336 results about "A posteriori probability" patented technology

It aims to appropriately manage the bias of the signal processing amount. 【Solution means】 The abnormality management device 1 uses, as teacher data, normal data indicating the number of normal packets distributed to each device for each time zone, and learns, by maximum likelihood estimation, the parameters of a probability model that outputs the posterior probability that the number of packets distributed to each device for each time zone is normal. A learning unit 11, the posterior probability for each device for each time zone estimated by the learned probability model, the probability distribution of the normal data for each device estimated based on the normal data, and the prior probability of being normal. A derivation unit 12 that derives the probability distribution of abnormal data indicating the number of abnormal packets distributed to each device in the time zone, and the probability distribution of the normal data and the probability distribution of the abnormal data for each device for each time zone are equal. And a setting unit 13 that sets, as a threshold value for abnormality determination of the number of packets distributed to each device, the number of packets corresponding to the value of the probability distribution that becomes the value.

The embodiment of the invention provides a dynamic risk assessment method and system based on perception and causal reasoning, and belongs to the technical field of automatic monitoring. The method comprises the following steps: acquiring a video data stream in real time and analyzing the video data stream into a structured dynamic visual scene representation; through a neural network model used for executing cross-modal semantic alignment, mapping the dynamic visual scene representation into activation evidence of nodes in a pre-constructed causal knowledge graph in a multi-modal embedding space, the nodes of the graph being risk events or risk factors; and performing probabilistic reasoning on the map based on the activation evidence to calculate the posterior probability of the node corresponding to the to-be-predicted risk event. According to the method, the problems that visual perception and causal reasoning cannot be effectively integrated and the evaluation result lacks interpretability in the prior art are solved, obstacles between visual information and abstract causal concepts are overcome by constructing a perception-mapping-reasoning technology closed loop, and the accuracy, transparency and credibility of risk evaluation are remarkably improved.

The purpose is to easily manage abnormal program operation. [Solution] The abnormality management device 1 includes a first learning unit 11 that uses normal data indicating processing resource usage data in which the processing resource usage corresponding to each process ID is normal as training data from among a plurality of processing resource usage data each including the usage of processing resources used in executing a process corresponding to each process ID, and learns parameters of a probability model that outputs a posterior probability that the processing resource usage corresponding to each process ID is normal by maximum likelihood estimation, and a derivation unit 12 that derives a probability distribution of abnormal data indicating processing resource usage data including abnormal processing resource usage based on the posterior probability estimated by the learned probability model, the probability distribution of the normal data, and the prior probability of normality.

The invention discloses a communication fault diagnosis method and device based on a power system, equipment and a medium. The method comprises the following steps: S1, collecting and outputting multi-source data; s2, preprocessing the multi-source data; s3, performing topological constraint attention mechanism weighting processing on the data matrix; s4, performing dynamic threshold calculation on the fusion feature matrix; s5, positioning the abnormal node list; s6, calculating to obtain a posterior probability; s7, matching the rule base to obtain a standardized disposal instruction; according to the method, the communication traffic is collected through the compressed sensing collection algorithm, the line impedance parameters are integrated into the observation matrix in combination with the topological parameters, key node data are collected preferentially, and the effective data acquisition rate is increased; the accuracy of switch false alarm identification is improved by outputting a time-space unified fusion feature matrix; the computing resources are focused to the abnormal nodes and neighborhoods thereof through the abnormal node mask matrix, so that the positioning precision of the aged equipment is improved, and the judgment omission rate caused by switch aging is prevented from being improved.

The invention belongs to the technical field of communication, and particularly relates to a multiplication active code decoding method based on an SO-ORBGRAND decoder. The SO-ORBGRAND decoder outputs soft information by calculating a correct posterior probability of a conjecture code word sequence, and high-performance decoding is realized through soft information exchange and optimization processing between the row decoder and the column decoder. In the iteration process, a method for judging the validity of the code word through the check matrix is designed by utilizing the polarization characteristic of the multiplication active code, so that the iteration is supported to jump out in advance to reduce the complexity. The invention provides a multiplication active code decoding algorithm based on an SO-ORBGRAND decoder, and compared with various non-system multiplication active code decoding algorithms and the performance of traditional long-code polarization codes, the method has remarkable advantages in error correction performance; a method for judging the validity of the code word through the check matrix by utilizing the polarization characteristic design of the multiplication positive code is provided, the complexity is reduced while the judgment success rate is improved, and the implementation overhead is reduced.

The invention relates to the technical field of intelligent substations, and discloses a safety measure checking method and system for an intelligent substation. The method comprises the steps of collecting multi-source real-time monitoring data of a target intelligent substation, and performing edge federation aggregation on the multi-source real-time monitoring data to obtain collaborative feature data; constructing a dynamic topological graph of the target intelligent substation based on the collaborative feature data, and performing short-term fault prediction on the target intelligent substation to obtain a short-term fault prediction result; performing probabilistic reasoning on each short-term fault event according to the fault probability propagation model to obtain a cascading fault posterior probability of the corresponding short-term fault event; performing multi-objective optimization sorting on each safety measure strategy to obtain a safety measure priority sequence; and performing simulation verification on the safety measure priority sequence according to the digital twin to obtain a check report. According to the method, a complete closed loop from risk analysis, rapid verification to strategy optimization is formed, and efficient and intelligent technical guarantee is provided for safe and stable operation of the intelligent substation.

The invention discloses a methane column concentration inversion method and system based on a physically-driven variational auto-encoder, relates to the technical field of greenhouse gas monitoring, and is used for solving the technical problem of low inversion reliability of an existing data-driven methane column concentration inversion mode. The methane column concentration inversion method based on the physical driving variational auto-encoder comprises the following steps: pre-training a decoder module through a loss function containing Jacobian matrix consistency constraint, and freezing network weights of all layers of the decoder module; taking the observation spectrum as the input of the encoder module, outputting posterior probability distribution by the encoder module, sampling any concentration value, and inputting the concentration value into the decoder module for forward simulation to generate a simulation spectrum corresponding to the concentration value; when the difference between the simulated spectrum and the observed spectrum is minimum, determining the optimal methane column concentration as an inversion encoder, and inputting the observed spectrum into an encoder module; and outputting the mean value and the standard deviation of the posterior probability distribution.

The application provides a polar code soft input soft output decoding method, a decoding device and a communication device; the decoding method comprises the following steps: (S1) performing fast serial cancellation list decoding under dynamic frozen bit constraint for all special nodes constituting a polar code; the types of the special nodes comprise rate zero, rate one, repetition and single parity check; (S2) calculating the approximation of the sum of the posterior probabilities of the legal code words not accessed under each special node after decoding; (S3) using the approximation of the code book probability obtained in the step (S2) to calculate the bit level soft information of the output polar code. The low-latency polar code soft input soft output decoding method provided by the application improves the parallelism by realizing fast soft output decoding based on the Rate0, Rate1, REP and SPC nodes, and significantly reduces the decoding latency without losing the soft output precision compared with the SO-SCL decoding algorithm.