9 results about "Human learning" patented technology

The application discloses a permanent magnet synchronous motor stator fault diagnosis method and system based on a human learning optimization algorithm, and the method comprises the following steps: obtaining a three-phase current signal of a stator of a permanent magnet synchronous motor, converting the signal into a two-dimensional time-frequency diagram after being decomposed by a variational mode and being demodulated by a Hilbert envelope; constructing a binary neural network for processing the two-dimensional time-frequency diagram and determining a search space; generating a candidate architecture by global search using a first human learning optimization algorithm; for each candidate architecture, fine-tuning the classification layer parameters thereof by proportional evolution using a second human learning optimization algorithm, taking the classification performance of a verification set as a fitness value, and iteratively obtaining an optimal model; inputting a current signal to be diagnosed into the model after the same preprocessing, and outputting a stator fault diagnosis result. Compared with the prior art, the application realizes low-overhead accurate diagnosis of weak faults of a permanent magnet synchronous motor stator by physical information driven preprocessing and double-layer human learning optimization.

1. Name of the product in this design: Desk (6120 extension). 2. Purpose of this design: For human learning purposes. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the key design points: Design 1 3D diagram 1. 5. Design 1 is designated as the basic design.

1. Name of the product in this design: Desk (5672). 2. Purpose of this design: For human learning purposes. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention discloses a large language model training method, device and equipment applied to a professional field and a storage medium, and the method comprises the steps: obtaining a related document of a current field, and carrying out the chapter splitting of the related document, and obtaining a plurality of text blocks; generating a plurality of structured question and answer pairs based on each text block, wherein each structured question and answer pair comprises questions and answers corresponding to the document chapters to which each text block belongs; and inputting each text block and each structured question and answer pair into a basic language model, and performing iterative training on the basic language model according to a preset progressive fine tuning strategy to obtain a target large language model. The domain document can be subdivided according to chapters and sections, structured question and answer training is performed on each text block, and then the model is trained by simulating a human learning process through the preset progressive fine tuning strategy, so that terminologies and concepts can be integrated step by step and iteratively; therefore, the knowledge adaptability of the model in the specific field is remarkably improved.

1. Name of the product in this design: Study Desk (A13XT3406). 2. Purpose of this design: For human learning purposes. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

1. Name of the product in this design: Storage Desk (T07XX4803). 2. Purpose of this design: For human learning purposes. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D rendering 1.

This invention discloses a cross-scenario autonomous driving decision-making method based on adaptive perception. This invention effectively transforms complex environmental information into basic scenarios and makes decisions based on these scenarios. Compared to traditional autonomous driving technologies, this invention shows significant advantages in complex traffic environments. When facing unfamiliar scenarios, this invention can utilize existing training experience and transformed perception images, reducing reliance on large amounts of data and long training times. By simulating the human learning and driving process, this invention enables the autonomous driving system to make accurate decisions using existing training knowledge in unfamiliar scenarios, thus avoiding dependence on large amounts of training data and long training times. Through this adaptive perception mechanism, it can also process and transform bird's-eye view images of varying complexity, providing more easily understood input to the decision-making module, resulting in a more efficient and adaptable autonomous driving solution.

1. Name of the product in this design: Desk with cabinet (X18XX3000). 2. Purpose of this design: For human learning purposes. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.