4results about How to "Improve selection speed" patented technology

The invention discloses a query optimizer selection method and device, equipment and a storage medium, and belongs to the technical field of data query. Each query optimizer constructs an expert network model, and the method comprises the following steps: inputting a to-be-optimized feature vector of a to-be-executed query statement into each expert network model to respectively obtain each first feature vector, and inputting the to-be-optimized feature vector into a preset ideal expert network model to obtain an ideal feature vector; based on each first feature vector and the ideal feature vector, generating a selected probability of each query optimizer; and taking the query optimizer with the maximum selected probability as a target optimizer of the to-be-executed query statement. Compared with a traditional method, estimation or prediction of vectorization representation of the execution plan is completed through internal interaction of the expert network model, the characteristics representing the execution plan can be rapidly obtained without interaction with a database, the operation efficiency is greatly improved, and the query optimizer selection speed is increased.

The invention discloses a method for realizing gesture data selection based on embedded Linux. The method comprises the following steps: storing target data into a created data storage structure; clicking a first row number and a first column number of clicking positions of the row height and the column width of the display list on the display list according to the monitored gesture clicking event; calculating a second row number and a second column number of the click position in the data storage structure according to the current reading position, the first row number and the first column number of the data storage structure; calculating a corresponding rectangular region on the data storage structure according to the second row number, the second column number and the row height and the column width of the data storage structure, and redrawing the background and the data of the rectangular region by using different colors; and writing a frame of data at the current reading position on the data storage structure into the FrameBuffer and refreshing the FrameBuffer. According to the invention, gesture click selection of data is realized on the interactive interface of the embedded system, and the flexibility and speed of embedded device control are improved.

This invention discloses a collaborative operation system and method for a drone and a robotic dog in a mining scenario. The system includes a drone, a robotic dog, and a wireless communication module. The drone and the robotic dog transmit data through the wireless communication module. The drone includes a laser terrain scanner, and the robotic dog is equipped with a high-definition camera and an infrared sensor. The laser terrain scanner is used to perform a global terrain scan of the mining blasting area to obtain laser point cloud data. The high-definition camera is used to identify obstacle elevation values, and the external sensors are used to collect road slope data. This invention utilizes a bidirectional BFS search algorithm combined with adjacent grid selection weights and priorities to generate multiple planned paths. The drone sends the planned paths to the robotic dog in advance, and the robotic dog only needs to select the optimal path based on the actual road conditions. The lightweight MobileNet model improves the robotic dog's computation speed and time, and the selection of the optimal path based on actual road conditions requires low hardware computing power.

The invention discloses an automatic lofting system and method for engineering surveying. The automatic lofting system is composed of a computer unit, an unmanned aerial vehicle unit and a piling robot unit. The computer unit selects lofting point coordinate data through installed software and exports a. Csv data file to the unmanned aerial vehicle unit and the piling robot unit through a network; the unmanned aerial vehicle unit comprises a vehicle body, a lifting support, a communication device, an unmanned aerial vehicle control terminal, a GPS receiver and a laser indicating device. The piling robot unit comprises a vehicle body, a jack, a timber pile bin box, a spraying device, a GPS receiver and a signal receiver. In the lofting process, the lofting mode is divided into a rapid lofting mode, a precise lofting mode and an auxiliary lofting mode, and a user can select and switch according to actual engineering requirements. According to the method, the selection speed of the lofting point is increased, indoor control lofting can be achieved, a traditional measurement lofting method is replaced, lofting and piling are integrated, and the working efficiency is greatly improved.