12results about How to "Implement risk assessment" patented technology

The invention provides a medical waste whole-process supervision method based on an intelligent medical waste monitoring platform, and the method comprises the steps: enabling collected smell data to be matched with pre-established medical waste smell component data, judging the type of medical waste to which a smell source belongs, and determining whether the smell concentration exceeds a preset threshold value or not; if the odor concentration exceeds the standard, microorganism information is obtained according to the relevance between the odor component information and microorganisms, and the microorganism breeding risk is evaluated in combination with temperature and humidity control parameters of the air conditioner; simulating airflow distribution of an air conditioning system, predicting diffusion paths and influence ranges of odor in different areas of a hospital by combining with position layout of an air outlet of the air conditioner, and generating an odor diffusion thermodynamic diagram; and according to the optimized disinfection scheme, the air conditioning system is controlled to enter a disinfection mode, the fresh air introduction proportion and the filtering efficiency grade are adjusted, a disinfectant is sprayed in the key area, and the disinfection effect is monitored in real time.

The invention discloses an agency bookkeeping intelligent auditing system and method based on an AI algorithm, and belongs to the technical field of agency bookkeeping intelligent auditing. The agency bookkeeping intelligent auditing system based on the AI algorithm comprises a data acquisition module, a risk assessment module, a resource allocation module and a self-adaptive adjustment module; the data acquisition module is used for collecting enterprise financial historical data, obtaining a historical trend chart of financial indexes, analyzing a historical trend of financial data and determining a financial auditing period; the risk assessment module is used for assessing the risk of the financial data, calculating a deviation index of a financial index, and performing risk grade division on the financial data according to the calculated deviation index of the financial index; the resource allocation module is used for allocating auditing resources; according to the agency bookkeeping auditing system and method, the agency bookkeeping auditing process is analyzed through the AI algorithm, and the problem that the auditing resources are distributed unevenly is solved.

The invention discloses a dynamic construction management method based on a BIM technology, and relates to the technical field of BIM, and the method comprises the following steps: S1, building an information sharing platform; s2, transmitting the data collected at the construction site to an information sharing platform in real time; s3, the information sharing platform synchronizes the data of the construction site to the BIM model in real time; and S4, making and adjusting construction decisions, and regularly carrying out online discussion meetings of all departments and constructors. By constructing the information sharing platform, the real-time safety synchronization function of the construction site data is realized, the construction site data is fed back to the BIM model in real time, the problem that the BIM model cannot be dynamically updated is solved, and the efficiency and coordination of construction management are improved.

The invention discloses a big data-based camp management safety risk assessment system and method, relates to the technical field of camp management, and solves the problem that the current camp management often depends on manual patrol to guarantee the safety of a camp and cannot monitor all areas in the camp in real time. Comprising a data acquisition module, a behavior analysis module, a security detection module, a video detection module and a digital twinning module, the digital twinning module is used for constructing a digital twinning model of a camp, the security detection module is used for performing real-time security detection on an area enclosed by an enclosing wall in the camp, and a risk assessment video of the detection area is obtained through detection; the video detection module is used for detecting a risk assessment video of a detection area in the camp to obtain a risk assessment picture of the detection area in the camp through detection, and the behavior analysis module is used for analyzing behaviors of triggering personnel in the camp to generate alarm signals of different grades and sending the alarm signals to the alarm module. According to the invention, risk assessment of camp safety management is realized based on big data.

The application discloses a bronze harmful rust risk assessment method based on hyperspectral imaging and belongs to the technical field of hyperspectral imaging. The method comprises the following steps: S1, hyperspectral data acquisition; S2, data preprocessing; S3, characteristic wave band extraction; S4, sub-index calculation and corresponding risk judgment; S5, comprehensive risk fusion; S6, environmental factor calculation and corrosion dynamic judgment; S7, risk grade judgment; and S8, prediction and evaluation. The method provides a quantitative, continuous, comparable risk score and discrete operation grade for cultural relic protection personnel, solves subjective dependence and experience difference problems, and realizes a leap from 'qualitative distribution' to 'quantitative risk assessment' and an upgrade from 'picture speaking' to 'digital decision-making'.

The present invention discloses a method and system for predicting and evaluating the trend of monitoring performance indicators of building structures, monitoring and acquiring the time series data of structural performance indicators, and dividing the training set and the test set; performing noise reduction processing, normalization and sliding window division on the obtained training set and the test set to obtain the divided training set and the test set; constructing a time series prediction model based on LSTM, and using the divided training set and the test set to train and test the time series prediction model; constructing an optimization objective function based on the goodness of fit of the model prediction result, optimizing the key parameter group of the time series prediction model using the particle swarm optimization algorithm, obtaining the optimal parameter group and the optimized time series prediction model; using the optimized time series prediction model to predict the future changes in monitoring indicator data, and performing over-limit graded warning and evaluation on the prediction results based on the preset warning threshold. The method provided by the present invention can realize the risk assessment of monitoring indicator prediction data.

The invention relates to a method, a system, equipment and a medium for obtaining a data flow link, and the method comprises the steps: obtaining a business flow link diagram and a deployment architecture diagram, confirming a micro-service tangency point of a business application, deploying a data collection probe in the form of an SDK assembly, and obtaining business data flow information; labeling a link label for a service operation corresponding to the service data flow information, and obtaining a data flow path by taking a service account as a dimension; creating a business domain knowledge base and a behavior judgment model; establishing a business behavior portrait, recognizing an abnormal operation by using the behavior judgment model and a preset illegal behavior recognition strategy, comparing the abnormal operation with the business behavior portrait corresponding to the business account, and performing risk assessment and early warning according to a comparison result; according to the method, multi-dimensional tangency point data acquisition is realized, a data flow link is completely restored and presented, abnormal events, illegal operation and other risks in a data processing flow are identified, early warning and management and control measures are effectively executed, and the security and compliance of data flow are improved.

The present invention discloses a security monitoring system based on knowledge graph and multimodal information, which specifically relates to the technical field of network node management, including building a deep learning model based on a convolutional neural network, using the trained deep learning model to predict the set of state values ​​of all network nodes at the next moment, and outputting a node state risk index by analyzing a fused fault state category matrix of the network nodes at the next moment; building a fault handling knowledge graph, inputting fault information into the fault handling knowledge graph, and outputting a fault theoretical handling operation; outputting a fault handling performance index by analyzing the fault theoretical handling operation and actual fault handling information; jointly analyzing the node state risk index, the fault handling performance index and the prediction accuracy, outputting a node risk control coefficient, taking measures based on the relationship between the node risk control coefficient and a threshold, and solving the problem that the prior art lacks node fault prediction in computer networks.

This invention provides a method and system for predicting the risk of preoperative condylar bone resorption, relating to the field of oral medicine technology. The method includes the following steps: acquiring and preprocessing small-field CBCT image data of the temporomandibular joint region of the patient to obtain the corresponding region of interest (ROI) of the condylar cancellous bone region; segmenting and extracting features from the ROI of the condylar cancellous bone region to obtain corresponding radiomics features; constructing a condylar bone resorption risk prediction model and inputting the radiomics features into the model for prediction to obtain the corresponding risk prediction results; generating patient risk grading information based on the risk prediction results to assist clinicians in making patient management decisions. This invention, by analyzing and modeling the radiomics features of the patient's preoperative condylar cancellous bone region, achieves the prediction of the risk of postoperative condylar bone resorption without using any postoperative images as prediction input.

The invention belongs to the field of financing management, and particularly discloses a financing management method and system for small and medium-sized enterprises, a terminal and a medium, an enterprise financing request is received, and financing demand information and enterprise basic information are extracted from the enterprise financing request; matching a financing product for the enterprise according to the financing demand information, and pushing the financing product to the enterprise; receiving an enterprise financing online application request, monitoring a financing progress and a repayment state, and displaying enterprise financing information at a front end; obtaining credit evaluation data from a target data source according to the enterprise basic information; processing the credit assessment data by using a pre-trained credit assessment large model to obtain enterprise credit assessment information; and pushing the enterprise evaluation information to an enterprise and a financial institution. The accuracy of risk assessment and financing product matching is improved, and the financing efficiency and success rate are improved.

The invention belongs to the technical field of safety vertical rods, and particularly relates to a safety vertical rod and method based on TMD vibration reduction and timely alarming. The safety vertical rod comprises a base which is fixed on the ground; the main vertical rod is arranged on the base; the spring reset system is connected with the base and the main vertical rod and is used for elastically limiting the swinging of the main vertical rod; the TMD damper unit is arranged at the top end of the main vertical rod and used for restraining the swing amplitude of the main vertical rod under the wind load; the telescopic safety belt reel is arranged at the top of the TMD damper unit and used for being connected with a safety belt; and the automatic alarm device is arranged at the top end of the retractable safety belt reel, is in signal connection with the TMD damper unit and is used for alarming. By arranging the TMD damper unit and the spring reset system, the inclination angle of the vertical rod under strong wind is reduced, and the wind resistance of the safe vertical rod is improved.

The embodiment of the present application provides a risk assessment method and related device for a cross-sea bridge, the method comprising: establishing a finite element model of a target bridge; performing a dynamic analysis on the finite element model to determine its accuracy; obtaining historical disaster data of the location of the target bridge; determining one or more risk events that affect the safety of the target bridge based on the historical disaster data; determining M key structures from N bridge parts of an accurate finite element model; dividing multiple damage indicators for each key structure in the M key components; calculating the failure probability of each key component in a corresponding damage state to obtain multiple first failure probabilities; calculating the failure probability of the target bridge based on each first failure probability in the multiple first failure probabilities to obtain multiple second failure probabilities; determining the risk level of the target bridge based on the multiple first failure probabilities and the multiple second failure probabilities. In this way, bridge risk assessment under the action of multiple risk factors is achieved.