3results about How to "Increase training time" patented technology

This utility model relates to the field of treadmill technology and discloses an intelligent treadmill with status monitoring function. It includes a base frame, with two support rollers rotatably connected to the upper side of the base frame. A variable-speed motor for driving the support rollers is fixedly installed on the back of the base frame. Running belts are provided on the surfaces of the two support rollers. A support frame is welded to the top of the base frame, and a control panel is provided on the top of the support frame. During training, the user wears a monitoring wristband on their wrist. The device monitors the user's body temperature, heart rate, and blood oxygen concentration. When the blood oxygen concentration drops, a solenoid valve opens, allowing oxygen from the oxygen tank to be ejected from the oxygen outlet through the extension tube, increasing the oxygen concentration at the user's face. This promotes increased blood oxygen levels, allowing for safer extension of training time and providing safety protection for users pushing their physical limits.

The application discloses an antenna substrate vibration base frequency optimization method based on machine learning, and belongs to the technical field of large-area thin-wall plate vibration optimization.The method steps are as follows: step one, identifying an active subspace; step two, adaptively constructing a surrogate model in the active subspace; step three, calling a Kriging surrogate model to estimate a sensitivity index; and step four, optimizing an antenna substrate in a reconstructed design space.The application combines a sensitivity analysis method based on an active subspace and an adaptive sampling strategy and a Bayesian optimization method to establish an antenna substrate vibration base frequency global optimization framework based on machine learning, and can efficiently complete the base frequency global optimization design of a large antenna substrate.The optimization verification on a large-scale antenna substrate with complex constraints shows that the method can overcome the problem of premature convergence of a traditional method, and can obtain a design with a better base frequency under less calculation time, and greatly improves the base frequency optimization efficiency of the antenna substrate.

The invention provides an indoor CSI fingerprint positioning method based on deep learning, and relates to the technical field of indoor wireless positioning. According to the method, abnormal value detection is carried out through an isolated forest algorithm, noise interference is eliminated by combining Hampel filtering and wavelet denoising, dimension reduction is carried out on amplitude and phase data by utilizing PCA, the data quality is effectively improved, and a foundation is laid for subsequent model training. A hybrid model combining a CNN, a BiLSTM and an attention mechanism is adopted, the CNN is responsible for extracting local spatial features, the BiLSTM captures a time sequence dependency relationship, the attention mechanism dynamically focuses key features, advantages are complementary, and the fingerprint classification precision is remarkably improved. And outputting the probability distribution of each reference point through a softmax function, selecting five points with the highest probability, and carrying out weighted average calculation on the coordinates by taking the probabilities of the five points as weights. According to the method, the spatial correlation of adjacent fingerprints is effectively utilized, the positioning result is smoothed, and the higher positioning precision is realized while the fluctuation is reduced.