16 results about "Spatial search" patented technology

This invention relates to the field of navigation assistance technology, and in particular to a dynamic obstacle prediction and obstacle avoidance path planning method based on multi-sensor fusion. This invention achieves comprehensive perception of dynamic obstacles through multiple sensors, providing a rich and reliable data foundation for subsequent processing. At the same time, it predicts the motion of dynamic obstacles through data processing fusion and model prediction, fully considering the motion inertia of obstacles to make their trajectory prediction closer to real physical laws. Furthermore, by "delineating the final obstacle avoidance target area", the global path search problem is transformed into a local but sufficiently large spatial search problem, significantly reducing the number of grids to be processed and the amount of search computation, meeting the stringent real-time requirements of mobile devices. Moreover, by constructing a cost function, it avoids areas that obstacles may occupy in the future in real time, thereby generating an obstacle avoidance planning path, which helps to improve path safety.

The prompt word determination method, device, electronic equipment and storage medium provided by the present application relate to the technical field of prompt word processing. The method obtains baseline prompt words and a test case set based on a preset service requirement; performs multi-round response testing on a target model by using the baseline prompt words and the test case set, obtains model behavior logs corresponding to each round of response testing, and obtains a prompt word position effect matrix and a vocabulary sensitivity knowledge base based on the model behavior logs corresponding to each round of response testing; and performs mixed variable space search processing by using the prompt word position effect matrix, the vocabulary sensitivity knowledge base and the model behavior logs corresponding to each round of response testing, to obtain effective prompt words, thereby improving the optimization efficiency of prompt words and enhancing the verifiability of results.

This invention discloses a pole angle consistency improvement method based on residue enhancement, relating to the fields of radar signal processing, target detection and recognition technology. This invention maps the complex values ​​of poles to two variables: real and imaginary parts. It uses an optimization algorithm to dynamically optimize the unnormalized real and imaginary parts of the poles. During the optimization process, the optimized poles and the frequency domain response echoes reconstructed by the original residues are brought closer to the frequency domain response echoes of the original poles theoretically obtained by increasing the residues in the vicinity of the frequency range corresponding to the optimized poles. This combines the spatial search of pole positions (adjusting frequency position) with the gain effect of the residue amplitude (increasing response intensity), effectively solving the problem of pole angle flickering caused by low echo energy contribution during pole extraction. It corrects pole positions at their root, identifies hidden poles, improves pole angle consistency, and generates a complete pole feature database.

This invention belongs to the field of power system technology, specifically relating to a method and system for mining rules for electricity price and fee consistency verification. The method includes: acquiring a verification dataset and calculating the equivalence partitions of quantity, price, and fee data; using a depth-first spatial search strategy to mine data consistency relationships, obtaining a set of consistency relationships in the data; using the obtained set of consistency relationships to perform rule parsing on the quantity, price, and fee consistency relationships; and identifying rare data in the quantity, price, and fee data through rule parsing. This invention applies a novel consistency rule mining method for categorized data to the verification of electricity price and fee data. It can proactively mine potential rules in the data, effectively overcoming the shortcomings of previous manual rule definition methods, such as high workload, long time consumption, insufficient rule coverage, and the ability to only discover abnormal business data covered by defined rules. This assists business personnel in completing the verification of electricity marketing quantity, price, and fee data more intelligently and comprehensively.

The application relates to a weak synchronization microseismic positioning method based on a time-frequency saliency mask. In view of the problems of low signal-to-noise ratio of microseismic signals in a complex environment, weak anti-interference ability of a traditional feature method and insufficient positioning precision, firstly, a short-time Fourier transform is adopted to construct a time-frequency representation, then a time-frequency saliency mask is introduced to enhance effective signal features, and an inter-station similarity matrix is constructed by combining energy normalization and a cross-correlation function, and finally, cross-correlation superposition positioning is carried out in a spatial search domain. The method can effectively suppress noise interference, improve the focusing of the cross-correlation peak value, and thus improve the microseismic event positioning precision and stability, and is suitable for application scenarios such as mine safety monitoring and disaster warning.

The application discloses a parameter setting method and system of PSS based on complex domain vector synthesis, and belongs to the technical field of power system automation and control. The method comprises the following steps: obtaining an open-loop frequency response, and extracting a phase lag characteristic curve of a channel; based on a complex domain vector synthesis model and the phase lag characteristic curve, a complex response calculation formula is constructed, a total open-loop phase is defined, a parameter vector is set and a parameter feasible region is determined, a target compensation phase is set, a weighted comprehensive phase error target function is defined, and a boundary value is set; the weighted comprehensive phase error target function is taken as a fitness function, parameter space searching is performed, and a parameter vector that minimizes the fitness function is solved; the parameter searching process of the global optimization algorithm is optimized; the optimal parameter set is verified in multiple dimensions and vector synthesis visual analysis is performed, and parameter setting of a power system stabilizer is completed. The application has correct principles, relatively high efficiency and accuracy in processing, and high engineering applicability.

The application belongs to the technical field of two-dimensional layout, and discloses an automatic layout method and system based on discrete space search. The method comprises the following steps: obtaining layout parameters and assigning initial priorities according to part areas, selecting high-priority untried parts after resetting the layout state, generating a placement scheme by traversing candidate placement points combined with 0° / 90° rotation, optimizing the layout according to the contact perimeter, and promoting the priority of the part if it is invalid; and then generating new candidate placement points based on the current layout, and completing the layout through multiple rounds of iteration. The system corresponds to nine modules such as parameter acquisition and state resetting, which work cooperatively. The application improves the idle space utilization, reduces isolated gaps, improves material utilization and layout completion rate, simplifies placement decision logic, controls calculation complexity, has high layout efficiency, can reduce enterprise production cost, and is suitable for two-dimensional rectangular layout scenes in the fields of industrial manufacturing, packaging and the like.

The present disclosure relates to a registration method and system for mouse brain tissue slice images. Based on the two-dimensional mouse brain tissue slice images to be registered and the section parameter prediction model, the spatial positioning parameters are determined to effectively replace the cumbersome three-dimensional spatial search and iterative matching in the prior art based on the one-time prediction of the section parameter prediction model, to improve the matching efficiency and give the robust spatial positioning parameters; based on the spatial positioning parameters, the two-dimensional mouse brain tissue slice images and the three-dimensional average mouse brain template atlas, the deformation mapping information is determined, based on the spatial positioning parameters and the three-dimensional standard atlas, the two-dimensional labeled slice is determined, and based on the two-dimensional labeled slice and the deformation mapping information, the registered mouse brain tissue slice images are determined, to perform subsequent fine alignment processing in the two-dimensional level, which not only greatly reduces the computational complexity and algorithm difficulty, but also forms an automatic workflow of intelligent three-dimensional positioning and efficient two-dimensional registration, thereby providing strong support for high-throughput analysis and clinical application.

This invention discloses a communication link disturbance detection method and system based on signal quality assessment, specifically relating to the field of communication link status detection and testing technology. It addresses the problem that existing technologies struggle to assess link status in real-time and automatically, and effectively detect antenna misalignment caused by environmental disturbances. The method involves acquiring receiver signal quality parameters in real-time and processing them within at least two observation windows of different time lengths to obtain corresponding stability indices. It analyzes the changing trends and time-varying patterns of each stability index in the horizontal and vertical spatial dimensions to obtain disturbance characteristics in both spatial and temporal dimensions. This allows for the determination of whether alignment disturbances caused by environmental factors exist and their types. When disturbances are present, a corresponding spatial search strategy is determined based on the type, and this strategy is executed based on the stability indices to find an antenna pointing position that optimizes the overall stability. Finally, a control command is generated to drive the antenna to adjust to this position.

The application discloses a river network hydraulic property interpolation method and related devices, and the application obtains a kernel width parameter vector that is adapted to an interpolation matrix through river network section information (i.e. section mileage and hydraulic properties of the section at different water levels), adopts a Gaussian kernel function, obtains a probability weight matrix, and converts a process of relying on logical judgment and spatial search in traditional interpolation into a weighted fusion process that is completely based on matrix operation, so that conditional judgment branches can be avoided, parallel computing potential of GUP can be fully exerted, the global rationality and stability of the interpolation result can be ensured while the computing efficiency is improved, the unity of the computing performance and the interpolation accuracy is realized, and efficient and high-precision calculation of the river network section property is realized.

This invention provides a multi-satellite collaborative resource scheduling method for airborne target space search missions, relating to the field of satellite observation resource scheduling technology. The method employs a 3D mesh vertex method to generate satellite observation strips, comprehensively considering the three-dimensional maneuvering characteristics of airborne targets. This extends the search mission from a two-dimensional plane to a three-dimensional space and avoids complex direct calculations of spatial geometry. This enables the search to effectively cover targets at different altitudes, solving the problem that traditional two-dimensional scheduling methods cannot reliably detect airborne targets due to neglecting the altitude dimension.

This invention belongs to the field of production scheduling technology for flexible manufacturing systems, specifically relating to a Petri net-based method for rescheduling urgent orders in flexible manufacturing systems. Based on the Petri net model of the flexible manufacturing system, this invention proposes a novel rescheduling strategy; when urgent orders arrive, it proposes a method for reconstructing the Petri net model and classifying and rearranging the processing sequence. In the design of the scheduling strategy, this invention optimizes and improves the genetic algorithm. First, it uses the Tent chaotic mapping method to generate the initial population, making the population distribution more uniform; second, in the selection operation of the inheritance operation, it adopts an elite retention strategy and a roulette wheel method, selecting the better individuals based on their fitness values; in the crossover operation, it uses the POX crossover method, which can effectively expand the range of neighborhood solutions; and in the mutation operation, it uses a non-uniform mutation rate to enhance the algorithm's spatial search capability, enabling it to perform a more comprehensive spatial search.

The application discloses a diffusion model reasoning acceleration method based on optimal time step sequence search and knowledge distillation, which constructs a unified search space covering time step sequences and corresponding model architecture configurations without overall fine-tuning of a pre-trained diffusion model, and searches for optimal time step sequences. Based on the optimal diffusion time step sequences obtained through the search, a knowledge distillation training method is designed, a main distillation loss function is constructed within a discrete time step subspace defined by the optimal diffusion time step sequences, and an adjacent time step consistency loss is introduced to relieve the discrete error introduced by a non-uniform time step span. In the reasoning stage, the teacher model is frozen, and the distilled student model is combined with an efficient sampler ACDMS based on UniPC and fusing flow matching dynamic correction to perform limited step sampling on the optimal time step sequence, so that reasoning acceleration is realized under the condition of keeping generation quality.

The application relates to a point cloud data simplification method, device, equipment, medium and program product. The method comprises the following steps: constructing a spatial search structure of a plane structured light point cloud data, the spatial search structure being used for marking the nearest neighbor points of each point cloud; determining the plane error between each point cloud and the nearest neighbor point corresponding to the point cloud, wherein the nearest neighbor point corresponding to each point cloud and the point cloud constitutes a point cloud pair; determining a target point cloud pair that needs to be simplified according to the plane error; updating the vertex position of the target point cloud pair to obtain a new vertex; and replacing the target point cloud pair with the new vertex to obtain simplified plane structured light point cloud data. Thus, the plane error of a point cloud pair and a neighborhood thereof can be calculated, the geometric complexity of a local region can be accurately quantified, the point cloud pairs of flat regions are preferentially simplified, the point cloud pairs of feature regions such as edges and corner points are reserved, and finally, a precise balance between feature reservation and simplification efficiency is achieved.

This invention discloses a method and system for calculating target values ​​on both sides of a road milling machine and controlling its actuators, relating to the fields of intelligent control of road construction equipment and three-dimensional construction data processing. The method includes: reading construction files and constructing a three-dimensional construction mesh; receiving positioning data and heading angle from a positioning antenna to obtain the antenna's position in the construction plane coordinate system, and calculating the real-time positions of the left and right endpoints of the milling drum based on the machine's geometric parameters and heading angle; performing a coarse-to-fine spatial search on the endpoints to determine adjacent station line intervals based on the real-time positions; constructing triangular units within the intervals and calculating the target values ​​of the left and right endpoints using centroid coordinate interpolation; generating control messages based on the target values ​​of the left and right endpoints and sending them to the left and right actuators via a communication bus. This invention provides continuous target value calculation, can enable tilt correction to improve endpoint positioning consistency, and has anomaly detection and safety handling capabilities.

The application discloses a cell metabolism model of an interpretable modular structure network. The modular network comprises an input layer, two hidden layers and an output layer. Firstly, the functions of each module are determined, the input layer is corresponded to the enzyme concentration in cells, the enzyme abundance data is used for calculation instead, the two hidden layers are corresponded to the upper bound of reaction flux and the size of reaction flux respectively, and finally, the output layer is defined as the concentration change of metabolites in cells. Four modules are integrated into a completed network model, and the connection between layers has practical significance. The connection parameters between layers are pretreated, the logical relationship between the processed parameters is determined, and the parameters and structure of the model are determined. The mathematical formula of the network is analyzed, the formula is deduced, and a solving method based on a differential evolution algorithm and a matrix null space search is developed. Finally, iteration parameters are set, and the metabolic model is simulated and calculated. The application can be applied to cell modeling in the fields of pharmaceutical, food and other industrial biology.