7results about How to "Reduce optimization time" patented technology

The invention provides a method for automatically generating a pixelated resonant cavity of an oscillator based on knowledge-driven reverse design. The method comprises the following steps: determining a topological region range of VCO resonant cavity design; determining a reverse design target; a priori knowledge driving pixel matrix drawing strategy is established, pixelated inductor topological structure drawing is completed in the topological region based on the drawing strategy, and a primary pixelated inductor topological structure quality factor and a secondary pixelated inductor topological structure quality factor are calculated; according to a reverse design target, searching a Q value of a primary pixelated inductance topological structure from a binary n * n matrix assembly at a given target frequency, and meanwhile, achieving a maximized optimal solution to obtain an optimal pixel topological structure; and constructing the voltage-controlled oscillator in combination with the optimal pixel topological structure. According to the method, batch automatic simulation and optimization of the optimal resonant cavity structure can be realized, and compared with manual design, the time cost is saved, and meanwhile, the performance is further improved.

The application discloses a group target RCS optimization method based on space mapping and multi-stage electromagnetic modeling, and the method comprises the following steps: under a given RCS threshold, for initial group target space distribution positions and postures, a hummingbird optimization algorithm is combined with an electromagnetic scattering solver based on a physical optical method to perform parameter optimization; the optimal solution of a coarse model is used as an initial design value of a fine model, a mode reconstruction algorithm is combined with a fast multipole technique to accelerate electromagnetic coupling calculation between targets; if the fine model result meets the RCS threshold requirement, the optimization is terminated; if the threshold is not met, a space mapping relationship between the coarse model and the fine model is established through parameter extraction, the next fine model design value is predicted, and RCS is recalculated for threshold judgment until convergence is achieved. The space mapping algorithm is combined with the coarse model with high calculation efficiency and the fine model with high precision, RCS optimization of the group target formation is realized quickly and accurately under the premise of ensuring electromagnetic calculation precision.

The invention relates to the technical field of cementitious material preparation, in particular to a low-carbon cementitious material preparation method and system utilizing solid waste resources, and the method comprises the steps: obtaining a solid waste component database, constructing a plurality of cementitious material reference data based on the solid waste component database and a plurality of historical cementitious materials, performing high-performance material selection in the original solid waste material group based on the multiple pieces of cementing material reference data and the performance weight group to obtain a target solid waste material group, performing response surface optimization on the target solid waste material group to obtain an optimal solid waste proportion group, and inputting the optimal solid waste proportion group and the target solid waste material group into a target random forest model to obtain a target random forest model; and preparing the target low-carbon gel on the basis of the optimal solid waste ratio group, the target solid waste material group, the curing conditions and the exciting agent ratio. The accuracy of performance prediction of the cementing material and the efficiency of the preparation process can be improved.

This invention discloses a method and apparatus for optimizing parameters of lightweight hydrogen storage cylinders based on adaptive optimization. The method includes: constructing a multi-agent collaborative optimization framework to define the functional boundaries of ant colony agents, NSGA-II agents, quantum annealing agents, and surrogate model agents, and clarifying the information interaction rules between agents; performing parameter collaborative optimization based on the multi-agent collaborative optimization framework according to collected design parameter samples and corresponding performance data of the hydrogen storage cylinder; dynamically adjusting the collaborative weights and optimization strategies of each agent by real-time monitoring of surrogate model prediction errors, population diversity, and algorithm convergence speed; selecting candidate solutions from the final Pareto front for real-world simulation verification; if the performance meets the design requirements, outputting the optimal parameter combination for the hydrogen storage cylinder; if not, feeding back the simulation results to the surrogate model agent for updating, and re-performing the iterative optimization process until the optimal parameter combination that meets the requirements is obtained.

This invention relates to the field of semantic intelligence optimization technology, and particularly to a method for semantic intelligence optimization of official documents based on a domain knowledge base and a large-scale intelligent model agent. The method includes: acquiring the text to be optimized and a set of reference texts; constructing a semantic loss function based on the text to be optimized and the set of reference texts, the semantic loss function including an intent consistency loss component and an expression normativity loss component; and performing semantic optimization in two stages with the goal of minimizing the total semantic loss function: in the first stage, the core intent of the user text is fused and aligned with that of the superior text to reduce the intent consistency loss component; in the second stage, the user text is matched and adapted to the normative expressions of the superior text to reduce the expression normativity loss component. This invention constructs a semantic loss function that includes intent consistency loss and expression normativity loss, achieving high-fidelity semantic alignment between the generated text and the reference standard.

The application relates to the technical field of vehicle noise, in particular to a vehicle wind noise modeling optimization method and device and a storage medium, wherein the method comprises the following steps: obtaining multiple modeling parameters of a target modeling area of a vehicle, then constructing a design space of the vehicle according to the multiple modeling parameters, and determining a wind noise index of the vehicle according to the design space, so as to construct a proxy model meeting preset proxy conditions according to the multiple modeling parameters and the wind noise index, and based on an optimization target and a constraint condition of the vehicle, the proxy model is used to perform optimization processing in the design space, so as to obtain a wind noise modeling optimization strategy of the target modeling area. Therefore, the problem that in the related art, due to the dependence on physical sample vehicle testing and multiple high-time-consuming CFD and CAA simulation iteration schemes, the development cost of the vehicle wind noise modeling is high, the development cycle is long, and the development efficiency is low is solved.

This invention relates to the field of production line lifecycle management technology, specifically to an intelligent operation system and method for a glass production line based on a digital twin. The system includes a digital process package generation module, a digital twin construction module, and a monitoring and verification module. This application uses the obtained glass performance indicators as constraints for multiphysics simulation and optimization to obtain a digital process package for the glass production line. This provides a standardized and directly executable process basis for subsequent production line operation, improving the consistency and reproducibility of process solutions in actual production. Furthermore, by combining the acquired BIM model and collected raw multi-source sensor data with the digital process package, a digital twin is constructed, achieving a high-precision bidirectional mapping between the physical production line and the digital twin. Finally, the status monitoring and verification of the production line operation are performed based on the digital twin, achieving more accurate and efficient glass production line management and solving the problems of low accuracy and real-time performance in existing glass production line management technologies.