6results about How to "Realize online optimization" patented technology

The invention discloses a communication monitoring method and a communication system. The system comprises a monitoring module, a feature extraction module, a dynamic identification module, a behavior analysis module, an adaptive optimization module and a visual interface module. The monitoring module collects communication data flow through a mirror image port, the feature extraction module extracts packet length, time interval, direction sequence and encryption features by using a multi-dimensional feature fusion algorithm, and the dynamic recognition module realizes multi-protocol type recognition based on an improved self-attention convolutional neural network. The behavior analysis module constructs a communication relation graph and performs abnormal communication tracing; and the adaptive optimization module realizes model self-learning and parameter optimization through reinforcement learning. According to the method, through sliding window sampling, self-correlation analysis, entropy detection and GNN map modeling, accurate identification and behavior restoration of implicit traffic in a complex network environment are realized. According to the method, high-precision identification can be kept under the conditions of multi-protocol mixing and encrypted communication, and the characteristics of intelligence, self-adaption and expandability are achieved.

This invention relates to the field of vibration control and health monitoring technology for civil engineering structures, specifically to an integrated device and control method for damping and vibration-induced de-icing of cable structures. This application achieves intelligent de-icing through a single device that combines damping vibration suppression with visual guidance, possessing a complete closed-loop control capability encompassing perception, decision-making, execution, and verification. It employs a progressive high-order modal excitation strategy, utilizing the complex local deformation of high-order modes to more effectively break down ice layer adhesion, fundamentally solving the industry problem of poor low-order modal excitation performance. Furthermore, the system can automatically select and upgrade the optimal mode according to different icing conditions, achieving online optimization of the de-icing strategy.

The invention discloses a source-network collaborative optimization system of a power market, relates to the technical field of power markets, and aims to generate a prediction interval set, a flexibility curve and a security constraint set, form a source-network joint feasible region and complete realizability check, complete multi-product joint clearing in the source-network joint feasible region and generate a time sequence power track and a price signal. According to the method, through source-network joint feasible region construction, security constraint preposition is integrated into market clearing, the operation safety and economy are improved, multi-product joint clearing and refined instruction decomposition are adopted, and the operation efficiency is improved. The market efficiency and the control precision are enhanced, the deviation immunity and the online optimization are realized by depending on closed-loop evaluation and data driving, and the fair and ordered market is guaranteed through a compliance mechanism.

The invention discloses an intelligent control system and method for a spherical inflatable antenna. The system comprises a man-machine interaction module, a control module, a data storage module, a sensor sensing module, a motor driving module, a high-stability antenna base supporting module, an air pressure adjusting module and an intelligent early warning module. The man-machine interaction module is used for scene selection, parameter configuration and state display and issuing an instruction to the control module; the sensor sensing module is used for collecting information and uploading the information to the control module; the control module is used for trajectory planning, cooperative inverse kinematics solution, pose control and stability judgment; the motor driving module drives the high-stability antenna base supporting module to complete azimuth and pitching motion; the air pressure driving module executes air supply, pressure relief and pressure stabilization to regulate and control the air pressure of the cavity; the data storage module is used for recording information; the intelligent early warning module is used for outputting an alarm and triggering protection control when the air pressure is abnormal, the posture is abnormal or the execution mechanism is abnormal. The communication stability can be improved, and the operation difficulty is reduced.

The invention discloses a port multi-resource low-carbon cooperative scheduling optimization method based on reinforcement learning, and the method comprises the steps: constructing a mixed integer nonlinear programming model comprising berths, quay cranes, storage yards and mobile shore power scheduling, and determining a target function and constraints; diversified initial solutions are generated according to the input data, and algorithm parameters are initialized; in the main iteration loop, a damage / repair operator pair is selected through a Q-learning agent, and ALNS damage-repair operation is executed to generate a candidate solution; according to an objective function and a simulated annealing acceptance criterion, determining whether to accept a candidate solution, and calculating and feeding back a reward to a Q-learning module to update a Q table and an operator weight; and gradually cooling the temperature, judging a termination condition, and outputting an optimal scheduling scheme and related performance indexes. According to the method, collaborative optimization of multiple resources such as ships, berths, quay cranes, mobile shore power and storage yards can be achieved, and the method has the advantages of being high in algorithm adaptability, high in solving efficiency, remarkable in carbon emission control effect and the like and is suitable for complex ports.

The application relates to the technical field of fertilizer control, and particularly discloses a corn variable fertilization control method and system for soda saline-alkali soil, which comprises the following steps: acquiring a regional map of a saline-alkali region, and counting fertilization components based on the regional map; determining detection points based on the positions of fertilization nozzles, acquiring soil parameters based on the detection points, and generating control instructions according to the soil parameters; performing space-time analysis on the acquired soil parameters, determining the correlation degrees of different detection points, and determining the mapping relationship between two soil parameters when the correlation degrees reach preset correlation degree thresholds; and recursively adjusting the soil parameter acquisition process of the detection points based on the correlation degrees; the application can simultaneously respond to the changes of rhizosphere alkalinity and sodium salt stress, significantly improve the nitrogen fertilizer utilization rate, reduce the ammonia volatilization loss, and effectively relieve the double stress of high pH and high SAR of the soda saline-alkali soil on the corn root system.