Patents
Literature
Patsnap Copilot is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Patsnap Copilot

347 results about "Data adaptive" patented technology

Sampling GPR method of continuous anomaly detection in collecting data flow of environment sensor

The invention discloses a sampling GPR method of continuous anomaly detection in a collecting data flow of an environment sensor, and belongs to the technical field of data monitoring of environment sensors. The sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor is used for solving the problem that anomaly detection can not be conducted in real time, wherein the problem is caused by the fact that data calculation amount is large in data flow anomaly detection of a traditional environment sensor. The sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor is based on a prediction-model method, a prediction model is built through historical data, the mean value and the confidence interval of current data are obtained, a current data value is compared with the confidence interval, and the current data value is regarded as exceptional data if the current data value exceeds the confidence interval. According to the sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor, less historical data are needed, algorithm operation efficiency is improved, and input training data are not required to be provided with category tags. The sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor can detect an exceptional situation in a self-adaptive mode according to real-time arrival data, and is applied to continuous exceptional data detection in collecting data flow of the environment sensor.
Owner:哈尔滨工业大学高新技术开发总公司

Multi-rate opportunistic routing method for wireless mesh network

The invention provides a multi-rate wireless mesh network routing method for opportunistic forwarding based on characteristics of radio broadcasting, which comprises the following steps: after a node transmits data, a plurality of nodes are selected as forwarding nodes; in the early stage of network setup, the nodes acquire a direct link delivery fraction via probe packets and set up an adjacency relation; an adjacency matrix of the total network is set up by using link status packets to switch link information; a node forwarding probability analysis system model is used to deduce a measurement (integrated transmission number) applicable to the presence of arbitrary paths, and a forwarding node selection strategy and a forwarding strategy are established on the basis of the integrated transmission number; the optimal path algorithm is used to select a major path, the nodes closer to the destination node than the source node can be selected into a forwarding list, and the forwarding nodes can be confined to the vicinity of the major path according to a certain screening rule; the forwarding node closest to the destination node is set to have the highest forwarding priority, and the forwarding priority is lowered with the increase of the distance from the destination node; and the destination node transmits an end-to-end response to the source node based on a certain rule to inform the source node of the number of the received packets, and the source node performs adaptive regulation on the transmission rate according to the data.
Owner:BEIJING UNIV OF POSTS & TELECOMM

Network analytic system and method supporting real-time mass data processing

ActiveCN103560943AEasy to handleReduce business capability requirementsData switching networksReal time analysisNetwork analytics
Provided are a network analytic system and method based on the mass data real-time processing technology. The system comprises a plurality of data adaptive nodes and data analytic clusters which are composed of a plurality of data analytic nodes and arranged in a network in a distribution mode, wherein the data analytic nodes support a P2P networking mode and a load balancing mechanism, so that the data analytic clusters have a telescopic function; the flow line type analytic processing process is completed among the data analytic nodes through an incident mechanism. According to the network analytic system and method supporting the real-time mass data processing, mass network data including operations of network fault monitoring, statistics, trouble shooting, diagnosis and the like can be analyzed and processed in real time, the network data can be analyzed in a fine mode, distribution type dynamic expansion is supported to expand system functions, and users can expand demands of themselves according to the analytic types to be detected in a self-defined manner. Furthermore, a distribution type structure is utilized by the system without excessively depending on single hardware performance, and the system can complete processing of complex logics of network data analysis and the like better. The system and method support multiple types of processing logics and lower the requirements for professional qualification of developers.
Owner:BEIJING UNIV OF POSTS & TELECOMM

Sensitive data self-adaptive desensitization method and system

The invention discloses a sensitive data self-adaptive desensitization method and system, and relates to the field of computer technology and information security, and the method comprises the following steps: a plurality of desensitization algorithms is added into a desensitization server, anda one-to-one corresponding quantitative relation between each desensitization algorithm and each desensitization effect in a plurality of desensitization effects is set; the desensitization server receives a desensitization instruction sent by the client device, and reads the original data from the datasource server according to the desensitization instruction; the desensitization server constructs a desensitization effect preference training set of the user for different sensitive data types to form a decision tree; and the desensitization server positions the sensitive data existing in the original data, determines the type of the sensitive data, selects a desensitization algorithm for the sensitive data by using a decision tree, and generates replacement data of the sensitive data according to the desensitization algorithm. The user configuration process is simple, and intelligent automatic configuration and automatic desensitization of the desensitization strategy can be realized.
Owner:STATE GRID ZHEJIANG ELECTRIC POWER
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products