6results about How to "Improve resilience" patented technology

The invention relates to the technical field of government affair services, in particular to an NLP entity recognition method based on semantic extension, which comprises the following steps: collecting multi-source time sequence data and generating an entrepreneurship ecological data graph through a dynamic time warping algorithm; dynamic evolution of a term library is realized by using a generative adversarial network, and a term semantic association graph is constructed in combination with a graph convolutional network; a double-path attention mechanism is deployed in a Transform encoder, and global semantics and local attention guided by terms are fused through a gating loop unit; modeling fuzzy query analysis into a Markov decision process, and optimizing a semantic extension strategy by adopting a reinforcement learning agent; multi-granularity features are extracted through a feature pyramid network, and model parameters are optimized in combination with a bidirectional long-short-term memory network and an online learning feedback loop; and finally, calculating entity service association strength by using a graph attention network, and generating an interpretable report based on a Shapley value attribution algorithm. A closed-loop learning system is formed, and the business starting policy matching accuracy is improved.

The invention discloses a voice interaction graphene AI intelligent tea table control method, and relates to the technical field of home voice interaction, and the method comprises the control steps: S1, monitoring a surrounding user instruction based on a built-in microphone of a tea table, and after the tea table receives the voice instruction, synchronously carrying out the preliminary noise reduction processing, and retaining the voice segment of the instruction; s2, training a data set containing a noise scene, enabling a built-in model to learn features for distinguishing voice and noise, and filtering non-voice signals in real time; and S3, for dialects and accents in different regions, collecting a scale data set, training a dialect recognition model, and inputting the obtained voice signal into the dialect recognition model to recognize and judge the current dialect and accents. Through preliminary noise reduction and microphone array layout, the voice acquisition quality is improved, and instruction omission is reduced; secondly, by training a multi-noise scene data set, the adaptability of the model to a complex environment is enhanced, and reliable recognition is guaranteed; and aiming at dialects and accent optimization, the product universality is improved.

The utility model relates to the technical field of industrial equipment installation, and discloses a flare barrel on-site winch type integral installation structure which comprises a flare tower, a flare main body and a flare barrel body, rotating blocks are fixedly connected to the front side and the rear side of the outer wall of the flare barrel body, and guide columns are rotationally connected to the sides, away from each other, of the two rotating blocks. And second air cylinders are fixedly connected to the sides, away from each other in the front-back direction, of the two guide columns correspondingly, square blocks are fixedly connected to the sides, away from each other in the front-back direction, of the two second air cylinders correspondingly, and a plurality of telescopic rods are fixedly connected to the sides, away from each other in the front-back direction, of the two guide columns correspondingly. According to the utility model, the torch barrel body is lifted to be right above the torch main body by using the winch, so that the T-shaped block slides into the T-shaped groove, the angle of the guide post is adjusted through the air cylinder I, the position of the T-shaped block is adjusted through the air cylinder II, the T-shaped block is ensured to slide into the T-shaped groove all the time, the installation convenience and the equipment adaptability are improved, and the cost is reduced.

A biological agent packing material, its preparation method, and its reactor for the simultaneous removal of ammonia nitrogen and nitrate are disclosed. The steps include: sludge enrichment and acclimatization, preparation of biological agent, preparation of steel slag and coal gangue micro-packing material, and biofilm formation. The reactor includes, from top to bottom, steel slag and coal gangue microporous packing material, porous aeration plates, guide plates, a support layer, a microporous aeration system, and filter plates. A backwash valve is installed at the bottom of the reactor, and the flow rate is controlled by a backwash water tank through a backwash flow meter. Backwashing is achieved by an inlet pump pumping water in conjunction with the porous aeration plates. An exhaust port is provided at the top of the reactor, and the water discharged through the outlet enters a sedimentation tank for sedimentation and drainage. The steel slag and coal gangue microporous packing material used in this invention simultaneously removes ammonia nitrogen and nitrate under the driving action of iron circulation. The preparation process is simple, suitable for domestic sewage and industrial wastewater, and features no secondary pollution, high biological activity, low cost, and simple operation and management. It has significant effects in the simultaneous removal of ammonia nitrogen and nitrate.

This invention discloses an anti-skid navigation control method for agricultural machinery based on historical driver data, comprising: S1, collecting operational data of the driver operating the agricultural machinery on slippery road sections, using the Pearson correlation coefficient method to screen key dependent variables affecting steering control, and constructing training samples; S2, constructing an attention-BP-LSTM neural network regression prediction model for desired wheel angle and steering wheel torque; S3, model training; S4, evaluating and verifying the model's prediction results; S5, deploying the model on the terminal controller of the agricultural machinery to acquire real-time operational data of the agricultural machinery. When slippage is detected, the model outputs the desired wheel angle and steering wheel torque, and, combined with the safety protection mechanism of output limiting and gradual control, automatically adjusts the steering mechanism of the agricultural machinery to control the agricultural machinery to escape slippage. This invention generates precise and real-time control commands through deep learning of the driver's historical sideslip correction data, solving the problems of traditional methods relying on physical models and lacking experience utilization.

The application discloses a power distribution network power supply optimization method and device, a storage medium and a computer device. The method comprises the following steps: determining a dynamic key node and a priority sequence thereof based on a real-time operation state of a power distribution network; constructing a power supply optimization model based on power supply constraints and optimization targets; decomposing the model into a main problem for processing discrete scheduling decision variables and a sub-problem for processing continuous network operation variables in a priority sequence; iteratively solving to obtain a target scheduling scheme and performing resource scheduling. The method of the application decouples discrete scheduling decisions and continuous power flow checking, improves the solving efficiency and engineering real-time performance of large-scale rolling scheduling problems, focuses the search process on a high-value solution area related to key node power supply guarantee, and effectively improves the key load power supply guarantee capability and the overall recovery resilience of the power distribution system.