42 results about "Design objective" patented technology

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.

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.

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.

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 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 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 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.

The invention discloses an III type composite material hydrogen storage container liner-composite layer integrated design method based on deep learning. The method comprises the following steps: firstly, determining a design target, design parameters and a value range and constraint conditions thereof according to design requirements, and generating an initial sample data set by adopting Latin hypercube sampling; performance parameters corresponding to all samples are obtained through numerical simulation, and design parameters are input into a Transform model in a structured matrix form for feature extraction and correlation modeling; performing data enhancement by using the trained model to generate an extended sample set; and finally, inputting the samples into a conditional constraint enhanced generative adversarial network, and generating a design scheme which meets various design constraints and achieves optimal balance on various performance indexes through adversarial training. According to the method, all design parameters of the inner container and the composite layer are fully considered, the generated design scheme ensures the optimal balance of the strength performance, the fatigue performance and the material cost of the container, and the design efficiency of similar products is remarkably improved.

The application discloses a micro-architecture design space exploration method based on deep learning, comprising: obtaining target processor micro-architecture parameters, constituting a design space, obtaining performance indicators of different design points in the design space, and dividing key modules based on the design points; creating a directed acyclic graph according to the key modules, constructing a prediction model using a graph attention network to obtain a parameter optimal solution in the directed acyclic graph that meets a design target; splicing the directed acyclic graph into a global graph to obtain interconnection parameters of the key modules, introducing federal learning to train a global prediction model, and predicting and evaluating performance data of the parameter optimal solution based on the global graph; and when the performance evaluation result meets a preset performance standard, outputting target configuration parameters of the target processor under each configuration dimension. The application performs micro-architecture design space exploration in a graph embedding space, provides decision support for chip design, and improves design efficiency and flexibility by taking the idea of coordination between different design stages and design modes.

This invention discloses a design method and apparatus for refractory high-entropy alloys based on a large model, relating to the field of alloy material design technology. The method includes: First, by generating and collecting data, pre-trained surrogate models for thermodynamics (covering phase diagrams, solidification processes, etc.) and mechanical properties are constructed, and calculation models for physical parameters such as valence electron concentration and density are established. Then, these models are integrated into a single ensemble model, and a large language model is introduced as the core of intelligent scheduling. The large model is responsible for parsing the design task, intelligently planning and calling the interfaces of each model based on a knowledge base and rule base. Finally, based on the set design objectives, a multi-objective genetic algorithm is initiated for iterative optimization and adaptive adjustment, efficiently outputting a final alloy design scheme that meets multiple performance requirements. This invention enables intelligent multi-objective design of refractory high-entropy alloys, solving the problem of high dependence on manual intervention.

This invention discloses a design method for a silicon-based mode divider. Based on a silicon-on-insulator (SiI) platform, it defines a bus waveguide, branch waveguides, and a functional region located between the bus and branch waveguides. The number of branch waveguides is n, determined by a linear combination of the input modes and bandwidths of the bus waveguides. The initial structures of the bus waveguides, branch waveguides, and functional regions are defined. Using an FDTD solver, each iteration requires m forward simulations and m adjoint simulations. The gradient field is calculated, and the dielectric constant parameters of the functional region are optimized using the gradient descent method based on the gradient field calculation results, updating the structure. Iteration continues until the design target is reached or further optimization is impossible, at which point it stops. The discrete dielectric constants are binarized, transforming the dielectric constants of the functional regions into a structure defined only by the functional regions. The final structure diagram is output. This invention also discloses a silicon-based mode divider designed using the above method.

This invention provides a base station design device and method for determining the placement of base stations in an environment where terminal usage fluctuates over time, by performing robust base station design with minimal computational effort. [Solution] The method using the station placement design device of the present disclosure involves arranging multiple base station installation candidates within a design target area, calculating the radio quality between each terminal and each base station installation candidate at each time step based on the movement prediction of multiple terminals within the design target area, creating a weighted directed graph for each time step with each terminal as a node, the connection between each terminal and each base station installation candidate as an edge, and each radio quality as the weight of each edge, obtaining a set of graphs, compressing the set of graphs in the time direction to obtain a compressed set of graphs, and selecting the placement location of a base station from multiple base station installation candidates based on the compressed set of graphs such that the sum of the probabilities of the existence of terminals whose radio quality is equal to or greater than the quality target value is equal to or greater than the design target value.

This invention discloses a multi-domain adaptive design rule method based on EMC data assets. It includes: acquiring the target application scenario identifier, functional type, IC combination, and design objectives; retrieving matching typical basic products and their derivative product cases to obtain their feature sets and mapping relationships; constructing an initial design concept by combining IC-level and system-level data assets; retrieving the standard essential characteristics of the target application scenario; constructing an EMC domain adaptation model, establishing an adaptive mapping based on verified mapping relationships, and quantitatively correcting and generating design rule parameters; outputting design rules containing constraint objects, types, target values, source metadata, and protection layer priorities; and structurally storing and assigning multi-dimensional tags. This invention establishes cross-application scenario mappings through typical basic products and derivative products, achieving quantitative adaptive generation of design rules, supporting cross-domain reuse, test prediction, rule self-evolution, and automatic generation of design documents, shifting EMC design from experience-based to data-driven.

The invention belongs to the technical field of circuit design, and discloses a method for impedance matching design based on a large language model, which comprises the following steps of: 1, collecting impedance matching design demand information for preprocessing, and outputting demand data; 2, semantic understanding, field extraction and structured mapping are carried out, a rule verification mechanism is adopted to carry out conversion unit unification, parameter range verification and missing information complementation, and standard structured design task description is generated; 3, judging a matching task type, selecting a corresponding design according to the matching task type, and generating a topological structure and parameters; 4, converting into a netlist file, performing S parameter simulation, analyzing key performance and indexes, judging initial structure performance, and generating a report and storing the report into an RAG knowledge base when a design target is met; 5, if not, parameter optimization is carried out, a report is generated and stored in an RAG knowledge base after optimization succeeds, modification suggestions are generated if the optimization succeeds for many times, and then redesign is carried out. According to the method, the matching structure design efficiency and accuracy of the large language model are improved.

This invention discloses a passive component selection method based on EMC data assets. It includes: acquiring the application scenario, design objectives, housing structure, and EMC standard requirements of the target product; acquiring port and PCB interconnect information to determine the protection priorities of emission suppression, immunity enhancement, and transient protection; retrieving IC-level and system-level EMC data assets to identify interference source pins and sensitive pins; searching historical design cases to extract successful solution characteristics and failure modes; calculating the required emission suppression, immunity enhancement, transient protection level, housing shielding effectiveness, and common-mode suppression requirements; establishing an inside-out forward design method to determine IC-level, PCB-level, and system-level three-layer protection and dynamically allocate weights; establishing a weighted scoring model, introducing a multi-dimensional labeling system for filter topology, generating and ranking candidate solutions; and integrating selection records into a closed-loop protection selection data asset. This invention achieves quantitative selection of passive components.

This invention belongs to the field of flowmeter technology and discloses a method for optimizing the impeller of a turbine flowmeter. The method includes: S1: collecting data on the physical properties, operating range, and performance indicators of the medium through a system to establish clear design constraint data; S2: integrating streamlined and multi-lead design concepts, and determining the blade structural parameters through mathematical modeling and simulation analysis; S3: ensuring precise matching between the processing process and design objectives through parameter modeling, accuracy threshold setting, process coordination, and data linkage; S4: manufacturing an impeller prototype based on the processing technology, and calibrating the blade size and angle parameters using equipment; S5: verifying linearity and starting flow rate indicators through data acquisition and analysis, and iteratively optimizing design and processing parameters; S6: establishing a large-scale batch production process based on the optimized final parameters. This invention solves the problems of large starting flow rate, poor linearity, and insufficient consistency of metering accuracy in turbine flowmeters under low Reynolds number conditions.

The application discloses a training data obtaining method and device applied to electromagnetic device design, a medium and equipment, and relates to the technical field of electromagnetic device design. The application utilizes the inverse mapping relationship between the electromagnetic response curve and the topological distribution of the frequency selective surface structure, firstly performs topological modeling and full-wave simulation, and utilizes a binary matrix to express the topological structure. In the iteration of the target function, the topological binary matrix and the electromagnetic response reserved in each iteration are taken as a training data set, more useful design information can be reserved, the electromagnetic response has more similar characteristics with the design target, misleading information is less, and the quality of the training data in the electromagnetic device design is improved.

The invention discloses a cantilever crane partition plate determination method and device, computer equipment and a storage medium, and relates to the technical field of cantilever crane optimization. The method comprises the steps of determining a design constraint and a design target based on a preset partition plate design demand, defining a direction and a boundary for subsequent optimization, avoiding design blindness, and ensuring that a scheme meets an actual engineering demand; on the basis of design constraints and design objectives, an optimal solution of a preset agent model is determined through a preset optimization algorithm, association between design parameters and response values can be efficiently established, optimization efficiency is greatly improved, meanwhile, scientificity of the solution is ensured, and empirical design limitation is avoided; and the partition plate design parameters corresponding to the optimal solution serve as target partition plate design parameters of the boom, it is guaranteed that the boom partition plate meets the constraints such as strength and stability, meanwhile, the design targets such as light weight are achieved, and the overall performance of the boom is improved.

A computer-implemented physics solver operates within a neural network framework. A neural network accepts a coordinate for each location within a design domain and outputs a local composition for each location. A model of the design domain is formed in a physics solver. The model includes discrete elements that encompass the design domain. A solution of the model provides a value of a design objective. For a plurality of iterations, the following is performed: the neural network determines current local compositions for the locations in the design domain corresponding to the discrete elements; the current local compositions are input into the discrete elements of the physics solver to obtain a current value of the design objective; and the current value of the design objective is used to find a loss gradient of a loss function. The loss gradient is used to update the neural network during the iterations.

The invention discloses a recommendation method and device for low-code process design and a medium, and the method comprises the steps: obtaining a current node type, a node connection sequence and a node configuration parameter in a design canvas, and generating a process context vector; performing sub-graph matching on the process context vector according to a pre-constructed process modeling knowledge graph to generate a target process sub-graph; analyzing the input natural language through a preset natural language model to obtain a business keyword and a design target; according to the graph neural network, the business keyword and the design target, confidence calculation is carried out on the target process sub-graph, and final recommendation content is obtained; and by designing a canvas, displaying the final recommended content. Through a collaborative method of context modeling, map intelligent retrieval and hybrid reasoning, the process design operation complexity is greatly reduced, and the process design efficiency is remarkably improved. And through multi-modal presentation and map industry compliance constraint, the process design reliability is improved.

The application discloses a method for constructing a GSC blocking matrix and a beamformer, and relates to the technical field of communication. The method comprises the following steps: constructing an initial expression of a Householder matrix Q according to a blocking matrix design target; performing a Householder transformation on a steering vector according to the initial expression to obtain an expected transformation result so as to make a target vector mapped as a first component non-zero; constructing a Householder vector containing a coefficient based on the result to obtain an expression of the Householder matrix; determining a constraint condition for making the Householder transformation result irrelevant based on the expression; determining a constraint condition for and based on the constraint condition; taking the constraint condition of and as a constraint condition of the expression of to obtain the blocking matrix. The application can improve the adaptability and engineering practicability of a Householder GSC beamforming structure under different array structures.

The invention discloses a power via hole design method and device, equipment and a storage medium. The method comprises the following steps: dividing the PCB into a plurality of functional areas according to electrical functions, and distributing a current weight factor, a thermal coupling weight factor and a signal integrity sensitivity weight factor for each functional area; the method comprises the following steps: dispersing a power supply via hole of a PCB into a plurality of infinitesimal segments with the same layer number as the PCB in the axial direction, and defining a geometric parameter set containing aperture, side wall copper thickness and anti-pad size for each infinitesimal segment; performing iterative optimization on the geometric parameter set of the infinitesimal segment based on the weight factor of the functional region to obtain a Pareto optimal solution set; and based on a preset design target of the PCB, selecting a target geometric parameter set from the Pareto optimal solution set, and designing the power supply via hole of the PCB according to the target geometric parameter set. The method solves the problem of cross-domain failure chain of the traditional equal-diameter power supply via hole design, and has the effects of realizing multi-physics field system-level collaborative optimization and remarkably improving the comprehensive performance of a power supply distribution network.

This application discloses an intelligent design method, apparatus, device, and readable storage medium for adjacent tunnel spatial relationships, relating to the field of tunnel engineering technology. It includes: acquiring basic data on existing tunnels and the engineering environment; determining the feasible spatial domain of the new tunnel based on the basic data and the design objectives of the new tunnel, and establishing a spatial relationship constraint model for adjacent tunnels; generating a set of candidate spatial layout schemes for the new tunnel within the feasible spatial domain, based on the spatial relationship constraint model; constructing an intelligent evaluation model to score and rank the feasible schemes in the candidate spatial layout scheme set; and outputting a recommended design scheme that meets the scoring requirements and its key spatial relationship parameters with existing tunnels. This method significantly improves design efficiency, reduces reliance on manual experience, and ensures the quantifiability and reproducibility of the design results.

The invention discloses a port connection interchange design method and system based on a graph vector quantization variational auto-encoder. The method comprises the following steps: converting an interchange structure into graph topology representation; constructing an interchange structure generation model based on a graph vector quantization variational auto-encoder, generating a new interchange structure under the condition of inputting an interchange design target index, and comprehensively evaluating the design performance and structural rationality of the generated interchange structure in combination with a graph attribute prediction module and a graph similarity evaluation module; the system comprises an encoder, a vector quantization module, a decoder, a conditional vector embedding module, a graph attribute prediction module and a graph similarity evaluation module. According to the method, diversified interchange schemes can be generated through efficient combination of different codebook vectors, so that rapid response to various traffic demands and design targets of port connection interchange design is realized, the scheme comparison and selection time is shortened, and the coverage and flexibility of the design scheme are improved.

The invention discloses an automatic design method for an electrical system of a traction substation kiosk based on characteristic value matching. The method comprises the following steps: carrying out structured hierarchical module division on the electrical system of the traction substation kiosk; carrying out feature value definition and weight distribution on each hierarchical module, and establishing a module feature value database; according to project design requirements, generating a design target feature value set of each level of target module; on the basis of the design target feature value set of each level of target module, obtaining a candidate module list of each level of target module in a module feature value database through similarity calculation, and selecting and obtaining a final matching result on the basis of the candidate module list; and finally, combining the matching results of the selected layers of modules, and automatically generating an electrical system design result file. Modules and characteristic value systems of corresponding levels are established according to industry characteristics, and automatic matching, recursive combination and local replacement of the modules are realized by using the method disclosed by the invention, so that the design efficiency and the reuse rate are remarkably improved.

The application discloses a pcb package design method and device, a terminal and a medium, and relates to the technical field of data processing. The method comprises the following steps: obtaining historical characteristic data corresponding to preprocessing; generating a preset design scheme model, and obtaining a first package design scheme according to the historical characteristic data; optimizing the first package design scheme based on a preset package design target, and obtaining a second package design scheme; updating the preset design scheme model according to the second package design scheme and the historical characteristic data, and obtaining an updated preset design scheme model; and obtaining a target package design scheme according to the historical characteristic data by using the updated preset design scheme model. The application aims to significantly improve the accuracy and reliability of package design through a data-driven intelligent design process, so as to adapt to different package specifications of customers.