13 results about "Unexpected events" patented technology

The invention provides a wireless sensing platform with an edge computing function, and relates to the technical field of wireless sensors. In order to solve the problems that in the prior art, a wireless sensor is large in data redundancy, high in transmission delay and weak in emergency recognition and response capacity in a complex scene, a joint processing mechanism combining a causal event recognition assembly, a causal data fusion assembly, an event separation assembly and a data distribution assembly is adopted. By detecting a causal change event in an environment and dynamically extracting and fusing sensor data with a strong causal relationship, redundant data transmission caused by emergencies is reduced, transmission delay is reduced, the robustness of causal data fusion in a concurrent event scene is improved, and the reliability of data fusion is improved. According to the invention, efficient and accurate sensing and response to emergencies in a complex environment are realized.

The application belongs to the technical field of information analysis, and particularly discloses a sudden event distortion information identification method and system, which comprises the following steps: constructing a keyword table of a sudden event according to keywords of the sudden event; screening a sudden event distortion information data set to construct a sudden event distortion information training data set and a test data set; building a first-stage verification large model through a sample embedding prompt strategy and building a second-stage review large model through a chain thinking prompt strategy; constructing an XLNet-BiLSTM hybrid model to identify sudden event distortion information; constructing a model dynamic integration rule considering the consequences of illusion relief and specific distortion scores, and obtaining the distortion information identification results of the two-stage large model and the XLNet-BiLSTM hybrid model. The application ensures the consistency and understandability of the identification results and the generated explanation, and highlights the transferability of information identification in different types of sudden events.

Systems and methods are disclosed for dynamic simulation, planning, detection and monitoring of emergence within complex adaptive systems. The system ingests real- time real-world event feeds from multiple sources, generates simulations of possible futures based on selected parameters, and encodes predicted outcomes of new emerging narratives in a dynamic simulation matrix. Machine-learning model-based search for disruptive events, breakthroughs and the momentum towards scenario outcomes continuously updates the simulation matrix to reflect changing conditions. The system also includes features such as the generation of early warning alerts and new simulations in response to breakthroughs or new information, monitoring key indicators, and generation of directed acyclic graphs (DAGs) to visualize interdependencies between macro-variables. Users can interact with the dynamic simulation matrix, selecting specific variables or interventions to explore further. The system enables proactive decision-making by anticipating and preparing for emerging narratives and events to simulate detect and monitor emergence in complex adaptive systems.

The invention provides an information transmission method, device and equipment, a readable storage medium and a program product, and the information transmission method comprises the steps: generating first prediction information; the first prediction information comprises one or more of RRM measurement prediction information, second prediction information of the first event, measurement event prediction information and prediction time information; sending the first prediction information to the network device; wherein the first event comprises a failure event or an unexpected event; the prediction time information is used for indicating a generation moment of the third prediction information, or a prediction execution starting moment or completion moment corresponding to the third prediction information, or a starting moment of an effective duration of the third prediction information; the third prediction information comprises one or more of RRM measurement prediction information, second prediction information of the first event and measurement event prediction information. According to the scheme, related contents such as reporting of the prediction scheme on the terminal side can be determined, so that the related scheme for accurately realizing the prediction on the UE side is supported.

The invention provides an emergency detection method, device and equipment and a storage medium, can be applied to scenes such as cloud technology and artificial intelligence, and relates to the field of large models in artificial intelligence. The method comprises the steps of determining an event type and an event element of media data according to text data corresponding to the media data and a trained event extraction model for each piece of media data in the media data generated in a target time period, taking the media data, the title of the text data and the event type and the event element of the media data as input of a trained event coding model, outputting word vectors of word elements of the text data, and clustering the text data corresponding to the media data generated in a target time period according to the word vectors of the word elements of the text data to obtain a clustering result; obtaining at least one text data set, determining one text data set as one event, determining the risk probability of the event corresponding to the text data set according to the trained risk prediction model, and determining the detection result of the event based on the risk probability of the event.

The invention relates to an emergency training drilling method and system based on three-dimensional simulation. The method comprises the following steps: based on a physical environment state parameter and a user operation instruction set of a previous period, analyzing the occurrence condition of an emergency of the current period, and obtaining emergency identification information of the current period; obtaining a three-dimensional drilling scene of the current period based on the physical environment state parameters of the previous period, the user operation instruction set, preset current environment parameters and emergency identification information of the current period; acquiring a user operation instruction set and a current physiological signal when the three-dimensional drilling scene of the current period is executed; based on the emergency identification information of the current period, the user operation instruction set, the physical environment state parameters and the current physiological signals, the emergency operation condition of the user is evaluated, and an operation matching result and a cognitive load evaluation result of the current period are obtained. By adopting the method, actual combat pertinence and training effectiveness of drilling can be improved.

This invention proposes a wireless sensing platform with edge computing capabilities, relating to the field of wireless sensor technology. Addressing the problems of high data redundancy, high transmission latency, and weak ability to identify and respond to sudden events in complex scenarios in existing wireless sensor technologies, this invention employs a joint processing mechanism combining a causal event identification component, a causal data fusion component, an event separation component, and a data allocation component. By detecting causal change events in the environment, it dynamically extracts and fuses sensor data with strong causal relationships, reducing redundant data transmission caused by sudden events, lowering transmission latency, and improving the robustness of causal data fusion in concurrent event scenarios. This achieves efficient and accurate perception and response to sudden events in complex environments.

The invention relates to the technical field of operation machinery, and discloses a data processing method and device and operation machinery, and the method comprises the steps: obtaining the current operation state of the operation machinery; and based on the current operation state, storing the current operation file of the operation machine twice or loading the stored operation file of the operation machine. The method can ensure that the operation data cannot be lost and improve the safety and reliability of the operation data under the unforeseen circumstances of power failure and the like of the operation machine, so that the operation safety of the operation machine is ensured, meanwhile, the previous working state can be quickly recovered when the data is recovered or the operation machine is restarted, and the working efficiency is improved. And the influence on the operation progress is reduced.

The present invention relates to the technical field of data processing, and provides a method, apparatus, electronic device and storage medium for determining intention burst information. The method includes: obtaining a first intention and a second intention, where the first intention is obtained by performing intention recognition on problems within a to-be-detected period, and the second intention is obtained by performing intention recognition on problems within a historical period, and the historical period is associated with the to-be-detected period; determining a first distribution of the first intention; determining a second distribution of the second intention; if the first distribution is inconsistent with the second distribution, determining the burst information of the first intention, so that a user can judge whether there is an unexpected event within the to-be-detected period according to the burst information. The present invention enables a user to timely discover the burst intention within the to-be-detected period according to the burst information, and then can respond to the burst intention in a targeted manner in a timely manner.

A method may include receiving binary data associated with one or more devices in a manufacturing plant, the binary data indicating whether one or more performance variables associated with the one or more devices are outside a predetermined range; receiving textual data associated with the one or more devices in the manufacturing plant; performing vectorization on the text data using a natural language processing technique to obtain vectorized data; receiving unexpected event data indicative of an unexpected event and an associated pre-failure period; and training a machine learning model using the binary data, the vectorized data, and the accident data to classify a state of the manufacturing plant as a normal operation period and a pre-failure period.

The invention relates to the technical field of artificial intelligence big data algorithms, and discloses a business process optimization method and system based on an artificial intelligence big data algorithm. In turn, external contextual information is obtained and parsed in response to the combined performance to identify external events associated with the particular operational anomalies. On the basis, causal association between the external event and the specific operation exception can be established, and an optimization strategy of the external event is generated according to the causal association. The method can deeply understand the'accident 'situation which is caused by external emergencies and has strong locality and dynamic characteristics, identify deep causes behind qualitative factors, and establish a complex causal relationship between the qualitative factors and quantitative operation index deterioration.

This invention discloses a robustness verification method and related equipment based on dynamic node tracking. The robustness verification method based on dynamic node tracking according to an embodiment of the invention includes establishing a list of key elements of the object to be verified, the list including state information of at least one key element; acquiring the nodes where the state information of the key elements changes when the object to be verified is executed without interruption; determining the injection timing based on the nodes where the state information of the key elements changes, and injecting an interruption event at the injection timing; verifying whether the object to be verified recovers to the expected target after the interruption event injection. The robustness verification method and related equipment based on dynamic node tracking according to an embodiment of the invention balance coverage, accuracy, and verification efficiency in the verification of recovery from sudden event interruptions.