97 results about "Node splitting" patented technology

A data structure, added to a modified form of the Blink-tree data structure, tracks delete states for nodes. The index delete state (DX) indicates whether it is safe to directly access an index node without re-traversing the B-tree. The DX state is maintained globally, outside of the tree structure. The data delete state (DD) indicates whether it is safe to post an index term for a new leaf node. A DD state is maintained in each level 1 node for its leaf nodes. Delete states indicate whether a specific node has not been deleted, or whether it may have been deleted. Delete states are used to remove the necessity for atomic node splits and chains of latches for deletes, while not requiring retraversal. This property of not requiring a retraversal is exploited to simplify the tree modification operations.

The invention discloses a method of sending a data package and incidentally sending a reverse interest package in content center network. The method includes the following steps : step 1, sending the interest package to the network to by a user A show that the user A is interested in the content; step 2, an intermediate node dealing with a request when the intermediate node in the network receives the interest package; step 3, combining a response data package and the interest package which needs to be requested by the user A to form a mixed data package by a user B when the user B wants to send a data request to the user A; step 4, the intermediate node splitting the mixed data package into a data package and a reverse interest package when the intermediate node in the network receives the mixed data package and respectively dealing with the data package and the reverse interest package; step 5, splitting the mixed data package by the user A when the user A receives the mixed data package, receiving the data package and delivering the data package to primary requested program, and meanwhile responding to the interest package by the user A and producing a corresponding data package. The method of sending the data package and incidentally sending the reverse interest package in content center network reduces transmission times of the package and improves information quantity and efficiency in once transmission.

A system and method for spectral node splitting in cable TV network based on hybrid fiber-coax architecture is disclosed. Two-way optical signals carrying video and / or multimedia content are received at a signal distribution node. Portions of the received signals are processed according to the functionality the direction thereof. Certain frequency ranges are passed intact while specific different downstream and specific different upstream frequency bands are converted in a manner as to be allowed to be multiplexed into an extended broadband signal. The frequency bands within the extended broadband signal are distributed selectively among separate branches of the network. The frequency bands dedicated to the upstream traffic are received selectively from the separate network branches to be back converted and transmitted upstream to the network controller.

Methods of updating b-tree data structures (e.g., b*tree data structure) using search key insertion and deletion operations proceed from respective known states (e.g., respective canonical forms). These insertion operations include inserting a first search key into the b-tree by reconfiguring (e.g., pre-processing) a plurality of sibling nodes of the b-tree into a predetermined overloaded form having a shape that is independent of a value of the first search key to be inserted therein. An operation is then performed to split the sibling nodes by redistributing the first and other search keys among an expanded plurality of the sibling nodes. These insertion operations use a process that trades off possibly performing additional memory accesses (e.g., to shift search keys (and / or handles or pointers) to the predetermined overloaded form) for the certainty that the same key movements are ultimately performed during operations to split sibling nodes.

A new method for simulation of general electrical circuits on parallel computing platforms is disclosed. Parallel simulation of general time-domain circuits that are represented by nonlinear / linear differential algebraic equations is accomplished by partitioning them into smaller subcircuits via a novel combination of the companion form representation of the given circuit and an efficient form of node splitting, during Newton Raphson iterations, at any time point. The new invention formulates the interface vectors between partitions, through purely binary vectors, leading to a high degree of parallelism, scalability and reduced computational and communication costs for synchronizing the solutions between various partitions. Parallel platforms considered can be diverse such as (including but not restricted to) multicore CPUs, distributed systems of computers. The new invention also provides for scalable parallel simulation of mixed-domain formulations, such as (including but not restricted to), integrated circuits, electronic packages, PCBs, electromagnetic modules, MEMS and optical components etc.

A novel node device enables transmission of a wideband signal, in compliance with various acceptable transmission standards and protocols. The signal consists of the legacy spectrum of about 5-860 MHz as well as a new downstream spectrum of about 1000-2000 MHz and a new upstream spectrum of about 2000-3000 MHz or about 930-1100 MHz. The novel device enables transfer of additional data in the upstream direction employing multiple upstream bands without making substantial investment in upstream physical node splitting thus providing networking services to residential subscribers, as well as to small and medium-sized businesses (SMB), which may operate under existing DOCSIS protocols and controlled by standard DOCSIS routers (CMTSs).

The invention discloses a three-dimensional R tree spacial index method considering levels of detail, which utilizes a globally optimal node selection method from bottom to top and then from top to bottom, selectively adopts a splitting mode of two into three and takes a newly-proposed three-dimensional Cauchy value as a node shape factor. The comprehensive evaluation index considering the node covering, overlapping and shape factors is enabled in the node selecting and node splitting operations, thereby ensuring the shape of the generated three-dimensional R tree to be reasonable. The management of levels of detail model is considered conveniently by means of a balanced hierarchical structure. The method supports the generation and inquiry of the spacial index of a two-dimensional and three-dimensional space target, has very high efficiencies of generation and inquiry, and can be applied to many professional fields correlative with the three-dimensional space such as various space database systems, three-dimensional roaming software and the like.

A system and method for spectral node splitting in cable TV network based on hybrid fiber-coax architecture is disclosed. Two-way optical signals carrying video and / or multimedia content are received at a signal distribution node. Portions of the received signals are processed according to the functionality the direction thereof. Certain frequency ranges are passed intact while specific different downstream and specific different upstream frequency bands are converted in a manner as to be allowed to be multiplexed into an extended broadband signal. The frequency bands within the extended broadband signal are distributed selectively among separate branches of the network. The frequency bands dedicated to the upstream traffic are received selectively from the separate network branches to be back converted and transmitted upstream to the network controller.

A region of a node is searched to find a content-defined split point. A split point of a node is determined based at least in part on hashes of entries in the node and the node is split based on the determined split point. The search region is searched for the first encountered split point and the node is split based on that split point. That split point is based on a predetermined bitmask of the hashes of the entries in the node satisfying a predetermined condition.

The invention belongs to the technical field of data mining, in particular to a method for searching for an approximate sequence of a given time sequence from a massive time sequence database. The method comprises the following steps of: adopting a tree index node representation mode; constructing indexes one by one according to an algorithm frame of the indexes; selecting an optimal strategy for node splitting; and performing query on the basis of the DSTree indexes to search for the approximate sequence of the given time sequence from the massive time sequence database. According to an indexing method, the length and dimension of an index sub-sequence are regulated according to the data distribution condition of the time sequence, and by a new index representation mode, a requirement for the provision of an upper distance bound can be met, and query efficiency can be greatly improved.

The invention discloses a router calculation method and a router calculation device. The router calculation method comprises the following steps of: dividing each network element node in an optical transmission network (OTN) into a plurality of network element sub nodes; configuring sub node links for the plurality of network element sub nodes, and establishing topological expansion information of the network element sub nodes according to the sub node links; and utilizing a constraint shortest path first (CSPF) algorithm to carry out router calculation on the network element sub nodes according to the topological expansion information. With the adoption of the router calculation method and device provided by the invention, resources of DXC (Data Exchange Control), OEP (Original Entry Point) and the like can be saved; the effective use ratio of an OXC (Optical Cross Connection) resource is improved; and the service consumption is reduced.

The invention discloses a CART-based decision-making tree construction method in cognitive computation. The method comprises the following steps: initializing a root node of a decision-making tree and a characteristic attribute set corresponding to the root node according to establishment rules of the decision-making tree; carrying out sorting of data in a training set; judging whether all sample data in a node is of the same type or not; calculating the optimum characteristic attributes and the suboptimum characteristic attributes of the node to be split; judging whether the node satisfies the selected optimum splitting attributes and splitting conditions of an interruption mechanism or not; if the node satisfies the selected optimum splitting attributes and the splitting conditions of the interruption mechanism, carrying out splitting through the optimum splitting attributes, then iteratively replacing a current node with the node split through the characteristic attributes, and adding two new leaf nodes respectively from a left branch and a right branch, so as to achieve automatic splitting of the decision-making tree; and if the node does not satisfy the selected optimum splitting attributes or the splitting conditions of the interruption mechanism, waiting for data stream inputs, carrying out sample updating, and continuing to calculate node splitting. The method provided by the invention has the advantages that the accuracy of data stream processing is further improved, so that the possibility of system blocking is reduced.

The invention relates to the field of banknote anti-counterfeit research, and specifically relates to a banknote authentication method based on a random forest. A multispectral image of a banknote acquired based on a sensor is processed using an embedded equipment chip. The method comprises the following steps: carrying out feature extraction in a specific area cut out based on an acquired original image and a gradient image thereof to get multiple features needed for classification; creating a single decision tree, and carrying out node splitting from a root node to leaf nodes; and building a random forest including multiple decision trees. Through the scheme, a random forest classifier which can be realized on embedded equipment is established, banknote authentication can be performed on a currency counter using a DSP chip as a processor, the banknote authentication of the currency counter is improved, counterfeit banknotes mixed in real ones can be accurately identified and classified, computation is quick, and the real-time requirement of the equipment is satisfied. The defect that the traditional authentication method has weak ability to identify unknown counterfeit banknotes and new currencies is overcome.

The invention discloses an electromechanical system logical relationship generation method and device and a building information model. The method includes: a conversion step, namely converting a physical relationship between pipeline components and electromechanical devices in a to-be-processed building information model into a corresponding topological relationship; a separation step, namely separating electromechanical device representing device nodes and pipeline component representing pipeline nodes in the topological relationship to obtain more than one subgraph acquired based on pipeline node splitting, wherein each subgraph represents pipeline groups in connection with one electromechanical device; a logic establishment step, namely establishing a logic connection relationship of different electromechanical devices according to an association relationship of different electromechanical devices connected to a same pipeline group. By adoption of the scheme, the logic connection relationship can be generated according to physical connection information, and accordingly fault positioning efficiency of the building information model in an operation and maintenance operation is improved.

The invention provides an establishing method of a product STL model spatial index structure, which is characterized in that a product STL model data file is read first, an axial bounding box of each triangular facet is established, corresponding data node of the triangular facet is established according to the center of the axial bounding box and the radius of a circumsphere and stored in a data node sequence, each data node in the sequence is inserted in the index structure through steps such as insertion position selection, node splitting, node axial bounding box adjustment and the like, and the data node with larger volume of the axial bounding box is reinserted in the index structure to further optimize the index structure and achieve the establishment of the product STL model spatial index structure. The establishing method can establish spatial index structures of various triangular grids with complex profiles, and has the characteristics of strong stability and high query efficiency.

The invention relates to a method and a device for testing an artificial intelligence behavior in a game and electronic equipment. The method comprises the following steps: modeling an artificial intelligence behavior tree in a configuration file to obtain a tree object; performing node splitting on the tree object to obtain a node set, performing branch splitting on the tree object to obtain a branch set and respectively recording execution conditions of branches in the branch set; respectively loading nodes in the node set into the game for test, respectively loading the branches in the branch set into the game for test after the recoded execution conditions are set and respectively loading the tree object into the game for test after the recoded execution conditions are set. Through the method and the device provided by the invention, the test efficiency aiming at an AI behavior in the game test can be improved.

The invention provides a rock bust danger level prediction method based on a local weighting C4.5 algorithm and relates to the technical field of rock burst prediction. The method includes the steps of firstly, adopting an MDLP method for conducting discretization on continuous attribute data in sample data, then adopting a local weighting method for selecting a training set and calculating the weight of samples, utilizing the weight of the samples to calculate an information gain ratio of each attribute, and selecting sample attributes as root nodes of a C4.5 decision tree and splitting attributes of other branch nodes according to the information gain ratios; finally, adopting the weight of the samples to substitute the sample number to conduct pessimistic pruning on the created decisiontree, and correspondingly achieving prediction of rock burst dangers and the like in a predicted area. According to the provided rock bust danger level prediction method based on the local weightingC4.5 algorithm, the defect is overcome that the preference selection values have too many attributes when information gain is adopted for selecting node splitting attributes in an ID3 algorithm; an over-fitting problem is avoided, and the prediction accuracy of a model is high.

The invention discloses a fast indexing method and system based on a position top-k keyword in a sliding window. The method comprises creating a data indexing model and performing query; the data indexing model is created as follows: determining a geographical range covered by a quadtree and a node splitting rule; accepting a data stream, and inserting data in a node; splitting the node satisfyinga splitting rule, and inserting the data in the nodes to generate a complete quadtree; storing reverse indexes by leaf nodes; and storing MG polymerization abstracts of sub nodes thereof by non leafnodes; and adjusting the structure of the quadtree; the query comprises: initializing a result set; performing a pruning operation to obtain a candidate result set; and selecting a word with the maximum value in a priority queue, starting to calculate, starting to traverse from the root node until an accurate score of the root node is found on the leaf nodes, putting the accurate score in the queue, and repeating the operation until the previous k words of the priority queue are invariable. By adoption of the fast indexing method and system, the cost can be effectively reduced, the query speedis improved, the search space can be effectively trimmed according to the word frequency and the location proximity, and the geographic text data stream with high arrival rate can be processed.

The invention discloses a secure multi-party computing method, an electronic device and a storage medium. The method comprises: a user node receiving a calculation request through a calculation contract, the calculation request comprising to-be-calculated data, and the calculation contract being deployed on a block chain; the user node splitting the to-be-calculated data into a plurality of piecesof sub-data by utilizing the calculation contract; the user node sending the first number of pieces of sub-data to different participation nodes in a participation node set by using a calculation contract; the user node receiving transaction information sent by the participation node by using the calculation contract, wherein the transaction information is obtained by calculating the sub-data bythe participation node under the condition that the sub-data is real; and the user node obtaining a final calculation result based on the transaction information by using the calculation contract. Inthis way, the data security can be improved.

The invention discloses a modelling method and system based on position top-k keyword query under a sliding window. The method comprises the following steps that 1, a geographical range covered by a quadtree and a node-splitting rule are determined; 2, a data flow is received, and data is inserted into nodes; 3, nodes which conform to the node-slitting rule in step 1 are split, and the intact quadtree is generated constantly by data inserting; 4, the word frequency of each leaf node is counted, and an reverse index of each leaf node is stored; 5, MG aggregated abstract information of each child node of each nonleaf node is stored; 6, the size of the sliding window needs to be maintained in the data inserting processes in step 4 and 5, a data item provided with the oldest timestamp is deleted, the newest data is added, and the index structure of the quadtree is adjusted. By means of the method, the cost is effectively reduced, the query speed is effectively improved, and geographical text data flows with high arrival rates can be processed.

A region of a node is searched to find a content-defined split point. A split point of a node is determined based at least in part on hashes of entries in the node and the node is split based on the determined split point. The search region is searched for the first encountered split point and the node is split based on that split point. That split point is based on a predetermined bitmask of thehashes of the entries in the node satisfying a predetermined condition.

The invention discloses a relay multi-path flow distribution method for minimizing transmission delay. The traditional traffic assignment method directly distributes the end-to-end traffic to the network sub-stream, which causes the performance degradation of transmission delay. The method of the invention splits paths according to a sink node under the condition that paths are not independent, and performs relay multi-path flow distribution. The method firstly collects information, splits the paths, and then carries out network path modeling, quality evaluation and transmission traffic assignment, calculates the queue delay of the paths, solves the traffic assignment with the minimum delay, couples the traffic assignment results, and minimizes the average transmission delay of the data packets arriving at the destination node. From the viewpoint of improving the performance of the live broadcast time delay, the method of the invention considers the situation that a sink node exists inthe multipath transmission, monitors the link information in real time, carries out the relay multipath flow distribution to obtain the minimum transmission time delay, and avoids the transmission performance degradation caused by the competition of the sub-streams for the shared link resources in the traditional flow distribution method.

The invention discloses an efficient mass data indexing method in cloud computing. According to the method, the node splitting history is recorded by use of a log on the basis of a distributed B-tree and the distributed B-tree is efficiently and simultaneously accessed based on the node splitting history, and therefore, the accessing and indexing efficiency of mass distributed data in the cloud computing environment can be effectively improved. The efficient mass data indexing method in the cloud computing is superior to an affair method because distributed locks need to be added to all nodes in the path from the root to a leaf node to be accessed in the affair method, and the efficient mass data indexing method only needs to lock the leaf node to be accessed; the efficient mass data indexing method is superior to a link method because the number of nodes to be traversed in the efficient mass data indexing method is smaller than that of the link method.

The embodiment of the invention provides a cross-feature federal abnormal data detection method and system based on an isolated forest, electronic equipment and a storage medium, and the method comprises the steps that: when each isolated tree in the federal isolated forest model is constructed, an initiator randomly selects one node splitting party from the initiator and each participant as a current node, and the node splitting party completes splitting of the current node; node splitting information is sent to the non-node splitting party for the non-node splitting party to perform the same node splitting, so that isolated trees with the same structure can be constructed by utilizing the feature data stored by each party under the condition that the feature data stored by the party is not leaked; and then an isolated forest can be formed, and abnormal data can be detected from the test sample more comprehensively by using the isolated forest.

A computing method for normalizing molecule graph data for hierarchical molecular generation can include: providing molecule graph data of a molecule having a node; recursively splitting the node into two nodes; iteratively recursively spilling other nodes into two nodes; generating generated molecular graph data of a generated molecule from node splitting; and providing a report with the generated molecular graph. A computing method can include: providing molecule graph data into a latent code generator having multiple levels with a forward and inverse; and generating latent codes by processing molecule graph data through multiple levels of operations, wherein each level of operations has a sequence of sublevels of operations in forward path and inverse path, wherein the sublevels of operations include node merging operation and node splitting operation; generating at least one molecular structure from latent codes; and outputting generate molecule graph data having the at least one molecular structure.

The invention discloses a power supply service satisfaction influence factor identification method based on a decision tree algorithm, and the method comprises the steps: importing a needed function library, constructing a decision tree through a USDUW function, and marking the algorithm as a decision point; when a decision tree is constructed, selecting a certain characteristic value as a node ofthe tree according to a given sample data set, and calculating the information entropy in the data in the data set; determining the number of decision points of the decision tree, and marking the probability and the profit and loss value of the decision points on a probability branch; and when the decision tree selects the decision features, selecting the feature with the maximum Gini exponentialgain value as the node splitting condition. The method is clear in organization, rigorous in program, quantitative and qualitative in analysis, the satisfaction degree of the power customer is analyzed by utilizing a fuzzy decision tree analysis method, and the satisfaction degree of the power customer to the power service under which conditions can be clearly known by establishing a rule, so that conditions are provided for improving the service and improving the satisfaction degree of the power customer in the future.

The invention provides a self-adaptive structure adjustment method and system for a machine learning data index structure. The method comprises the following steps: a node selection step: selecting nodes in the machine learning data index structure one by one according to a preset node number sequence; a node analysis step: analyzing the selected nodes, and executing corresponding structure adjustment operation according to the cache data volume in the nodes and the error range size: if the cache data volume in the nodes or the prediction error of the machine learning model in the nodes is toolarge, executing a node splitting step; if the cache data volume and the error range in the node and the adjacent node are both too small, the two nodes execute a node merging step; otherwise, endingthe process. According to the fine-grained machine learning index structure adjustment method provided by the invention, compared with retraining of all data, the number of retrained models can be reduced, and the influence on performance of irrelevant models and cache during structure adjustment is avoided.

The invention provides a decision tree incremental learning method oriented to information big data. In front of a splitting node, a plurality of attribute values of each candidate attribute in the node are independently combined into two groups, and the candidate attribute with highest information gain is selected to divide the node into two branches. On an aspect of selecting a next node which is to be split, corresponding node splitting measurement values are calculated for all candidate nodes, and the candidate node which has a largest node splitting measurement value is always selected as a next splitting node. IID5R increases a function for evaluating classification attribute quality. By use of the method, NOLCDT is combined with the IID5R to put forward a hybrid classifier algorithm HCS (Hyperspherical Color Sharpening) which mainly consists of two stages of constructing an initial decision tree and carrying out incremental learning. According to the NOLCDT, an initial decision tree is established, and then, the IID5R is used to carry out the incremental learning. The HCS algorithm synthesizes the advantages of the decision tree and the incremental learning so as to bring convenience in comprehension and be suitable for the incremental learning.