9results about How to "Self-learning ability" patented technology

The invention relates to a queuing order detection method and apparatus, an electronic device and a medium. The method comprises the steps of obtaining a real-time video of a team in a queuing process; identifying a figure image in each frame of image in the obtained real-time video by using the constructed deep learning neural network to obtain position information of all people in each frame of image; performing straight line fitting on the position information of the owner in each frame of image to obtain a team fitting straight line; acquiring the vertical distance between the position information of each person in each frame of image and the team fitting straight line; when the vertical distance between the personal position information and the fitting straight line in the team is out of the threshold range, an alarm is given out for reminding, and non-contact intelligent monitoring on the queuing order of the crowd is realized; the recognition accuracy of targets such as personnel is improved; through deep learning, when position information confirmation is carried out, identification is carried out through a deep learning neural network, a certain self-learning capability is possessed, and adaptability is stronger.

This application relates to the field of soil remediation technology, and discloses a method, system, and storage medium for real-time monitoring of soil remediation effects. The method includes: collecting multi-depth data samples of soil in the vertical direction to construct a stratified soil characteristic dataset; identifying locations of highly heterogeneous sections based on the dataset; injecting a tracer at these locations and imaging in real time to obtain a sequence of infiltration path images; using a random forest model to predict diffusion velocity and blockage point locations, dynamically adjusting injection parameters to eliminate blockage, and obtaining infiltration path data; tracking and quantifying the effects of the soil amendment on each soil layer through time-series analysis to obtain quantitative indicators of the effect; comparing these indicators with the initial dataset to optimize the stratification model and construct a stratified monitoring framework; integrating multi-depth data samples to validate the framework and generating an evaluation report on the soil remediation effect. This invention achieves accurate characterization of soil vertical stratification characteristics and scientific, quantitative evaluation of remediation effects, improving the efficiency of soil amendment use.

The present invention relates to the technical field of control systems, and discloses a remote monitoring method and system for a skin effect electric heating system based on big data. The present invention first introduces a linear auxiliary model to construct a minimization criterion function, and optimizes the parameters in the minimization criterion function based on an artificial rabbit optimization algorithm to obtain a skin effect electric heating system model; then, by training a fuzzy RBF neural network, the output control quantity controls the duty cycle and frequency and feeds back to a PID controller to regulate the temperature of the skin effect electric heating system; then, based on a graph neural network, time and space extraction is performed to obtain a multi-time scale time feature set and a multi-time scale space feature set, respectively, and temperature prediction is achieved based on a Bi‑GRU neural network; finally, a monitoring platform and a database are established to achieve data monitoring and storage of the skin effect electric heating system. The present invention achieves the purpose of remote monitoring by regulating the temperature of the skin effect electric heating system, and the remote monitoring results are accurate and objective.

This invention discloses a radar-coordinated braking control method for electric-assist bicycles in complex road conditions, relating to the field of electric-assist bicycle control technology. The method includes acquiring radar-detected rear target signals, determining the presence of collision risk based on the changing trend of the rear target signals, and identifying the movement pattern of the rear targets; acquiring the rider's pedaling torque signal; when a collision risk is determined, predicting the moment when the rider's pedaling torque will begin to decrease based on the changing trend of the rear target signals; at the predicted moment, initiating mechanical braking pre-pressure and simultaneously reducing the motor's assist output. This invention utilizes residual assist to provide soft support for the rider's body posture, compensating for the instability caused by the forward shift of the center of gravity, and solving the timing conflict problem between braking intervention and rider posture changes in existing technologies. This improves braking efficiency in dangerous rear-end scenarios while enhancing the stability and smoothness of the riding process.

The present application provides a kind of methanol hydrogen energy risk assessment method and device based on fusion strategy for ship, it is related to system safety engineering and risk management technical field, the risk assessment method of the present application includes: through system level hazard analysis, the unsafe control behavior of power system is identified, and combined with component level failure analysis, a hazard causal chain from bottom physical failure mode to top system level hazard is constructed;Based on hazard causal chain, a hierarchical causal hazard and operability knowledge graph is constructed;Through multi-modal perception to the running state of power system, unstructured multi-modal data stream is converted into a structured semantic event sequence in real time;Structured semantic event and causal hazard and operability knowledge graph are matched and cognitively reasoned to output the diagnosis report to the current risk state of power system, so as to complete risk assessment.

This invention provides a subsea pipeline oil leak early warning system and method based on multiphysics digital twins, relating to the field of marine oil and gas development technology. The early warning system includes: an anchored buoy platform, an underwater glider, multiphysics sensors, a base workstation, a digital twin cloud platform, and an intelligent early warning module. The anchored buoy platform provides fixed-point observation, while the underwater glider conducts mobile patrols, forming a collaborative observation network to collect environmental data from the pipeline's location. The digital twin cloud platform establishes a multiphysics digital twin model, analyzes it in real time, and automatically generates tiered early warnings; the intelligent early warning module executes the tiered warnings. This invention, through the collaborative design of multiphysics digital twins and intelligent early warning, fundamentally solves the problems of real-time performance and accuracy in subsea pipeline oil leak detection. It not only achieves multi-dimensional data fusion and high-fidelity simulation but also improves the system's robustness in harsh marine environments, significantly reducing the risk of environmental pollution.

The invention relates to an intelligent pressure bra and a control method thereof. Comprising a bra main body, a pressure sensing module, a posture sensing module, a pressure adjusting module and a central control module, the pressure sensing module, the posture sensing module and the pressure adjusting module are fixedly connected to the bra main body; the pressure sensing module is used for collecting original chest pressure signals of a patient; the posture sensing module is used for collecting an original posture signal of a patient; the pressure adjusting module and the pressure sensing module are correspondingly arranged; the central control module is connected with the pressure sensing module, the posture sensing module and the pressure adjusting module and used for processing data, communicating with remote terminal equipment and controlling the pressure adjusting module. Compared with the prior art, the method has the advantages that real-time closed-loop adjustment is realized; the compression strategy is dynamically optimized in combination with the posture of the patient, and the safety and accuracy of postoperative rehabilitation are improved.

This application provides a method and system for intelligently optimizing the cutting path and parameters of a laser cutting machine, belonging to the field of laser cutting machine control technology. The method includes: acquiring task parameters and querying a process parameter experience model library to generate initial processing parameters; simultaneously employing an improved genetic-ant colony hybrid algorithm to solve for the theoretically optimal cutting path sequence; collecting multi-source feature information and inputting it into a pre-trained state recognition model to identify the current cutting state in real time; dynamically adjusting the laser power and cutting speed based on the current cutting state; and performing local replanning of the theoretically optimal cutting path sequence based on multi-source feature information, including geometric deviation compensation and dynamic collision avoidance, to generate corrected motion control commands; and using an incremental learning algorithm to update and optimize the dual-channel convolutional neural network and the process parameter experience model library. This application shortens processing time, improves cutting quality stability, reduces energy consumption and defect rate, and enhances the level of intelligence.

The application discloses a kind of rubber bladder hydraulic forming follow-up damping device and method, it is related to rubber bladder forming technical field, including follow-up damping device, rubber bladder forming mechanism and deep learning coordination control system, deep learning coordination control system is connected with follow-up damping device and rubber bladder forming mechanism, rubber bladder forming mechanism is set in the upper portion of follow-up damping device, follow-up damping device is set in the upper portion of upper top cylinder.The application adopts the above structure a kind of rubber bladder hydraulic forming follow-up damping device and method, rubber bladder hydraulic forming follow-up damping device is designed, the device is controlled to realize the dynamic coordination control of " bladder pressure-punch displacement " in starting liquid filling pressurization stage by deep learning coordination control system, ensure that plate is always in stable deformation state in deformation process, to suppress the problem of plate flange area buckling in the process that rubber bladder is completely laid on the surface of plate, i.e. liquid filling pressurization stage.