7results about How to "Make up for uncertainty" patented technology

The invention discloses an underground water pollution path micro-analysis method based on a graph neural network. The method comprises the following steps: S1, acquiring a historical data set and a real-time monitoring data set of underground water pollution; s2, using a fuzzy membership function to represent the language level of the fuzzy variable; s3, constructing a fuzzy logic rule base based on the historical data set; s4, using a fuzzy inference system to process fuzzy variables in the historical data set; s5, constructing an underground water pollution path diagram structure model based on the historical data set and the real-time monitoring data set; s6, constructing an incidence matrix between the nodes; s7, based on the trained graph neural network model, inputting water flow velocity, pollutant concentration and geologic structure parameters in the real-time monitoring data set; s8, generating real-time prediction of a pollution diffusion path; and S9, outputting an analysis result of the groundwater pollution path. The problems that in the prior art, a pollution diffusion path is difficult to accurately predict under a complex geological structure, and real-time dynamic response is insufficient are solved.

The invention discloses a flexible pressure monitoring system for hip replacement surgery, and belongs to the technical field of biomedical instruments. The flexible pressure monitoring system comprises a flexible front-end signal acquisition module, a rear-end signal processing module and an upper computer system, the flexible front-end signal acquisition module is connected with the rear-end signal processing module, and the rear-end signal processing module is connected with the upper computer system; the flexible front-end signal acquisition module comprises a flexible pressure sensor, and the flexible pressure sensor is arranged at a hip joint; the flexible pressure sensor comprises a flexible substrate, an electrode layer, a spacing layer, a sensitive layer and a packaging layer. According to the flexible pressure monitoring system, the uncertainty that the operation effect is judged only according to experience in the hip joint replacement operation process is made up, clear pressure distribution at the hip joint in the operation process can be provided for surgeons, and objective mechanical data are provided for selection and adaptation of prostheses.

The invention belongs to the technical field of railway comprehensive video monitoring, and relates to a railway station crowd anomaly detection method and system based on sparse feature tracking and a neural network, and a readable medium, and the method comprises the following steps: collecting a video image, and carrying out the preprocessing of the video image; carrying out local feature extraction on the preprocessed video image to extract coordinates of a plurality of key points; through sparse feature tracking, obtaining a moving track of the key point between adjacent video frames; according to the key points on each frame, a triangular mesh is generated through a Delaunay triangulation method, the key points are vertexes, and the relation between the adjacent key points is an edge; and generating a descriptor according to the triangular grid, and converting into a low-dimensional crowd state classification result according to the multi-dimensional descriptor. A targeted crowd behavior descriptor and a classifier with low performance requirements are adopted, balance of detection accuracy and detection efficiency is achieved, and the detection method suitable for real-time railway station monitoring is formed.

A data center cooling system control method and device based on a constraint neural network, the method comprising: acquiring thermodynamic parameters of a data center cooling system in real time, and constructing an original database; preprocessing data in the original database to obtain a power consumption dataset and a chip temperature dataset; training a power consumption prediction neural network using the power consumption dataset and a penalty function; training a chip temperature prediction neural network using the chip temperature dataset and the penalty function; the penalty function for temperature prediction adopts an adaptive penalty function, and a penalty factor is introduced when the model predicted temperature is lower than the actual temperature, so that the model predicted temperature is always higher than the actual temperature; and taking the minimum power consumption of the system as an optimization objective, and taking the actual temperature of the chip being less than the upper limit of the chip temperature as a constraint condition, the optimal control parameters under different environmental temperature and humidity and heat load are optimized. The optimization control result can be maintained within the critical temperature of the chip, and the energy saving of the data center is maximized.

The invention provides a variable-parameter segmented ground pre-grouting system and method for a multi-layer aquifer, a three-dimensional grouting hole structure is adopted, and a graded grouting unit and a real-time monitoring unit work cooperatively: three-dimensional grouting holes are arranged at intervals of inner and outer double circles of long and short holes to form a closed water plugging barrier; the graded grouting unit is provided with high-pressure and low-pressure grouting pumps to meet the grouting requirements of deep and shallow holes; the real-time monitoring unit guarantees construction precision and data acquisition through an inclinometer and a pressure and flow sensor. The construction comprises the steps of early-stage investigation, test calibration, segmented downward grouting, variable parameter dynamic adjustment, quality detection and special part treatment, the grouting pressure, the slurry ratio and the segmented height are dynamically optimized based on the stratum characteristics, and the grouting blind area is eliminated in combination with a one-sequence cement-water glass double-liquid slurry and two-sequence chemical slurry synergistic process; precise plugging of multiple aquifers is achieved, curtain continuity and compactness are improved, construction risks are controllable, the construction period is shortened by 15%-20%, and slurry consumption is reduced by 18%.

The application relates to the technical field of low-altitude atmospheric monitoring, and particularly discloses a low-altitude meteorological digital twin reconstruction method based on three-dimensional entity data modeling, which realizes seamless connection from a regional macro wind field to a city micro flow field through the combination of a mesoscale meteorological model and a computational fluid dynamics model, directly considers the physical action of a ground surface feature on airflow based on real city three-dimensional data modeling, continuously corrects the error of a CFD grid model through real-time observation data, makes up for the uncertainty of pure numerical simulation, improves the capturing capability of spatiotemporal mutation phenomena, and further supplements the prediction of complex turbulent flow phenomena that are difficult to analyze by using a computational fluid dynamics model through an intelligent prediction model to mine hidden rules in data, so that the precision of city boundary layer airflow simulation can be significantly improved, and more accurate meteorological guarantee services can be provided for the fields of atmospheric environment monitoring, city planning, aviation safety and the like.

The application relates to a motor open-phase protection method, a controller and a washing equipment. The method samples three-phase currents of a motor, obtains a three-phase current data sequence of a current sampling window, calculates a current integral imbalance degree based on the three-phase current data sequence, performs phase mutation detection based on the three-phase current data sequence, generates a phase deviation amount, and then performs weighted fusion on the current integral imbalance degree and the phase deviation amount to obtain a fusion score. Finally, a hierarchical protection action is executed based on the fusion score. Therefore, the method can accurately detect an open-phase fault, has rapid response and high robustness, and meanwhile, the fusion score can directly reflect the fault severity, facilitating the execution of subsequent protection actions, and realizing the cooperative optimization of rapidity and reliability.