35results about How to "Demonstrate feasibility" patented technology

The invention discloses a convolutional twin point network leaf profile splicing system based on multi-space similarity, including a data acquisition module, a convolutional twin point network and a data splicing module. The convolutional twin point network includes a network module that iterates several times, and a network module Including feature extraction module, matching matrix module, attention mechanism module and singular value decomposition module; feature extraction module uses edge convolution network structure to extract high-dimensional spatial features in source point cloud and target point cloud, and then uses high-dimensional spatial features and The coordinate space calculates the feature space matching matrix and the coordinate space matching matrix respectively, and then handles the conflict between the feature space matching matrix and the coordinate space matching matrix through the attention mechanism to obtain the final matching matrix, and calculates the source point cloud through the final matching matrix The corresponding relationship with the midpoint of the target point cloud, and finally the rigid body transformation is obtained through singular value decomposition, and the optimal rigid body transformation is obtained based on multiple iterations.

The invention provides a feature value analysis system for small-interference stability of a large-scale power system, and belongs to the technical field of power system simulation and analysis. The feature value analysis system comprises a BPA data interface module for achieving seamless read-write operation of a BPA data file, a sparse matrix calculation module for achieving relevant sparse matrix processing in small-interference stability feature value analysis, a power flow calculation module, a system modeling and linearization module, a state matrix calculation module, an all feature value calculation engine module, a partial feature value calculation engine module and an oscillation mode extraction and analysis module. Omni-bearing and missing-free feature value simulation analysis for small-interference stability of an actual large-scale power grid is achieved by the adoption of TTQRE and IRAM and JDM with multiple calculation schemes.

The invention discloses a convolutional twin point network blade profile splicing system based on multi-scale feature fusion, including a data acquisition module, a convolutional twin point network and a data splicing module. The convolutional twin point network includes a network module that iterates several times, The network module includes a feature extraction module, a feature space matching module and a singular value decomposition module; the feature extraction module uses the edge convolution network structure of the improved pyramid structure to extract the high-dimensional spatial features in the source point cloud and the target point cloud, and then utilizes The high-dimensional spatial features calculate the feature space matching matrix, and use the feature space matching matrix to calculate the correspondence between the points in the two point cloud data (source point cloud and target point cloud), and finally obtain the two point cloud data ( The rigid body transformation between the source point cloud and the target point cloud), and the optimal rigid body transformation is solved according to multiple iterations. The experimental results show the feasibility and good practical application prospects of this method.

The invention discloses a fuzzy information granulation-based method for predicting temperature fluctuation ranges of transformer winding hot spots, including determining the number of granulation time windows according to the fuzzy information granulation quality, and extracting effective information of original data by using the fuzzy information granulation technology; The wavelet neural network prediction model is constructed based on effective information, and the structural parameters of the wavelet neural network are optimized through the harmony search algorithm; the temperature fluctuation range of transformer winding hot spots is predicted using the adjusted model of structure and parameters. The prediction accuracy of the invention is high, and has certain guiding significance for the operation and maintenance of the transformer.

The invention provides a dual-track flight landing real-time scheduling method. The method comprises the steps of building a dual-track flight cellular automation model, simulating a dual-track airport terminal area to form the dual-track flight cellular automation model, inspecting airport flight data at each moment, placing flights reaching the boundary of the airport terminal area into the dual-track cellular automation model, and carrying out updating on the flight speed, flight distance and a landing runway of each flight in the dual-track flight cellular automation model according to the interval between the adjacent flights, the distance between the airport and each flight, and the air line of each flight in the dual-track flight cellular automation model. According to the dual-track flight landing real-time scheduling method, due to the dual-track airport design, the flow management of the flights inside the dual-track airport terminal area can be achieved, and the feasibility, effectiveness and real-time performance for achieving the dual-track flight landing real-time scheduling are reflected.

The invention provides a concept connection method for medical diagnosis texts. The method employs a recurrent neural network model and simulates a series of complicated morphological and syntactic conversions employed by a rule-based system, summarizes and arranges invisible concepts during testing by using vector type concept symbols, shares the features thereof and predicts the whole traversal along multiple layers of a graph to perform concept connection. The method comprises the steps of firstly, establishing a recurrent neural network system (RNNs) which includes a span encoder, a concept encoder and a decoder; secondly, training the model, wherein the basic data source of the model is from the systematized nomenclature of medicine-clinical terms (SNOMED-CT) in a knowledge graph and input-output values; thirdly, employing a rule-based algorithm, applying a series of complicated morphological and syntactic conversions, identifying the spans of medical records accurately, and adding tags to form a big data set of correlated concepts; fourthly, performing concept connection on the results of the last step. The method has higher accuracy and a higher recall rate.

The invention relates to the technical field of trailers, and discloses a trailer structure for road management, which includes a universal wheel, the top surface of the universal wheel is fixedly connected with a bearing 1, and the middle part of the bearing 1 is fixedly sleeved on the screw thread. The bottom end of the rod, the lower part of the threaded rod is threaded in the middle of the spiral ring, the top of the threaded rod is fixedly connected with a fixed ring, and the middle part of the fixed ring is movably socketed with a pry bar protruding from the outer body . The present invention adopts the design of the prying tube and the transmission rod. When it is necessary to tow the vehicle on the slope, the prying bar can be sleeved in the inner cavity of the prying tube. If the vehicle on the trailer is out of control on the slope , you can pull the pry bar upwards in time, then the rubber sheet will be closely attached to the ground, thereby increasing the friction between the trailer and the ground until the vehicle is stopped, which solves the problem that the transmission trailer lacks a braking structure , reflecting the safety of the device.

The invention discloses a test device and evaluation method for the injectability of horizontal grouting of highway subgrade. The grouting device is used to inject slurry into the grouting flower pipe arranged horizontally in the test grouting box, and the grouting flower pipe and the test grouting box The other spaces inside the body constitute the sand filling area, and the sand filling to be tested is filled in to simulate the formation of the subgrade structure. The pipe wall is uniformly provided with a plurality of grouting through holes, and the slurry enters the sand filling layer along the grouting holes, thereby realizing the simulation of the injectability of the slurry along the sand filling layer. This device has a simple structure and can Realize the preparation, pumping and grouting simulation of grouting materials, through the grouting sand tube and grouting sand table test on the grouting ability, obtain the seepage parameter index, and reflect the grouting effect in the test soil sample formation through the index Injectability analysis to effectively demonstrate the feasibility of subgrade grouting operations.