Decision tree model

About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.

View Planning of a Multi-rotor Unmanned Air Vehicle for Tree Modeling Using Silhouette-Based Shape Estimation.

Abstract: The use of a multi-rotor unmanned air vehicle (UAV) in image acquisition tasks is promising for three-dimensional (3D) object modeling. Such an autonomous data acquisition system can be useful to handle the geometric complexity of objects such as trees and the inherent difficulties of image capture. In this paper, we address the problem of view planning for a camera-equipped multi-rotor UAV to acquire an adequate set of images that leads to more detailed and complete knowledge of the 3D tree model. The proposed algorithm based on shape-from-silhouette methods incorporates both expected new visual information and vehicle movement. Occupancy estimation for volumetric object model serves as a baseline measure of new information. The outlined approach determines next best views across the viewpoint space bounded by the sensor coverage and the capability of the UAV with minimal a priori knowledge of the object. Simulation studies conducted with virtual reality environments show the effectiveness of the algorithm.

Robot positioning and navigation method based on bag-of-words tree cluster model

Abstract: The invention discloses a robot positioning and navigation method based on a bag-of-words tree cluster model. The method comprises the following steps: 1) inputting a long-time video stream containing a low dynamic indoor scene change; 2) performing off-line feature extraction on an image of the video stream; 3) clustering the obtained features through a k-means++ algorithm; 4) performing iterative clustering on the subspace obtained after clustering; 5) building a bag-of-words tree model for features after iterative clustering; 6) building a bag-of-words tree cluster model; 7) summarizing the motion law of a low dynamic object through a statistical principle; 8) analyzing and determining a bag-of-words tree model corresponding to the current moment based on the motion law according to the bag-of-words tree cluster model; and 9) using the determined bag-of-words tree model for loopback detection to realize robot positioning and navigation in a low dynamic environment. According to the invention, long-time self positioning and navigation of a robot can be realized in a low dynamic environment such as indoor space and the like at low cost under the condition of avoiding the use of expensive laser sensors.

Student Performances Prediction Based on Improved C4.5 Decision Tree Algorithm

Abstract: Data mining is a new technology and has successfully applied on a lot of fields. In this paper we applied a decision tree for mining the information that hides inside the student scores. In this paper, the C4.5 decision tree algorithm is improved. Using this improved algorithm, the decision tree model is produced and the classification rules are extracted. Finally, student performances are predicted. This technology helps a lot in middle school teaching improvement, and the quality of teaching becomes better.

Open computing language (OpenCL)-based red-black tree acceleration algorithm

Abstract: The invention discloses an open computing language (OpenCL)-based red-black tree acceleration algorithm. The method includes that according to the characteristic that multiple calculations are capable of being parallel processed during establishing the red-black tree, an OpenCL heterogeneous platform is adopted to rapidly establish a red-black tree model on the basis of big data; with an idea of employing graphics processing unit (GPU) acceleration, to-be-operated data are divided into multiple data blocks, and multiple cores enter a data insertion operation at the same time by the GPU; and after operations of all GPUs are synchronized, by means of a merge operation, the whole red-black tree is established. The OpenCL-based red-black tree acceleration algorithm has the advantages that in the situation of the big data, the red-black tree is rapid to be established within a short time.