117 results about "Pruning algorithm" patented technology

A system and method for planning placement of virtual machines VMs in a computing environment comprising a set of hosting machines HM. The method includes constructing a bipartite directed graph-based model that represents both a current and a target placement states, both including virtual machine nodes v in VM and nodes h in HM. Using a technique of graph pruning, the method iteratively generates a plan for achieving a desired target placement starting from the current placement without temporarily violating any policy or resource constraint. The application of the pruning algorithm to VM deployment automation necessarily defines a new model. The methodology employed safely manages concurrent changes in a datacenter, so that the environment can adjust faster to changing constraints. Furthermore, the present invention allows detection of migration cycles, caused by deadlocked combinations of capacity and policy constraints, and resolving them.

The invention relates to a mobile phone screen MURA defect detection method based on a convolution neural network pruning algorithm. The mobile phone screen MURA defect detection method based on a convolution neural network pruning algorithm includes the steps: 1) customizing a depth convolution neural network, and utilizing the existing training data to train a neural network of detecting a mobile phone screen MURA defect; 2) utilizing an adaptive template coupling method to perform pruning operation on the convolution neural network, reducing the network scale, and reducing the algorithm running time; 3) zooming the mobile phone screen images shot by a high resolution camera, forming an image pyramid, for the image of each scale, utilizing a sliding window method to segment the images into small blocks, and taking all the small blocks of images as one group and sending the group to the convolution neural network; and 4) selecting all the characteristic images of the intermediate layer as the response images for the defect, and utilizing a threshold segmentation method to finally obtain the area position of the mobile phone screen MURA defect.

The invention provides an automatic entity basic information generation system and method based on a Markov model, which are suitable for generating basic data of a test and trial scene of an information system. Entity attribute data relating to the system and the method has an enumeration type characteristic. The method comprises a step of defining an attribute priority sequence, a step of constructing a multiple-valued depended statistical decision tree and a step of carrying out parameter study and pruning algorithm. The system comprises a device for defining attribute priority sequence, a device for constructing the multiple-valued depended statistical decision tree and a device for carrying out the parameter study and the pruning algorithm.

The invention provides a mobile robot path planning method based on an improved RRT algorithm in an indoor environment. A high-precision grid map of a robot working environment is established; map segmentation is carried out, and then a next grid needing to be searched is determined by adopting a neighborhood extension strategy; the type of a search grid and the number of effective sampling pointsare determined through a random sampling experiment, then the effective sampling points are added into a random tree according to a neighborhood optimal principle, state updating is conducted on thegrid based on a memory strategy, and finally smoothing processing is conducted on an obtained planning path through a pruning algorithm and a Bezier curve. Due to introduction of map segmentation andobstacle edge detection ideas, the sampling efficiency of an RRT algorithm in complex maps such as narrow channels is improved; due to introduction of a memory mechanism and a neighborhood extension strategy, the planning success rate of the algorithm in a complex environment is increased; a father node is selected according to the neighborhood optimal mode, and problems that the algorithm randomness is high, and the path is not optimal are solved.

A database spread over multiple nodes allows each node to store a journal recording changes made to the database and also allows a journaling component to manage the memory space available for journaling. Two threshold size values may be specified for the journal. The first threshold value specifies a journal size at which to being pruning the journal on a given node. A journal pruning algorithm may be used to identify journal entries that may be removed. For example, once a given transaction completes (i.e., commits) the journal entries related to that transaction may be pruned from the journal. The second threshold value specifies the maximum size of the journal. After reaching this size, journal entries may be written to disk instead of the in-memory journal.

A resource-efficient live streaming system includes a broadcaster and a streaming server. The broadcaster receives a live feed and broadcasts a media stream to the streaming server containing several descriptions of the live feed along with control information. The broadcaster includes a stream thinner that implements a pruning algorithm. If descriptions from different streams are similar enough, one or more of them may be discarded without penalizing the quality of service perceived by the receivers. The streaming server assembles compressed data units into streams according to the control information from the broadcaster. The streaming server may also gather client feedback in order to estimate the status of the transmission channels and forwards the information to the broadcaster. The streaming server builds and streams media information to clients according to user preferences and receiver capabilities.

The invention discloses an oil production data frequent pattern mining method based on weak wildcard, and relates to the field of data mining. The oil production data frequent pattern mining method based on the weak wildcard comprises the steps that 1, oil field daily fluid production time series data is converted into a coding sequence; 2, the coding sequence is mined to obtain different types of frequent sequence patterns, and an oil well is comprehensively depicted from various angles. The method has the advantages that the mining problem of three frequent sequence patterns is defined, the different types of frequent patterns can be mined from actual oil well production data, and the oil well is comprehensively depicted from the different angles; an algorithm is simple and efficient, a pruning algorithm is achieved, the time complexity is low, and the method is conveniently achieved in real time; a pattern filter technique is proposed, the different types of frequent patterns such as the powerful pattern, the special pattern and the popular pattern can be obtained through filtration for the different requirements; the method can be widely applied to various time series data.

The invention discloses a coal ash fusion temperature forecasting method based on a construction-pruning mixed optimizing RBF (Radial Basis Function) network, which is characterized by comprising the following two stages of crude regulation and fine regulation: the crude regulation stage comprises the steps of dynamically increasing the number of hidden nodes according to a principle of enabling an energy function to be minimum, selecting corresponding sample input as a data center and stopping till the number of the hidden nodes meets a stopping criterion; the fine regulation stage comprisesthe steps of further regulating the structure and the parameters of the RBF network, which are obtained through the crude regulation by using a Gaussian regularization method, establishing the corresponding construction-pruning mixed optimizing RBF network on the basis of the chemical constituents of coal ash, and forecasting coal ash fusion temperature through the construction-pruning mixed optimizing RBF network. A construction-pruning mixed optimizing algorithm (CPHM) effectively integrates the advantages of a construction algorithm and a pruning algorithm, can not only dynamically regulate the number of the hidden nodes of the RBF network, but also enable the data center of the RBF network to change in a self-adaption way; and in addition, the invention has the advantages of smaller structure, better generalization capability and higher robustness.

The invention relates to a master-slave mode snake-like robot system and a position control method thereof. Master manipulator information of a master robot is obtained and subjected to master-slave mapping change to obtain master-slave mapping position information. Actual displacement variation of a slave robot is obtained, and slave manipulator position error is obtained through calculation according to the actual displacement variation of the slave robot. According to the master-slave mapping position information and the slave manipulator position error, slave manipulator angle variation is obtained by processing with a neural network correlation pruning algorithm and output to the slave robot so as to control the slave robot to move following with the master robot. Through the neural network correlation pruning algorithm, precise position control over the slave robot and the master robot is achieved, reverse kinematics does not need to be conducted on the slave robot, solution multiplicity is avoided, the number of degrees of freedom of the slave robot is not limited, and control real-time performance is improved.

A resource-efficient live streaming system includes a broadcaster and a streaming server. The broadcaster receives a live feed and broadcasts a media stream to the streaming server containing several descriptions of the live feed along with control information. The broadcaster includes a stream thinner that implements a pruning algorithm. If descriptions from different streams are similar enough, one or more of them may be discarded without penalizing the quality of service perceived by the receivers. The streaming server assembles compressed data units into streams according to the control information from the broadcaster. The streaming server may also gather client feedback in order to estimate the status of the transmission channels and forwards the information to the broadcaster. The streaming server builds and streams media information to clients according to user preferences and receiver capabilities.