3results about How to "Optimal control parameters" patented technology

This invention discloses an energy-saving method and system based on data sensing, belonging to the field of energy-saving optimization technology. The method includes: using a sensor array to collect raw multi-source sensor data, performing data preprocessing and feature extraction to generate room occupancy status and a state vector; based on the room occupancy status, inputting the state vector into a macroscopic decision-making agent constructed based on a reinforcement learning algorithm to generate an optimal dynamic weight coefficient vector; based on the optimal dynamic weight coefficient vector, using an improved Hippo optimization algorithm to solve a multi-objective optimization function to generate an optimal equipment control parameter vector; executing the optimal equipment control parameter vector, returning to the sensor data acquisition step, calculating the immediate reward value after the decision, and updating the macroscopic decision-making agent using the corresponding state transition data. This invention solves the problems of poor flexibility, low optimization accuracy, and difficulty in balancing multiple objectives in existing energy-saving control strategies.

The present invention provides an intelligent control method and system for the post-peak destruction process of hard rock under true triaxial surface disturbance, which divides the target rock into surface areas, and divides each surface area into a vertical coverage area, a first component force coverage area, and a second component force coverage area according to the force direction, and then analyzes the characteristic information change status in each area respectively, obtains the first influence correlation coefficient, the second influence correlation coefficient, and the third influence correlation coefficient respectively, and finally calculates the comprehensive control value based on each influence correlation coefficient, which is used to train the control parameter prediction model, so as to predict the optimal control parameters, which are used to effectively control the post-peak destruction process of hard rock of the target rock under true triaxial surface disturbance. In the above manner, the present invention can make full use of data resources to comprehensively count the changing laws of the internal structure of the rock, avoid the errors caused by analyzing only a single characteristic information, and improve the accuracy of data detection and analysis.

The invention discloses a method and system for controlling indoor air quality through a five-constant system. The method comprises the steps that a sample data processing module obtains historical air quality information and corresponding overall sample data of purification equipment output frequency data in the historical day in different time periods; associating the output frequency data of the purification equipment in different time periods every day with the historical air quality information to obtain associated sample data; the model calculation and processing module inputs the current divided time period and the current historical air quality information into a target machine learning model for model calculation and processing, calculates the set similarity between the current divided time period and the current historical air quality information and the associated sample data, and then determines a matching result with the highest similarity; and the air quality feedback regulation module directly controls the purification equipment to carry out intervention control treatment according to a matching result output by the model calculation processing module. The method has the technical advantages of high adaptability, energy conservation, high efficiency, high control intelligence and the like.