30 results about "Causal link" patented technology

A computer-readable medium to direct a computer to function in a specified manner includes executable instructions to construct a strategy map characterizing a presumed causal link between a first business metric and a second business metric. A first pattern within data associated with the first business metric is identified; a second pattern within data associated with the second business metric is located. Any relationship between the first pattern and the second pattern is specified.

A method of adapting a security configuration of a data processing application at runtime, and a system, together with its computing architecture, are disclosed. The system stores a causal network comprising a plurality of nodes and a plurality of incoming and outgoing causal links associated therewith, wherein each node of the causal network is associated with a security concern or a requirement that can be affected by any configuration of the security controls. The current value of assets nodes, as well as those of the security concerns that can be affected by monitored contextual factors, are updated. The control nodes corresponding to the security controls is updated according to the security configuration whose utility is evaluated by the causal network. The node corresponding to the at least one variable is updated with the determined current value, which is propagated through the causal network through the causal links associated with the updated node. The security configuration with the highest utility is selected and replaces the actual configuration by activating and / or deactivating the security functions corresponding to security control nodes enabled / disabled in the selected security configuration.

A method for creating a predictive model is disclosed herein, including the steps of determining trends and patterns in electronic data, using at least a first machine language algorithm, refining the determination of the algorithm, searching for social models that describe the identified trends and patterns using at least a second machine language algorithm, verifying causal links, constructing at least one model about human node behavior and interactions, utilizing the social models to do at least one of the following: validate hypotheses, predict future behavior, and examine hypothetical scenarios, automatically updating predictions when new data is introduced, using probabilistic techniques to learn hierarchical structure in unstructured text, continuously updating a set of themes, examining grammatical rules of each component of text, matching grammatical constituents to semantic roles, and reorganizing data into clusters of entities with common attributes.

The invention discloses an aviation safety accident causal relationship extraction method. The method comprises the steps of text data preprocessing; extracting explicit causal relationships; Extracting an implicit causal relationship; and generating a causal relationship chain. The method has the advantages that the mode matching method is applied to extraction of the explicit causal relationshipof the aviation safety accident, and the bidirectional LSTM method based on the self-attention mechanism is adopted; applying the At-BiLstm + PI to implicit causal relationship extraction, giving a single accident causal relationship chain on the basis that identification and extraction of a single aviation safety accident causal relationship pair are effectively achieved, and good data and method support is provided for scene reproduction and comprehensive analysis of aviation safety accidents.

A computer-readable medium to direct a computer to function in a specified manner includes executable instructions to construct a strategy map characterizing a presumed causal link between a first business metric and a second business metric. A first pattern within data associated with the first business metric is identified; a second pattern within data associated with the second business metric is located. Any relationship between the first pattern and the second pattern is specified.

A method of adapting a security configuration of a data processing application at runtime, and a system, together with its computing architecture, are disclosed. The system stores a causal network comprising a plurality of nodes and a plurality of incoming and outgoing causal links associated therewith, wherein each node of the causal network is associated with a security concern or a requirement that can be affected by any configuration of the security controls. The current value of assets nodes, as well as those of the security concerns that can be affected by monitored contextual factors, are updated. The control nodes corresponding to the security controls is updated according to the security configuration whose utility is evaluated by the causal network. The node corresponding to the at least one variable is updated with the determined current value, which is propagated through the causal network through the causal links associated with the updated node. The security configuration with the highest utility is selected and replaces the actual configuration by activating and / or deactivating the security functions corresponding to security control nodes enabled / disabled in the selected security configuration.

The invention discloses a safety state confirmation method based on construction parameters. Different construction risk factors are selected for different construction nodes in a project to serve as random variables for safety state confirmation; determining a sequence and a relationship of the random variables in different construction nodes, obtaining the sequence and the relationship of the random variables by training a convolutional neural network and / or determining the sequence and the relationship of the variables according to a causal relationship, counting occurrence frequencies of various accidents at different construction nodes, and constructing a three-layer risk accident causal chain, distributing conditional probability distribution of different nodes in the causal chain according to the obtained risk accident causal chain, sorting possible risk accidents and occurrence probabilities according to accident severity to obtain first sorting data and second sorting data, and when a constructor enters a construction node at the position, determining the occurrence probability of the risk accidents according to the first sorting data and the second sorting data. And confirming the safety state of the personnel according to the sequence of the first sorted data and the second sorted data.

The present invention relates to control, monitoring, and automation. The present invention more specifically relates to pattern-based intelligent control, monitoring and automation. The invention performs pattern-based monitoring. It collects signal data from one or more signals. The signal data define signal data streams. It then transforms each of the signal data streams into trends. It also discovers patterns based on the trends within each signal data stream and / or across the signal data streams. The patterns are optionally used for diagnostics and root cause analysis, online plant monitoring and operation control, plant optimization, and other environments where a causal link or correlation may exist between related inputs, states and / or outputs.

The invention discloses a causal link analysis method, causal link analysis equipment and a computer readable storage medium. The method comprises the steps: carrying out the recording and analysis ofa production process of a specified object, and obtaining a plurality of specified variables corresponding to the production process; determining an undirected correlation link among the plurality ofspecified variables based on a relevancy judgment rule; predicting the undirected correlation link according to a causal probability prediction model to obtain a directed causal probability value corresponding to the undirected correlation link; determining a directed causal link among the plurality of specified variables according to the directed causal probability values, wherein the directed causal link is used for representing a causal relationship of the specified object production process; and the mutual influence sequence of the specified variables in the production process can be known.

Summarization of an input story can be accomplished through identification of causal relationships, both explicit and implicit. The input story is transformed into an interpretation sequence, using syntactic cues, and common sense knowledge of an average reader. The interpretation sequence is a time ordered semantic representation of the input story, comprised of story elements. The common sense knowledge includes inference rules, which, from story elements already present, can add additional story elements to the interpretation sequence. Application of inference rules, based on type, can be prioritized. Summarization of the interpretation sequence can be accomplished by the selection of explicit story elements, according to a connection-based strategy, or a concept-based strategy. Regarding a concept-based strategy, metrics can be applied, to select the concepts for contra-causal searching of the interpretation sequence. Options can be provided, for the exclusion of means, or the inclusion of implicit, story elements in the output summary.

Embodiments of the present invention provide a failure prediction method and device for a cluster system. The method includes: performing cluster analysis on event sequence pattern sets according to failure event sets of the cluster system to obtain event sequence clusters; performing causal correlation analysis on event sequence clusters to obtain causal correlation path clusters; performing failure analysis on causal correlation path clusters to obtain The failure mode of the cluster system; according to the failure mode, the failure prediction of the cluster system is carried out. The failure prediction method and device of the cluster system provided by the embodiments of the present invention cluster the event sequence pattern set to obtain the causal correlation path cluster, thereby obtaining the failure mode of the cluster system, and predicting the failure of the cluster system according to the obtained failure mode. Through in-depth analysis and mining of cluster system logs, reliable failure rules for failure prediction can be obtained, thereby improving the recall rate of failure prediction.

The invention relates to a product quality characteristic error traceability analysis method based on multi-source perception, which comprises the following steps of establishing causal relationship between processes by using historical data; screening the historical data so as to compose the screened historical data into a sample space; taking the sample space as the analysis standard, and monitoring the real-time data by a T2 control chart method; performing the orthogonal decomposition on the outbound T2 value according to the causality to obtain decomposition terms; carrying out the out-of-bounds analysis on the T2 statistic value of the decomposition term, and locating the problem procedure. The method of the invention utilizes a large amount of multiple historical data to complete the analysis of the correlation relation between the processes, and reduces the influence brought by the subjective factors. The out-of-bounds T2 value is decomposed according to the relationship directed graph obtained from the analysis process of the relationship between processes, so as to determine the problem process, achieve the accurate grasp of the process, and then achieve the purpose of problem traceability.

A system for identifying a causal link, the system including a diagnostic generator module configured to receive a first user symptom datum, receive diagnostic training data, and generate using a supervised machine-learning process a diagnostic model that outputs a first prognosis. The system includes a prognostic chaining module configured to receive an expert input dataset, receive the first user symptom datum and the first prognosis, generate a gaussian mixture clustering model and identify a first causal link chained to the first prognosis. The system includes a causal link module configured to receive the first prognosis chained to the first causal link, receive a second prognosis chained to a second causal link, and evaluate the first causal link and the second causal link to calculate a degree of similarity between the first causal link and the second causal link.

The invention relates to a method and a system for extracting causal relationships between affairs. The method comprises the following steps: segmenting a to-be-processed text through punctuations, and obtaining at least one clause; according to the clauses and predefined causal links, judging whether causal relationships exist among the clauses or not, generating a first causal set, and defining the corresponding clauses as cause fragments and result fragments respectively; according to the cause fragments and result fragments and by using dependency grammar, dividing the cause fragments and result fragments into at least one candidate event, judging causal relationships between candidate events, generating a second causal set, and obtaining sub-cause fragments and sub-result fragments corresponding to the cause fragments and result fragments; extracting sub-result fragments in the cause fragments as causes of a text core relationship, and extracting sub-cause fragments in the result fragments as results in the text core relationship. According to the method and the system, a causal relationship of a subsequent cause and a preceding result can be identified, and the cause and the result are accurately extracted, so that the effectiveness of the cause and effect relationship identification is improved.

A method is provided for maintaining an onboard reasoner for diagnosing failures on an aircraft that includes aircraft systems configured to report faults to the onboard reasoner. The method includes accessing diagnostic data received from an onboard computer of the aircraft that includes the onboard reasoner. An off-board reasoner builds an off-board diagnostic causal model that describes causal relationships between the failed tests and the diagnosed failure modes. The off-board diagnostic causal model is compared to the diagnostic data. Based thereon, a discrepancy is identified between the graph of the off-board diagnostic causal model, and the other graph of the onboard diagnostic causal model, to determine a new causal relationship relative to the known causal relationships. The onboard diagnostic causal model is updated to further describe the new causal relationship, including producing an updated model, and uploading the updated model to the onboard computer.

According to one embodiment, a method comprises evaluating messages between nodes of a distributed computing environment. Based on timing relationships of the messages, probability of causal links between pairs of messages determined. Based on the determined probability, at least one causal path comprising a plurality of causal links is inferred. Further, an overall probability that the inferred causal path is accurate is determined. In certain embodiments, the overall probability is output for the corresponding causal path to provide an indication of the confidence of the accuracy of such inferred causal path.

A massive clonal expansion of activated CD8+ T-cells with increased frequency of HPV 16-specific CD8+ T-cells was discovered to be a characteristic of oral lichen planus (OLP), indicating a causal link between HPV infection and the dysimmune process. The invention relates to compositions and methods for the diagnosis and treatment of OLP patients.