5results about How to "Achieve accumulation" patented technology

The utility model discloses a control system for realizing drainage by tidal liquid level difference, including storage and discharge control room, the inside one side of storage and discharge control room is provided with filter assembly, and one end of filter assembly is connected with control component no.

This invention provides a method for optimizing agent tool invocation knowledge based on the evolution of an experience path graph. The method includes: upon the agent's first successful task completion, recording the agent's tool invocation sequence, input / output parameters, and execution results to generate a structured invocation log, and converting the log into standardized invocation path knowledge units; performing structured and semantic representation on the invocation path knowledge units, storing the structured representation in a graph database and the semantic representation in a vector database; constructing an experience path knowledge graph using task intent, tool entities, and invocation paths as heterogeneous nodes. This graph records the multidimensional relationships between tasks, paths, and tools, and adds execution performance and feedback attributes to the path nodes, thus optimizing the agent's tool invocation knowledge. This aims to improve the efficiency and robustness of the agent's tool invocation in a multi-task environment.

The application discloses a coal mine underground gas prevention and treatment method, device, equipment and medium. Multi-source sensing data of a target area in a coal mine is acquired, spatio-temporal alignment and standardized fusion are performed to generate a spatio-temporal data matrix, a pre-trained GNN-LSTM hybrid model is input, and gas emission prediction data of each monitoring point within a preset time window is output. The prediction data and the running state of the ventilation system are jointly input into a pre-trained deep reinforcement learning decision model, the optimal ventilation control instruction is determined from a preset action set based on multi-objective optimization, and the instruction is sent to a ventilation control equipment to adjust the frequency of a fan or the opening degree of a damper. Through the fusion of multi-source information, dynamic and accurate prediction and intelligent decision, advanced warning and automatic control of gas prevention and treatment are realized, the frequency and duration of gas over-limit are effectively reduced, gas accumulation is prevented from the source, and the safety level of coal mine production is significantly improved.

The application discloses a kind of robust fast secret channel construction methods for amplitude using CSS spread spectrum modulation, mainly solve the problems, such as the limited transmission distance and capacity of secret channel in the existing low-power wide-area network environment, steps include: the modulation method design of secret channel;Signal frame structure design and frame detection;The demodulation method design of secret channel;Analysis is carried out to the information loss in the demodulation process of secret signal.The application designs the LoRa physical layer secret channel modulated by amplitude using CSS spread spectrum modulation method, designs the modulation and demodulation method of secret channel, analyzes the information loss in the demodulation process of secret signal, constructs the robust fast secret channel, widens the construction scene of secret channel, and the operation method is simple and clear, has practical value.

The invention discloses a multi-device collaborative efficient online adaptation method, which comprises the following steps: for devices with rich computing power resources, processing a first model in the devices by adopting an online collaborative adaptation mode based on forward and back propagation: when domain offset is detected, dynamically storing weights learned by the models into a shared knowledge base; new knowledge is captured in the adaptation process by introducing a new parameter matrix into the first model parameters; and for equipment with low computing power, processing a second model in the equipment by adopting an online collaborative adaptation mode which only utilizes forward propagation, and carrying out online adaptation on the model by directly utilizing an existing shared knowledge base. According to the method, the knowledge base is dynamically updated and shared, so that accumulation, sharing and dynamic utilization of knowledge among multiple devices are realized; and different online cooperative adaptation modes are adopted for processing for equipment with different computing power, so that the energy efficiency and practicability of online adaptation in practical application are greatly improved. The method can be widely applied to the technical field of transfer learning.