with uncertain distribution or uncertain inverse distribution, constructing a reliability measurement model of the structure based on the uncertain test; determining a structural optimization design objective function, and establishing a design optimization model with the structural performance reliability constraint and the objective function in combination with the reliability measurement model; and constructing an equivalent analytic solution model of the design optimization model, and obtaining an optimal design variable in combination with boundary conditions of the design variables. By means of the method, product reliability analysis can be achieved and the optimal design scheme can be obtained under the condition that cognition is uncertain.

The present invention relates to the field of boring machine spindle design, and in particular to a boring machine spindle design method and system based on finite element analysis, the method comprising: by collecting spindle design objectives and processing environment conditions, establishing a spindle geometry model, extracting key performance characteristics of the spindle geometry model, obtaining a key performance characteristic set, gridding the key performance characteristic set, dividing the key performance characteristic set into a plurality of grid regions, evaluating the performance influence of the processing environment conditions on the spindle based on the gridding process, obtaining a gridding process result, generating an optimization analysis result for the gridding process result, and revising parameters to obtain a spindle design implementation plan. Through the present invention, the problem that the actual performance of the spindle cannot be accurately predicted under complex working environments and high load conditions is effectively solved, and the processing quality and precision are effectively improved.

The invention discloses an automatic optimization method based on a CAD model, and relates to the technical field of engineering design automation and computer aided design optimization. The method does not depend on manual predefined parameter dimensions any more, directly takes topology and geometric features of the CATIA model as core input, constructs a complete geometric optimization link through automatic extraction, structure mapping and optimization algorithm cooperative processing, ensures synchronous evolution of geometric features and design targets in the optimization iteration process, and improves the optimization efficiency of the CATIA model. And the optimization efficiency and stability are obviously improved. A reinforcement learning or evolutionary algorithm is built in the system to perform efficient search and multi-round adaptive iteration on geometric feature vectors, and global optimization of a complex structure can be completed without manual intervention. According to the method, automatic model generation of an optimization result is realized through a CATIA API and a macro command interface, and manual geometry reconstruction by an engineer is not needed. CATIA can be written back through one key according to optimized feature information, the closed-loop automatic process of input, optimization and output is achieved, the design period is remarkably shortened, and the iteration response efficiency is improved.