11 results about "Environmental security" patented technology

Systems and methods for adaptive threat detection system configuration based on advanced environmental security ranking. A method includes real-time adjustment of system components, including EDR agents, event scoring units, and event enrichment units, in response to changing threat landscapes and network environments. A method further includes retraining machine learning models, controlling thresholds, and selecting event datasets for training and testing. Additionally, a system configuration manager dynamically adjusts detection engine parameters, including correlation levels, rule-based detector settings, and the depth of analysis.

The invention discloses a tunnel environment safety risk assessment method and system based on deep learning, and the method comprises the steps: obtaining multi-source data of a tunnel, and obtaining environment data if a preset condition is satisfied; performing feature extraction on the image data to obtain a damage feature vector; inputting the environmental data and the damage feature vector into a prediction model to output a damage propagation risk index; calculating a structural stability coefficient of the tunnel based on the stress distribution data, and inputting the damage propagation risk index, the structural stability coefficient and the environmental data into a risk assessment model so as to generate a first influence weight of the damage propagation risk index and a second influence weight of the structural stability coefficient according to the environmental data, and the damage propagation risk index and the structure stability coefficient are fused based on the first influence weight and the second influence weight to obtain an environmental safety risk assessment result of the tunnel, so that accurate assessment of the tunnel collapse risk can be improved through implementation of the tunnel collapse risk assessment method and device.

The application discloses a kind of QRA consequence simulation methods based on CFD, it is related to environmental simulation technical field, for solving the problem of reducing the accuracy of evaluation, the problem of increasing environmental pollution risk, by calling historical database to obtain waste liquid discharge historical information and setting two types of propagation benchmark, setting detection time and initial condition of discharge and calculating hindering characteristics, in the detection time, carry out simulation in advance to generate detection result, then based on initial condition, carry out formal simulation, the detection result and hindering characteristics are predicted to each time point propagation characteristics, compare the prediction result with two types of propagation benchmark and input fuzzy rule output, based on the output result, evaluate the propagation consequence of waste liquid under initial condition and input into interactive interface, significantly improve the scientificity and reliability of industrial waste liquid discharge risk assessment, provide more reference basis for environmental safety decision and emergency management, reduce environmental pollution risk, improve risk prediction result accuracy.

The invention discloses an information and environment security risk identification method based on multi-modal data analysis, and aims to solve the problem that the'coupling risk 'of information security and environment security in a network-physical system is difficult to jointly identify. The method comprises the following steps: acquiring and aligning network side data and environment side data with timestamps and asset identifiers; outputting a network anomaly probability, an affected control object and a control instruction parameter by using a Transform network side security detection model; constructing two groups of boundary conditions of an abnormal control instruction and a baseline control instruction based on the affected control object, and performing conditional deduction in the physical information neural network model to obtain two environmental state prediction sequences; calculating an anti-fact deduction residual score according to the residual difference between the observation data and the two prediction sequences; and inputting the network side evidence and the environment side evidence into the micro evidence fusion model to obtain a coupling risk score and grade, and outputting a corresponding influenced control object, thereby realizing the technical effects of interpretable joint identification and grading early warning of the information security and environment security coupling risk.

The application discloses a kind of based on deep learning's tunnel environment safety risk assessment method and system, comprising: obtaining the multi-source data of tunnel, if satisfying preset condition then obtaining environmental data;Image data is extracted to feature, and damage feature vector is obtained;Environmental data and damage feature vector are input into prediction model, to output damage propagation risk index;Based on stress distribution data, the structural stability coefficient of tunnel is calculated, and damage propagation risk index, structural stability coefficient and environmental data are input into risk assessment model, to generate the first influence weight of damage propagation risk index and the second influence weight of structural stability coefficient according to environmental data, and based on the first influence weight and the second influence weight respectively on damage propagation risk index and structural stability coefficient Fusion, obtain the environmental safety risk assessment result of tunnel, therefore, by implementing the application, it can improve the accurate evaluation of tunnel collapse risk.

The invention provides a regional drainage basin sudden environmental event early warning method based on big data, and relates to the technical field of data processing, and the method comprises the steps: obtaining historical pollution event data, and carrying out the frequency statistics of pollution events according to space grids and time segments; establishing a gridding early warning threshold matrix by using negative binomial distribution; collecting multi-source monitoring data of a target drainage basin in real time, and counting the frequency of new pollution events according to a space-time grid; the statistical result is compared with the early warning threshold value matrix of the corresponding grid in real time, and if the frequency number of the new pollution events exceeds the early warning threshold value, graded early warning is triggered; carrying out confidence verification on a newly-issued event which does not trigger early warning, and dynamically recalculating negative binomial distribution parameters of verified data; and based on the negative binomial distribution parameters after recalculation, optimizing the gridding early warning threshold matrix. According to the method, the false alarm rate is reduced while the environmental safety is guaranteed, and scientific, dynamic and reliable decision support is provided for regional watershed environmental risk management.

The application discloses a coastal airport intelligent ecological regulation system based on digital twinning and multi-objective optimization, belongs to the technical field of intelligent airport operation management and environmental safety control, and comprises a state reconstruction module, an original real-time data set of a physical sensor and an environmental prediction state generated by a digital twinning model are acquired, and a fused environmental state is generated by performing weighted fusion based on a deviation measurement between the data set and the environmental prediction state; a risk assessment module, based on the fused environmental state, quantifies a predicted flight safety risk and an ecological resilience risk, and determines dynamic weights corresponding to the two risks respectively according to a preset rule to obtain a weighted risk assessment result; and a collaborative decision optimization module, based on the weighted risk assessment result, solves a multi-objective optimization problem with a risk weighted sum as an objective function to generate optimal regulation instructions, and the application ensures all-weather and high-reliability environmental state acquisition.

This invention discloses a mining path optimization method and system incorporating geological data, belonging to the field of path optimization technology. A mining path optimization system incorporating geological data includes a geological data modeling module and a mining path optimization module. This invention introduces the mining heat hazard mechanism into the path planning process, and by constructing mining environmental load data and an environmental saturation model, it achieves a quantitative assessment of the risks of high temperature, high humidity, and pollutant accumulation, avoiding the heat hazard hazards caused by traditional path planning neglecting environmental safety factors. Based on real-time geological monitoring data and roadway topology, it dynamically calculates the heat and moisture exchange capacity and pollutant dilution capacity of roadway nodes, enabling the path planning results to accurately reflect changes in underground ventilation and environmental conditions, thus improving the accuracy of planning decisions.

The invention discloses a CFD-based QRA consequence simulation method, relates to the technical field of environmental simulation, is used for solving the problems of reduced evaluation precision and increased environmental pollution risk, and is used for obtaining waste liquid discharge historical information by calling a historical database, setting two types of propagation references, setting detection time and initial discharge conditions and calculating obstruction characteristics. The method comprises the following steps: performing simulation to generate a detection result in detection time, then performing formal simulation based on initial conditions, integrating the detection result and obstruction characteristics to predict propagation characteristics of each time point, comparing a prediction result with two types of propagation references, and inputting a fuzzy rule for output. The propagation consequence of the waste liquid under the initial condition is evaluated based on the output result and transmitted to an interactive interface, so that the scientificity and reliability of industrial waste liquid discharge risk evaluation are remarkably improved, a more reference basis is provided for environmental safety decision and emergency management, the environmental pollution risk is reduced, and the risk prediction result precision is improved.

The invention discloses an environment safety intelligent monitoring and early warning analysis method, which relates to the field of intelligent monitoring and early warning analysis, and comprises the following steps: constructing an environment monitoring data pool; the AI video analysis model analyzes the video data in real time to generate a video analysis event; when it is monitored that a sensor generates an alarm signal or a video analysis event meeting an early warning condition is recognized, an adjacent monitoring device is automatically dispatched to focus on an event occurrence area, video data are collected and rechecked, a side AI model extracts multi-dimensional historical and real-time monitoring data associated with the event from a data pool, and the multi-dimensional historical and real-time monitoring data are stored in a database; carrying out fusion analysis on the data and the rechecked video data, and outputting an event verification result with a confidence score; and according to the confidence score, querying the preset hierarchical early warning-disposal mapping table, and dynamically executing corresponding early warning information release and field equipment linkage control, thereby realizing a closed loop from passive warning to active intelligent research, judgment and disposal, and effectively improving the real-time performance, accuracy and automation level of environmental safety monitoring.

The invention provides a visit management method based on multi-modal data and a computer readable medium, and relates to the technical field of computers. The method comprises the following steps: collecting multi-modal data of a monitored object; integrating the multi-modal data through time to obtain at least one multi-modal instance; extracting various features of the monitored object from each multi-modal instance, wherein the various features comprise any one or more of the following features: a behavior rule feature, an emotion fluctuation feature, a social relationship feature and an environmental security feature; associating the various features with the identity information of the monitored object, performing risk assessment based on the associated information, and constructing a user portrait of the monitored object; and determining a visit scheme for the monitored object based on the user portrait. The method achieves the precise insight of the demands and risks of the monitored objects, facilitates the improvement of the distribution efficiency and accuracy of visit resources, reduces the management risks of a monitoring region, and achieves the early intervention.