8results about How to "Improve search accuracy" patented technology

The application discloses a mobile device path planning method and an electronic device. The mobile device path planning method comprises the following steps: constructing a fitness function of mobile device path planning; initializing a particle swarm population, and a particle position is used for encoding a candidate path composed of multiple intermediate path point coordinates; performing multiple iterations of optimization, in each iteration, after each velocity and position update is completed, performing a dimension-by-dimension optimization operation on the entire population, the dimension-by-dimension optimization operation searches the path point coordinates of the candidate path encoded by all particle positions in the population dimension by dimension, and optimizes the corresponding path point coordinates in the global optimal position; after the iterations are completed, determining an optimal path based on the path encoded by the global optimal position. The application overcomes the defect that the effective local feature is lost due to simple elimination of low fitness particles in the existing PSO algorithm; meanwhile, repeated calculation of full path evaluation is avoided, and the real-time performance and high efficiency of algorithm operation are ensured while the optimization precision is effectively improved.

This invention discloses a method and system for injecting knowledge into large-scale models for vertical industries, belonging to the field of large-scale model knowledge injection technology. The method involves: collecting professional knowledge data from vertical industries, performing denoising, structured transformation, and terminology standardization; dividing the data into knowledge modules and associating them with vectorized indexes and metadata tags to form a vertical industry knowledge base; parsing the semantic feature vector of the input question using a dynamic routing classifier and routing it to the target knowledge module in the vertical industry knowledge base; employing a hybrid retrieval strategy to recall relevant document sets from the target knowledge module and deduplicate them to generate enhanced retrieval results; based on this, concatenating the enhanced retrieval results with the input question using industry-specific prompt templates; and inputting the LoRA-tuned large-scale model to generate accurate answers conforming to industry standards. This invention solves the problem of insufficient knowledge adaptability of large-scale models in vertical industries, improving the accuracy and applicability of large-scale models in vertical industries.

This invention relates to the field of 3D layout technology, specifically to a center cube layout method based on an intelligent heuristic algorithm, comprising the following steps: S1, determining the size parameters of the space to be laid out, the number of objects to be laid out, and the size parameters of each object to be laid out, setting layout constraints and preset goals; S2, constructing a mathematical model of the center cube layout problem, defining the layout state, envelope box, center cube, available space, and envelope box fill rate; S3, designing an intelligent heuristic algorithm, which is designed according to the available space calculation strategy, the available space cube selection strategy, and the object placement strategy; S4, based on the intelligent heuristic algorithm designed in S3, combined with the parameters of S1 and the mathematical model of S2, solving the center cube layout, outputting a layout scheme that satisfies the layout constraints and preset goals, thereby improving the engineering feasibility of the layout scheme.

This invention discloses a method for predicting the unsteady acoustic quality of electric drives based on intelligent sensors. Specifically, it includes: acquiring noise signals and extracting sound pressure level, loudness, sharpness, speech intelligibility, and priority speech interference level to form a feature vector sequence and dataset; constructing a neural network to determine nodes and form network parameter vectors; establishing an information entropy budget allocation model, mapping each feature to an information budget variable vector, setting constraints to construct an objective function containing budget constraint terms and prediction error terms, and embedding the budget variables into the feature representation; constructing a particle swarm, uniformly encoding the information budget vector and network parameter vector into particle state vectors and then initializing them; introducing an information budget modulation factor during iteration to weight the velocity update component, achieving co-evolution of the two; updating the optimal particle based on fitness, outputting the optimal information budget and network parameters to construct a prediction model; and inputting the feature vector sequence to output the prediction result. This invention assigns independent budgets to each acoustic feature, dynamically co-optimizes, and achieves high accuracy and fast response.

This invention discloses a rapid bridge damping ratio identification method based on a stationary inspection vehicle, belonging to the field of bridge structure vibration testing technology. The method includes: parking the inspection vehicle at the mid-span of the bridge under inspection; exciting the bridge vibration using a passing vehicle and then driving away; collecting the acceleration response of the inspection vehicle in the attenuation segment; establishing a dynamic model of the attenuation segment of the vehicle-bridge coupled system; constructing a two-degree-of-freedom joint state model, internalizing the vehicle-bridge interaction force as a linear combination of system state variables; extracting the effective attenuation segment through signal preprocessing and introducing a dual anti-noise mechanism of adaptive signal-to-noise ratio weights and Huber weights; and employing a profiled two-stage parameter identification strategy, first locking the frequency and modal mass, and then finely scanning and identifying the bridge's first-order damping ratio. This invention requires only a single inspection vehicle and an acceleration sensor, eliminating the need to deploy sensors on the bridge structure. It has strong anti-interference capabilities, high identification accuracy, and is suitable for rapid inspection of small-to-medium span bridges.

The present application relates to a kind of sound image archives two-dimension fusion intelligent retrieval system and method, including archive data preprocessing module, photo and sound image fusion face recognition library, two-dimension fusion retrieval model and double-engine collaborative retrieval scheduling module, photo and sound image fusion face recognition library establishes the association index of face feature and business attribute;Two-dimension fusion retrieval model dynamically adjusts the matching weight of photo and business attribute, sets similarity threshold, filters out the archives of two-dimension comprehensive matching degree standard;In double-engine collaborative retrieval scheduling module, first by face recognition retrieval engine according to face feature matching candidate archives, output candidate archive set, then by attribute screening engine according to user setting condition to candidate archive carries out business attribute matching, the archives of matching success are output, obtain target archive.The present application has the advantages that: by constructing fusion face recognition library, two-dimension fusion retrieval model and double-engine collaborative retrieval scheduling module, realize fast and accurate retrieval.

A method for measuring the bulk density of topsoil based on the sound wave penetration characteristics belongs to the field of intelligent agricultural sensing technology. In the sound wave penetration characteristic acquisition system of this invention, a digital power amplifier board is electrically connected to a subwoofer, a DC power supply, and a computer terminal; a data acquisition card is electrically connected to a microphone and the computer terminal; and a robotic arm is electrically connected to the DC power supply and the computer terminal. The robotic arm, through five servo motors in coordinated control, achieves automatic grasping, precise positioning, and vertical insertion of the ring cutter tube, ensuring consistent sample placement. The computer terminal is equipped with a soil bulk density measurement model based on an adaptive mutant particle swarm optimization variational mode decomposition model and an adaptive mutant particle swarm optimization BP neural network. This system can automatically acquire real-time soil penetration sound waves and realize soil bulk density inversion based on sound wave penetration characteristics. The soil bulk density measurement model of this invention has high timeliness and high accuracy.

The present application relates to the technical field of production planning and operation optimization, in particular to a cigarette equipment capacity matching optimization method based on an improved NSGA-Ⅱ algorithm, comprising: obtaining basic data of matching of cigarette production resources and demand; calculating constraint parameters of each product according to the basic data; constructing a cigarette equipment capacity matching multi-objective optimization model based on the constraint parameters; solving the cigarette equipment capacity matching multi-objective optimization model based on the improved NSGA-Ⅱ algorithm to obtain an optimal capacity matching scheme. The embodiment of the present application constructs a multi-objective optimization model, covers capacity gap, surplus rate balance and overtime, and improves the accuracy and efficiency of the algorithm in a complex production environment through an improved initial population generation strategy and a self-adaptive crossover and mutation mechanism. The method can accurately match capacity and demand, reduce waste, overtime and uneven load, significantly improve production efficiency and resource utilization, and optimize cigarette production management.